From dc7c70c2f60a741c5f1fcb54aa2ec06d3976f38b Mon Sep 17 00:00:00 2001
From: zz_y <zeyingz@umd.edu>
Date: Tue, 13 Oct 2026 15:16:59 +0000
Subject: [PATCH 1/5] study: KLL k 25-800 (2x steps), DDSketch alpha 0.1, Hydra
 W 65536; --sketches/--configs to add configs to an existing study

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01FhcWJExZcmVqS6r6rEtjis
---
 scripts/study_saturation.py      | 36 +++++++++++++++++++++++++-------
 scripts/test_study_saturation.py | 18 ++++++++++++++--
 2 files changed, 45 insertions(+), 9 deletions(-)

diff --git a/scripts/study_saturation.py b/scripts/study_saturation.py
index fe8a1a4b..1747b275 100644
--- a/scripts/study_saturation.py
+++ b/scripts/study_saturation.py
@@ -68,15 +68,17 @@
 FREQ_CONFIGS = [f"rows={r} cols={c}" for r in (3, 5) for c in (256, 1024, 4096, 16384)]
 
 # (family, variant, configs, comparator, error metric). The error metric is
-# also the cost table's accuracy_metric; configs step 4x in the size knob
-# (asap HLL is compiled at lg_k 12, 14, 16 only, so it has no lg_k 10).
+# also the cost table's accuracy_metric. HLL steps 4x in registers (asap HLL
+# is compiled at lg_k 12, 14, 16 only); KLL steps 2x in k and DDSketch adds
+# alpha 0.1, so a looser accuracy target has a cheaper config to move to.
 SKETCHES = [
     ("frequency", "cms-fastpath-vector2d", FREQ_CONFIGS, "frequency", "are_top100"),
     ("frequency", "countsketch-fastpath-vector2d", FREQ_CONFIGS, "frequency", "are_top100"),
     ("topk", "cms-heap-topk-fastpath-vector2d", FREQ_CONFIGS, "topk", "precision_at_k"),
     ("cardinality", "hll", ["lg_k=12", "lg_k=14", "lg_k=16"], "cardinality", "relative_error"),
-    ("quantile", "kll-percall", ["k=50", "k=200", "k=800"], "rank-error", "mean_rank_err"),
-    ("quantile", "dd", ["alpha=0.005", "alpha=0.01", "alpha=0.02", "alpha=0.05"],
+    ("quantile", "kll-percall", ["k=25", "k=50", "k=100", "k=200", "k=400", "k=800"],
+     "rank-error", "mean_rank_err"),
+    ("quantile", "dd", ["alpha=0.005", "alpha=0.01", "alpha=0.02", "alpha=0.05", "alpha=0.1"],
      # Mean over probes, like KLL: both answer the same quantile query.
      "relative-value-error", "mean_relative_value_error"),
 ]
@@ -178,11 +180,15 @@
     "eval": ([("hydra_http", "i64", ["hydra-hll", "hydra-univmon-cardinality"]),
               ("hydra_flows", "i64", ["hydra-hll", "hydra-univmon-cardinality"]),
               ("hydra_http_latency", "f64", ["hydra-kll"])],
-             (1024, 4096, 16384), (100_000, 1_000_000, 10_000_000), (1, 4, 16), 3),
+             (1024, 4096, 16384, 65536), (100_000, 1_000_000, 10_000_000), (1, 4, 16), 3),
     "generic": ([(stem, "i64", list(HYDRA_CELLS))
                  for stem in ("hydra_hier_d2", "hydra_hier_d3", "hydra_hier")],
                 (1024, 4096), (1_000_000,), (1, 4), 2),
 }
+# The widest W a variant runs at: a UnivMon grid at 3 x 65536 is ~20 GB, 16
+# of them in a merge more than a machine holds, and its error has saturated
+# by 16384 anyway.
+HYDRA_MAX_W = {"hydra-univmon-cardinality": 16384}
 HYDRA_DATAGEN = os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", "configs",
                              "datagen")
 HYDRA_TABLE = "hydra_saturation.csv"
@@ -407,13 +413,18 @@ def optimizer_cost(args, families):
     for family, variant, configs, comparator, metric in SKETCHES:
         if family not in families or family not in OPTIMIZER_FAMILIES:
             continue
+        if args.sketches and variant not in args.sketches.split(","):
+            continue
         metrics[variant] = metric
+        if args.configs:
+            configs = [c for c in configs if c in args.configs.split(",")]
         for config in configs[:1] if args.one_config else configs:
             heaps = [f" heap={h}" for h in TOPK_HEAPS] if family == "topk" else [""]
             for heap in heaps:
                 rows.append((variant, "lib", ["--config", config + heap], comparator,
                              cost_dataset(family)))
-    for variant, comparator, spec in EXACT_COST_ROWS:
+    # --sketches adds rows to an existing table, which has the exact ones.
+    for variant, comparator, spec in [] if args.sketches else EXACT_COST_ROWS:
         metrics[variant] = EXACT_METRIC
         rows.append((variant, "exact", [], comparator, ["--spec", spec, "--dtype", "i64"]))
     # Hydra: each eval variant on its datasets at the full schema, at each
@@ -438,7 +449,7 @@ def optimizer_cost(args, families):
                 metrics[variant] = HYDRA_COST_METRIC
                 hydra_ws = {int(x) for x in args.hydra_ws.split(",")} if args.hydra_ws else None
                 for w in ws[:1] if args.one_config else ws:
-                    if hydra_ws and w not in hydra_ws:
+                    if (hydra_ws and w not in hydra_ws) or w > HYDRA_MAX_W.get(variant, w):
                         continue
                     config = hydra_config(variant, w)
                     rows.append((variant, "lib", ["--config", config], None,
@@ -573,6 +584,8 @@ def hydra_jobs(sweeps, specs, records=None):
             groupings = hydra_groupings(hydra_labels(specs[stem]))
             for variant, w, grouping, n, m, seed in itertools.product(
                     variants, ws, groupings, ns, shards, range(1, seeds + 1)):
+                if w > HYDRA_MAX_W.get(variant, w):
+                    continue
                 jobs.append((stem, dtype, variant, hydra_config(variant, w), w, grouping, n,
                              m, seed))
     return jobs
@@ -793,6 +806,11 @@ def main():
                         help="hydra: --phase optimizer-cost's Hydra rows")
     parser.add_argument("--one-config", action="store_true",
                         help="only the first config of each sketch")
+    parser.add_argument("--sketches",
+                        help="only these variants of --families (e.g. kll-percall)")
+    parser.add_argument("--configs",
+                        help="only these configs of them (e.g. k=25,k=100), to add new "
+                             "configs to an existing study")
     parser.add_argument("--thetas", default="0,0.5,0.8,1.0,1.2,1.5,2.0")
     parser.add_argument("--cardinalities", default="1000,100000,10000000")
     parser.add_argument("--alphas", default="1.1,1.5,2,3")
@@ -875,6 +893,10 @@ def main():
     for family, variant, configs, comparator, metric in SKETCHES:
         if family not in families:
             continue
+        if args.sketches and variant not in args.sketches.split(","):
+            continue
+        if args.configs:
+            configs = [c for c in configs if c in args.configs.split(",")]
         configs = configs[:1] if args.one_config else configs
         if family == "topk":
             configs = [c + ("" if k == TOPK_K else f" topk_k={k}")
diff --git a/scripts/test_study_saturation.py b/scripts/test_study_saturation.py
index fdc5e226..e6668b32 100644
--- a/scripts/test_study_saturation.py
+++ b/scripts/test_study_saturation.py
@@ -18,8 +18,8 @@
 sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
 
 from study_saturation import (  # noqa: E402
-    HYDRA_COLUMNS, checkpoints, covered_max, hydra_groupings, hydra_labels, hydra_spec,
-    n_saturation, n_star, read_curve, read_per_group)
+    HYDRA_COLUMNS, HYDRA_DATAGEN, HYDRA_SWEEPS, checkpoints, covered_max, hydra_groupings,
+    hydra_jobs, hydra_labels, hydra_spec, n_saturation, n_star, read_curve, read_per_group)
 
 SCRIPT = os.path.join(os.path.dirname(os.path.abspath(__file__)), "study_saturation.py")
 
@@ -824,5 +824,19 @@ def test_resume_reruns_a_cut_off_row_and_replaces_the_table(self):
         self.assertEqual(len(rows), 10)
 
 
+class HydraWidthTest(unittest.TestCase):
+    def test_univmon_stops_at_16384_and_the_others_reach_65536(self):
+        specs = {}
+        for stem, _, _ in HYDRA_SWEEPS["eval"][0]:
+            with open(os.path.join(HYDRA_DATAGEN, f"{stem}.yaml")) as f:
+                specs[stem] = f.read()
+        widths = {}
+        for job in hydra_jobs(["eval"], specs):
+            widths.setdefault(job[2], set()).add(job[4])
+        self.assertEqual(max(widths["hydra-univmon-cardinality"]), 16384)
+        self.assertEqual(max(widths["hydra-hll"]), 65536)
+        self.assertEqual(max(widths["hydra-kll"]), 65536)
+
+
 if __name__ == "__main__":
     unittest.main()

From fad4bfff78ab77e08d60a4dfb29f7a096e81ecee Mon Sep 17 00:00:00 2001
From: zz_y <zeyingz@umd.edu>
Date: Tue, 13 Oct 2026 23:58:22 +0000
Subject: [PATCH 2/5] study: Hydra cost rows past W 16384 merge 4 shards (16
 grids of 3.2 GB do not fit)

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 scripts/study_saturation.py | 9 ++++++++-
 1 file changed, 8 insertions(+), 1 deletion(-)

diff --git a/scripts/study_saturation.py b/scripts/study_saturation.py
index 1747b275..6f96b82c 100644
--- a/scripts/study_saturation.py
+++ b/scripts/study_saturation.py
@@ -94,6 +94,8 @@
 CROSSOVER_FACTORS = (10, 100)
 
 MERGE_SHARDS = 16
+# Hydra cost rows wider than 16384 merge this many shards (see optimizer_cost).
+HYDRA_WIDE_MERGE_SHARDS = 4
 
 # --phase optimizer-cost: the one data shape every sketch's cost is measured
 # at, the synthetic evaluation's dataset (ProjectASAP/ASAPQuery#777):
@@ -473,9 +475,14 @@ def sketchbench(variant, library, config, data, passes):
         # Cost first: flatten keeps the first pass's query timings.
         runs, warmup = HYDRA_COST_RUNS if variant.startswith("hydra-") else \
             (COST_RUNS, COST_WARMUP)
+        # A Hydra grid past 3 x 16384 holds GBs; 16 of them in one merge do
+        # not fit, so it merges 4 (merge CPU is per merge either way).
+        wide = variant.startswith("hydra-") and \
+            int(re.search(r"cols=(\d+)", config[1]).group(1)) > 16384
         sketchbench(variant, library, config, data, [
             "--operations", "insert,query,merge", "--metrics", "throughput,cpu,memory",
-            "--merge-shards", str(MERGE_SHARDS), "--runs", str(runs),
+            "--merge-shards", str(HYDRA_WIDE_MERGE_SHARDS if wide else MERGE_SHARDS),
+            "--runs", str(runs),
             "--warmup-runs", str(warmup)])
         sketchbench(variant, library, config, data, [
             "--operations", "query", "--metrics", "accuracy", "--runs", "1",

From a7188f681918cdbe14bb23e69b3dac3af1463726 Mon Sep 17 00:00:00 2001
From: zz_y <zeyingz@umd.edu>
Date: Wed, 14 Oct 2026 02:19:36 +0000
Subject: [PATCH 3/5] =?UTF-8?q?eval:=20=C2=A76.3=20rerun=20on=20the=20dens?=
 =?UTF-8?q?er=20grid=20(KLL=20k=2025-800,=20DDSketch=20alpha=200.1,=20Hydr?=
 =?UTF-8?q?a=20W=2065536)?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Inputs: the new configs' curves appended to autosketch-vs-asap-inputs (raw
records in raw/dense_*), 7 cost rows (63 in all), and 999 Hydra runs at
W = 65536 (7,778 in all). Results: the 12 workloads at 95% (with plans) and
at 90% and 99%, on #210's tables.

CPU cost falls 0-1.4%, Fargate cost up to 13% (smaller KLL/DDSketch nearer
the target). 90% still equals 95%. Hydra is never chosen, even at W = 65536.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 .../autosketch-vs-asap-hydra/README.md        |   97 +-
 .../autosketch-benchmark-times.json           |    2 +
 .../fig_cost_vs_sla.png                       |  Bin 376788 -> 350477 bytes
 .../autosketch-vs-asap-hydra/fig_frontier.png |  Bin 529793 -> 531895 bytes
 .../fig_planning_time.png                     |  Bin 69533 -> 66048 bytes
 .../fig_rollup_ablation.png                   |  Bin 87393 -> 87857 bytes
 .../inputs/saturation/hydra_saturation.csv    |  999 +++++
 .../optimizer_cost/rqe_atomic_costs.json      |  303 ++
 ...mplatesall-shared1-metrics16.plans.json.gz |  Bin 942552 -> 840751 bytes
 ...emplatesall-shared1-metrics8.plans.json.gz |  Bin 476093 -> 423823 bytes
 ...nthetic-templatesall-shared1.plans.json.gz |  Bin 65571 -> 57838 bytes
 ...nthetic-templatesall-shared8.plans.json.gz |  Bin 117240 -> 102083 bytes
 ...tesclassic-shared1-metrics16.plans.json.gz |  Bin 259549 -> 246615 bytes
 ...atesclassic-shared1-metrics8.plans.json.gz |  Bin 138345 -> 130830 bytes
 ...tic-templatesclassic-shared1.plans.json.gz |  Bin 24149 -> 21119 bytes
 ...tic-templatesclassic-shared8.plans.json.gz |  Bin 42265 -> 39582 bytes
 ...multigroup-shared1-metrics16.plans.json.gz |  Bin 292549 -> 258928 bytes
 ...smultigroup-shared1-metrics8.plans.json.gz |  Bin 152485 -> 136335 bytes
 ...-templatesmultigroup-shared1.plans.json.gz |  Bin 26102 -> 23250 bytes
 ...-templatesmultigroup-shared8.plans.json.gz |  Bin 49348 -> 44366 bytes
 .../autosketch-vs-asap-hydra/summary_sla.md   |  968 ++--
 .../summary_synthetic.md                      |  404 +-
 ...c-templatesall-shared1-metrics16-tp95.json | 3240 ++++++--------
 ...ic-templatesall-shared1-metrics8-tp95.json | 2846 ++++++------
 .../synthetic-templatesall-shared1-tp95.json  | 2510 ++++++-----
 .../synthetic-templatesall-shared8-tp95.json  | 2436 +++++-----
 ...mplatesclassic-shared1-metrics16-tp95.json | 3298 +++++++-------
 ...emplatesclassic-shared1-metrics8-tp95.json | 3106 ++++++-------
 ...nthetic-templatesclassic-shared1-tp95.json | 2938 ++++++------
 ...nthetic-templatesclassic-shared8-tp95.json | 2966 ++++++-------
 ...atesmultigroup-shared1-metrics16-tp95.json | 2646 +++++------
 ...latesmultigroup-shared1-metrics8-tp95.json | 2454 +++++-----
 ...etic-templatesmultigroup-shared1-tp95.json | 2286 +++++-----
 ...etic-templatesmultigroup-shared8-tp95.json | 2286 +++++-----
 .../autosketch-vs-asap-inputs/README.md       |    5 +
 .../autosketch-vs-asap-inputs/raw/README.md   |   20 +
 .../dense_dd_a2.saturation_accuracy.jsonl.gz  |  Bin 0 -> 2837 bytes
 .../dense_dd_a3.saturation_accuracy.jsonl.gz  |  Bin 0 -> 3226 bytes
 .../dense_grid_q.saturation_accuracy.jsonl.gz |  Bin 0 -> 123729 bytes
 .../dense_kll_a2.saturation_accuracy.jsonl.gz |  Bin 0 -> 70801 bytes
 .../dense_kll_a3.saturation_accuracy.jsonl.gz |  Bin 0 -> 69914 bytes
 ...mizer_cost_h.rqe_atomic_costs_raw.jsonl.gz |  Bin 0 -> 3406 bytes
 ...mizer_cost_q.rqe_atomic_costs_raw.jsonl.gz |  Bin 0 -> 3104 bytes
 .../saturation/out_1e9/saturation.csv         |    8 +
 .../saturation/out_1e9/saturation_curve.csv   |  168 +
 .../out_1e9/saturation_merge_curve.csv        | 1122 +++++
 .../out_grid_1e7_cost/saturation.csv          |   16 +
 .../out_grid_1e7_cost/saturation_curve.csv    |  272 ++
 .../saturation_merge_curve.csv                | 1088 +++++
 .../autosketch-vs-asap-targets/README.md      |   69 +-
 .../fig_cost_vs_target.png                    |  Bin 118701 -> 120711 bytes
 ...g_cost_vs_target_at_autosketch_latency.png |  Bin 116901 -> 119050 bytes
 .../summary_targets.md                        |  128 +-
 ...templatesall-shared1-metrics16-tacc90.json | 3908 +++++++---------
 ...templatesall-shared1-metrics16-tacc99.json | 3134 +++++++------
 ...-templatesall-shared1-metrics8-tacc90.json | 3510 +++++++--------
 ...-templatesall-shared1-metrics8-tacc99.json | 2924 ++++++------
 ...synthetic-templatesall-shared1-tacc90.json | 3174 +++++++------
 ...synthetic-templatesall-shared1-tacc99.json | 2742 ++++++------
 ...synthetic-templatesall-shared8-tacc90.json | 3196 +++++++------
 ...synthetic-templatesall-shared8-tacc99.json | 2797 ++++++------
 ...latesclassic-shared1-metrics16-tacc90.json | 3950 ++++++++---------
 ...latesclassic-shared1-metrics16-tacc99.json | 3516 +++++++--------
 ...platesclassic-shared1-metrics8-tacc90.json | 3758 ++++++++--------
 ...platesclassic-shared1-metrics8-tacc99.json | 3452 +++++++-------
 ...hetic-templatesclassic-shared1-tacc90.json | 3590 ++++++++-------
 ...hetic-templatesclassic-shared1-tacc99.json | 3396 +++++++-------
 ...hetic-templatesclassic-shared8-tacc90.json | 3634 ++++++++-------
 ...hetic-templatesclassic-shared8-tacc99.json | 3388 +++++++-------
 ...esmultigroup-shared1-metrics16-tacc90.json | 2644 +++++------
 ...esmultigroup-shared1-metrics16-tacc99.json |  550 +--
 ...tesmultigroup-shared1-metrics8-tacc90.json | 2452 +++++-----
 ...tesmultigroup-shared1-metrics8-tacc99.json |  406 +-
 ...ic-templatesmultigroup-shared1-tacc90.json | 2284 +++++-----
 ...ic-templatesmultigroup-shared1-tacc99.json |  280 +-
 ...ic-templatesmultigroup-shared8-tacc90.json | 2284 +++++-----
 ...ic-templatesmultigroup-shared8-tacc99.json |  280 +-
 77 files changed, 51648 insertions(+), 52282 deletions(-)
 create mode 100644 rqe-optimizer/results/autosketch-vs-asap-inputs/raw/dense_dd_a2.saturation_accuracy.jsonl.gz
 create mode 100644 rqe-optimizer/results/autosketch-vs-asap-inputs/raw/dense_dd_a3.saturation_accuracy.jsonl.gz
 create mode 100644 rqe-optimizer/results/autosketch-vs-asap-inputs/raw/dense_grid_q.saturation_accuracy.jsonl.gz
 create mode 100644 rqe-optimizer/results/autosketch-vs-asap-inputs/raw/dense_kll_a2.saturation_accuracy.jsonl.gz
 create mode 100644 rqe-optimizer/results/autosketch-vs-asap-inputs/raw/dense_kll_a3.saturation_accuracy.jsonl.gz
 create mode 100644 rqe-optimizer/results/autosketch-vs-asap-inputs/raw/dense_optimizer_cost_h.rqe_atomic_costs_raw.jsonl.gz
 create mode 100644 rqe-optimizer/results/autosketch-vs-asap-inputs/raw/dense_optimizer_cost_q.rqe_atomic_costs_raw.jsonl.gz

diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/README.md b/rqe-optimizer/results/autosketch-vs-asap-hydra/README.md
index c20db564..f349452f 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/README.md
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/README.md
@@ -18,7 +18,12 @@ everything added since #138:
   (`topk(32, sum by (label_0) (rate(data_total[w])))`) are dropped, as
   ASAPQuery's engine would need per-series counter deltas to serve them
   (2026-10-13 rerun of the classic and all workloads; the multi-grouping
-  results are unchanged).
+  results are unchanged);
+- a **denser config grid** (2026-10-14, #213): KLL `k` ∈ {25, 50, 100, 200,
+  400, 800} (was 50/200/800), DDSketch α adds 0.1, and Hydra grids add
+  W = 65536 (hydra-hll, hydra-kll). Only the new configs were measured and
+  appended to the curves, the cost table and the Hydra study. HLL stays at
+  `lg_k` 12/14/16, the precisions asap_sketchlib builds.
 
 Cost is billed by use (sketch-bench `docs/rqe_optimizer_cost_model.md`):
 `w_cpu · AUC(CPU) + w_mem · AUC(memory)`, at two weight settings (CPU only, in
@@ -43,24 +48,24 @@ Cost of each method's cheapest plan (no latency bound), absolute:
 
 | Workload | RQEs | Weights | ASAP | ASAP (no roll-ups) | PerQuery | AutoSketch | RQEs rolled up | Deployments (with / without roll-ups) |
 |---|---|---|---|---|---|---|---|---|
-| mixed (classic) | 42 | CPU (vCPU) | 2.38 | 2.38 | 7.77 | 2,739 | 0 | 6 / 6 |
-| mixed (classic) | 42 | Fargate ($/h) | 0.170 | 0.170 | 0.623 | 136 | 0 | 6 / 6 |
-| mixed, r = 8 | 76 | CPU | 2.47 | 2.47 | 13.6 | 3,284 | 0 | 6 / 6 |
-| mixed, m = 8 | 336 | CPU | 19.1 | 19.1 | 62.2 | 21,916 | 0 | 48 / 48 |
-| mixed, m = 16 | 672 | CPU | 38.1 | 38.1 | 124 | 43,831 | 0 | 96 / 96 |
-| mixed, m = 16 | 672 | Fargate | 2.73 | 2.73 | 9.97 | 2,175 | 0 | 96 / 96 |
-| multi-grouping | 62 | CPU | 0.221 | 0.551 | 1.07 | 10.2 | 52 | 5 / 26 |
-| multi-grouping | 62 | Fargate | 0.0137 | 0.0339 | 0.0597 | 0.430 | 52 | 5 / 26 |
-| multi-grouping, r = 8 | 124 | CPU | 0.242 | 0.573 | 2.04 | 12.3 | 104 | 5 / 26 |
-| multi-grouping, m = 8 | 496 | CPU | 1.77 | 4.41 | 8.55 | 81.7 | 416 | 40 / 208 |
-| multi-grouping, m = 16 | 992 | CPU | 3.53 | 8.81 | 17.1 | 163 | 832 | 80 / 416 |
-| multi-grouping, m = 16 | 992 | Fargate | 0.218 | 0.542 | 0.955 | 6.87 | 832 | 80 / 416 |
-| mixed + multi-grouping | 104 | CPU | 2.60 | 2.93 | 8.84 | 2,750 | 52 | 11 / 32 |
-| mixed + multi-grouping | 104 | Fargate | 0.184 | 0.204 | 0.683 | 136 | 52 | 11 / 32 |
-| mixed + multi-grouping, r = 8 | 200 | CPU | 2.71 | 3.04 | 15.6 | 3,296 | 104 | 11 / 32 |
-| mixed + multi-grouping, m = 8 | 832 | CPU | 20.8 | 23.5 | 70.7 | 21,997 | 416 | 88 / 256 |
-| mixed + multi-grouping, m = 16 | 1664 | CPU | 41.7 | 47.0 | 141 | 43,995 | 832 | 176 / 512 |
-| mixed + multi-grouping, m = 16 | 1664 | Fargate | 2.95 | 3.27 | 10.9 | 2,182 | 832 | 176 / 512 |
+| mixed (classic) | 42 | CPU (vCPU) | 2.35 | 2.35 | 7.67 | 2,701 | 0 | 6 / 6 |
+| mixed (classic) | 42 | Fargate ($/h) | 0.149 | 0.149 | 0.487 | 127 | 0 | 6 / 6 |
+| mixed, r = 8 | 76 | CPU | 2.43 | 2.43 | 13.5 | 3,239 | 0 | 6 / 6 |
+| mixed, m = 8 | 336 | CPU | 18.8 | 18.8 | 61.3 | 21,610 | 0 | 48 / 48 |
+| mixed, m = 16 | 672 | CPU | 37.6 | 37.6 | 123 | 43,221 | 0 | 96 / 96 |
+| mixed, m = 16 | 672 | Fargate | 2.38 | 2.38 | 7.78 | 2,035 | 0 | 96 / 96 |
+| multi-grouping | 62 | CPU | 0.22 | 0.55 | 1.07 | 9.65 | 52 | 5 / 26 |
+| multi-grouping | 62 | Fargate | 0.0134 | 0.0333 | 0.0589 | 0.406 | 52 | 5 / 26 |
+| multi-grouping, r = 8 | 124 | CPU | 0.241 | 0.572 | 2.04 | 11.6 | 104 | 5 / 26 |
+| multi-grouping, m = 8 | 496 | CPU | 1.76 | 4.4 | 8.54 | 77.2 | 416 | 40 / 208 |
+| multi-grouping, m = 16 | 992 | CPU | 3.52 | 8.8 | 17.1 | 154 | 832 | 80 / 416 |
+| multi-grouping, m = 16 | 992 | Fargate | 0.215 | 0.532 | 0.942 | 6.5 | 832 | 80 / 416 |
+| mixed + multi-grouping | 104 | CPU | 2.57 | 2.9 | 8.74 | 2,711 | 52 | 11 / 32 |
+| mixed + multi-grouping | 104 | Fargate | 0.162 | 0.182 | 0.545 | 128 | 52 | 11 / 32 |
+| mixed + multi-grouping, r = 8 | 200 | CPU | 2.68 | 3.01 | 15.5 | 3,250 | 104 | 11 / 32 |
+| mixed + multi-grouping, m = 8 | 832 | CPU | 20.6 | 23.2 | 69.9 | 21,688 | 416 | 88 / 256 |
+| mixed + multi-grouping, m = 16 | 1664 | CPU | 41.1 | 46.4 | 140 | 43,375 | 832 | 176 / 512 |
+| mixed + multi-grouping, m = 16 | 1664 | Fargate | 2.6 | 2.92 | 8.73 | 2,042 | 832 | 176 / 512 |
 
 Every workload: 0 RQEs dropped, 0 sanity violations (ASAP ≤ ASAP without
 roll-ups ≤ PerQuery, and ASAP ≤ AutoSketch). `summary_synthetic.md` has
@@ -71,18 +76,32 @@ plus its measured benchmark, approxbench accuracy runs at 1e8 items):
 
 | Workload | RQEs | ASAP | PerQuery | AutoSketch |
 |---|---|---|---|---|
-| mixed (classic) | 42 | 0.44 s | 0.49 s | 0.002 s + 212 s |
-| mixed, m = 16 | 672 | 8.1 s | 8.9 s | 0.027 s + 3,394 s |
-| multi-grouping | 62 | 0.41 s | 0.22 s | 0.002 s + 269 s |
-| multi-grouping, m = 16 | 992 | 7.0 s | 4.1 s | 0.037 s + 4,309 s |
-| mixed + multi-grouping | 104 | 0.94 s | 0.64 s | 0.005 s + 481 s |
-| mixed + multi-grouping, m = 16 | 1664 | 15.6 s | 13.0 s | 0.137 s + 7,702 s |
+| mixed | 42 | 0.99 s | 1.6 s | 0.0031 s + 169 s |
+| mixed, m = 16 | 672 | 7.4 s | 12.0 s | 0.024 s + 2,710 s |
+| multi-grouping | 62 | 0.52 s | 0.28 s | 0.0023 s + 227 s |
+| multi-grouping, m = 16 | 992 | 8.5 s | 5 s | 0.037 s + 3,625 s |
+| mixed + multi-grouping | 104 | 2.1 s | 2.2 s | 0.0075 s + 396 s |
+| mixed + multi-grouping, m = 16 | 1664 | 16.1 s | 17.1 s | 0.064 s + 6,335 s |
+
+The denser grid gives ASAP and PerQuery more candidates (6 KLL and 5 DDSketch
+configs instead of 3 and 4), so their MILPs are larger than before
+(mixed + multi-grouping: 0.94 → 2.1 s). AutoSketch reaches a feasible config
+sooner (15 probes instead of 19 on mixed + multi-grouping), so its measured
+benchmark is shorter (481 → 396 s).
+
+**What the denser grid changed** (95%, cheapest plans): CPU cost falls 0–1.4%
+(mixed 2.38 → 2.35 vCPU, mixed + multi-grouping 2.60 → 2.57), since insert
+CPU per item is flat across configs (KLL ≈ 30 ns, DDSketch ≈ 19 ns at every
+size). Memory-weighted cost falls more, as plans pick a smaller KLL or
+DDSketch closer to the target: Fargate 0.170 → 0.149 $/h on mixed (−13%),
+0.184 → 0.162 on mixed + multi-grouping (−12%), 0.0137 → 0.0134 on
+multi-grouping. No conclusion changes.
 
 ### Roll-ups
 
 On the **multi-grouping** set, ASAP serves 52 of 62 RQEs from a finer
 deployment, cutting its deployments from 26 to 5 and its cost by **60%**
-(0.551 → 0.221 vCPU; 0.0339 → 0.0137 $/h), and by the same share at r = 8,
+(0.550 → 0.220 vCPU; 0.0333 → 0.0134 $/h), and by the same share at r = 8,
 m = 8 and m = 16. The cube (template 16) is the clearest case: one KLL
 deployment at (region, service, endpoint) answers all 14 p99 RQEs. Every
 deployment ingests the whole stream, so cost grows with the number of
@@ -90,11 +109,11 @@ groupings kept. A KLL or DDSketch merge summarizes the pooled data of the
 merged groups, so a roll-up answers a coarse group's p99, not a quantile of
 quantiles (KLL reads its measured merge curve).
 
-On **mixed + multi-grouping**, roll-ups save 11% (2.93 → 2.60 vCPU, 32 → 11
+On **mixed + multi-grouping**, roll-ups save 11% (2.90 → 2.57 vCPU, 32 → 11
 deployments): the classic templates, whose streams have one grouping each,
 are most of the cost. On classic alone, roll-ups never apply and the two ASAP
-lines coincide. ASAP's ~3× advantage over PerQuery on classic (7.77 vs. 2.38
-vCPU; 1.8–3.3× at every SLA) comes from sharing deployments across RQEs at
+lines coincide. ASAP's ~3× advantage over PerQuery on classic (7.67 vs. 2.35
+vCPU; 1.7–3.3× at every SLA) comes from sharing deployments across RQEs at
 the same grouping.
 
 ### Hydra
@@ -113,6 +132,12 @@ Google 2011; not committed) agreed: Hydra meets 0.05 only for groups holding
 ≥ 1–5% of records, and per-group sketches that grow with n use less memory
 than the grid at the W that needs.
 
+W = 65536 (#213) widens what Hydra is accurate for: on groups holding ≥ 1% of
+the records, the worst error at 1e7 records drops from 0.283 to 0.039
+(hydra-hll, `http`), 0.074 to 0.021 (hydra-hll, `flows`) and 0.054 to 0.017
+(hydra-kll). But it is the most expensive grid on every axis (3.3 GB per
+hydra-hll grid, 6.2 µs per insert on `http`), and it is never chosen either.
+
 hydra-univmon-cardinality reads ≈ 100% error at N ≥ 1e6 at every W
 (8 layers × a small heap saturate at ~1e6 distinct values per cell), so it is
 ruled out by accuracy; cardinality's Hydra candidate is hydra-hll.
@@ -160,15 +185,17 @@ zcat plans/synthetic-templatesmultigroup-shared1.plans.json.gz | jq '.plans[]
 ## Inputs
 
 - `inputs/saturation/optimizer_cost/rqe_atomic_costs.json`: the cost table,
-  56 rows, measured serially on idle clnode138 (`study_saturation.py --phase
+  63 rows (56, plus #213's KLL `k` 25/100/400, DDSketch α 0.1 and Hydra
+  W = 65536 rows), measured serially on idle clnode138 (`study_saturation.py --phase
   optimizer-cost --seeds 3 --hydra-variants hydra-hll,hydra-kll`), including
   Hydra rows per dataset (`measured_at.dataset`) and #192's KLL footprint.
 - `inputs/saturation/hydra_saturation.csv`: the Hydra study (`--phase hydra`,
-  #202), 6,779 runs on 4 CloudLab nodes; hydra-kll on `hydra_http_latency`
+  #202), 7,778 runs on 4 CloudLab nodes (#213 added 999 at W = 65536); hydra-kll on `hydra_http_latency`
   rerun with per-service latency scales (×1–10 log-uniform), so groups differ
   in distribution as they do in practice.
 - The accuracy curves (`out_grid_1e7_cost/`, `out_1e9/`) are the committed
-  #138 study's, in `../autosketch-vs-asap-inputs/saturation/` (#194).
+  #138 study's, in `../autosketch-vs-asap-inputs/saturation/` (#194), with
+  #213's new KLL and DDSketch configs appended.
 - `inputs/tables/`: the workloads, `export_autosketch_eval_table.py
   --synthetic` (classic, multigroup and all × r ∈ {1, 8} × m ∈ {1, 8, 16}).
 
@@ -220,3 +247,9 @@ measured and each workload's benchmark time is unchanged.
 - Template 12 groups by (dst_subnet, proto) rather than (dst_subnet,
   dst_port): answering 1e6 groups every minute took ~49 s and set every
   plan's batch latency above the largest SLA.
+
+Denser grid (2026-10-14, #213, runner at sketch-bench eval/dense-grid):
+multi-grouping on the 4 CloudLab nodes clnode109/155/167/178, then classic and
+all on #210's tables on the same 4 nodes, each node running its share
+serially. Plans: `--runs 1`, without `--no-chosen`, extracted with
+`scripts/extract_autosketch_plans.py`.
diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/autosketch-benchmark-times.json b/rqe-optimizer/results/autosketch-vs-asap-hydra/autosketch-benchmark-times.json
index 4da336cb..6a390d31 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/autosketch-benchmark-times.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/autosketch-benchmark-times.json
@@ -7,11 +7,13 @@
   "[\"dd\", {\"alpha\": 0.01}, null, 0.0, 2.0]": 21.549985619960353,
   "[\"dd\", {\"alpha\": 0.02}, null, 0.0, 2.0]": 22.274108413956128,
   "[\"dd\", {\"alpha\": 0.05}, null, 0.0, 2.0]": 21.460699204995763,
+  "[\"dd\", {\"alpha\": 0.1}, null, 0.0, 2.0]": 22.29261576803401,
   "[\"hll\", {\"lg_k\": 12}, 0.0, 1000000.0, null]": 38.143390018027276,
   "[\"hll\", {\"lg_k\": 12}, 0.8, 1000000.0, null]": 39.95713640097529,
   "[\"hll\", {\"lg_k\": 14}, 0.0, 1000000.0, null]": 40.32202102598967,
   "[\"hll\", {\"lg_k\": 14}, 0.8, 1000000.0, null]": 40.74274828098714,
   "[\"kll-percall\", {\"k\": 200}, null, 0.0, 2.0]": 22.40906461601844,
+  "[\"kll-percall\", {\"k\": 25}, null, 0.0, 2.0]": 22.67945937020704,
   "[\"kll-percall\", {\"k\": 50}, null, 0.0, 2.0]": 22.422631791967433
  }
 }
\ No newline at end of file
diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/fig_cost_vs_sla.png b/rqe-optimizer/results/autosketch-vs-asap-hydra/fig_cost_vs_sla.png
index 0a014e34278e5ac977bceb9f1a4e3c6e71c8e1c3..b2ab988a80ce6ccf8566041d26a47ab113293c28 100644
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/fig_planning_time.png b/rqe-optimizer/results/autosketch-vs-asap-hydra/fig_planning_time.png
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/inputs/saturation/hydra_saturation.csv b/rqe-optimizer/results/autosketch-vs-asap-hydra/inputs/saturation/hydra_saturation.csv
index 68437315..77b76454 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/inputs/saturation/hydra_saturation.csv
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/inputs/saturation/hydra_saturation.csv
@@ -6778,3 +6778,1002 @@ hydra-kll,quantile,rows=3 cols=1024 cell_k=200,3,1024,hydra_http_latency,"region
 hydra-kll,quantile,rows=3 cols=1024 cell_k=200,3,1024,hydra_http_latency,"region,service,endpoint,status",4,1000000,15000000,1,,1,0.2524544663819616,0.2516831683168317,0.40693069306930696,0.5000000000000001,9716,0.16232079514868755,0.0397909865461834
 hydra-kll,quantile,rows=3 cols=1024 cell_k=200,3,1024,hydra_http_latency,"region,endpoint,status",4,10000000,150000000,1,,2,0.21272145033640244,0.18630868039926232,0.38109400293641527,0.48496516318298505,10000,0.20109537826642254,0.03532569707734709
 hydra-kll,quantile,rows=3 cols=4096 cell_k=200,3,4096,hydra_http_latency,"region,service,endpoint,status",4,10000000,150000000,1,,3,0.25120237505377413,0.25293539425885037,0.4034788724774117,0.5000000000000001,10000,0.02568445350920431,0.004053199878974521
+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_http,endpoint,4,10000000,150000000,4,interleaved,2,0.0728360998953834,0.005499047550587643,0.10097267253358036,5.206871868289191,625,0.014291867677463817,0.0018754999034669168
+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_http,service,4,10000000,150000000,4,interleaved,1,0.005530756948997668,0.004590684329406019,0.012876874118303206,0.017791007105429205,25,0.017791007105429205,0.013883380175169989
+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_http,endpoint,4,10000000,150000000,16,interleaved,3,0.07222332998411211,0.00564516129032258,0.09846678023850085,5.288011695906433,625,0.014848771737505605,0.007258726077001052
+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_http,service,4,10000000,150000000,16,interleaved,2,0.004669121047366289,0.004465243731326037,0.009214741880575238,0.02042727465694415,25,0.02042727465694415,0.009214741880575238
+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_http,region,4,10000000,150000000,16,interleaved,1,0.006378082282848842,0.008662082309606665,0.010451649112532524,0.010451649112532524,4,0.010451649112532524,0.010451649112532524
+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_http,"region,endpoint",4,10000000,150000000,4,interleaved,1,0.3472395101697469,0.005877742946708464,0.4562043795620438,80.53250773993808,2500,0.01985715658328796,0.0023828849721706864
+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_flows,"dst_subnet,dst_port",3,10000000,70000000,4,interleaved,2,125.42946266727307,61.5,259.0,96971.0,421342,0.01909871655094585,0.0023153822300320433
+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_flows,"dst_subnet,proto",3,10000000,70000000,4,interleaved,3,0.3317528437306147,0.16428571428571428,0.6700404858299596,40.97922848664688,3000,0.019814977518217997,0.012008040861064393
+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_http,"service,endpoint,status",4,10000000,150000000,4,interleaved,1,0.733740535746045,0.006265664160401002,0.9852941176470589,85.50909090909092,2500,0.01894434654084475,7.386329662444734e-05
+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_http,"region,service,status",4,10000000,150000000,4,interleaved,3,0.05580297049061036,0.006060606060606061,0.10914359304571797,3.5660486674391656,400,0.01569340093254332,0.0046354376247623105
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+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_flows,proto,3,10000000,70000000,16,interleaved,1,0.007966916607912935,0.008268325721042982,0.008635449625161131,0.008635449625161131,3,0.008635449625161131,0.008635449625161131
+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_http,"region,endpoint,status",4,100000,1500000,16,interleaved,2,1.0196100768542626,0.0,1.5,302.0,6948,0.007511737089201878,0.0019646365422396855
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+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_flows,"dst_subnet,dst_port",3,1000000,7000000,16,interleaved,3,15.16337464396736,8.0,31.0,5635.0,124653,0.01249434644957033,0.003366341499373418
+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_http,region,4,1000000,15000000,16,interleaved,1,0.0013632820390592488,0.0012377778085109325,0.0020772915376845126,0.0020772915376845126,4,0.0020772915376845126,0.0020772915376845126
+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_http,"region,endpoint,status",4,1000000,15000000,16,interleaved,1,3.864426050395395,0.0,3.740740740740741,1398.0,9716,0.016546685290641454,0.00017188037126160193
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+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_flows,proto,3,1000000,7000000,16,interleaved,2,0.003426180014797333,0.0037543397412578275,0.005896646458661757,0.005896646458661757,3,0.005896646458661757,0.005896646458661757
+hydra-hll,cardinality,rows=3 cols=65536,3,65536,hydra_flows,"dst_subnet,dst_port,proto",3,1000000,7000000,16,interleaved,2,15.98411827574434,8.0,32.5,16255.0,188140,0.0077675489067894135,0.0077675489067894135
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/inputs/saturation/optimizer_cost/rqe_atomic_costs.json b/rqe-optimizer/results/autosketch-vs-asap-hydra/inputs/saturation/optimizer_cost/rqe_atomic_costs.json
index d1c9cf7c..8fc449cd 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/inputs/saturation/optimizer_cost/rqe_atomic_costs.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/inputs/saturation/optimizer_cost/rqe_atomic_costs.json
@@ -2267,5 +2267,308 @@
       "schema_width": 4,
       "dataset": "hydra_http_latency"
     }
+  },
+  {
+    "sketch": "kll-percall",
+    "sketch_config": {
+      "algorithm": "kll-percall",
+      "params": {
+        "k": 25
+      }
+    },
+    "mem_bytes_per_instance": 4840.0,
+    "insert_cpu_secs": 2.98468e-08,
+    "merge_cpu_secs": 3.48e-06,
+    "query_cpu_secs": 2.671287128712871e-06,
+    "query_accuracy": {
+      "accuracy_runs": 1.0,
+      "grid_points": 101.0,
+      "items": 1000000.0,
+      "max_rank_err": 0.091847,
+      "mean_rank_err": 0.019547755775577557
+    },
+    "accuracy_metric": "mean_rank_err",
+    "measured_at": {
+      "items_per_instance": 1000000,
+      "keys_per_instance": null,
+      "value_range": null,
+      "merge_operand_items": 62500,
+      "distribution": {
+        "kind": "pareto",
+        "alpha": 2.0,
+        "scale": 1000.0,
+        "seed": 42
+      }
+    }
+  },
+  {
+    "sketch": "kll-percall",
+    "sketch_config": {
+      "algorithm": "kll-percall",
+      "params": {
+        "k": 100
+      }
+    },
+    "mem_bytes_per_instance": 7032.0,
+    "insert_cpu_secs": 3.01354e-08,
+    "merge_cpu_secs": 4.6400000000000005e-06,
+    "query_cpu_secs": 3.843564356435643e-06,
+    "query_accuracy": {
+      "accuracy_runs": 1.0,
+      "grid_points": 101.0,
+      "items": 1000000.0,
+      "max_rank_err": 0.01705,
+      "mean_rank_err": 0.005246435643564355
+    },
+    "accuracy_metric": "mean_rank_err",
+    "measured_at": {
+      "items_per_instance": 1000000,
+      "keys_per_instance": null,
+      "value_range": null,
+      "merge_operand_items": 62500,
+      "distribution": {
+        "kind": "pareto",
+        "alpha": 2.0,
+        "scale": 1000.0,
+        "seed": 42
+      }
+    }
+  },
+  {
+    "sketch": "kll-percall",
+    "sketch_config": {
+      "algorithm": "kll-percall",
+      "params": {
+        "k": 400
+      }
+    },
+    "mem_bytes_per_instance": 16432.0,
+    "insert_cpu_secs": 3.09384e-08,
+    "merge_cpu_secs": 1.1346666666666668e-05,
+    "query_cpu_secs": 1.3297029702970296e-05,
+    "query_accuracy": {
+      "accuracy_runs": 1.0,
+      "grid_points": 101.0,
+      "items": 1000000.0,
+      "max_rank_err": 0.005301,
+      "mean_rank_err": 0.0018005775577557756
+    },
+    "accuracy_metric": "mean_rank_err",
+    "measured_at": {
+      "items_per_instance": 1000000,
+      "keys_per_instance": null,
+      "value_range": null,
+      "merge_operand_items": 62500,
+      "distribution": {
+        "kind": "pareto",
+        "alpha": 2.0,
+        "scale": 1000.0,
+        "seed": 42
+      }
+    }
+  },
+  {
+    "sketch": "dd",
+    "sketch_config": {
+      "algorithm": "dd",
+      "params": {
+        "alpha": 0.1
+      }
+    },
+    "mem_bytes_per_instance": 336.0,
+    "insert_cpu_secs": 1.8831000000000002e-08,
+    "merge_cpu_secs": 4.1333333333333333e-07,
+    "query_cpu_secs": 1.188118811881188e-07,
+    "query_accuracy": {
+      "accuracy_runs": 1.0,
+      "grid_points": 101.0,
+      "items": 1000000.0,
+      "max_relative_value_error": 0.09933099747729664,
+      "mean_relative_value_error": 0.04830375834163406,
+      "scored_points": 101.0,
+      "unanswered_points": 0.0
+    },
+    "accuracy_metric": "mean_relative_value_error",
+    "measured_at": {
+      "items_per_instance": 1000000,
+      "keys_per_instance": null,
+      "value_range": null,
+      "merge_operand_items": 62500,
+      "distribution": {
+        "kind": "pareto",
+        "alpha": 2.0,
+        "scale": 1000.0,
+        "seed": 42
+      }
+    }
+  },
+  {
+    "sketch": "hydra-hll",
+    "sketch_config": {
+      "algorithm": "hydra-hll",
+      "params": {
+        "cols": 65536,
+        "rows": 3
+      }
+    },
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+    "insert_cpu_secs": 6.187214666666667e-06,
+    "merge_cpu_secs": 2.732486777777778,
+    "query_cpu_secs": 0.02637,
+    "query_accuracy": {
+      "aae_all": 189.5,
+      "aae_top1": 215.0,
+      "accuracy_runs": 1.0,
+      "are_all": 0.0013632820390592488,
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+      "err_p50": 0.0012377778085109325,
+      "err_p90": 0.002077291537684513,
+      "fanned_mass": 15000000.0,
+      "group_columns": 1.0,
+      "groups_scored": 4.0,
+      "l1_err": 758.0,
+      "l2_err": 393.91877335308607,
+      "probes": 4.0,
+      "probes_all": 4.0,
+      "probes_top1": 1.0,
+      "records": 1000000.0,
+      "relative_error_mean": 0.0013632820390592488,
+      "relative_error_p99": 0.002077291537684513,
+      "schema_width": 4.0,
+      "subpopulations": 4.0
+    },
+    "accuracy_metric": "err_max",
+    "measured_at": {
+      "items_per_instance": 1000000,
+      "keys_per_instance": 10000,
+      "value_range": [
+        1.0,
+        1000000.0
+      ],
+      "merge_operand_items": 250000,
+      "distribution": {
+        "kind": "zipf",
+        "skewness": 0.8,
+        "population_size": 1000000,
+        "seed": 5
+      },
+      "schema_width": 4,
+      "dataset": "hydra_http"
+    }
+  },
+  {
+    "sketch": "hydra-hll",
+    "sketch_config": {
+      "algorithm": "hydra-hll",
+      "params": {
+        "cols": 65536,
+        "rows": 3
+      }
+    },
+    "mem_bytes_per_instance": 3271557376.0,
+    "insert_cpu_secs": 3.0767939999999998e-06,
+    "merge_cpu_secs": 2.675697111111111,
+    "query_cpu_secs": 0.00034407766666666673,
+    "query_accuracy": {
+      "aae_all": 26.964,
+      "aae_top1": 990.0,
+      "aae_top10": 311.4,
+      "aae_top100": 59.7,
+      "aae_top1000": 26.964,
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+      "groups_scored": 1000.0,
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+      "l2_err": 3061.421565220968,
+      "probes": 1000.0,
+      "probes_all": 1000.0,
+      "probes_top1": 1.0,
+      "probes_top10": 10.0,
+      "probes_top100": 100.0,
+      "probes_top1000": 1000.0,
+      "records": 1000000.0,
+      "relative_error_mean": 0.11428121142635247,
+      "relative_error_p99": 1.0957446808510638,
+      "schema_width": 3.0,
+      "subpopulations": 1000.0
+    },
+    "accuracy_metric": "err_max",
+    "measured_at": {
+      "items_per_instance": 1000000,
+      "keys_per_instance": 3000000,
+      "value_range": [
+        0.0,
+        1000000.0
+      ],
+      "merge_operand_items": 250000,
+      "distribution": {
+        "kind": "uniform",
+        "lower_bound": 0.0,
+        "upper_bound": 1000000.0,
+        "seed": 4
+      },
+      "schema_width": 3,
+      "dataset": "hydra_flows"
+    }
+  },
+  {
+    "sketch": "hydra-kll",
+    "sketch_config": {
+      "algorithm": "hydra-kll",
+      "params": {
+        "cell_k": 200,
+        "cols": 65536,
+        "rows": 3
+      }
+    },
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+      "group_columns": 1.0,
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+      "items": 1000000.0,
+      "max_rank_err": 0.008793567780795014,
+      "mean_rank_err": 0.002932765855833572,
+      "probes": 4.0,
+      "records": 1000000.0,
+      "schema_width": 4.0,
+      "subpopulations": 4.0
+    },
+    "accuracy_metric": "err_max",
+    "measured_at": {
+      "items_per_instance": 1000000,
+      "keys_per_instance": 10000,
+      "value_range": null,
+      "merge_operand_items": 250000,
+      "distribution": {
+        "kind": "pareto",
+        "alpha": 2.0,
+        "scale": 1000.0,
+        "seed": 5
+      },
+      "schema_width": 4,
+      "dataset": "hydra_http_latency"
+    }
   }
 ]
\ No newline at end of file
diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/plans/synthetic-templatesall-shared1-metrics16.plans.json.gz b/rqe-optimizer/results/autosketch-vs-asap-hydra/plans/synthetic-templatesall-shared1-metrics16.plans.json.gz
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/summary_sla.md b/rqe-optimizer/results/autosketch-vs-asap-hydra/summary_sla.md
index bf3ae080..08134ae9 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/summary_sla.md
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/summary_sla.md
@@ -4,712 +4,712 @@ Each method's cost by use (`w_cpu · AUC(CPU) + w_mem · AUC(memory)`) at each S
 
 ## mixed: 42 RQEs
 
-Sanity violations: 0. Tightest feasible SLA: ASAP 87.7 ms, PerQuery 87.7 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 212 s.
+Sanity violations: 0. Tightest feasible SLA: ASAP 87.7 ms, PerQuery 87.7 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 169 s.
 
 | weights | SLA (ms) | method | cost | latency (ms) | CPU (vCPU) | GiB | meets SLA |
 |---|---|---|---|---|---|---|---|
-| cpu | 100 | ASAP | 34.1 | 99.8 | 34.1 | 34.1 | yes |
-| cpu | 100 | ASAP (no roll-ups) | 34.1 | 99.8 | 34.1 | 34.1 | yes |
-| cpu | 100 | PerQuery-CostAware | 60.1 | 97.4 | 60.1 | 75.6 | yes |
-| cpu | 100 | AutoSketch-Adapted | 2.74e+03 | 1.01e+03 | 2.74e+03 | 5.62e+03 | **no** |
-| cpu | 300 | ASAP | 10.6 | 291 | 10.6 | 15.5 | yes |
-| cpu | 300 | ASAP (no roll-ups) | 10.6 | 291 | 10.6 | 15.5 | yes |
-| cpu | 300 | PerQuery-CostAware | 21 | 291 | 21 | 67.7 | yes |
-| cpu | 300 | AutoSketch-Adapted | 2.74e+03 | 1.01e+03 | 2.74e+03 | 5.62e+03 | **no** |
-| cpu | 1e+03 | ASAP | 4.22 | 980 | 4.22 | 29.1 | yes |
-| cpu | 1e+03 | ASAP (no roll-ups) | 4.22 | 980 | 4.22 | 29.1 | yes |
-| cpu | 1e+03 | PerQuery-CostAware | 10.5 | 980 | 10.5 | 155 | yes |
-| cpu | 1e+03 | AutoSketch-Adapted | 2.74e+03 | 1.01e+03 | 2.74e+03 | 5.62e+03 | **no** |
-| cpu | 3e+03 | ASAP | 2.41 | 2.68e+03 | 2.41 | 16.3 | yes |
-| cpu | 3e+03 | ASAP (no roll-ups) | 2.41 | 2.68e+03 | 2.41 | 16.3 | yes |
-| cpu | 3e+03 | PerQuery-CostAware | 7.98 | 2.68e+03 | 7.98 | 139 | yes |
-| cpu | 3e+03 | AutoSketch-Adapted | 2.74e+03 | 1.01e+03 | 2.74e+03 | 5.62e+03 | yes |
-| cpu | 1e+04 | ASAP | 2.41 | 2.68e+03 | 2.41 | 16.3 | yes |
-| cpu | 1e+04 | ASAP (no roll-ups) | 2.41 | 2.68e+03 | 2.41 | 16.3 | yes |
-| cpu | 1e+04 | PerQuery-CostAware | 7.77 | 3.33e+03 | 7.77 | 72.8 | yes |
-| cpu | 1e+04 | AutoSketch-Adapted | 2.74e+03 | 1.01e+03 | 2.74e+03 | 5.62e+03 | yes |
-| fargate | 100 | ASAP | 1.48 | 96.9 | 34.5 | 18.2 | yes |
-| fargate | 100 | ASAP (no roll-ups) | 1.48 | 96.9 | 34.5 | 18.2 | yes |
-| fargate | 100 | PerQuery-CostAware | 2.77 | 97.4 | 60.2 | 74.9 | yes |
-| fargate | 100 | AutoSketch-Adapted | 136 | 1.01e+03 | 2.74e+03 | 5.62e+03 | **no** |
-| fargate | 300 | ASAP | 0.499 | 291 | 10.6 | 15.5 | yes |
-| fargate | 300 | ASAP (no roll-ups) | 0.499 | 291 | 10.6 | 15.5 | yes |
-| fargate | 300 | PerQuery-CostAware | 1.15 | 291 | 21 | 67 | yes |
-| fargate | 300 | AutoSketch-Adapted | 136 | 1.01e+03 | 2.74e+03 | 5.62e+03 | **no** |
-| fargate | 1e+03 | ASAP | 0.242 | 896 | 4.24 | 15.7 | yes |
-| fargate | 1e+03 | ASAP (no roll-ups) | 0.242 | 896 | 4.24 | 15.7 | yes |
-| fargate | 1e+03 | PerQuery-CostAware | 0.732 | 896 | 10.7 | 67.3 | yes |
-| fargate | 1e+03 | AutoSketch-Adapted | 136 | 1.01e+03 | 2.74e+03 | 5.62e+03 | **no** |
-| fargate | 3e+03 | ASAP | 0.17 | 2.68e+03 | 2.41 | 16.3 | yes |
-| fargate | 3e+03 | ASAP (no roll-ups) | 0.17 | 2.68e+03 | 2.41 | 16.3 | yes |
-| fargate | 3e+03 | PerQuery-CostAware | 0.628 | 2.68e+03 | 8.04 | 67.9 | yes |
-| fargate | 3e+03 | AutoSketch-Adapted | 136 | 1.01e+03 | 2.74e+03 | 5.62e+03 | yes |
-| fargate | 1e+04 | ASAP | 0.17 | 2.68e+03 | 2.41 | 16.3 | yes |
-| fargate | 1e+04 | ASAP (no roll-ups) | 0.17 | 2.68e+03 | 2.41 | 16.3 | yes |
-| fargate | 1e+04 | PerQuery-CostAware | 0.623 | 3.26e+03 | 7.92 | 67.9 | yes |
-| fargate | 1e+04 | AutoSketch-Adapted | 136 | 1.01e+03 | 2.74e+03 | 5.62e+03 | yes |
+| cpu | 100 | ASAP | 33.4 | 96.9 | 33.4 | 12.2 | yes |
+| cpu | 100 | ASAP (no roll-ups) | 33.4 | 96.9 | 33.4 | 12.2 | yes |
+| cpu | 100 | PerQuery-CostAware | 56 | 97.4 | 56 | 40.2 | yes |
+| cpu | 100 | AutoSketch-Adapted | 2.7e+03 | 1.01e+03 | 2.7e+03 | 4e+03 | **no** |
+| cpu | 300 | ASAP | 10.4 | 295 | 10.4 | 10.5 | yes |
+| cpu | 300 | ASAP (no roll-ups) | 10.4 | 295 | 10.4 | 10.5 | yes |
+| cpu | 300 | PerQuery-CostAware | 19.4 | 295 | 19.4 | 36.8 | yes |
+| cpu | 300 | AutoSketch-Adapted | 2.7e+03 | 1.01e+03 | 2.7e+03 | 4e+03 | **no** |
+| cpu | 1e+03 | ASAP | 4.12 | 989 | 4.12 | 10.9 | yes |
+| cpu | 1e+03 | ASAP (no roll-ups) | 4.12 | 989 | 4.12 | 10.9 | yes |
+| cpu | 1e+03 | PerQuery-CostAware | 10.1 | 989 | 10.1 | 37.9 | yes |
+| cpu | 1e+03 | AutoSketch-Adapted | 2.7e+03 | 1.01e+03 | 2.7e+03 | 4e+03 | **no** |
+| cpu | 3e+03 | ASAP | 2.38 | 2.68e+03 | 2.38 | 11.8 | yes |
+| cpu | 3e+03 | ASAP (no roll-ups) | 2.38 | 2.68e+03 | 2.38 | 11.8 | yes |
+| cpu | 3e+03 | PerQuery-CostAware | 7.78 | 2.97e+03 | 7.78 | 38.5 | yes |
+| cpu | 3e+03 | AutoSketch-Adapted | 2.7e+03 | 1.01e+03 | 2.7e+03 | 4e+03 | yes |
+| cpu | 1e+04 | ASAP | 2.38 | 2.68e+03 | 2.38 | 11.8 | yes |
+| cpu | 1e+04 | ASAP (no roll-ups) | 2.38 | 2.68e+03 | 2.38 | 11.8 | yes |
+| cpu | 1e+04 | PerQuery-CostAware | 7.67 | 3.33e+03 | 7.67 | 39.8 | yes |
+| cpu | 1e+04 | AutoSketch-Adapted | 2.7e+03 | 1.01e+03 | 2.7e+03 | 4e+03 | yes |
+| fargate | 100 | ASAP | 1.41 | 96.9 | 33.4 | 12.2 | yes |
+| fargate | 100 | ASAP (no roll-ups) | 1.41 | 96.9 | 33.4 | 12.2 | yes |
+| fargate | 100 | PerQuery-CostAware | 2.45 | 97.4 | 56 | 40.2 | yes |
+| fargate | 100 | AutoSketch-Adapted | 127 | 1.01e+03 | 2.7e+03 | 4e+03 | **no** |
+| fargate | 300 | ASAP | 0.466 | 295 | 10.4 | 10.5 | yes |
+| fargate | 300 | ASAP (no roll-ups) | 0.466 | 295 | 10.4 | 10.5 | yes |
+| fargate | 300 | PerQuery-CostAware | 0.951 | 295 | 19.4 | 36.8 | yes |
+| fargate | 300 | AutoSketch-Adapted | 127 | 1.01e+03 | 2.7e+03 | 4e+03 | **no** |
+| fargate | 1e+03 | ASAP | 0.215 | 989 | 4.12 | 10.9 | yes |
+| fargate | 1e+03 | ASAP (no roll-ups) | 0.215 | 989 | 4.12 | 10.9 | yes |
+| fargate | 1e+03 | PerQuery-CostAware | 0.576 | 989 | 10.1 | 37.9 | yes |
+| fargate | 1e+03 | AutoSketch-Adapted | 127 | 1.01e+03 | 2.7e+03 | 4e+03 | **no** |
+| fargate | 3e+03 | ASAP | 0.149 | 2.68e+03 | 2.38 | 11.8 | yes |
+| fargate | 3e+03 | ASAP (no roll-ups) | 0.149 | 2.68e+03 | 2.38 | 11.8 | yes |
+| fargate | 3e+03 | PerQuery-CostAware | 0.487 | 2.97e+03 | 7.78 | 38.5 | yes |
+| fargate | 3e+03 | AutoSketch-Adapted | 127 | 1.01e+03 | 2.7e+03 | 4e+03 | yes |
+| fargate | 1e+04 | ASAP | 0.149 | 2.68e+03 | 2.38 | 11.8 | yes |
+| fargate | 1e+04 | ASAP (no roll-ups) | 0.149 | 2.68e+03 | 2.38 | 11.8 | yes |
+| fargate | 1e+04 | PerQuery-CostAware | 0.487 | 2.97e+03 | 7.78 | 38.5 | yes |
+| fargate | 1e+04 | AutoSketch-Adapted | 127 | 1.01e+03 | 2.7e+03 | 4e+03 | yes |
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | SLA (ms) | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|---|
-| cpu | 100 | 0 | 11 | 11 | 34.1 | 34.1 | 0.0% |
-| cpu | 300 | 0 | 10 | 10 | 10.6 | 10.6 | 0.0% |
-| cpu | 1e+03 | 0 | 7 | 7 | 4.22 | 4.22 | 0.0% |
-| cpu | 3e+03 | 0 | 6 | 6 | 2.41 | 2.41 | 0.0% |
-| cpu | 1e+04 | 0 | 6 | 6 | 2.41 | 2.41 | 0.0% |
-| fargate | 100 | 0 | 11 | 11 | 1.48 | 1.48 | 0.0% |
-| fargate | 300 | 0 | 10 | 10 | 0.499 | 0.499 | 0.0% |
-| fargate | 1e+03 | 0 | 7 | 7 | 0.242 | 0.242 | 0.0% |
-| fargate | 3e+03 | 0 | 6 | 6 | 0.17 | 0.17 | 0.0% |
-| fargate | 1e+04 | 0 | 6 | 6 | 0.17 | 0.17 | 0.0% |
+| cpu | 100 | 0 | 11 | 11 | 33.4 | 33.4 | 0.0% |
+| cpu | 300 | 0 | 10 | 10 | 10.4 | 10.4 | 0.0% |
+| cpu | 1e+03 | 0 | 7 | 7 | 4.12 | 4.12 | 0.0% |
+| cpu | 3e+03 | 0 | 6 | 6 | 2.38 | 2.38 | 0.0% |
+| cpu | 1e+04 | 0 | 6 | 6 | 2.38 | 2.38 | 0.0% |
+| fargate | 100 | 0 | 11 | 11 | 1.41 | 1.41 | 0.0% |
+| fargate | 300 | 0 | 10 | 10 | 0.466 | 0.466 | 0.0% |
+| fargate | 1e+03 | 0 | 7 | 7 | 0.215 | 0.215 | 0.0% |
+| fargate | 3e+03 | 0 | 6 | 6 | 0.149 | 0.149 | 0.0% |
+| fargate | 1e+04 | 0 | 6 | 6 | 0.149 | 0.149 | 0.0% |
 
 ## multi-grouping: 62 RQEs
 
-Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 490 ms; planning time (search + measured benchmark) 269 s.
+Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 490 ms; planning time (search + measured benchmark) 227 s.
 
 | weights | SLA (ms) | method | cost | latency (ms) | CPU (vCPU) | GiB | meets SLA |
 |---|---|---|---|---|---|---|---|
 | cpu | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 100 | AutoSketch-Adapted | 10.2 | 490 | 10.2 | 3.55 | **no** |
+| cpu | 100 | AutoSketch-Adapted | 9.65 | 490 | 9.65 | 3.51 | **no** |
 | cpu | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 300 | AutoSketch-Adapted | 10.2 | 490 | 10.2 | 3.55 | **no** |
-| cpu | 1e+03 | ASAP | 0.221 | 557 | 0.221 | 1.06 | yes |
-| cpu | 1e+03 | ASAP (no roll-ups) | 0.551 | 959 | 0.551 | 2.6 | yes |
-| cpu | 1e+03 | PerQuery-CostAware | 1.07 | 959 | 1.07 | 3.69 | yes |
-| cpu | 1e+03 | AutoSketch-Adapted | 10.2 | 490 | 10.2 | 3.55 | yes |
-| cpu | 3e+03 | ASAP | 0.221 | 557 | 0.221 | 1.06 | yes |
-| cpu | 3e+03 | ASAP (no roll-ups) | 0.551 | 959 | 0.551 | 2.6 | yes |
-| cpu | 3e+03 | PerQuery-CostAware | 1.07 | 959 | 1.07 | 3.69 | yes |
-| cpu | 3e+03 | AutoSketch-Adapted | 10.2 | 490 | 10.2 | 3.55 | yes |
-| cpu | 1e+04 | ASAP | 0.221 | 557 | 0.221 | 1.06 | yes |
-| cpu | 1e+04 | ASAP (no roll-ups) | 0.551 | 959 | 0.551 | 2.6 | yes |
-| cpu | 1e+04 | PerQuery-CostAware | 1.07 | 959 | 1.07 | 3.69 | yes |
-| cpu | 1e+04 | AutoSketch-Adapted | 10.2 | 490 | 10.2 | 3.55 | yes |
+| cpu | 300 | AutoSketch-Adapted | 9.65 | 490 | 9.65 | 3.51 | **no** |
+| cpu | 1e+03 | ASAP | 0.22 | 557 | 0.22 | 1.01 | yes |
+| cpu | 1e+03 | ASAP (no roll-ups) | 0.55 | 959 | 0.55 | 2.47 | yes |
+| cpu | 1e+03 | PerQuery-CostAware | 1.07 | 959 | 1.07 | 3.51 | yes |
+| cpu | 1e+03 | AutoSketch-Adapted | 9.65 | 490 | 9.65 | 3.51 | yes |
+| cpu | 3e+03 | ASAP | 0.22 | 557 | 0.22 | 1.01 | yes |
+| cpu | 3e+03 | ASAP (no roll-ups) | 0.55 | 959 | 0.55 | 2.47 | yes |
+| cpu | 3e+03 | PerQuery-CostAware | 1.07 | 959 | 1.07 | 3.51 | yes |
+| cpu | 3e+03 | AutoSketch-Adapted | 9.65 | 490 | 9.65 | 3.51 | yes |
+| cpu | 1e+04 | ASAP | 0.22 | 557 | 0.22 | 1.01 | yes |
+| cpu | 1e+04 | ASAP (no roll-ups) | 0.55 | 959 | 0.55 | 2.47 | yes |
+| cpu | 1e+04 | PerQuery-CostAware | 1.07 | 959 | 1.07 | 3.51 | yes |
+| cpu | 1e+04 | AutoSketch-Adapted | 9.65 | 490 | 9.65 | 3.51 | yes |
 | fargate | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 100 | AutoSketch-Adapted | 0.43 | 490 | 10.2 | 3.55 | **no** |
+| fargate | 100 | AutoSketch-Adapted | 0.406 | 490 | 9.65 | 3.51 | **no** |
 | fargate | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 300 | AutoSketch-Adapted | 0.43 | 490 | 10.2 | 3.55 | **no** |
-| fargate | 1e+03 | ASAP | 0.0137 | 557 | 0.224 | 1.03 | yes |
-| fargate | 1e+03 | ASAP (no roll-ups) | 0.0339 | 959 | 0.559 | 2.52 | yes |
-| fargate | 1e+03 | PerQuery-CostAware | 0.0597 | 959 | 1.08 | 3.61 | yes |
-| fargate | 1e+03 | AutoSketch-Adapted | 0.43 | 490 | 10.2 | 3.55 | yes |
-| fargate | 3e+03 | ASAP | 0.0137 | 557 | 0.224 | 1.03 | yes |
-| fargate | 3e+03 | ASAP (no roll-ups) | 0.0339 | 959 | 0.559 | 2.52 | yes |
-| fargate | 3e+03 | PerQuery-CostAware | 0.0597 | 959 | 1.08 | 3.61 | yes |
-| fargate | 3e+03 | AutoSketch-Adapted | 0.43 | 490 | 10.2 | 3.55 | yes |
-| fargate | 1e+04 | ASAP | 0.0137 | 557 | 0.224 | 1.03 | yes |
-| fargate | 1e+04 | ASAP (no roll-ups) | 0.0339 | 959 | 0.559 | 2.52 | yes |
-| fargate | 1e+04 | PerQuery-CostAware | 0.0597 | 959 | 1.08 | 3.61 | yes |
-| fargate | 1e+04 | AutoSketch-Adapted | 0.43 | 490 | 10.2 | 3.55 | yes |
+| fargate | 300 | AutoSketch-Adapted | 0.406 | 490 | 9.65 | 3.51 | **no** |
+| fargate | 1e+03 | ASAP | 0.0134 | 557 | 0.22 | 1.01 | yes |
+| fargate | 1e+03 | ASAP (no roll-ups) | 0.0333 | 959 | 0.55 | 2.47 | yes |
+| fargate | 1e+03 | PerQuery-CostAware | 0.0589 | 959 | 1.07 | 3.51 | yes |
+| fargate | 1e+03 | AutoSketch-Adapted | 0.406 | 490 | 9.65 | 3.51 | yes |
+| fargate | 3e+03 | ASAP | 0.0134 | 557 | 0.22 | 1.01 | yes |
+| fargate | 3e+03 | ASAP (no roll-ups) | 0.0333 | 959 | 0.55 | 2.47 | yes |
+| fargate | 3e+03 | PerQuery-CostAware | 0.0589 | 959 | 1.07 | 3.51 | yes |
+| fargate | 3e+03 | AutoSketch-Adapted | 0.406 | 490 | 9.65 | 3.51 | yes |
+| fargate | 1e+04 | ASAP | 0.0134 | 557 | 0.22 | 1.01 | yes |
+| fargate | 1e+04 | ASAP (no roll-ups) | 0.0333 | 959 | 0.55 | 2.47 | yes |
+| fargate | 1e+04 | PerQuery-CostAware | 0.0589 | 959 | 1.07 | 3.51 | yes |
+| fargate | 1e+04 | AutoSketch-Adapted | 0.406 | 490 | 9.65 | 3.51 | yes |
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | SLA (ms) | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|---|
-| cpu | 1e+03 | 52 | 5 | 26 | 0.221 | 0.551 | 59.9% |
-| cpu | 3e+03 | 52 | 5 | 26 | 0.221 | 0.551 | 59.9% |
-| cpu | 1e+04 | 52 | 5 | 26 | 0.221 | 0.551 | 59.9% |
-| fargate | 1e+03 | 52 | 5 | 26 | 0.0137 | 0.0339 | 59.7% |
-| fargate | 3e+03 | 52 | 5 | 26 | 0.0137 | 0.0339 | 59.7% |
-| fargate | 1e+04 | 52 | 5 | 26 | 0.0137 | 0.0339 | 59.7% |
+| cpu | 1e+03 | 52 | 5 | 26 | 0.22 | 0.55 | 60.0% |
+| cpu | 3e+03 | 52 | 5 | 26 | 0.22 | 0.55 | 60.0% |
+| cpu | 1e+04 | 52 | 5 | 26 | 0.22 | 0.55 | 60.0% |
+| fargate | 1e+03 | 52 | 5 | 26 | 0.0134 | 0.0333 | 59.7% |
+| fargate | 3e+03 | 52 | 5 | 26 | 0.0134 | 0.0333 | 59.7% |
+| fargate | 1e+04 | 52 | 5 | 26 | 0.0134 | 0.0333 | 59.7% |
 
 ## mixed, r = 8: 76 RQEs
 
-Sanity violations: 0. Tightest feasible SLA: ASAP 87.7 ms, PerQuery 87.7 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 212 s.
+Sanity violations: 0. Tightest feasible SLA: ASAP 87.7 ms, PerQuery 87.7 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 169 s.
 
 | weights | SLA (ms) | method | cost | latency (ms) | CPU (vCPU) | GiB | meets SLA |
 |---|---|---|---|---|---|---|---|
-| cpu | 100 | ASAP | 34.1 | 99.8 | 34.1 | 34.1 | yes |
-| cpu | 100 | ASAP (no roll-ups) | 34.1 | 99.8 | 34.1 | 34.1 | yes |
-| cpu | 100 | PerQuery-CostAware | 74 | 97.4 | 74 | 106 | yes |
-| cpu | 100 | AutoSketch-Adapted | 3.28e+03 | 1.01e+03 | 3.28e+03 | 5.85e+03 | **no** |
-| cpu | 300 | ASAP | 10.6 | 291 | 10.6 | 15.5 | yes |
-| cpu | 300 | ASAP (no roll-ups) | 10.6 | 291 | 10.6 | 15.5 | yes |
-| cpu | 300 | PerQuery-CostAware | 28.8 | 291 | 28.8 | 98 | yes |
-| cpu | 300 | AutoSketch-Adapted | 3.28e+03 | 1.01e+03 | 3.28e+03 | 5.85e+03 | **no** |
-| cpu | 1e+03 | ASAP | 4.25 | 980 | 4.25 | 29.1 | yes |
-| cpu | 1e+03 | ASAP (no roll-ups) | 4.25 | 980 | 4.25 | 29.1 | yes |
-| cpu | 1e+03 | PerQuery-CostAware | 16.5 | 980 | 16.5 | 185 | yes |
-| cpu | 1e+03 | AutoSketch-Adapted | 3.28e+03 | 1.01e+03 | 3.28e+03 | 5.85e+03 | **no** |
-| cpu | 3e+03 | ASAP | 2.47 | 2.68e+03 | 2.47 | 16.3 | yes |
-| cpu | 3e+03 | ASAP (no roll-ups) | 2.47 | 2.68e+03 | 2.47 | 16.3 | yes |
-| cpu | 3e+03 | PerQuery-CostAware | 13.8 | 2.68e+03 | 13.8 | 169 | yes |
-| cpu | 3e+03 | AutoSketch-Adapted | 3.28e+03 | 1.01e+03 | 3.28e+03 | 5.85e+03 | yes |
-| cpu | 1e+04 | ASAP | 2.47 | 2.68e+03 | 2.47 | 16.3 | yes |
-| cpu | 1e+04 | ASAP (no roll-ups) | 2.47 | 2.68e+03 | 2.47 | 16.3 | yes |
-| cpu | 1e+04 | PerQuery-CostAware | 13.6 | 3.33e+03 | 13.6 | 103 | yes |
-| cpu | 1e+04 | AutoSketch-Adapted | 3.28e+03 | 1.01e+03 | 3.28e+03 | 5.85e+03 | yes |
-| fargate | 100 | ASAP | 1.48 | 96.9 | 34.5 | 18.2 | yes |
-| fargate | 100 | ASAP (no roll-ups) | 1.48 | 96.9 | 34.5 | 18.2 | yes |
-| fargate | 100 | PerQuery-CostAware | 3.4 | 97.4 | 74.4 | 87.7 | yes |
-| fargate | 100 | AutoSketch-Adapted | 159 | 1.01e+03 | 3.28e+03 | 5.85e+03 | **no** |
-| fargate | 300 | ASAP | 0.5 | 291 | 10.6 | 15.5 | yes |
-| fargate | 300 | ASAP (no roll-ups) | 0.5 | 291 | 10.6 | 15.5 | yes |
-| fargate | 300 | PerQuery-CostAware | 1.53 | 291 | 29 | 79.8 | yes |
-| fargate | 300 | AutoSketch-Adapted | 159 | 1.01e+03 | 3.28e+03 | 5.85e+03 | **no** |
-| fargate | 1e+03 | ASAP | 0.243 | 896 | 4.26 | 15.7 | yes |
-| fargate | 1e+03 | ASAP (no roll-ups) | 0.243 | 896 | 4.26 | 15.7 | yes |
-| fargate | 1e+03 | PerQuery-CostAware | 1.04 | 896 | 16.8 | 80.3 | yes |
-| fargate | 1e+03 | AutoSketch-Adapted | 159 | 1.01e+03 | 3.28e+03 | 5.85e+03 | **no** |
-| fargate | 3e+03 | ASAP | 0.173 | 2.68e+03 | 2.47 | 16.3 | yes |
-| fargate | 3e+03 | ASAP (no roll-ups) | 0.173 | 2.68e+03 | 2.47 | 16.3 | yes |
-| fargate | 3e+03 | PerQuery-CostAware | 0.924 | 2.68e+03 | 13.9 | 80.9 | yes |
-| fargate | 3e+03 | AutoSketch-Adapted | 159 | 1.01e+03 | 3.28e+03 | 5.85e+03 | yes |
-| fargate | 1e+04 | ASAP | 0.173 | 2.68e+03 | 2.47 | 16.3 | yes |
-| fargate | 1e+04 | ASAP (no roll-ups) | 0.173 | 2.68e+03 | 2.47 | 16.3 | yes |
-| fargate | 1e+04 | PerQuery-CostAware | 0.919 | 3.26e+03 | 13.8 | 80.9 | yes |
-| fargate | 1e+04 | AutoSketch-Adapted | 159 | 1.01e+03 | 3.28e+03 | 5.85e+03 | yes |
+| cpu | 100 | ASAP | 33.4 | 96.9 | 33.4 | 12.2 | yes |
+| cpu | 100 | ASAP (no roll-ups) | 33.4 | 96.9 | 33.4 | 12.2 | yes |
+| cpu | 100 | PerQuery-CostAware | 68.9 | 97.4 | 68.9 | 47.3 | yes |
+| cpu | 100 | AutoSketch-Adapted | 3.24e+03 | 1.01e+03 | 3.24e+03 | 4.16e+03 | **no** |
+| cpu | 300 | ASAP | 10.4 | 295 | 10.4 | 10.5 | yes |
+| cpu | 300 | ASAP (no roll-ups) | 10.4 | 295 | 10.4 | 10.5 | yes |
+| cpu | 300 | PerQuery-CostAware | 26.7 | 295 | 26.7 | 43.9 | yes |
+| cpu | 300 | AutoSketch-Adapted | 3.24e+03 | 1.01e+03 | 3.24e+03 | 4.16e+03 | **no** |
+| cpu | 1e+03 | ASAP | 4.16 | 989 | 4.16 | 10.9 | yes |
+| cpu | 1e+03 | ASAP (no roll-ups) | 4.16 | 989 | 4.16 | 10.9 | yes |
+| cpu | 1e+03 | PerQuery-CostAware | 16 | 989 | 16 | 45.2 | yes |
+| cpu | 1e+03 | AutoSketch-Adapted | 3.24e+03 | 1.01e+03 | 3.24e+03 | 4.16e+03 | **no** |
+| cpu | 3e+03 | ASAP | 2.43 | 2.68e+03 | 2.43 | 11.8 | yes |
+| cpu | 3e+03 | ASAP (no roll-ups) | 2.43 | 2.68e+03 | 2.43 | 11.8 | yes |
+| cpu | 3e+03 | PerQuery-CostAware | 13.6 | 2.97e+03 | 13.6 | 45.8 | yes |
+| cpu | 3e+03 | AutoSketch-Adapted | 3.24e+03 | 1.01e+03 | 3.24e+03 | 4.16e+03 | yes |
+| cpu | 1e+04 | ASAP | 2.43 | 2.68e+03 | 2.43 | 11.8 | yes |
+| cpu | 1e+04 | ASAP (no roll-ups) | 2.43 | 2.68e+03 | 2.43 | 11.8 | yes |
+| cpu | 1e+04 | PerQuery-CostAware | 13.5 | 3.33e+03 | 13.5 | 47 | yes |
+| cpu | 1e+04 | AutoSketch-Adapted | 3.24e+03 | 1.01e+03 | 3.24e+03 | 4.16e+03 | yes |
+| fargate | 100 | ASAP | 1.41 | 96.9 | 33.4 | 12.2 | yes |
+| fargate | 100 | ASAP (no roll-ups) | 1.41 | 96.9 | 33.4 | 12.2 | yes |
+| fargate | 100 | PerQuery-CostAware | 3 | 97.4 | 68.9 | 47.3 | yes |
+| fargate | 100 | AutoSketch-Adapted | 150 | 1.01e+03 | 3.24e+03 | 4.16e+03 | **no** |
+| fargate | 300 | ASAP | 0.467 | 295 | 10.4 | 10.5 | yes |
+| fargate | 300 | ASAP (no roll-ups) | 0.467 | 295 | 10.4 | 10.5 | yes |
+| fargate | 300 | PerQuery-CostAware | 1.28 | 295 | 26.7 | 43.9 | yes |
+| fargate | 300 | AutoSketch-Adapted | 150 | 1.01e+03 | 3.24e+03 | 4.16e+03 | **no** |
+| fargate | 1e+03 | ASAP | 0.217 | 989 | 4.16 | 10.9 | yes |
+| fargate | 1e+03 | ASAP (no roll-ups) | 0.217 | 989 | 4.16 | 10.9 | yes |
+| fargate | 1e+03 | PerQuery-CostAware | 0.851 | 989 | 16 | 45.2 | yes |
+| fargate | 1e+03 | AutoSketch-Adapted | 150 | 1.01e+03 | 3.24e+03 | 4.16e+03 | **no** |
+| fargate | 3e+03 | ASAP | 0.151 | 2.68e+03 | 2.43 | 11.8 | yes |
+| fargate | 3e+03 | ASAP (no roll-ups) | 0.151 | 2.68e+03 | 2.43 | 11.8 | yes |
+| fargate | 3e+03 | PerQuery-CostAware | 0.754 | 2.97e+03 | 13.6 | 45.8 | yes |
+| fargate | 3e+03 | AutoSketch-Adapted | 150 | 1.01e+03 | 3.24e+03 | 4.16e+03 | yes |
+| fargate | 1e+04 | ASAP | 0.151 | 2.68e+03 | 2.43 | 11.8 | yes |
+| fargate | 1e+04 | ASAP (no roll-ups) | 0.151 | 2.68e+03 | 2.43 | 11.8 | yes |
+| fargate | 1e+04 | PerQuery-CostAware | 0.754 | 2.97e+03 | 13.6 | 45.8 | yes |
+| fargate | 1e+04 | AutoSketch-Adapted | 150 | 1.01e+03 | 3.24e+03 | 4.16e+03 | yes |
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | SLA (ms) | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|---|
-| cpu | 100 | 0 | 11 | 11 | 34.1 | 34.1 | 0.0% |
-| cpu | 300 | 0 | 10 | 10 | 10.6 | 10.6 | 0.0% |
-| cpu | 1e+03 | 0 | 7 | 7 | 4.25 | 4.25 | 0.0% |
-| cpu | 3e+03 | 0 | 6 | 6 | 2.47 | 2.47 | 0.0% |
-| cpu | 1e+04 | 0 | 6 | 6 | 2.47 | 2.47 | 0.0% |
-| fargate | 100 | 0 | 11 | 11 | 1.48 | 1.48 | 0.0% |
-| fargate | 300 | 0 | 10 | 10 | 0.5 | 0.5 | 0.0% |
-| fargate | 1e+03 | 0 | 7 | 7 | 0.243 | 0.243 | 0.0% |
-| fargate | 3e+03 | 0 | 6 | 6 | 0.173 | 0.173 | 0.0% |
-| fargate | 1e+04 | 0 | 6 | 6 | 0.173 | 0.173 | 0.0% |
+| cpu | 100 | 0 | 11 | 11 | 33.4 | 33.4 | 0.0% |
+| cpu | 300 | 0 | 10 | 10 | 10.4 | 10.4 | 0.0% |
+| cpu | 1e+03 | 0 | 7 | 7 | 4.16 | 4.16 | 0.0% |
+| cpu | 3e+03 | 0 | 6 | 6 | 2.43 | 2.43 | 0.0% |
+| cpu | 1e+04 | 0 | 6 | 6 | 2.43 | 2.43 | 0.0% |
+| fargate | 100 | 0 | 11 | 11 | 1.41 | 1.41 | 0.0% |
+| fargate | 300 | 0 | 10 | 10 | 0.467 | 0.467 | 0.0% |
+| fargate | 1e+03 | 0 | 7 | 7 | 0.217 | 0.217 | 0.0% |
+| fargate | 3e+03 | 0 | 6 | 6 | 0.151 | 0.151 | 0.0% |
+| fargate | 1e+04 | 0 | 6 | 6 | 0.151 | 0.151 | 0.0% |
 
 ## mixed + multi-grouping: 104 RQEs
 
-Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 481 s.
+Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 396 s.
 
 | weights | SLA (ms) | method | cost | latency (ms) | CPU (vCPU) | GiB | meets SLA |
 |---|---|---|---|---|---|---|---|
 | cpu | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 100 | AutoSketch-Adapted | 2.75e+03 | 1.01e+03 | 2.75e+03 | 5.62e+03 | **no** |
+| cpu | 100 | AutoSketch-Adapted | 2.71e+03 | 1.01e+03 | 2.71e+03 | 4.01e+03 | **no** |
 | cpu | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 300 | AutoSketch-Adapted | 2.75e+03 | 1.01e+03 | 2.75e+03 | 5.62e+03 | **no** |
-| cpu | 1e+03 | ASAP | 4.44 | 980 | 4.44 | 30.2 | yes |
-| cpu | 1e+03 | ASAP (no roll-ups) | 4.77 | 980 | 4.77 | 31.7 | yes |
-| cpu | 1e+03 | PerQuery-CostAware | 11.5 | 980 | 11.5 | 158 | yes |
-| cpu | 1e+03 | AutoSketch-Adapted | 2.75e+03 | 1.01e+03 | 2.75e+03 | 5.62e+03 | **no** |
-| cpu | 3e+03 | ASAP | 2.64 | 2.68e+03 | 2.64 | 17.4 | yes |
-| cpu | 3e+03 | ASAP (no roll-ups) | 2.97 | 2.68e+03 | 2.97 | 18.9 | yes |
-| cpu | 3e+03 | PerQuery-CostAware | 9.05 | 2.68e+03 | 9.05 | 142 | yes |
-| cpu | 3e+03 | AutoSketch-Adapted | 2.75e+03 | 1.01e+03 | 2.75e+03 | 5.62e+03 | yes |
-| cpu | 1e+04 | ASAP | 2.64 | 2.68e+03 | 2.64 | 17.4 | yes |
-| cpu | 1e+04 | ASAP (no roll-ups) | 2.97 | 2.68e+03 | 2.97 | 18.9 | yes |
-| cpu | 1e+04 | PerQuery-CostAware | 8.84 | 3.33e+03 | 8.84 | 76.4 | yes |
-| cpu | 1e+04 | AutoSketch-Adapted | 2.75e+03 | 1.01e+03 | 2.75e+03 | 5.62e+03 | yes |
+| cpu | 300 | AutoSketch-Adapted | 2.71e+03 | 1.01e+03 | 2.71e+03 | 4.01e+03 | **no** |
+| cpu | 1e+03 | ASAP | 4.34 | 989 | 4.34 | 11.9 | yes |
+| cpu | 1e+03 | ASAP (no roll-ups) | 4.67 | 989 | 4.67 | 13.3 | yes |
+| cpu | 1e+03 | PerQuery-CostAware | 11.1 | 989 | 11.1 | 41.4 | yes |
+| cpu | 1e+03 | AutoSketch-Adapted | 2.71e+03 | 1.01e+03 | 2.71e+03 | 4.01e+03 | **no** |
+| cpu | 3e+03 | ASAP | 2.6 | 2.68e+03 | 2.6 | 12.8 | yes |
+| cpu | 3e+03 | ASAP (no roll-ups) | 2.93 | 2.68e+03 | 2.93 | 14.3 | yes |
+| cpu | 3e+03 | PerQuery-CostAware | 8.85 | 2.97e+03 | 8.85 | 42 | yes |
+| cpu | 3e+03 | AutoSketch-Adapted | 2.71e+03 | 1.01e+03 | 2.71e+03 | 4.01e+03 | yes |
+| cpu | 1e+04 | ASAP | 2.6 | 2.68e+03 | 2.6 | 12.8 | yes |
+| cpu | 1e+04 | ASAP (no roll-ups) | 2.93 | 2.68e+03 | 2.93 | 14.3 | yes |
+| cpu | 1e+04 | PerQuery-CostAware | 8.74 | 3.33e+03 | 8.74 | 43.3 | yes |
+| cpu | 1e+04 | AutoSketch-Adapted | 2.71e+03 | 1.01e+03 | 2.71e+03 | 4.01e+03 | yes |
 | fargate | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 100 | AutoSketch-Adapted | 136 | 1.01e+03 | 2.75e+03 | 5.62e+03 | **no** |
+| fargate | 100 | AutoSketch-Adapted | 128 | 1.01e+03 | 2.71e+03 | 4.01e+03 | **no** |
 | fargate | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 300 | AutoSketch-Adapted | 136 | 1.01e+03 | 2.75e+03 | 5.62e+03 | **no** |
-| fargate | 1e+03 | ASAP | 0.255 | 896 | 4.46 | 16.7 | yes |
-| fargate | 1e+03 | ASAP (no roll-ups) | 0.275 | 959 | 4.8 | 18.2 | yes |
-| fargate | 1e+03 | PerQuery-CostAware | 0.792 | 959 | 11.8 | 70.9 | yes |
-| fargate | 1e+03 | AutoSketch-Adapted | 136 | 1.01e+03 | 2.75e+03 | 5.62e+03 | **no** |
-| fargate | 3e+03 | ASAP | 0.184 | 2.68e+03 | 2.64 | 17.4 | yes |
-| fargate | 3e+03 | ASAP (no roll-ups) | 0.204 | 2.68e+03 | 2.97 | 18.8 | yes |
-| fargate | 3e+03 | PerQuery-CostAware | 0.688 | 2.68e+03 | 9.12 | 71.5 | yes |
-| fargate | 3e+03 | AutoSketch-Adapted | 136 | 1.01e+03 | 2.75e+03 | 5.62e+03 | yes |
-| fargate | 1e+04 | ASAP | 0.184 | 2.68e+03 | 2.64 | 17.4 | yes |
-| fargate | 1e+04 | ASAP (no roll-ups) | 0.204 | 2.68e+03 | 2.97 | 18.8 | yes |
-| fargate | 1e+04 | PerQuery-CostAware | 0.683 | 3.26e+03 | 9 | 71.5 | yes |
-| fargate | 1e+04 | AutoSketch-Adapted | 136 | 1.01e+03 | 2.75e+03 | 5.62e+03 | yes |
+| fargate | 300 | AutoSketch-Adapted | 128 | 1.01e+03 | 2.71e+03 | 4.01e+03 | **no** |
+| fargate | 1e+03 | ASAP | 0.229 | 989 | 4.34 | 11.9 | yes |
+| fargate | 1e+03 | ASAP (no roll-ups) | 0.249 | 989 | 4.67 | 13.3 | yes |
+| fargate | 1e+03 | PerQuery-CostAware | 0.635 | 989 | 11.1 | 41.4 | yes |
+| fargate | 1e+03 | AutoSketch-Adapted | 128 | 1.01e+03 | 2.71e+03 | 4.01e+03 | **no** |
+| fargate | 3e+03 | ASAP | 0.162 | 2.68e+03 | 2.6 | 12.8 | yes |
+| fargate | 3e+03 | ASAP (no roll-ups) | 0.182 | 2.68e+03 | 2.93 | 14.3 | yes |
+| fargate | 3e+03 | PerQuery-CostAware | 0.545 | 2.97e+03 | 8.85 | 42 | yes |
+| fargate | 3e+03 | AutoSketch-Adapted | 128 | 1.01e+03 | 2.71e+03 | 4.01e+03 | yes |
+| fargate | 1e+04 | ASAP | 0.162 | 2.68e+03 | 2.6 | 12.8 | yes |
+| fargate | 1e+04 | ASAP (no roll-ups) | 0.182 | 2.68e+03 | 2.93 | 14.3 | yes |
+| fargate | 1e+04 | PerQuery-CostAware | 0.545 | 2.97e+03 | 8.85 | 42 | yes |
+| fargate | 1e+04 | AutoSketch-Adapted | 128 | 1.01e+03 | 2.71e+03 | 4.01e+03 | yes |
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | SLA (ms) | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|---|
-| cpu | 1e+03 | 52 | 12 | 33 | 4.44 | 4.77 | 6.9% |
-| cpu | 3e+03 | 52 | 11 | 32 | 2.64 | 2.97 | 11.1% |
-| cpu | 1e+04 | 52 | 11 | 32 | 2.64 | 2.97 | 11.1% |
-| fargate | 1e+03 | 52 | 12 | 33 | 0.255 | 0.275 | 7.3% |
-| fargate | 3e+03 | 52 | 11 | 32 | 0.184 | 0.204 | 9.9% |
-| fargate | 1e+04 | 52 | 11 | 32 | 0.184 | 0.204 | 9.9% |
+| cpu | 1e+03 | 52 | 12 | 33 | 4.34 | 4.67 | 7.1% |
+| cpu | 3e+03 | 52 | 11 | 32 | 2.6 | 2.93 | 11.3% |
+| cpu | 1e+04 | 52 | 11 | 32 | 2.6 | 2.93 | 11.3% |
+| fargate | 1e+03 | 52 | 12 | 33 | 0.229 | 0.249 | 8.0% |
+| fargate | 3e+03 | 52 | 11 | 32 | 0.162 | 0.182 | 10.9% |
+| fargate | 1e+04 | 52 | 11 | 32 | 0.162 | 0.182 | 10.9% |
 
 ## multi-grouping, r = 8: 124 RQEs
 
-Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 490 ms; planning time (search + measured benchmark) 269 s.
+Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 490 ms; planning time (search + measured benchmark) 227 s.
 
 | weights | SLA (ms) | method | cost | latency (ms) | CPU (vCPU) | GiB | meets SLA |
 |---|---|---|---|---|---|---|---|
 | cpu | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 100 | AutoSketch-Adapted | 12.3 | 490 | 12.3 | 4.52 | **no** |
+| cpu | 100 | AutoSketch-Adapted | 11.6 | 490 | 11.6 | 4.46 | **no** |
 | cpu | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 300 | AutoSketch-Adapted | 12.3 | 490 | 12.3 | 4.52 | **no** |
-| cpu | 1e+03 | ASAP | 0.242 | 557 | 0.242 | 1.06 | yes |
-| cpu | 1e+03 | ASAP (no roll-ups) | 0.573 | 959 | 0.573 | 2.6 | yes |
-| cpu | 1e+03 | PerQuery-CostAware | 2.04 | 959 | 2.04 | 4.69 | yes |
-| cpu | 1e+03 | AutoSketch-Adapted | 12.3 | 490 | 12.3 | 4.52 | yes |
-| cpu | 3e+03 | ASAP | 0.242 | 557 | 0.242 | 1.06 | yes |
-| cpu | 3e+03 | ASAP (no roll-ups) | 0.573 | 959 | 0.573 | 2.6 | yes |
-| cpu | 3e+03 | PerQuery-CostAware | 2.04 | 959 | 2.04 | 4.69 | yes |
-| cpu | 3e+03 | AutoSketch-Adapted | 12.3 | 490 | 12.3 | 4.52 | yes |
-| cpu | 1e+04 | ASAP | 0.242 | 557 | 0.242 | 1.06 | yes |
-| cpu | 1e+04 | ASAP (no roll-ups) | 0.573 | 959 | 0.573 | 2.6 | yes |
-| cpu | 1e+04 | PerQuery-CostAware | 2.04 | 959 | 2.04 | 4.69 | yes |
-| cpu | 1e+04 | AutoSketch-Adapted | 12.3 | 490 | 12.3 | 4.52 | yes |
+| cpu | 300 | AutoSketch-Adapted | 11.6 | 490 | 11.6 | 4.46 | **no** |
+| cpu | 1e+03 | ASAP | 0.241 | 557 | 0.241 | 1.01 | yes |
+| cpu | 1e+03 | ASAP (no roll-ups) | 0.572 | 959 | 0.572 | 2.47 | yes |
+| cpu | 1e+03 | PerQuery-CostAware | 2.04 | 959 | 2.04 | 4.47 | yes |
+| cpu | 1e+03 | AutoSketch-Adapted | 11.6 | 490 | 11.6 | 4.46 | yes |
+| cpu | 3e+03 | ASAP | 0.241 | 557 | 0.241 | 1.01 | yes |
+| cpu | 3e+03 | ASAP (no roll-ups) | 0.572 | 959 | 0.572 | 2.47 | yes |
+| cpu | 3e+03 | PerQuery-CostAware | 2.04 | 959 | 2.04 | 4.47 | yes |
+| cpu | 3e+03 | AutoSketch-Adapted | 11.6 | 490 | 11.6 | 4.46 | yes |
+| cpu | 1e+04 | ASAP | 0.241 | 557 | 0.241 | 1.01 | yes |
+| cpu | 1e+04 | ASAP (no roll-ups) | 0.572 | 959 | 0.572 | 2.47 | yes |
+| cpu | 1e+04 | PerQuery-CostAware | 2.04 | 959 | 2.04 | 4.47 | yes |
+| cpu | 1e+04 | AutoSketch-Adapted | 11.6 | 490 | 11.6 | 4.46 | yes |
 | fargate | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 100 | AutoSketch-Adapted | 0.517 | 490 | 12.3 | 4.52 | **no** |
+| fargate | 100 | AutoSketch-Adapted | 0.489 | 490 | 11.6 | 4.46 | **no** |
 | fargate | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 300 | AutoSketch-Adapted | 0.517 | 490 | 12.3 | 4.52 | **no** |
-| fargate | 1e+03 | ASAP | 0.0145 | 557 | 0.245 | 1.03 | yes |
-| fargate | 1e+03 | ASAP (no roll-ups) | 0.0347 | 959 | 0.581 | 2.52 | yes |
-| fargate | 1e+03 | PerQuery-CostAware | 0.104 | 959 | 2.05 | 4.62 | yes |
-| fargate | 1e+03 | AutoSketch-Adapted | 0.517 | 490 | 12.3 | 4.52 | yes |
-| fargate | 3e+03 | ASAP | 0.0145 | 557 | 0.245 | 1.03 | yes |
-| fargate | 3e+03 | ASAP (no roll-ups) | 0.0347 | 959 | 0.581 | 2.52 | yes |
-| fargate | 3e+03 | PerQuery-CostAware | 0.104 | 959 | 2.05 | 4.62 | yes |
-| fargate | 3e+03 | AutoSketch-Adapted | 0.517 | 490 | 12.3 | 4.52 | yes |
-| fargate | 1e+04 | ASAP | 0.0145 | 557 | 0.245 | 1.03 | yes |
-| fargate | 1e+04 | ASAP (no roll-ups) | 0.0347 | 959 | 0.581 | 2.52 | yes |
-| fargate | 1e+04 | PerQuery-CostAware | 0.104 | 959 | 2.05 | 4.62 | yes |
-| fargate | 1e+04 | AutoSketch-Adapted | 0.517 | 490 | 12.3 | 4.52 | yes |
+| fargate | 300 | AutoSketch-Adapted | 0.489 | 490 | 11.6 | 4.46 | **no** |
+| fargate | 1e+03 | ASAP | 0.0143 | 557 | 0.241 | 1.01 | yes |
+| fargate | 1e+03 | ASAP (no roll-ups) | 0.0342 | 959 | 0.572 | 2.47 | yes |
+| fargate | 1e+03 | PerQuery-CostAware | 0.103 | 959 | 2.04 | 4.47 | yes |
+| fargate | 1e+03 | AutoSketch-Adapted | 0.489 | 490 | 11.6 | 4.46 | yes |
+| fargate | 3e+03 | ASAP | 0.0143 | 557 | 0.241 | 1.01 | yes |
+| fargate | 3e+03 | ASAP (no roll-ups) | 0.0342 | 959 | 0.572 | 2.47 | yes |
+| fargate | 3e+03 | PerQuery-CostAware | 0.103 | 959 | 2.04 | 4.47 | yes |
+| fargate | 3e+03 | AutoSketch-Adapted | 0.489 | 490 | 11.6 | 4.46 | yes |
+| fargate | 1e+04 | ASAP | 0.0143 | 557 | 0.241 | 1.01 | yes |
+| fargate | 1e+04 | ASAP (no roll-ups) | 0.0342 | 959 | 0.572 | 2.47 | yes |
+| fargate | 1e+04 | PerQuery-CostAware | 0.103 | 959 | 2.04 | 4.47 | yes |
+| fargate | 1e+04 | AutoSketch-Adapted | 0.489 | 490 | 11.6 | 4.46 | yes |
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | SLA (ms) | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|---|
-| cpu | 1e+03 | 104 | 5 | 26 | 0.242 | 0.573 | 57.8% |
-| cpu | 3e+03 | 104 | 5 | 26 | 0.242 | 0.573 | 57.8% |
-| cpu | 1e+04 | 104 | 5 | 26 | 0.242 | 0.573 | 57.8% |
-| fargate | 1e+03 | 104 | 5 | 26 | 0.0145 | 0.0347 | 58.2% |
-| fargate | 3e+03 | 104 | 5 | 26 | 0.0145 | 0.0347 | 58.2% |
-| fargate | 1e+04 | 104 | 5 | 26 | 0.0145 | 0.0347 | 58.2% |
+| cpu | 1e+03 | 104 | 5 | 26 | 0.241 | 0.572 | 57.9% |
+| cpu | 3e+03 | 104 | 5 | 26 | 0.241 | 0.572 | 57.9% |
+| cpu | 1e+04 | 104 | 5 | 26 | 0.241 | 0.572 | 57.9% |
+| fargate | 1e+03 | 104 | 5 | 26 | 0.0143 | 0.0342 | 58.2% |
+| fargate | 3e+03 | 104 | 5 | 26 | 0.0143 | 0.0342 | 58.2% |
+| fargate | 1e+04 | 104 | 5 | 26 | 0.0143 | 0.0342 | 58.2% |
 
 ## mixed + multi-grouping, r = 8: 200 RQEs
 
-Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 481 s.
+Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 396 s.
 
 | weights | SLA (ms) | method | cost | latency (ms) | CPU (vCPU) | GiB | meets SLA |
 |---|---|---|---|---|---|---|---|
 | cpu | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 100 | AutoSketch-Adapted | 3.3e+03 | 1.01e+03 | 3.3e+03 | 5.85e+03 | **no** |
+| cpu | 100 | AutoSketch-Adapted | 3.25e+03 | 1.01e+03 | 3.25e+03 | 4.17e+03 | **no** |
 | cpu | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 300 | AutoSketch-Adapted | 3.3e+03 | 1.01e+03 | 3.3e+03 | 5.85e+03 | **no** |
-| cpu | 1e+03 | ASAP | 4.49 | 980 | 4.49 | 30.2 | yes |
-| cpu | 1e+03 | ASAP (no roll-ups) | 4.83 | 980 | 4.83 | 31.7 | yes |
-| cpu | 1e+03 | PerQuery-CostAware | 18.5 | 980 | 18.5 | 189 | yes |
-| cpu | 1e+03 | AutoSketch-Adapted | 3.3e+03 | 1.01e+03 | 3.3e+03 | 5.85e+03 | **no** |
-| cpu | 3e+03 | ASAP | 2.71 | 2.68e+03 | 2.71 | 17.4 | yes |
-| cpu | 3e+03 | ASAP (no roll-ups) | 3.04 | 2.68e+03 | 3.04 | 18.9 | yes |
-| cpu | 3e+03 | PerQuery-CostAware | 15.8 | 2.68e+03 | 15.8 | 173 | yes |
-| cpu | 3e+03 | AutoSketch-Adapted | 3.3e+03 | 1.01e+03 | 3.3e+03 | 5.85e+03 | yes |
-| cpu | 1e+04 | ASAP | 2.71 | 2.68e+03 | 2.71 | 17.4 | yes |
-| cpu | 1e+04 | ASAP (no roll-ups) | 3.04 | 2.68e+03 | 3.04 | 18.9 | yes |
-| cpu | 1e+04 | PerQuery-CostAware | 15.6 | 3.33e+03 | 15.6 | 107 | yes |
-| cpu | 1e+04 | AutoSketch-Adapted | 3.3e+03 | 1.01e+03 | 3.3e+03 | 5.85e+03 | yes |
+| cpu | 300 | AutoSketch-Adapted | 3.25e+03 | 1.01e+03 | 3.25e+03 | 4.17e+03 | **no** |
+| cpu | 1e+03 | ASAP | 4.4 | 989 | 4.4 | 11.9 | yes |
+| cpu | 1e+03 | ASAP (no roll-ups) | 4.73 | 989 | 4.73 | 13.3 | yes |
+| cpu | 1e+03 | PerQuery-CostAware | 18.1 | 989 | 18.1 | 49.6 | yes |
+| cpu | 1e+03 | AutoSketch-Adapted | 3.25e+03 | 1.01e+03 | 3.25e+03 | 4.17e+03 | **no** |
+| cpu | 3e+03 | ASAP | 2.68 | 2.68e+03 | 2.68 | 12.8 | yes |
+| cpu | 3e+03 | ASAP (no roll-ups) | 3.01 | 2.68e+03 | 3.01 | 14.3 | yes |
+| cpu | 3e+03 | PerQuery-CostAware | 15.6 | 2.97e+03 | 15.6 | 50.2 | yes |
+| cpu | 3e+03 | AutoSketch-Adapted | 3.25e+03 | 1.01e+03 | 3.25e+03 | 4.17e+03 | yes |
+| cpu | 1e+04 | ASAP | 2.68 | 2.68e+03 | 2.68 | 12.8 | yes |
+| cpu | 1e+04 | ASAP (no roll-ups) | 3.01 | 2.68e+03 | 3.01 | 14.3 | yes |
+| cpu | 1e+04 | PerQuery-CostAware | 15.5 | 3.33e+03 | 15.5 | 51.5 | yes |
+| cpu | 1e+04 | AutoSketch-Adapted | 3.25e+03 | 1.01e+03 | 3.25e+03 | 4.17e+03 | yes |
 | fargate | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 100 | AutoSketch-Adapted | 160 | 1.01e+03 | 3.3e+03 | 5.85e+03 | **no** |
+| fargate | 100 | AutoSketch-Adapted | 150 | 1.01e+03 | 3.25e+03 | 4.17e+03 | **no** |
 | fargate | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 300 | AutoSketch-Adapted | 160 | 1.01e+03 | 3.3e+03 | 5.85e+03 | **no** |
-| fargate | 1e+03 | ASAP | 0.257 | 896 | 4.51 | 16.7 | yes |
-| fargate | 1e+03 | ASAP (no roll-ups) | 0.277 | 959 | 4.84 | 18.2 | yes |
-| fargate | 1e+03 | PerQuery-CostAware | 1.14 | 959 | 18.8 | 84.9 | yes |
-| fargate | 1e+03 | AutoSketch-Adapted | 160 | 1.01e+03 | 3.3e+03 | 5.85e+03 | **no** |
-| fargate | 3e+03 | ASAP | 0.187 | 2.68e+03 | 2.72 | 17.4 | yes |
-| fargate | 3e+03 | ASAP (no roll-ups) | 0.207 | 2.68e+03 | 3.05 | 18.8 | yes |
-| fargate | 3e+03 | PerQuery-CostAware | 1.03 | 2.68e+03 | 16 | 85.5 | yes |
-| fargate | 3e+03 | AutoSketch-Adapted | 160 | 1.01e+03 | 3.3e+03 | 5.85e+03 | yes |
-| fargate | 1e+04 | ASAP | 0.187 | 2.68e+03 | 2.72 | 17.4 | yes |
-| fargate | 1e+04 | ASAP (no roll-ups) | 0.207 | 2.68e+03 | 3.05 | 18.8 | yes |
-| fargate | 1e+04 | PerQuery-CostAware | 1.02 | 3.26e+03 | 15.8 | 85.5 | yes |
-| fargate | 1e+04 | AutoSketch-Adapted | 160 | 1.01e+03 | 3.3e+03 | 5.85e+03 | yes |
+| fargate | 300 | AutoSketch-Adapted | 150 | 1.01e+03 | 3.25e+03 | 4.17e+03 | **no** |
+| fargate | 1e+03 | ASAP | 0.231 | 989 | 4.4 | 11.9 | yes |
+| fargate | 1e+03 | ASAP (no roll-ups) | 0.251 | 989 | 4.73 | 13.3 | yes |
+| fargate | 1e+03 | PerQuery-CostAware | 0.953 | 989 | 18.1 | 49.6 | yes |
+| fargate | 1e+03 | AutoSketch-Adapted | 150 | 1.01e+03 | 3.25e+03 | 4.17e+03 | **no** |
+| fargate | 3e+03 | ASAP | 0.165 | 2.68e+03 | 2.68 | 12.8 | yes |
+| fargate | 3e+03 | ASAP (no roll-ups) | 0.185 | 2.68e+03 | 3.01 | 14.3 | yes |
+| fargate | 3e+03 | PerQuery-CostAware | 0.856 | 2.97e+03 | 15.6 | 50.2 | yes |
+| fargate | 3e+03 | AutoSketch-Adapted | 150 | 1.01e+03 | 3.25e+03 | 4.17e+03 | yes |
+| fargate | 1e+04 | ASAP | 0.165 | 2.68e+03 | 2.68 | 12.8 | yes |
+| fargate | 1e+04 | ASAP (no roll-ups) | 0.185 | 2.68e+03 | 3.01 | 14.3 | yes |
+| fargate | 1e+04 | PerQuery-CostAware | 0.856 | 2.97e+03 | 15.6 | 50.2 | yes |
+| fargate | 1e+04 | AutoSketch-Adapted | 150 | 1.01e+03 | 3.25e+03 | 4.17e+03 | yes |
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | SLA (ms) | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|---|
-| cpu | 1e+03 | 104 | 12 | 33 | 4.49 | 4.83 | 6.9% |
-| cpu | 3e+03 | 104 | 11 | 32 | 2.71 | 3.04 | 10.9% |
-| cpu | 1e+04 | 104 | 11 | 32 | 2.71 | 3.04 | 10.9% |
-| fargate | 1e+03 | 104 | 12 | 33 | 0.257 | 0.277 | 7.3% |
-| fargate | 3e+03 | 104 | 11 | 32 | 0.187 | 0.207 | 9.8% |
-| fargate | 1e+04 | 104 | 11 | 32 | 0.187 | 0.207 | 9.8% |
+| cpu | 1e+03 | 104 | 12 | 33 | 4.4 | 4.73 | 7.0% |
+| cpu | 3e+03 | 104 | 11 | 32 | 2.68 | 3.01 | 11.0% |
+| cpu | 1e+04 | 104 | 11 | 32 | 2.68 | 3.01 | 11.0% |
+| fargate | 1e+03 | 104 | 12 | 33 | 0.231 | 0.251 | 7.9% |
+| fargate | 3e+03 | 104 | 11 | 32 | 0.165 | 0.185 | 10.7% |
+| fargate | 1e+04 | 104 | 11 | 32 | 0.165 | 0.185 | 10.7% |
 
 ## mixed, m = 8: 336 RQEs
 
-Sanity violations: 0. Tightest feasible SLA: ASAP 87.7 ms, PerQuery 87.7 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 1.7e+03 s.
+Sanity violations: 0. Tightest feasible SLA: ASAP 87.7 ms, PerQuery 87.7 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 1.36e+03 s.
 
 | weights | SLA (ms) | method | cost | latency (ms) | CPU (vCPU) | GiB | meets SLA |
 |---|---|---|---|---|---|---|---|
-| cpu | 100 | ASAP | 273 | 99.8 | 273 | 273 | yes |
-| cpu | 100 | ASAP (no roll-ups) | 273 | 99.8 | 273 | 273 | yes |
-| cpu | 100 | PerQuery-CostAware | 481 | 97.4 | 481 | 605 | yes |
-| cpu | 100 | AutoSketch-Adapted | 2.19e+04 | 1.01e+03 | 2.19e+04 | 4.49e+04 | **no** |
-| cpu | 300 | ASAP | 85 | 291 | 85 | 124 | yes |
-| cpu | 300 | ASAP (no roll-ups) | 85 | 291 | 85 | 124 | yes |
-| cpu | 300 | PerQuery-CostAware | 168 | 291 | 168 | 542 | yes |
-| cpu | 300 | AutoSketch-Adapted | 2.19e+04 | 1.01e+03 | 2.19e+04 | 4.49e+04 | **no** |
-| cpu | 1e+03 | ASAP | 33.8 | 980 | 33.8 | 233 | yes |
-| cpu | 1e+03 | ASAP (no roll-ups) | 33.8 | 980 | 33.8 | 233 | yes |
-| cpu | 1e+03 | PerQuery-CostAware | 83.7 | 980 | 83.7 | 1.24e+03 | yes |
-| cpu | 1e+03 | AutoSketch-Adapted | 2.19e+04 | 1.01e+03 | 2.19e+04 | 4.49e+04 | **no** |
-| cpu | 3e+03 | ASAP | 19.3 | 2.68e+03 | 19.3 | 131 | yes |
-| cpu | 3e+03 | ASAP (no roll-ups) | 19.3 | 2.68e+03 | 19.3 | 131 | yes |
-| cpu | 3e+03 | PerQuery-CostAware | 63.9 | 2.68e+03 | 63.9 | 1.11e+03 | yes |
-| cpu | 3e+03 | AutoSketch-Adapted | 2.19e+04 | 1.01e+03 | 2.19e+04 | 4.49e+04 | yes |
-| cpu | 1e+04 | ASAP | 19.3 | 2.68e+03 | 19.3 | 131 | yes |
-| cpu | 1e+04 | ASAP (no roll-ups) | 19.3 | 2.68e+03 | 19.3 | 131 | yes |
-| cpu | 1e+04 | PerQuery-CostAware | 62.2 | 3.33e+03 | 62.2 | 582 | yes |
-| cpu | 1e+04 | AutoSketch-Adapted | 2.19e+04 | 1.01e+03 | 2.19e+04 | 4.49e+04 | yes |
-| fargate | 100 | ASAP | 11.8 | 96.9 | 276 | 145 | yes |
-| fargate | 100 | ASAP (no roll-ups) | 11.8 | 96.9 | 276 | 145 | yes |
-| fargate | 100 | PerQuery-CostAware | 22.2 | 97.4 | 481 | 599 | yes |
-| fargate | 100 | AutoSketch-Adapted | 1.09e+03 | 1.01e+03 | 2.19e+04 | 4.49e+04 | **no** |
-| fargate | 300 | ASAP | 4 | 291 | 85 | 124 | yes |
-| fargate | 300 | ASAP (no roll-ups) | 4 | 291 | 85 | 124 | yes |
-| fargate | 300 | PerQuery-CostAware | 9.2 | 291 | 168 | 536 | yes |
-| fargate | 300 | AutoSketch-Adapted | 1.09e+03 | 1.01e+03 | 2.19e+04 | 4.49e+04 | **no** |
-| fargate | 1e+03 | ASAP | 1.93 | 896 | 33.9 | 126 | yes |
-| fargate | 1e+03 | ASAP (no roll-ups) | 1.93 | 896 | 33.9 | 126 | yes |
-| fargate | 1e+03 | PerQuery-CostAware | 5.85 | 896 | 85.4 | 538 | yes |
-| fargate | 1e+03 | AutoSketch-Adapted | 1.09e+03 | 1.01e+03 | 2.19e+04 | 4.49e+04 | **no** |
-| fargate | 3e+03 | ASAP | 1.36 | 2.68e+03 | 19.3 | 131 | yes |
-| fargate | 3e+03 | ASAP (no roll-ups) | 1.36 | 2.68e+03 | 19.3 | 131 | yes |
-| fargate | 3e+03 | PerQuery-CostAware | 5.02 | 2.68e+03 | 64.3 | 543 | yes |
-| fargate | 3e+03 | AutoSketch-Adapted | 1.09e+03 | 1.01e+03 | 2.19e+04 | 4.49e+04 | yes |
-| fargate | 1e+04 | ASAP | 1.36 | 2.68e+03 | 19.3 | 131 | yes |
-| fargate | 1e+04 | ASAP (no roll-ups) | 1.36 | 2.68e+03 | 19.3 | 131 | yes |
-| fargate | 1e+04 | PerQuery-CostAware | 4.98 | 3.26e+03 | 63.4 | 543 | yes |
-| fargate | 1e+04 | AutoSketch-Adapted | 1.09e+03 | 1.01e+03 | 2.19e+04 | 4.49e+04 | yes |
+| cpu | 100 | ASAP | 267 | 96.9 | 267 | 97.7 | yes |
+| cpu | 100 | ASAP (no roll-ups) | 267 | 96.9 | 267 | 97.7 | yes |
+| cpu | 100 | PerQuery-CostAware | 448 | 97.4 | 448 | 322 | yes |
+| cpu | 100 | AutoSketch-Adapted | 2.16e+04 | 1.01e+03 | 2.16e+04 | 3.2e+04 | **no** |
+| cpu | 300 | ASAP | 82.9 | 295 | 82.9 | 84 | yes |
+| cpu | 300 | ASAP (no roll-ups) | 82.9 | 295 | 82.9 | 84 | yes |
+| cpu | 300 | PerQuery-CostAware | 155 | 295 | 155 | 294 | yes |
+| cpu | 300 | AutoSketch-Adapted | 2.16e+04 | 1.01e+03 | 2.16e+04 | 3.2e+04 | **no** |
+| cpu | 1e+03 | ASAP | 33 | 989 | 33 | 87 | yes |
+| cpu | 1e+03 | ASAP (no roll-ups) | 33 | 989 | 33 | 87 | yes |
+| cpu | 1e+03 | PerQuery-CostAware | 80.5 | 989 | 80.5 | 303 | yes |
+| cpu | 1e+03 | AutoSketch-Adapted | 2.16e+04 | 1.01e+03 | 2.16e+04 | 3.2e+04 | **no** |
+| cpu | 3e+03 | ASAP | 19.1 | 2.68e+03 | 19.1 | 94.5 | yes |
+| cpu | 3e+03 | ASAP (no roll-ups) | 19.1 | 2.68e+03 | 19.1 | 94.5 | yes |
+| cpu | 3e+03 | PerQuery-CostAware | 62.3 | 2.97e+03 | 62.3 | 308 | yes |
+| cpu | 3e+03 | AutoSketch-Adapted | 2.16e+04 | 1.01e+03 | 2.16e+04 | 3.2e+04 | yes |
+| cpu | 1e+04 | ASAP | 19.1 | 2.68e+03 | 19.1 | 94.5 | yes |
+| cpu | 1e+04 | ASAP (no roll-ups) | 19.1 | 2.68e+03 | 19.1 | 94.5 | yes |
+| cpu | 1e+04 | PerQuery-CostAware | 61.3 | 3.33e+03 | 61.3 | 318 | yes |
+| cpu | 1e+04 | AutoSketch-Adapted | 2.16e+04 | 1.01e+03 | 2.16e+04 | 3.2e+04 | yes |
+| fargate | 100 | ASAP | 11.3 | 96.9 | 267 | 97.7 | yes |
+| fargate | 100 | ASAP (no roll-ups) | 11.3 | 96.9 | 267 | 97.7 | yes |
+| fargate | 100 | PerQuery-CostAware | 19.6 | 97.4 | 448 | 322 | yes |
+| fargate | 100 | AutoSketch-Adapted | 1.02e+03 | 1.01e+03 | 2.16e+04 | 3.2e+04 | **no** |
+| fargate | 300 | ASAP | 3.73 | 295 | 82.9 | 84 | yes |
+| fargate | 300 | ASAP (no roll-ups) | 3.73 | 295 | 82.9 | 84 | yes |
+| fargate | 300 | PerQuery-CostAware | 7.61 | 295 | 155 | 294 | yes |
+| fargate | 300 | AutoSketch-Adapted | 1.02e+03 | 1.01e+03 | 2.16e+04 | 3.2e+04 | **no** |
+| fargate | 1e+03 | ASAP | 1.72 | 989 | 33 | 87 | yes |
+| fargate | 1e+03 | ASAP (no roll-ups) | 1.72 | 989 | 33 | 87 | yes |
+| fargate | 1e+03 | PerQuery-CostAware | 4.61 | 989 | 80.5 | 303 | yes |
+| fargate | 1e+03 | AutoSketch-Adapted | 1.02e+03 | 1.01e+03 | 2.16e+04 | 3.2e+04 | **no** |
+| fargate | 3e+03 | ASAP | 1.19 | 2.68e+03 | 19.1 | 94.5 | yes |
+| fargate | 3e+03 | ASAP (no roll-ups) | 1.19 | 2.68e+03 | 19.1 | 94.5 | yes |
+| fargate | 3e+03 | PerQuery-CostAware | 3.89 | 2.97e+03 | 62.3 | 308 | yes |
+| fargate | 3e+03 | AutoSketch-Adapted | 1.02e+03 | 1.01e+03 | 2.16e+04 | 3.2e+04 | yes |
+| fargate | 1e+04 | ASAP | 1.19 | 2.68e+03 | 19.1 | 94.5 | yes |
+| fargate | 1e+04 | ASAP (no roll-ups) | 1.19 | 2.68e+03 | 19.1 | 94.5 | yes |
+| fargate | 1e+04 | PerQuery-CostAware | 3.89 | 2.97e+03 | 62.3 | 308 | yes |
+| fargate | 1e+04 | AutoSketch-Adapted | 1.02e+03 | 1.01e+03 | 2.16e+04 | 3.2e+04 | yes |
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | SLA (ms) | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|---|
-| cpu | 100 | 0 | 88 | 88 | 273 | 273 | 0.0% |
-| cpu | 300 | 0 | 80 | 80 | 85 | 85 | 0.0% |
-| cpu | 1e+03 | 0 | 56 | 56 | 33.8 | 33.8 | 0.0% |
-| cpu | 3e+03 | 0 | 48 | 48 | 19.3 | 19.3 | 0.0% |
-| cpu | 1e+04 | 0 | 48 | 48 | 19.3 | 19.3 | 0.0% |
-| fargate | 100 | 0 | 88 | 88 | 11.8 | 11.8 | 0.0% |
-| fargate | 300 | 0 | 80 | 80 | 4 | 4 | 0.0% |
-| fargate | 1e+03 | 0 | 56 | 56 | 1.93 | 1.93 | 0.0% |
-| fargate | 3e+03 | 0 | 48 | 48 | 1.36 | 1.36 | 0.0% |
-| fargate | 1e+04 | 0 | 48 | 48 | 1.36 | 1.36 | 0.0% |
+| cpu | 100 | 0 | 88 | 88 | 267 | 267 | 0.0% |
+| cpu | 300 | 0 | 80 | 80 | 82.9 | 82.9 | 0.0% |
+| cpu | 1e+03 | 0 | 56 | 56 | 33 | 33 | 0.0% |
+| cpu | 3e+03 | 0 | 48 | 48 | 19.1 | 19.1 | 0.0% |
+| cpu | 1e+04 | 0 | 48 | 48 | 19.1 | 19.1 | 0.0% |
+| fargate | 100 | 0 | 88 | 88 | 11.3 | 11.3 | 0.0% |
+| fargate | 300 | 0 | 80 | 80 | 3.73 | 3.73 | 0.0% |
+| fargate | 1e+03 | 0 | 56 | 56 | 1.72 | 1.72 | 0.0% |
+| fargate | 3e+03 | 0 | 48 | 48 | 1.19 | 1.19 | 0.0% |
+| fargate | 1e+04 | 0 | 48 | 48 | 1.19 | 1.19 | 0.0% |
 
 ## multi-grouping, m = 8: 496 RQEs
 
-Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 490 ms; planning time (search + measured benchmark) 2.15e+03 s.
+Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 490 ms; planning time (search + measured benchmark) 1.81e+03 s.
 
 | weights | SLA (ms) | method | cost | latency (ms) | CPU (vCPU) | GiB | meets SLA |
 |---|---|---|---|---|---|---|---|
 | cpu | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 100 | AutoSketch-Adapted | 81.7 | 490 | 81.7 | 28.4 | **no** |
+| cpu | 100 | AutoSketch-Adapted | 77.2 | 490 | 77.2 | 28.1 | **no** |
 | cpu | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 300 | AutoSketch-Adapted | 81.7 | 490 | 81.7 | 28.4 | **no** |
-| cpu | 1e+03 | ASAP | 1.77 | 557 | 1.77 | 8.52 | yes |
-| cpu | 1e+03 | ASAP (no roll-ups) | 4.41 | 959 | 4.41 | 20.8 | yes |
-| cpu | 1e+03 | PerQuery-CostAware | 8.55 | 959 | 8.55 | 29.5 | yes |
-| cpu | 1e+03 | AutoSketch-Adapted | 81.7 | 490 | 81.7 | 28.4 | yes |
-| cpu | 3e+03 | ASAP | 1.77 | 557 | 1.77 | 8.52 | yes |
-| cpu | 3e+03 | ASAP (no roll-ups) | 4.41 | 959 | 4.41 | 20.8 | yes |
-| cpu | 3e+03 | PerQuery-CostAware | 8.55 | 959 | 8.55 | 29.5 | yes |
-| cpu | 3e+03 | AutoSketch-Adapted | 81.7 | 490 | 81.7 | 28.4 | yes |
-| cpu | 1e+04 | ASAP | 1.77 | 557 | 1.77 | 8.52 | yes |
-| cpu | 1e+04 | ASAP (no roll-ups) | 4.41 | 959 | 4.41 | 20.8 | yes |
-| cpu | 1e+04 | PerQuery-CostAware | 8.55 | 959 | 8.55 | 29.5 | yes |
-| cpu | 1e+04 | AutoSketch-Adapted | 81.7 | 490 | 81.7 | 28.4 | yes |
+| cpu | 300 | AutoSketch-Adapted | 77.2 | 490 | 77.2 | 28.1 | **no** |
+| cpu | 1e+03 | ASAP | 1.76 | 557 | 1.76 | 8.12 | yes |
+| cpu | 1e+03 | ASAP (no roll-ups) | 4.4 | 959 | 4.4 | 19.8 | yes |
+| cpu | 1e+03 | PerQuery-CostAware | 8.54 | 959 | 8.54 | 28.1 | yes |
+| cpu | 1e+03 | AutoSketch-Adapted | 77.2 | 490 | 77.2 | 28.1 | yes |
+| cpu | 3e+03 | ASAP | 1.76 | 557 | 1.76 | 8.12 | yes |
+| cpu | 3e+03 | ASAP (no roll-ups) | 4.4 | 959 | 4.4 | 19.8 | yes |
+| cpu | 3e+03 | PerQuery-CostAware | 8.54 | 959 | 8.54 | 28.1 | yes |
+| cpu | 3e+03 | AutoSketch-Adapted | 77.2 | 490 | 77.2 | 28.1 | yes |
+| cpu | 1e+04 | ASAP | 1.76 | 557 | 1.76 | 8.12 | yes |
+| cpu | 1e+04 | ASAP (no roll-ups) | 4.4 | 959 | 4.4 | 19.8 | yes |
+| cpu | 1e+04 | PerQuery-CostAware | 8.54 | 959 | 8.54 | 28.1 | yes |
+| cpu | 1e+04 | AutoSketch-Adapted | 77.2 | 490 | 77.2 | 28.1 | yes |
 | fargate | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 100 | AutoSketch-Adapted | 3.44 | 490 | 81.7 | 28.4 | **no** |
+| fargate | 100 | AutoSketch-Adapted | 3.25 | 490 | 77.2 | 28.1 | **no** |
 | fargate | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 300 | AutoSketch-Adapted | 3.44 | 490 | 81.7 | 28.4 | **no** |
-| fargate | 1e+03 | ASAP | 0.109 | 557 | 1.79 | 8.22 | yes |
-| fargate | 1e+03 | ASAP (no roll-ups) | 0.271 | 959 | 4.47 | 20.2 | yes |
-| fargate | 1e+03 | PerQuery-CostAware | 0.477 | 959 | 8.61 | 28.9 | yes |
-| fargate | 1e+03 | AutoSketch-Adapted | 3.44 | 490 | 81.7 | 28.4 | yes |
-| fargate | 3e+03 | ASAP | 0.109 | 557 | 1.79 | 8.22 | yes |
-| fargate | 3e+03 | ASAP (no roll-ups) | 0.271 | 959 | 4.47 | 20.2 | yes |
-| fargate | 3e+03 | PerQuery-CostAware | 0.477 | 959 | 8.61 | 28.9 | yes |
-| fargate | 3e+03 | AutoSketch-Adapted | 3.44 | 490 | 81.7 | 28.4 | yes |
-| fargate | 1e+04 | ASAP | 0.109 | 557 | 1.79 | 8.22 | yes |
-| fargate | 1e+04 | ASAP (no roll-ups) | 0.271 | 959 | 4.47 | 20.2 | yes |
-| fargate | 1e+04 | PerQuery-CostAware | 0.477 | 959 | 8.61 | 28.9 | yes |
-| fargate | 1e+04 | AutoSketch-Adapted | 3.44 | 490 | 81.7 | 28.4 | yes |
+| fargate | 300 | AutoSketch-Adapted | 3.25 | 490 | 77.2 | 28.1 | **no** |
+| fargate | 1e+03 | ASAP | 0.107 | 557 | 1.76 | 8.12 | yes |
+| fargate | 1e+03 | ASAP (no roll-ups) | 0.266 | 959 | 4.4 | 19.8 | yes |
+| fargate | 1e+03 | PerQuery-CostAware | 0.471 | 959 | 8.54 | 28.1 | yes |
+| fargate | 1e+03 | AutoSketch-Adapted | 3.25 | 490 | 77.2 | 28.1 | yes |
+| fargate | 3e+03 | ASAP | 0.107 | 557 | 1.76 | 8.12 | yes |
+| fargate | 3e+03 | ASAP (no roll-ups) | 0.266 | 959 | 4.4 | 19.8 | yes |
+| fargate | 3e+03 | PerQuery-CostAware | 0.471 | 959 | 8.54 | 28.1 | yes |
+| fargate | 3e+03 | AutoSketch-Adapted | 3.25 | 490 | 77.2 | 28.1 | yes |
+| fargate | 1e+04 | ASAP | 0.107 | 557 | 1.76 | 8.12 | yes |
+| fargate | 1e+04 | ASAP (no roll-ups) | 0.266 | 959 | 4.4 | 19.8 | yes |
+| fargate | 1e+04 | PerQuery-CostAware | 0.471 | 959 | 8.54 | 28.1 | yes |
+| fargate | 1e+04 | AutoSketch-Adapted | 3.25 | 490 | 77.2 | 28.1 | yes |
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | SLA (ms) | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|---|
-| cpu | 1e+03 | 416 | 40 | 208 | 1.77 | 4.41 | 59.9% |
-| cpu | 3e+03 | 416 | 40 | 208 | 1.77 | 4.41 | 59.9% |
-| cpu | 1e+04 | 416 | 40 | 208 | 1.77 | 4.41 | 59.9% |
-| fargate | 1e+03 | 416 | 40 | 208 | 0.109 | 0.271 | 59.7% |
-| fargate | 3e+03 | 416 | 40 | 208 | 0.109 | 0.271 | 59.7% |
-| fargate | 1e+04 | 416 | 40 | 208 | 0.109 | 0.271 | 59.7% |
+| cpu | 1e+03 | 416 | 40 | 208 | 1.76 | 4.4 | 60.0% |
+| cpu | 3e+03 | 416 | 40 | 208 | 1.76 | 4.4 | 60.0% |
+| cpu | 1e+04 | 416 | 40 | 208 | 1.76 | 4.4 | 60.0% |
+| fargate | 1e+03 | 416 | 40 | 208 | 0.107 | 0.266 | 59.7% |
+| fargate | 3e+03 | 416 | 40 | 208 | 0.107 | 0.266 | 59.7% |
+| fargate | 1e+04 | 416 | 40 | 208 | 0.107 | 0.266 | 59.7% |
 
 ## mixed, m = 16: 672 RQEs
 
-Sanity violations: 0. Tightest feasible SLA: ASAP 87.7 ms, PerQuery 87.7 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 3.39e+03 s.
+Sanity violations: 0. Tightest feasible SLA: ASAP 87.7 ms, PerQuery 87.7 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 2.71e+03 s.
 
 | weights | SLA (ms) | method | cost | latency (ms) | CPU (vCPU) | GiB | meets SLA |
 |---|---|---|---|---|---|---|---|
-| cpu | 100 | ASAP | 546 | 99.8 | 546 | 545 | yes |
-| cpu | 100 | ASAP (no roll-ups) | 546 | 99.8 | 546 | 545 | yes |
-| cpu | 100 | PerQuery-CostAware | 962 | 97.4 | 962 | 1.21e+03 | yes |
-| cpu | 100 | AutoSketch-Adapted | 4.38e+04 | 1.01e+03 | 4.38e+04 | 8.99e+04 | **no** |
-| cpu | 300 | ASAP | 170 | 291 | 170 | 248 | yes |
-| cpu | 300 | ASAP (no roll-ups) | 170 | 291 | 170 | 248 | yes |
-| cpu | 300 | PerQuery-CostAware | 336 | 291 | 336 | 1.08e+03 | yes |
-| cpu | 300 | AutoSketch-Adapted | 4.38e+04 | 1.01e+03 | 4.38e+04 | 8.99e+04 | **no** |
-| cpu | 1e+03 | ASAP | 67.6 | 980 | 67.6 | 466 | yes |
-| cpu | 1e+03 | ASAP (no roll-ups) | 67.6 | 980 | 67.6 | 466 | yes |
-| cpu | 1e+03 | PerQuery-CostAware | 167 | 980 | 167 | 2.48e+03 | yes |
-| cpu | 1e+03 | AutoSketch-Adapted | 4.38e+04 | 1.01e+03 | 4.38e+04 | 8.99e+04 | **no** |
-| cpu | 3e+03 | ASAP | 38.6 | 2.68e+03 | 38.6 | 261 | yes |
-| cpu | 3e+03 | ASAP (no roll-ups) | 38.6 | 2.68e+03 | 38.6 | 261 | yes |
-| cpu | 3e+03 | PerQuery-CostAware | 128 | 2.68e+03 | 128 | 2.22e+03 | yes |
-| cpu | 3e+03 | AutoSketch-Adapted | 4.38e+04 | 1.01e+03 | 4.38e+04 | 8.99e+04 | yes |
-| cpu | 1e+04 | ASAP | 38.6 | 2.68e+03 | 38.6 | 261 | yes |
-| cpu | 1e+04 | ASAP (no roll-ups) | 38.6 | 2.68e+03 | 38.6 | 261 | yes |
-| cpu | 1e+04 | PerQuery-CostAware | 124 | 3.33e+03 | 124 | 1.16e+03 | yes |
-| cpu | 1e+04 | AutoSketch-Adapted | 4.38e+04 | 1.01e+03 | 4.38e+04 | 8.99e+04 | yes |
-| fargate | 100 | ASAP | 23.6 | 96.9 | 552 | 291 | yes |
-| fargate | 100 | ASAP (no roll-ups) | 23.6 | 96.9 | 552 | 291 | yes |
-| fargate | 100 | PerQuery-CostAware | 44.3 | 97.4 | 962 | 1.2e+03 | yes |
-| fargate | 100 | AutoSketch-Adapted | 2.17e+03 | 1.01e+03 | 4.38e+04 | 8.99e+04 | **no** |
-| fargate | 300 | ASAP | 7.99 | 291 | 170 | 248 | yes |
-| fargate | 300 | ASAP (no roll-ups) | 7.99 | 291 | 170 | 248 | yes |
-| fargate | 300 | PerQuery-CostAware | 18.4 | 291 | 336 | 1.07e+03 | yes |
-| fargate | 300 | AutoSketch-Adapted | 2.17e+03 | 1.01e+03 | 4.38e+04 | 8.99e+04 | **no** |
-| fargate | 1e+03 | ASAP | 3.86 | 896 | 67.8 | 251 | yes |
-| fargate | 1e+03 | ASAP (no roll-ups) | 3.86 | 896 | 67.8 | 251 | yes |
-| fargate | 1e+03 | PerQuery-CostAware | 11.7 | 896 | 171 | 1.08e+03 | yes |
-| fargate | 1e+03 | AutoSketch-Adapted | 2.17e+03 | 1.01e+03 | 4.38e+04 | 8.99e+04 | **no** |
-| fargate | 3e+03 | ASAP | 2.73 | 2.68e+03 | 38.6 | 261 | yes |
-| fargate | 3e+03 | ASAP (no roll-ups) | 2.73 | 2.68e+03 | 38.6 | 261 | yes |
-| fargate | 3e+03 | PerQuery-CostAware | 10 | 2.68e+03 | 129 | 1.09e+03 | yes |
-| fargate | 3e+03 | AutoSketch-Adapted | 2.17e+03 | 1.01e+03 | 4.38e+04 | 8.99e+04 | yes |
-| fargate | 1e+04 | ASAP | 2.73 | 2.68e+03 | 38.6 | 261 | yes |
-| fargate | 1e+04 | ASAP (no roll-ups) | 2.73 | 2.68e+03 | 38.6 | 261 | yes |
-| fargate | 1e+04 | PerQuery-CostAware | 9.97 | 3.26e+03 | 127 | 1.09e+03 | yes |
-| fargate | 1e+04 | AutoSketch-Adapted | 2.17e+03 | 1.01e+03 | 4.38e+04 | 8.99e+04 | yes |
+| cpu | 100 | ASAP | 535 | 96.9 | 535 | 195 | yes |
+| cpu | 100 | ASAP (no roll-ups) | 535 | 96.9 | 535 | 195 | yes |
+| cpu | 100 | PerQuery-CostAware | 896 | 97.4 | 896 | 644 | yes |
+| cpu | 100 | AutoSketch-Adapted | 4.32e+04 | 1.01e+03 | 4.32e+04 | 6.4e+04 | **no** |
+| cpu | 300 | ASAP | 166 | 295 | 166 | 168 | yes |
+| cpu | 300 | ASAP (no roll-ups) | 166 | 295 | 166 | 168 | yes |
+| cpu | 300 | PerQuery-CostAware | 311 | 295 | 311 | 589 | yes |
+| cpu | 300 | AutoSketch-Adapted | 4.32e+04 | 1.01e+03 | 4.32e+04 | 6.4e+04 | **no** |
+| cpu | 1e+03 | ASAP | 66 | 989 | 66 | 174 | yes |
+| cpu | 1e+03 | ASAP (no roll-ups) | 66 | 989 | 66 | 174 | yes |
+| cpu | 1e+03 | PerQuery-CostAware | 161 | 989 | 161 | 606 | yes |
+| cpu | 1e+03 | AutoSketch-Adapted | 4.32e+04 | 1.01e+03 | 4.32e+04 | 6.4e+04 | **no** |
+| cpu | 3e+03 | ASAP | 38.1 | 2.68e+03 | 38.1 | 189 | yes |
+| cpu | 3e+03 | ASAP (no roll-ups) | 38.1 | 2.68e+03 | 38.1 | 189 | yes |
+| cpu | 3e+03 | PerQuery-CostAware | 125 | 2.97e+03 | 125 | 616 | yes |
+| cpu | 3e+03 | AutoSketch-Adapted | 4.32e+04 | 1.01e+03 | 4.32e+04 | 6.4e+04 | yes |
+| cpu | 1e+04 | ASAP | 38.1 | 2.68e+03 | 38.1 | 189 | yes |
+| cpu | 1e+04 | ASAP (no roll-ups) | 38.1 | 2.68e+03 | 38.1 | 189 | yes |
+| cpu | 1e+04 | PerQuery-CostAware | 123 | 3.33e+03 | 123 | 636 | yes |
+| cpu | 1e+04 | AutoSketch-Adapted | 4.32e+04 | 1.01e+03 | 4.32e+04 | 6.4e+04 | yes |
+| fargate | 100 | ASAP | 22.5 | 96.9 | 535 | 196 | yes |
+| fargate | 100 | ASAP (no roll-ups) | 22.5 | 96.9 | 535 | 196 | yes |
+| fargate | 100 | PerQuery-CostAware | 39.2 | 97.4 | 896 | 644 | yes |
+| fargate | 100 | AutoSketch-Adapted | 2.04e+03 | 1.01e+03 | 4.32e+04 | 6.4e+04 | **no** |
+| fargate | 300 | ASAP | 7.46 | 295 | 166 | 168 | yes |
+| fargate | 300 | ASAP (no roll-ups) | 7.46 | 295 | 166 | 168 | yes |
+| fargate | 300 | PerQuery-CostAware | 15.2 | 295 | 311 | 589 | yes |
+| fargate | 300 | AutoSketch-Adapted | 2.04e+03 | 1.01e+03 | 4.32e+04 | 6.4e+04 | **no** |
+| fargate | 1e+03 | ASAP | 3.45 | 989 | 66 | 174 | yes |
+| fargate | 1e+03 | ASAP (no roll-ups) | 3.45 | 989 | 66 | 174 | yes |
+| fargate | 1e+03 | PerQuery-CostAware | 9.22 | 989 | 161 | 606 | yes |
+| fargate | 1e+03 | AutoSketch-Adapted | 2.04e+03 | 1.01e+03 | 4.32e+04 | 6.4e+04 | **no** |
+| fargate | 3e+03 | ASAP | 2.38 | 2.68e+03 | 38.1 | 189 | yes |
+| fargate | 3e+03 | ASAP (no roll-ups) | 2.38 | 2.68e+03 | 38.1 | 189 | yes |
+| fargate | 3e+03 | PerQuery-CostAware | 7.78 | 2.97e+03 | 125 | 616 | yes |
+| fargate | 3e+03 | AutoSketch-Adapted | 2.04e+03 | 1.01e+03 | 4.32e+04 | 6.4e+04 | yes |
+| fargate | 1e+04 | ASAP | 2.38 | 2.68e+03 | 38.1 | 189 | yes |
+| fargate | 1e+04 | ASAP (no roll-ups) | 2.38 | 2.68e+03 | 38.1 | 189 | yes |
+| fargate | 1e+04 | PerQuery-CostAware | 7.78 | 2.97e+03 | 125 | 616 | yes |
+| fargate | 1e+04 | AutoSketch-Adapted | 2.04e+03 | 1.01e+03 | 4.32e+04 | 6.4e+04 | yes |
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | SLA (ms) | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|---|
-| cpu | 100 | 0 | 176 | 176 | 546 | 546 | 0.0% |
-| cpu | 300 | 0 | 160 | 160 | 170 | 170 | 0.0% |
-| cpu | 1e+03 | 0 | 112 | 112 | 67.6 | 67.6 | 0.0% |
-| cpu | 3e+03 | 0 | 96 | 96 | 38.6 | 38.6 | 0.0% |
-| cpu | 1e+04 | 0 | 96 | 96 | 38.6 | 38.6 | 0.0% |
-| fargate | 100 | 0 | 176 | 176 | 23.6 | 23.6 | 0.0% |
-| fargate | 300 | 0 | 160 | 160 | 7.99 | 7.99 | 0.0% |
-| fargate | 1e+03 | 0 | 112 | 112 | 3.86 | 3.86 | 0.0% |
-| fargate | 3e+03 | 0 | 96 | 96 | 2.73 | 2.73 | 0.0% |
-| fargate | 1e+04 | 0 | 96 | 96 | 2.73 | 2.73 | 0.0% |
+| cpu | 100 | 0 | 176 | 176 | 535 | 535 | 0.0% |
+| cpu | 300 | 0 | 160 | 160 | 166 | 166 | 0.0% |
+| cpu | 1e+03 | 0 | 112 | 112 | 66 | 66 | 0.0% |
+| cpu | 3e+03 | 0 | 96 | 96 | 38.1 | 38.1 | 0.0% |
+| cpu | 1e+04 | 0 | 96 | 96 | 38.1 | 38.1 | 0.0% |
+| fargate | 100 | 0 | 176 | 176 | 22.5 | 22.5 | 0.0% |
+| fargate | 300 | 0 | 160 | 160 | 7.46 | 7.46 | 0.0% |
+| fargate | 1e+03 | 0 | 112 | 112 | 3.45 | 3.45 | 0.0% |
+| fargate | 3e+03 | 0 | 96 | 96 | 2.38 | 2.38 | 0.0% |
+| fargate | 1e+04 | 0 | 96 | 96 | 2.38 | 2.38 | 0.0% |
 
 ## mixed + multi-grouping, m = 8: 832 RQEs
 
-Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 3.85e+03 s.
+Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 3.17e+03 s.
 
 | weights | SLA (ms) | method | cost | latency (ms) | CPU (vCPU) | GiB | meets SLA |
 |---|---|---|---|---|---|---|---|
 | cpu | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 100 | AutoSketch-Adapted | 2.2e+04 | 1.01e+03 | 2.2e+04 | 4.5e+04 | **no** |
+| cpu | 100 | AutoSketch-Adapted | 2.17e+04 | 1.01e+03 | 2.17e+04 | 3.2e+04 | **no** |
 | cpu | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 300 | AutoSketch-Adapted | 2.2e+04 | 1.01e+03 | 2.2e+04 | 4.5e+04 | **no** |
-| cpu | 1e+03 | ASAP | 35.5 | 980 | 35.5 | 242 | yes |
-| cpu | 1e+03 | ASAP (no roll-ups) | 38.2 | 980 | 38.2 | 254 | yes |
-| cpu | 1e+03 | PerQuery-CostAware | 92.3 | 980 | 92.3 | 1.27e+03 | yes |
-| cpu | 1e+03 | AutoSketch-Adapted | 2.2e+04 | 1.01e+03 | 2.2e+04 | 4.5e+04 | **no** |
-| cpu | 3e+03 | ASAP | 21.1 | 2.68e+03 | 21.1 | 139 | yes |
-| cpu | 3e+03 | ASAP (no roll-ups) | 23.7 | 2.68e+03 | 23.7 | 151 | yes |
-| cpu | 3e+03 | PerQuery-CostAware | 72.4 | 2.68e+03 | 72.4 | 1.14e+03 | yes |
-| cpu | 3e+03 | AutoSketch-Adapted | 2.2e+04 | 1.01e+03 | 2.2e+04 | 4.5e+04 | yes |
-| cpu | 1e+04 | ASAP | 21.1 | 2.68e+03 | 21.1 | 139 | yes |
-| cpu | 1e+04 | ASAP (no roll-ups) | 23.7 | 2.68e+03 | 23.7 | 151 | yes |
-| cpu | 1e+04 | PerQuery-CostAware | 70.7 | 3.33e+03 | 70.7 | 612 | yes |
-| cpu | 1e+04 | AutoSketch-Adapted | 2.2e+04 | 1.01e+03 | 2.2e+04 | 4.5e+04 | yes |
+| cpu | 300 | AutoSketch-Adapted | 2.17e+04 | 1.01e+03 | 2.17e+04 | 3.2e+04 | **no** |
+| cpu | 1e+03 | ASAP | 34.7 | 989 | 34.7 | 95.1 | yes |
+| cpu | 1e+03 | ASAP (no roll-ups) | 37.4 | 989 | 37.4 | 107 | yes |
+| cpu | 1e+03 | PerQuery-CostAware | 89 | 989 | 89 | 331 | yes |
+| cpu | 1e+03 | AutoSketch-Adapted | 2.17e+04 | 1.01e+03 | 2.17e+04 | 3.2e+04 | **no** |
+| cpu | 3e+03 | ASAP | 20.8 | 2.68e+03 | 20.8 | 103 | yes |
+| cpu | 3e+03 | ASAP (no roll-ups) | 23.5 | 2.68e+03 | 23.5 | 114 | yes |
+| cpu | 3e+03 | PerQuery-CostAware | 70.8 | 2.97e+03 | 70.8 | 336 | yes |
+| cpu | 3e+03 | AutoSketch-Adapted | 2.17e+04 | 1.01e+03 | 2.17e+04 | 3.2e+04 | yes |
+| cpu | 1e+04 | ASAP | 20.8 | 2.68e+03 | 20.8 | 103 | yes |
+| cpu | 1e+04 | ASAP (no roll-ups) | 23.5 | 2.68e+03 | 23.5 | 114 | yes |
+| cpu | 1e+04 | PerQuery-CostAware | 69.9 | 3.33e+03 | 69.9 | 346 | yes |
+| cpu | 1e+04 | AutoSketch-Adapted | 2.17e+04 | 1.01e+03 | 2.17e+04 | 3.2e+04 | yes |
 | fargate | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 100 | AutoSketch-Adapted | 1.09e+03 | 1.01e+03 | 2.2e+04 | 4.5e+04 | **no** |
+| fargate | 100 | AutoSketch-Adapted | 1.02e+03 | 1.01e+03 | 2.17e+04 | 3.2e+04 | **no** |
 | fargate | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 300 | AutoSketch-Adapted | 1.09e+03 | 1.01e+03 | 2.2e+04 | 4.5e+04 | **no** |
-| fargate | 1e+03 | ASAP | 2.04 | 896 | 35.7 | 134 | yes |
-| fargate | 1e+03 | ASAP (no roll-ups) | 2.2 | 959 | 38.4 | 146 | yes |
-| fargate | 1e+03 | PerQuery-CostAware | 6.33 | 959 | 94 | 567 | yes |
-| fargate | 1e+03 | AutoSketch-Adapted | 1.09e+03 | 1.01e+03 | 2.2e+04 | 4.5e+04 | **no** |
-| fargate | 3e+03 | ASAP | 1.47 | 2.68e+03 | 21.1 | 139 | yes |
-| fargate | 3e+03 | ASAP (no roll-ups) | 1.63 | 2.68e+03 | 23.8 | 151 | yes |
-| fargate | 3e+03 | PerQuery-CostAware | 5.5 | 2.68e+03 | 72.9 | 572 | yes |
-| fargate | 3e+03 | AutoSketch-Adapted | 1.09e+03 | 1.01e+03 | 2.2e+04 | 4.5e+04 | yes |
-| fargate | 1e+04 | ASAP | 1.47 | 2.68e+03 | 21.1 | 139 | yes |
-| fargate | 1e+04 | ASAP (no roll-ups) | 1.63 | 2.68e+03 | 23.8 | 151 | yes |
-| fargate | 1e+04 | PerQuery-CostAware | 5.46 | 3.26e+03 | 72 | 572 | yes |
-| fargate | 1e+04 | AutoSketch-Adapted | 1.09e+03 | 1.01e+03 | 2.2e+04 | 4.5e+04 | yes |
+| fargate | 300 | AutoSketch-Adapted | 1.02e+03 | 1.01e+03 | 2.17e+04 | 3.2e+04 | **no** |
+| fargate | 1e+03 | ASAP | 1.83 | 989 | 34.7 | 95.1 | yes |
+| fargate | 1e+03 | ASAP (no roll-ups) | 1.99 | 989 | 37.4 | 107 | yes |
+| fargate | 1e+03 | PerQuery-CostAware | 5.08 | 989 | 89 | 331 | yes |
+| fargate | 1e+03 | AutoSketch-Adapted | 1.02e+03 | 1.01e+03 | 2.17e+04 | 3.2e+04 | **no** |
+| fargate | 3e+03 | ASAP | 1.3 | 2.68e+03 | 20.8 | 103 | yes |
+| fargate | 3e+03 | ASAP (no roll-ups) | 1.46 | 2.68e+03 | 23.5 | 114 | yes |
+| fargate | 3e+03 | PerQuery-CostAware | 4.36 | 2.97e+03 | 70.8 | 336 | yes |
+| fargate | 3e+03 | AutoSketch-Adapted | 1.02e+03 | 1.01e+03 | 2.17e+04 | 3.2e+04 | yes |
+| fargate | 1e+04 | ASAP | 1.3 | 2.68e+03 | 20.8 | 103 | yes |
+| fargate | 1e+04 | ASAP (no roll-ups) | 1.46 | 2.68e+03 | 23.5 | 114 | yes |
+| fargate | 1e+04 | PerQuery-CostAware | 4.36 | 2.97e+03 | 70.8 | 336 | yes |
+| fargate | 1e+04 | AutoSketch-Adapted | 1.02e+03 | 1.01e+03 | 2.17e+04 | 3.2e+04 | yes |
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | SLA (ms) | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|---|
-| cpu | 1e+03 | 416 | 96 | 264 | 35.5 | 38.2 | 6.9% |
-| cpu | 3e+03 | 416 | 88 | 256 | 21.1 | 23.7 | 11.1% |
-| cpu | 1e+04 | 416 | 88 | 256 | 21.1 | 23.7 | 11.1% |
-| fargate | 1e+03 | 416 | 96 | 264 | 2.04 | 2.2 | 7.3% |
-| fargate | 3e+03 | 416 | 88 | 256 | 1.47 | 1.63 | 9.9% |
-| fargate | 1e+04 | 416 | 88 | 256 | 1.47 | 1.63 | 9.9% |
+| cpu | 1e+03 | 416 | 96 | 264 | 34.7 | 37.4 | 7.1% |
+| cpu | 3e+03 | 416 | 88 | 256 | 20.8 | 23.5 | 11.3% |
+| cpu | 1e+04 | 416 | 88 | 256 | 20.8 | 23.5 | 11.3% |
+| fargate | 1e+03 | 416 | 96 | 264 | 1.83 | 1.99 | 8.0% |
+| fargate | 3e+03 | 416 | 88 | 256 | 1.3 | 1.46 | 10.9% |
+| fargate | 1e+04 | 416 | 88 | 256 | 1.3 | 1.46 | 10.9% |
 
 ## multi-grouping, m = 16: 992 RQEs
 
-Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 490 ms; planning time (search + measured benchmark) 4.31e+03 s.
+Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 490 ms; planning time (search + measured benchmark) 3.62e+03 s.
 
 | weights | SLA (ms) | method | cost | latency (ms) | CPU (vCPU) | GiB | meets SLA |
 |---|---|---|---|---|---|---|---|
 | cpu | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 100 | AutoSketch-Adapted | 163 | 490 | 163 | 56.8 | **no** |
+| cpu | 100 | AutoSketch-Adapted | 154 | 490 | 154 | 56.1 | **no** |
 | cpu | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 300 | AutoSketch-Adapted | 163 | 490 | 163 | 56.8 | **no** |
-| cpu | 1e+03 | ASAP | 3.53 | 557 | 3.53 | 17 | yes |
-| cpu | 1e+03 | ASAP (no roll-ups) | 8.81 | 959 | 8.81 | 41.5 | yes |
-| cpu | 1e+03 | PerQuery-CostAware | 17.1 | 959 | 17.1 | 59 | yes |
-| cpu | 1e+03 | AutoSketch-Adapted | 163 | 490 | 163 | 56.8 | yes |
-| cpu | 3e+03 | ASAP | 3.53 | 557 | 3.53 | 17 | yes |
-| cpu | 3e+03 | ASAP (no roll-ups) | 8.81 | 959 | 8.81 | 41.5 | yes |
-| cpu | 3e+03 | PerQuery-CostAware | 17.1 | 959 | 17.1 | 59 | yes |
-| cpu | 3e+03 | AutoSketch-Adapted | 163 | 490 | 163 | 56.8 | yes |
-| cpu | 1e+04 | ASAP | 3.53 | 557 | 3.53 | 17 | yes |
-| cpu | 1e+04 | ASAP (no roll-ups) | 8.81 | 959 | 8.81 | 41.5 | yes |
-| cpu | 1e+04 | PerQuery-CostAware | 17.1 | 959 | 17.1 | 59 | yes |
-| cpu | 1e+04 | AutoSketch-Adapted | 163 | 490 | 163 | 56.8 | yes |
+| cpu | 300 | AutoSketch-Adapted | 154 | 490 | 154 | 56.1 | **no** |
+| cpu | 1e+03 | ASAP | 3.52 | 557 | 3.52 | 16.2 | yes |
+| cpu | 1e+03 | ASAP (no roll-ups) | 8.8 | 959 | 8.8 | 39.5 | yes |
+| cpu | 1e+03 | PerQuery-CostAware | 17.1 | 959 | 17.1 | 56.2 | yes |
+| cpu | 1e+03 | AutoSketch-Adapted | 154 | 490 | 154 | 56.1 | yes |
+| cpu | 3e+03 | ASAP | 3.52 | 557 | 3.52 | 16.2 | yes |
+| cpu | 3e+03 | ASAP (no roll-ups) | 8.8 | 959 | 8.8 | 39.5 | yes |
+| cpu | 3e+03 | PerQuery-CostAware | 17.1 | 959 | 17.1 | 56.2 | yes |
+| cpu | 3e+03 | AutoSketch-Adapted | 154 | 490 | 154 | 56.1 | yes |
+| cpu | 1e+04 | ASAP | 3.52 | 557 | 3.52 | 16.2 | yes |
+| cpu | 1e+04 | ASAP (no roll-ups) | 8.8 | 959 | 8.8 | 39.5 | yes |
+| cpu | 1e+04 | PerQuery-CostAware | 17.1 | 959 | 17.1 | 56.2 | yes |
+| cpu | 1e+04 | AutoSketch-Adapted | 154 | 490 | 154 | 56.1 | yes |
 | fargate | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 100 | AutoSketch-Adapted | 6.87 | 490 | 163 | 56.8 | **no** |
+| fargate | 100 | AutoSketch-Adapted | 6.5 | 490 | 154 | 56.1 | **no** |
 | fargate | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 300 | AutoSketch-Adapted | 6.87 | 490 | 163 | 56.8 | **no** |
-| fargate | 1e+03 | ASAP | 0.218 | 557 | 3.59 | 16.4 | yes |
-| fargate | 1e+03 | ASAP (no roll-ups) | 0.542 | 959 | 8.94 | 40.4 | yes |
-| fargate | 1e+03 | PerQuery-CostAware | 0.955 | 959 | 17.2 | 57.8 | yes |
-| fargate | 1e+03 | AutoSketch-Adapted | 6.87 | 490 | 163 | 56.8 | yes |
-| fargate | 3e+03 | ASAP | 0.218 | 557 | 3.59 | 16.4 | yes |
-| fargate | 3e+03 | ASAP (no roll-ups) | 0.542 | 959 | 8.94 | 40.4 | yes |
-| fargate | 3e+03 | PerQuery-CostAware | 0.955 | 959 | 17.2 | 57.8 | yes |
-| fargate | 3e+03 | AutoSketch-Adapted | 6.87 | 490 | 163 | 56.8 | yes |
-| fargate | 1e+04 | ASAP | 0.218 | 557 | 3.59 | 16.4 | yes |
-| fargate | 1e+04 | ASAP (no roll-ups) | 0.542 | 959 | 8.94 | 40.4 | yes |
-| fargate | 1e+04 | PerQuery-CostAware | 0.955 | 959 | 17.2 | 57.8 | yes |
-| fargate | 1e+04 | AutoSketch-Adapted | 6.87 | 490 | 163 | 56.8 | yes |
+| fargate | 300 | AutoSketch-Adapted | 6.5 | 490 | 154 | 56.1 | **no** |
+| fargate | 1e+03 | ASAP | 0.215 | 557 | 3.52 | 16.2 | yes |
+| fargate | 1e+03 | ASAP (no roll-ups) | 0.532 | 959 | 8.8 | 39.5 | yes |
+| fargate | 1e+03 | PerQuery-CostAware | 0.942 | 959 | 17.1 | 56.2 | yes |
+| fargate | 1e+03 | AutoSketch-Adapted | 6.5 | 490 | 154 | 56.1 | yes |
+| fargate | 3e+03 | ASAP | 0.215 | 557 | 3.52 | 16.2 | yes |
+| fargate | 3e+03 | ASAP (no roll-ups) | 0.532 | 959 | 8.8 | 39.5 | yes |
+| fargate | 3e+03 | PerQuery-CostAware | 0.942 | 959 | 17.1 | 56.2 | yes |
+| fargate | 3e+03 | AutoSketch-Adapted | 6.5 | 490 | 154 | 56.1 | yes |
+| fargate | 1e+04 | ASAP | 0.215 | 557 | 3.52 | 16.2 | yes |
+| fargate | 1e+04 | ASAP (no roll-ups) | 0.532 | 959 | 8.8 | 39.5 | yes |
+| fargate | 1e+04 | PerQuery-CostAware | 0.942 | 959 | 17.1 | 56.2 | yes |
+| fargate | 1e+04 | AutoSketch-Adapted | 6.5 | 490 | 154 | 56.1 | yes |
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | SLA (ms) | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|---|
-| cpu | 1e+03 | 832 | 80 | 416 | 3.53 | 8.81 | 59.9% |
-| cpu | 3e+03 | 832 | 80 | 416 | 3.53 | 8.81 | 59.9% |
-| cpu | 1e+04 | 832 | 80 | 416 | 3.53 | 8.81 | 59.9% |
-| fargate | 1e+03 | 832 | 80 | 416 | 0.218 | 0.542 | 59.7% |
-| fargate | 3e+03 | 832 | 80 | 416 | 0.218 | 0.542 | 59.7% |
-| fargate | 1e+04 | 832 | 80 | 416 | 0.218 | 0.542 | 59.7% |
+| cpu | 1e+03 | 832 | 80 | 416 | 3.52 | 8.8 | 60.0% |
+| cpu | 3e+03 | 832 | 80 | 416 | 3.52 | 8.8 | 60.0% |
+| cpu | 1e+04 | 832 | 80 | 416 | 3.52 | 8.8 | 60.0% |
+| fargate | 1e+03 | 832 | 80 | 416 | 0.215 | 0.532 | 59.7% |
+| fargate | 3e+03 | 832 | 80 | 416 | 0.215 | 0.532 | 59.7% |
+| fargate | 1e+04 | 832 | 80 | 416 | 0.215 | 0.532 | 59.7% |
 
 ## mixed + multi-grouping, m = 16: 1664 RQEs
 
-Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 7.7e+03 s.
+Sanity violations: 0. Tightest feasible SLA: ASAP 490 ms, PerQuery 490 ms. AutoSketch latency 1.01e+03 ms; planning time (search + measured benchmark) 6.34e+03 s.
 
 | weights | SLA (ms) | method | cost | latency (ms) | CPU (vCPU) | GiB | meets SLA |
 |---|---|---|---|---|---|---|---|
 | cpu | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 100 | AutoSketch-Adapted | 4.4e+04 | 1.01e+03 | 4.4e+04 | 8.99e+04 | **no** |
+| cpu | 100 | AutoSketch-Adapted | 4.34e+04 | 1.01e+03 | 4.34e+04 | 6.41e+04 | **no** |
 | cpu | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | cpu | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | cpu | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| cpu | 300 | AutoSketch-Adapted | 4.4e+04 | 1.01e+03 | 4.4e+04 | 8.99e+04 | **no** |
-| cpu | 1e+03 | ASAP | 71.1 | 980 | 71.1 | 483 | yes |
-| cpu | 1e+03 | ASAP (no roll-ups) | 76.4 | 980 | 76.4 | 508 | yes |
-| cpu | 1e+03 | PerQuery-CostAware | 185 | 980 | 185 | 2.54e+03 | yes |
-| cpu | 1e+03 | AutoSketch-Adapted | 4.4e+04 | 1.01e+03 | 4.4e+04 | 8.99e+04 | **no** |
-| cpu | 3e+03 | ASAP | 42.2 | 2.68e+03 | 42.2 | 278 | yes |
-| cpu | 3e+03 | ASAP (no roll-ups) | 47.4 | 2.68e+03 | 47.4 | 303 | yes |
-| cpu | 3e+03 | PerQuery-CostAware | 145 | 2.68e+03 | 145 | 2.28e+03 | yes |
-| cpu | 3e+03 | AutoSketch-Adapted | 4.4e+04 | 1.01e+03 | 4.4e+04 | 8.99e+04 | yes |
-| cpu | 1e+04 | ASAP | 42.2 | 2.68e+03 | 42.2 | 278 | yes |
-| cpu | 1e+04 | ASAP (no roll-ups) | 47.4 | 2.68e+03 | 47.4 | 303 | yes |
-| cpu | 1e+04 | PerQuery-CostAware | 141 | 3.33e+03 | 141 | 1.22e+03 | yes |
-| cpu | 1e+04 | AutoSketch-Adapted | 4.4e+04 | 1.01e+03 | 4.4e+04 | 8.99e+04 | yes |
+| cpu | 300 | AutoSketch-Adapted | 4.34e+04 | 1.01e+03 | 4.34e+04 | 6.41e+04 | **no** |
+| cpu | 1e+03 | ASAP | 69.5 | 989 | 69.5 | 190 | yes |
+| cpu | 1e+03 | ASAP (no roll-ups) | 74.8 | 989 | 74.8 | 213 | yes |
+| cpu | 1e+03 | PerQuery-CostAware | 178 | 989 | 178 | 663 | yes |
+| cpu | 1e+03 | AutoSketch-Adapted | 4.34e+04 | 1.01e+03 | 4.34e+04 | 6.41e+04 | **no** |
+| cpu | 3e+03 | ASAP | 41.6 | 2.68e+03 | 41.6 | 205 | yes |
+| cpu | 3e+03 | ASAP (no roll-ups) | 46.9 | 2.68e+03 | 46.9 | 229 | yes |
+| cpu | 3e+03 | PerQuery-CostAware | 142 | 2.97e+03 | 142 | 672 | yes |
+| cpu | 3e+03 | AutoSketch-Adapted | 4.34e+04 | 1.01e+03 | 4.34e+04 | 6.41e+04 | yes |
+| cpu | 1e+04 | ASAP | 41.6 | 2.68e+03 | 41.6 | 205 | yes |
+| cpu | 1e+04 | ASAP (no roll-ups) | 46.9 | 2.68e+03 | 46.9 | 229 | yes |
+| cpu | 1e+04 | PerQuery-CostAware | 140 | 3.33e+03 | 140 | 693 | yes |
+| cpu | 1e+04 | AutoSketch-Adapted | 4.34e+04 | 1.01e+03 | 4.34e+04 | 6.41e+04 | yes |
 | fargate | 100 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 100 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 100 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 100 | AutoSketch-Adapted | 2.18e+03 | 1.01e+03 | 4.4e+04 | 8.99e+04 | **no** |
+| fargate | 100 | AutoSketch-Adapted | 2.04e+03 | 1.01e+03 | 4.34e+04 | 6.41e+04 | **no** |
 | fargate | 300 | ASAP | infeasible (tightest 490 ms) |||||
 | fargate | 300 | ASAP (no roll-ups) | infeasible (tightest 490 ms) |||||
 | fargate | 300 | PerQuery-CostAware | infeasible (tightest 490 ms) |||||
-| fargate | 300 | AutoSketch-Adapted | 2.18e+03 | 1.01e+03 | 4.4e+04 | 8.99e+04 | **no** |
-| fargate | 1e+03 | ASAP | 4.08 | 896 | 71.4 | 268 | yes |
-| fargate | 1e+03 | ASAP (no roll-ups) | 4.41 | 959 | 76.7 | 292 | yes |
-| fargate | 1e+03 | PerQuery-CostAware | 12.7 | 959 | 188 | 1.13e+03 | yes |
-| fargate | 1e+03 | AutoSketch-Adapted | 2.18e+03 | 1.01e+03 | 4.4e+04 | 8.99e+04 | **no** |
-| fargate | 3e+03 | ASAP | 2.95 | 2.68e+03 | 42.2 | 278 | yes |
-| fargate | 3e+03 | ASAP (no roll-ups) | 3.27 | 2.68e+03 | 47.6 | 302 | yes |
-| fargate | 3e+03 | PerQuery-CostAware | 11 | 2.68e+03 | 146 | 1.14e+03 | yes |
-| fargate | 3e+03 | AutoSketch-Adapted | 2.18e+03 | 1.01e+03 | 4.4e+04 | 8.99e+04 | yes |
-| fargate | 1e+04 | ASAP | 2.95 | 2.68e+03 | 42.2 | 278 | yes |
-| fargate | 1e+04 | ASAP (no roll-ups) | 3.27 | 2.68e+03 | 47.6 | 302 | yes |
-| fargate | 1e+04 | PerQuery-CostAware | 10.9 | 3.26e+03 | 144 | 1.14e+03 | yes |
-| fargate | 1e+04 | AutoSketch-Adapted | 2.18e+03 | 1.01e+03 | 4.4e+04 | 8.99e+04 | yes |
+| fargate | 300 | AutoSketch-Adapted | 2.04e+03 | 1.01e+03 | 4.34e+04 | 6.41e+04 | **no** |
+| fargate | 1e+03 | ASAP | 3.66 | 989 | 69.5 | 190 | yes |
+| fargate | 1e+03 | ASAP (no roll-ups) | 3.98 | 989 | 74.8 | 213 | yes |
+| fargate | 1e+03 | PerQuery-CostAware | 10.2 | 989 | 178 | 663 | yes |
+| fargate | 1e+03 | AutoSketch-Adapted | 2.04e+03 | 1.01e+03 | 4.34e+04 | 6.41e+04 | **no** |
+| fargate | 3e+03 | ASAP | 2.6 | 2.68e+03 | 41.6 | 205 | yes |
+| fargate | 3e+03 | ASAP (no roll-ups) | 2.92 | 2.68e+03 | 46.9 | 229 | yes |
+| fargate | 3e+03 | PerQuery-CostAware | 8.73 | 2.97e+03 | 142 | 672 | yes |
+| fargate | 3e+03 | AutoSketch-Adapted | 2.04e+03 | 1.01e+03 | 4.34e+04 | 6.41e+04 | yes |
+| fargate | 1e+04 | ASAP | 2.6 | 2.68e+03 | 41.6 | 205 | yes |
+| fargate | 1e+04 | ASAP (no roll-ups) | 2.92 | 2.68e+03 | 46.9 | 229 | yes |
+| fargate | 1e+04 | PerQuery-CostAware | 8.73 | 2.97e+03 | 142 | 672 | yes |
+| fargate | 1e+04 | AutoSketch-Adapted | 2.04e+03 | 1.01e+03 | 4.34e+04 | 6.41e+04 | yes |
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | SLA (ms) | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|---|
-| cpu | 1e+03 | 832 | 192 | 528 | 71.1 | 76.4 | 6.9% |
-| cpu | 3e+03 | 832 | 176 | 512 | 42.2 | 47.4 | 11.1% |
-| cpu | 1e+04 | 832 | 176 | 512 | 42.2 | 47.4 | 11.1% |
-| fargate | 1e+03 | 832 | 192 | 528 | 4.08 | 4.41 | 7.3% |
-| fargate | 3e+03 | 832 | 176 | 512 | 2.95 | 3.27 | 9.9% |
-| fargate | 1e+04 | 832 | 176 | 512 | 2.95 | 3.27 | 9.9% |
+| cpu | 1e+03 | 832 | 192 | 528 | 69.5 | 74.8 | 7.1% |
+| cpu | 3e+03 | 832 | 176 | 512 | 41.6 | 46.9 | 11.3% |
+| cpu | 1e+04 | 832 | 176 | 512 | 41.6 | 46.9 | 11.3% |
+| fargate | 1e+03 | 832 | 192 | 528 | 3.66 | 3.98 | 8.0% |
+| fargate | 3e+03 | 832 | 176 | 512 | 2.6 | 2.92 | 10.9% |
+| fargate | 1e+04 | 832 | 176 | 512 | 2.6 | 2.92 | 10.9% |
diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/summary_synthetic.md b/rqe-optimizer/results/autosketch-vs-asap-hydra/summary_synthetic.md
index 30e9950b..fc8f4ba9 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/summary_synthetic.md
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/summary_synthetic.md
@@ -4,372 +4,372 @@ Cost by use: `w_cpu · AUC(CPU) + w_mem · AUC(memory)` (CPU only, in vCPU; Farg
 
 ## mixed + multi-grouping
 
-104 RQEs on 9 streams; dropped: 0; sanity violations: 0. AutoSketch: 316 probes, 19 distinct (metric, config); measured benchmark 481 s at N = 1e+08 (paper rate 1.14e+03 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 490 ms.
+104 RQEs on 9 streams; dropped: 0; sanity violations: 0. AutoSketch: 238 probes, 15 distinct (metric, config); measured benchmark 396 s at N = 1e+08 (paper rate 900 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 490 ms.
 
 | weights | method | cost (unbounded) | CPU (vCPU) | GiB | latency (ms) | median latency (ms) | planning (s) | cost at AutoSketch's latency |
 |---|---|---|---|---|---|---|---|---|
-| cpu | ASAP | 2.6 | 2.6 | 22.4 | 1.34e+04 | 51.1 | 0.939 | 4.44 |
-| cpu | ASAP (no roll-ups) | 2.93 | 2.93 | 24 | 1.34e+04 | 39 | 0.907 | 4.77 |
-| cpu | PerQuery-CostAware | 8.84 | 8.84 | 76.4 | 3.33e+03 | 59.9 | 0.64 | 11.5 |
-| cpu | AutoSketch-Adapted | 2.75e+03 | 2.75e+03 | 5.62e+03 | 1.01e+03 | 10.3 | 481 | 2.75e+03 |
-| fargate | ASAP | 0.184 | 2.64 | 17.4 | 2.68e+03 | 51.1 | 1.07 | 0.255 |
-| fargate | ASAP (no roll-ups) | 0.204 | 2.97 | 18.8 | 2.68e+03 | 39 | 0.938 | 0.275 |
-| fargate | PerQuery-CostAware | 0.683 | 9 | 71.5 | 3.26e+03 | 59.9 | 0.645 | 0.792 |
-| fargate | AutoSketch-Adapted | 136 | 2.75e+03 | 5.62e+03 | 1.01e+03 | 10.3 | 481 | 136 |
+| cpu | ASAP | 2.57 | 2.57 | 17.9 | 1.34e+04 | 46.7 | 2.09 | 4.34 |
+| cpu | ASAP (no roll-ups) | 2.9 | 2.9 | 19.3 | 1.34e+04 | 39 | 2.03 | 4.67 |
+| cpu | PerQuery-CostAware | 8.74 | 8.74 | 43.3 | 3.33e+03 | 59.1 | 2.23 | 11.1 |
+| cpu | AutoSketch-Adapted | 2.71e+03 | 2.71e+03 | 4.01e+03 | 1.01e+03 | 9.45 | 396 | 2.71e+03 |
+| fargate | ASAP | 0.162 | 2.6 | 12.8 | 2.68e+03 | 46.7 | 2.39 | 0.229 |
+| fargate | ASAP (no roll-ups) | 0.182 | 2.93 | 14.3 | 2.68e+03 | 39 | 2.19 | 0.249 |
+| fargate | PerQuery-CostAware | 0.545 | 8.85 | 42 | 2.97e+03 | 59.1 | 2.24 | 0.635 |
+| fargate | AutoSketch-Adapted | 128 | 2.71e+03 | 4.01e+03 | 1.01e+03 | 9.45 | 396 | 128 |
 
 Frontier points (latency ms, cost), by weights:
 
-- cpu, ASAP: (490, 7.26), (649, 5.97), (813, 5.21), (980, 4.44), (1.08e+03, 4.38), (1.48e+03, 4.05), (2.68e+03, 2.64), (1.34e+04, 2.6)
-- cpu, ASAP (no roll-ups): (490, 7.76), (649, 6.34), (813, 5.57), (980, 4.77), (1.08e+03, 4.71), (1.48e+03, 4.38), (2.68e+03, 2.97), (1.34e+04, 2.93)
-- cpu, PerQuery-CostAware: (490, 16.6), (575, 14.6), (673, 13.3), (813, 12.4), (980, 11.5), (1.14e+03, 10.9), (1.34e+03, 10.4), (1.63e+03, 9.94), (1.96e+03, 9.89), (2.29e+03, 9.43), (2.68e+03, 9.05), (3.33e+03, 8.84)
-- fargate, ASAP: (490, 0.367), (557, 0.318), (649, 0.315), (765, 0.286), (896, 0.255), (1.08e+03, 0.251), (1.3e+03, 0.248), (1.48e+03, 0.241), (2.29e+03, 0.213), (2.68e+03, 0.184)
-- fargate, ASAP (no roll-ups): (490, 0.395), (557, 0.34), (649, 0.337), (765, 0.308), (896, 0.277), (959, 0.275), (1.08e+03, 0.271), (1.3e+03, 0.268), (1.48e+03, 0.262), (2.29e+03, 0.233), (2.68e+03, 0.204)
-- fargate, PerQuery-CostAware: (490, 0.993), (575, 0.905), (673, 0.854), (813, 0.816), (959, 0.792), (1.14e+03, 0.761), (1.34e+03, 0.738), (1.63e+03, 0.723), (2.29e+03, 0.702), (2.68e+03, 0.688), (3.26e+03, 0.683)
+- cpu, ASAP: (490, 7.19), (658, 5.91), (765, 5.16), (989, 4.34), (1.19e+03, 4.29), (1.48e+03, 4.02), (2.68e+03, 2.6), (1.34e+04, 2.57)
+- cpu, ASAP (no roll-ups): (490, 7.69), (658, 6.28), (765, 5.52), (989, 4.67), (1.19e+03, 4.62), (1.48e+03, 4.35), (2.68e+03, 2.93), (1.34e+04, 2.9)
+- cpu, PerQuery-CostAware: (490, 16.4), (575, 14.2), (673, 12.9), (765, 12.2), (959, 11.5), (989, 11.1), (1.14e+03, 10.8), (1.34e+03, 10.2), (1.49e+03, 9.8), (2.29e+03, 9.31), (2.68e+03, 8.95), (3.33e+03, 8.74)
+- fargate, ASAP: (490, 0.344), (557, 0.296), (592, 0.293), (765, 0.262), (896, 0.232), (989, 0.229), (1.19e+03, 0.226), (1.48e+03, 0.22), (2.29e+03, 0.192), (2.68e+03, 0.162)
+- fargate, ASAP (no roll-ups): (490, 0.372), (557, 0.317), (592, 0.315), (765, 0.284), (896, 0.254), (989, 0.249), (1.19e+03, 0.246), (1.48e+03, 0.24), (2.29e+03, 0.211), (2.68e+03, 0.182)
+- fargate, PerQuery-CostAware: (490, 0.844), (575, 0.759), (673, 0.703), (765, 0.674), (896, 0.65), (989, 0.635), (1.19e+03, 0.613), (1.49e+03, 0.584), (1.98e+03, 0.578), (2.29e+03, 0.564), (2.97e+03, 0.545)
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|
-| cpu | 52 | 11 | 32 | 2.6 | 2.93 | 11.2% |
-| fargate | 52 | 11 | 32 | 0.184 | 0.204 | 9.9% |
+| cpu | 52 | 11 | 32 | 2.57 | 2.9 | 11.4% |
+| fargate | 52 | 11 | 32 | 0.162 | 0.182 | 10.9% |
 
 ## mixed + multi-grouping, m = 8
 
-832 RQEs on 72 streams; dropped: 0; sanity violations: 0. AutoSketch: 2528 probes, 152 distinct (metric, config); measured benchmark 3.85e+03 s at N = 1e+08 (paper rate 9.12e+03 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 490 ms.
+832 RQEs on 72 streams; dropped: 0; sanity violations: 0. AutoSketch: 1904 probes, 120 distinct (metric, config); measured benchmark 3.17e+03 s at N = 1e+08 (paper rate 7.2e+03 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 490 ms.
 
 | weights | method | cost (unbounded) | CPU (vCPU) | GiB | latency (ms) | median latency (ms) | planning (s) | cost at AutoSketch's latency |
 |---|---|---|---|---|---|---|---|---|
-| cpu | ASAP | 20.8 | 20.8 | 179 | 1.34e+04 | 51.1 | 6.49 | 35.5 |
-| cpu | ASAP (no roll-ups) | 23.5 | 23.5 | 192 | 1.34e+04 | 39 | 6.12 | 38.2 |
-| cpu | PerQuery-CostAware | 70.7 | 70.7 | 612 | 3.33e+03 | 59.9 | 5.6 | 92.3 |
-| cpu | AutoSketch-Adapted | 2.2e+04 | 2.2e+04 | 4.5e+04 | 1.01e+03 | 10.3 | 3.85e+03 | 2.2e+04 |
-| fargate | ASAP | 1.47 | 21.1 | 139 | 2.68e+03 | 51.1 | 8.69 | 2.04 |
-| fargate | ASAP (no roll-ups) | 1.63 | 23.8 | 151 | 2.68e+03 | 39 | 7.4 | 2.2 |
-| fargate | PerQuery-CostAware | 5.46 | 72 | 572 | 3.26e+03 | 59.9 | 5.65 | 6.33 |
-| fargate | AutoSketch-Adapted | 1.09e+03 | 2.2e+04 | 4.5e+04 | 1.01e+03 | 10.3 | 3.85e+03 | 1.09e+03 |
+| cpu | ASAP | 20.6 | 20.6 | 143 | 1.34e+04 | 46.7 | 18.3 | 34.7 |
+| cpu | ASAP (no roll-ups) | 23.2 | 23.2 | 155 | 1.34e+04 | 39 | 17.5 | 37.4 |
+| cpu | PerQuery-CostAware | 69.9 | 69.9 | 346 | 3.33e+03 | 59.1 | 19.7 | 89 |
+| cpu | AutoSketch-Adapted | 2.17e+04 | 2.17e+04 | 3.2e+04 | 1.01e+03 | 9.45 | 3.17e+03 | 2.17e+04 |
+| fargate | ASAP | 1.3 | 20.8 | 103 | 2.68e+03 | 46.7 | 22.7 | 1.83 |
+| fargate | ASAP (no roll-ups) | 1.46 | 23.5 | 114 | 2.68e+03 | 39 | 18.8 | 1.99 |
+| fargate | PerQuery-CostAware | 4.36 | 70.8 | 336 | 2.97e+03 | 59.1 | 19.7 | 5.08 |
+| fargate | AutoSketch-Adapted | 1.02e+03 | 2.17e+04 | 3.2e+04 | 1.01e+03 | 9.45 | 3.17e+03 | 1.02e+03 |
 
 Frontier points (latency ms, cost), by weights:
 
-- cpu, ASAP: (490, 58.1), (649, 47.8), (813, 41.7), (980, 35.5), (1.08e+03, 35), (1.48e+03, 32.4), (2.68e+03, 21.1), (1.34e+04, 20.8)
-- cpu, ASAP (no roll-ups): (490, 62), (649, 50.7), (813, 44.6), (980, 38.2), (1.08e+03, 37.7), (1.48e+03, 35.1), (2.68e+03, 23.7), (1.34e+04, 23.5)
-- cpu, PerQuery-CostAware: (490, 133), (575, 117), (673, 106), (813, 99), (980, 92.3), (1.14e+03, 87.4), (1.34e+03, 82.9), (1.63e+03, 79.5), (1.96e+03, 79.1), (2.29e+03, 75.4), (2.68e+03, 72.4), (3.33e+03, 70.7)
-- fargate, ASAP: (490, 2.93), (557, 2.55), (649, 2.52), (765, 2.29), (896, 2.04), (1.08e+03, 2.01), (1.3e+03, 1.98), (1.48e+03, 1.93), (2.29e+03, 1.71), (2.68e+03, 1.47)
-- fargate, ASAP (no roll-ups): (490, 3.16), (557, 2.72), (649, 2.7), (765, 2.46), (896, 2.22), (959, 2.2), (1.08e+03, 2.17), (1.3e+03, 2.14), (1.48e+03, 2.09), (2.29e+03, 1.87), (2.68e+03, 1.63)
-- fargate, PerQuery-CostAware: (490, 7.95), (575, 7.24), (673, 6.84), (813, 6.53), (959, 6.33), (1.14e+03, 6.09), (1.34e+03, 5.91), (1.63e+03, 5.78), (2.29e+03, 5.62), (2.68e+03, 5.5), (3.26e+03, 5.46)
+- cpu, ASAP: (490, 57.5), (658, 47.3), (765, 41.3), (989, 34.7), (1.19e+03, 34.3), (1.48e+03, 32.1), (2.68e+03, 20.8), (1.34e+04, 20.6)
+- cpu, ASAP (no roll-ups): (490, 61.5), (658, 50.2), (765, 44.2), (989, 37.4), (1.19e+03, 36.9), (1.48e+03, 34.8), (2.68e+03, 23.5), (1.34e+04, 23.2)
+- cpu, PerQuery-CostAware: (490, 131), (575, 114), (673, 103), (765, 97.2), (959, 91.9), (989, 89), (1.14e+03, 86.2), (1.34e+03, 81.8), (1.49e+03, 78.4), (2.29e+03, 74.5), (2.68e+03, 71.6), (3.33e+03, 69.9)
+- fargate, ASAP: (490, 2.75), (557, 2.36), (592, 2.34), (765, 2.1), (896, 1.86), (989, 1.83), (1.19e+03, 1.81), (1.48e+03, 1.76), (2.29e+03, 1.53), (2.68e+03, 1.3)
+- fargate, ASAP (no roll-ups): (490, 2.97), (557, 2.54), (592, 2.52), (765, 2.27), (896, 2.03), (989, 1.99), (1.19e+03, 1.97), (1.48e+03, 1.92), (2.29e+03, 1.69), (2.68e+03, 1.46)
+- fargate, PerQuery-CostAware: (490, 6.75), (575, 6.07), (673, 5.62), (765, 5.39), (896, 5.2), (989, 5.08), (1.19e+03, 4.91), (1.49e+03, 4.67), (1.98e+03, 4.63), (2.29e+03, 4.51), (2.97e+03, 4.36)
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|
-| cpu | 416 | 88 | 256 | 20.8 | 23.5 | 11.2% |
-| fargate | 416 | 88 | 256 | 1.47 | 1.63 | 9.9% |
+| cpu | 416 | 88 | 256 | 20.6 | 23.2 | 11.4% |
+| fargate | 416 | 88 | 256 | 1.3 | 1.46 | 10.9% |
 
 ## mixed + multi-grouping, m = 16
 
-1664 RQEs on 144 streams; dropped: 0; sanity violations: 0. AutoSketch: 5056 probes, 304 distinct (metric, config); measured benchmark 7.7e+03 s at N = 1e+08 (paper rate 1.82e+04 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 490 ms.
+1664 RQEs on 144 streams; dropped: 0; sanity violations: 0. AutoSketch: 3808 probes, 240 distinct (metric, config); measured benchmark 6.34e+03 s at N = 1e+08 (paper rate 1.44e+04 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 490 ms.
 
 | weights | method | cost (unbounded) | CPU (vCPU) | GiB | latency (ms) | median latency (ms) | planning (s) | cost at AutoSketch's latency |
 |---|---|---|---|---|---|---|---|---|
-| cpu | ASAP | 41.7 | 41.7 | 359 | 1.34e+04 | 51.1 | 15.6 | 71.1 |
-| cpu | ASAP (no roll-ups) | 47 | 47 | 383 | 1.34e+04 | 39 | 14.3 | 76.4 |
-| cpu | PerQuery-CostAware | 141 | 141 | 1.22e+03 | 3.33e+03 | 59.9 | 12.9 | 185 |
-| cpu | AutoSketch-Adapted | 4.4e+04 | 4.4e+04 | 8.99e+04 | 1.01e+03 | 10.3 | 7.7e+03 | 4.4e+04 |
-| fargate | ASAP | 2.95 | 42.2 | 278 | 2.68e+03 | 51.1 | 22.6 | 4.08 |
-| fargate | ASAP (no roll-ups) | 3.27 | 47.6 | 302 | 2.68e+03 | 39 | 18.6 | 4.41 |
-| fargate | PerQuery-CostAware | 10.9 | 144 | 1.14e+03 | 3.26e+03 | 59.9 | 13.1 | 12.7 |
-| fargate | AutoSketch-Adapted | 2.18e+03 | 4.4e+04 | 8.99e+04 | 1.01e+03 | 10.3 | 7.7e+03 | 2.18e+03 |
+| cpu | ASAP | 41.1 | 41.1 | 286 | 1.34e+04 | 46.7 | 16.1 | 69.5 |
+| cpu | ASAP (no roll-ups) | 46.4 | 46.4 | 309 | 1.34e+04 | 39 | 15.1 | 74.8 |
+| cpu | PerQuery-CostAware | 140 | 140 | 693 | 3.33e+03 | 59.1 | 17.1 | 178 |
+| cpu | AutoSketch-Adapted | 4.34e+04 | 4.34e+04 | 6.41e+04 | 1.01e+03 | 9.45 | 6.34e+03 | 4.34e+04 |
+| fargate | ASAP | 2.6 | 41.6 | 205 | 2.68e+03 | 46.7 | 22.2 | 3.66 |
+| fargate | ASAP (no roll-ups) | 2.92 | 46.9 | 229 | 2.68e+03 | 39 | 18.5 | 3.98 |
+| fargate | PerQuery-CostAware | 8.73 | 142 | 672 | 2.97e+03 | 59.1 | 17.2 | 10.2 |
+| fargate | AutoSketch-Adapted | 2.04e+03 | 4.34e+04 | 6.41e+04 | 1.01e+03 | 9.45 | 6.34e+03 | 2.04e+03 |
 
 Frontier points (latency ms, cost), by weights:
 
-- cpu, ASAP: (490, 116), (649, 95.6), (813, 83.3), (980, 71.1), (1.08e+03, 70.1), (1.48e+03, 64.8), (2.68e+03, 42.2), (1.34e+04, 41.7)
-- cpu, ASAP (no roll-ups): (490, 124), (649, 101), (813, 89.1), (980, 76.4), (1.08e+03, 75.4), (1.48e+03, 70.1), (2.68e+03, 47.4), (1.34e+04, 47)
-- cpu, PerQuery-CostAware: (490, 266), (575, 233), (673, 212), (813, 198), (980, 185), (1.14e+03, 175), (1.34e+03, 166), (1.63e+03, 159), (1.96e+03, 158), (2.29e+03, 151), (2.68e+03, 145), (3.33e+03, 141)
-- fargate, ASAP: (490, 5.87), (557, 5.09), (649, 5.05), (765, 4.58), (896, 4.08), (1.08e+03, 4.01), (1.3e+03, 3.97), (1.48e+03, 3.86), (2.29e+03, 3.41), (2.68e+03, 2.95)
-- fargate, ASAP (no roll-ups): (490, 6.32), (557, 5.45), (649, 5.4), (765, 4.93), (896, 4.43), (959, 4.41), (1.08e+03, 4.34), (1.3e+03, 4.29), (1.48e+03, 4.19), (2.29e+03, 3.73), (2.68e+03, 3.27)
-- fargate, PerQuery-CostAware: (490, 15.9), (575, 14.5), (673, 13.7), (813, 13.1), (959, 12.7), (1.14e+03, 12.2), (1.34e+03, 11.8), (1.63e+03, 11.6), (2.29e+03, 11.2), (2.68e+03, 11), (3.26e+03, 10.9)
+- cpu, ASAP: (490, 115), (658, 94.6), (765, 82.5), (989, 69.5), (1.19e+03, 68.6), (1.48e+03, 64.3), (2.68e+03, 41.6), (1.34e+04, 41.1)
+- cpu, ASAP (no roll-ups): (490, 123), (658, 100), (765, 88.4), (989, 74.8), (1.19e+03, 73.9), (1.48e+03, 69.6), (2.68e+03, 46.9), (1.34e+04, 46.4)
+- cpu, PerQuery-CostAware: (490, 262), (575, 228), (673, 206), (765, 194), (959, 184), (989, 178), (1.14e+03, 172), (1.34e+03, 164), (1.49e+03, 157), (2.29e+03, 149), (2.68e+03, 143), (3.33e+03, 140)
+- fargate, ASAP: (490, 5.5), (557, 4.73), (592, 4.69), (765, 4.2), (896, 3.71), (989, 3.66), (1.19e+03, 3.62), (1.48e+03, 3.52), (2.29e+03, 3.06), (2.68e+03, 2.6)
+- fargate, ASAP (no roll-ups): (490, 5.95), (557, 5.07), (592, 5.03), (765, 4.55), (896, 4.06), (989, 3.98), (1.19e+03, 3.94), (1.48e+03, 3.84), (2.29e+03, 3.38), (2.68e+03, 2.92)
+- fargate, PerQuery-CostAware: (490, 13.5), (575, 12.1), (673, 11.2), (765, 10.8), (896, 10.4), (989, 10.2), (1.19e+03, 9.82), (1.49e+03, 9.35), (1.98e+03, 9.25), (2.29e+03, 9.03), (2.97e+03, 8.73)
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|
-| cpu | 832 | 176 | 512 | 41.7 | 47 | 11.2% |
-| fargate | 832 | 176 | 512 | 2.95 | 3.27 | 9.9% |
+| cpu | 832 | 176 | 512 | 41.1 | 46.4 | 11.4% |
+| fargate | 832 | 176 | 512 | 2.6 | 2.92 | 10.9% |
 
 ## mixed + multi-grouping, r = 8
 
-200 RQEs on 9 streams; dropped: 0; sanity violations: 0. AutoSketch: 596 probes, 19 distinct (metric, config); measured benchmark 481 s at N = 1e+08 (paper rate 1.14e+03 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 490 ms.
+200 RQEs on 9 streams; dropped: 0; sanity violations: 0. AutoSketch: 454 probes, 15 distinct (metric, config); measured benchmark 396 s at N = 1e+08 (paper rate 900 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 490 ms.
 
 | weights | method | cost (unbounded) | CPU (vCPU) | GiB | latency (ms) | median latency (ms) | planning (s) | cost at AutoSketch's latency |
 |---|---|---|---|---|---|---|---|---|
-| cpu | ASAP | 2.71 | 2.71 | 17.4 | 2.68e+03 | 51.1 | 1.72 | 4.49 |
-| cpu | ASAP (no roll-ups) | 3.04 | 3.04 | 18.9 | 2.68e+03 | 39 | 1.64 | 4.83 |
-| cpu | PerQuery-CostAware | 15.6 | 15.6 | 107 | 3.33e+03 | 34 | 1.26 | 18.5 |
-| cpu | AutoSketch-Adapted | 3.3e+03 | 3.3e+03 | 5.85e+03 | 1.01e+03 | 5.33 | 481 | 3.3e+03 |
-| fargate | ASAP | 0.187 | 2.72 | 17.4 | 2.68e+03 | 51.1 | 1.99 | 0.257 |
-| fargate | ASAP (no roll-ups) | 0.207 | 3.05 | 18.8 | 2.68e+03 | 39 | 1.82 | 0.277 |
-| fargate | PerQuery-CostAware | 1.02 | 15.8 | 85.5 | 3.26e+03 | 34 | 1.27 | 1.14 |
-| fargate | AutoSketch-Adapted | 160 | 3.3e+03 | 5.85e+03 | 1.01e+03 | 5.33 | 481 | 160 |
+| cpu | ASAP | 2.68 | 2.68 | 12.8 | 2.68e+03 | 46.7 | 2.28 | 4.4 |
+| cpu | ASAP (no roll-ups) | 3.01 | 3.01 | 14.3 | 2.68e+03 | 39 | 2.18 | 4.73 |
+| cpu | PerQuery-CostAware | 15.5 | 15.5 | 51.5 | 3.33e+03 | 34 | 2.13 | 18.1 |
+| cpu | AutoSketch-Adapted | 3.25e+03 | 3.25e+03 | 4.17e+03 | 1.01e+03 | 5.33 | 396 | 3.25e+03 |
+| fargate | ASAP | 0.165 | 2.68 | 12.8 | 2.68e+03 | 46.7 | 2.53 | 0.231 |
+| fargate | ASAP (no roll-ups) | 0.185 | 3.01 | 14.3 | 2.68e+03 | 39 | 2.39 | 0.251 |
+| fargate | PerQuery-CostAware | 0.856 | 15.6 | 50.2 | 2.97e+03 | 34 | 2.14 | 0.953 |
+| fargate | AutoSketch-Adapted | 150 | 3.25e+03 | 4.17e+03 | 1.01e+03 | 5.33 | 396 | 150 |
 
 Frontier points (latency ms, cost), by weights:
 
-- cpu, ASAP: (490, 7.29), (557, 6.09), (649, 6.02), (765, 5.28), (896, 4.51), (980, 4.49), (1.08e+03, 4.44), (1.3e+03, 4.38), (1.48e+03, 4.11), (2.29e+03, 3.42), (2.68e+03, 2.71)
-- cpu, ASAP (no roll-ups): (490, 7.79), (557, 6.46), (649, 6.38), (765, 5.65), (896, 4.87), (980, 4.83), (1.08e+03, 4.77), (1.3e+03, 4.71), (1.48e+03, 4.44), (2.29e+03, 3.75), (2.68e+03, 3.04)
-- cpu, PerQuery-CostAware: (490, 24.3), (575, 21.7), (673, 20.3), (813, 19.3), (980, 18.5), (1.14e+03, 17.9), (1.34e+03, 17.2), (1.63e+03, 16.7), (1.96e+03, 16.7), (2.29e+03, 16.2), (2.68e+03, 15.8), (3.33e+03, 15.6)
-- fargate, ASAP: (490, 0.368), (557, 0.32), (649, 0.317), (765, 0.288), (896, 0.257), (1.08e+03, 0.253), (1.3e+03, 0.25), (1.48e+03, 0.244), (2.29e+03, 0.216), (2.68e+03, 0.187)
-- fargate, ASAP (no roll-ups): (490, 0.396), (557, 0.342), (649, 0.339), (765, 0.31), (896, 0.279), (959, 0.277), (1.08e+03, 0.273), (1.3e+03, 0.27), (1.48e+03, 0.264), (2.29e+03, 0.236), (2.68e+03, 0.207)
-- fargate, PerQuery-CostAware: (490, 1.37), (575, 1.26), (673, 1.2), (813, 1.16), (959, 1.14), (1.14e+03, 1.11), (1.34e+03, 1.08), (1.63e+03, 1.06), (2.29e+03, 1.04), (2.68e+03, 1.03), (3.26e+03, 1.02)
+- cpu, ASAP: (490, 7.22), (557, 6.03), (658, 5.96), (765, 5.2), (896, 4.46), (989, 4.4), (1.19e+03, 4.34), (1.48e+03, 4.08), (2.29e+03, 3.39), (2.68e+03, 2.68)
+- cpu, ASAP (no roll-ups): (490, 7.72), (557, 6.4), (658, 6.32), (765, 5.57), (896, 4.82), (989, 4.73), (1.19e+03, 4.67), (1.48e+03, 4.41), (2.29e+03, 3.72), (2.68e+03, 3.01)
+- cpu, PerQuery-CostAware: (490, 24.1), (575, 21.4), (673, 19.8), (765, 19.1), (959, 18.4), (989, 18.1), (1.14e+03, 17.7), (1.34e+03, 17), (1.49e+03, 16.6), (2.29e+03, 16.1), (2.68e+03, 15.7), (3.33e+03, 15.5)
+- fargate, ASAP: (490, 0.345), (557, 0.297), (592, 0.295), (765, 0.264), (896, 0.234), (989, 0.231), (1.19e+03, 0.228), (1.48e+03, 0.222), (2.29e+03, 0.194), (2.68e+03, 0.165)
+- fargate, ASAP (no roll-ups): (490, 0.373), (557, 0.319), (592, 0.316), (765, 0.286), (896, 0.256), (989, 0.251), (1.19e+03, 0.248), (1.48e+03, 0.242), (2.29e+03, 0.214), (2.68e+03, 0.185)
+- fargate, PerQuery-CostAware: (490, 1.19), (575, 1.08), (673, 1.02), (765, 0.992), (896, 0.968), (989, 0.953), (1.19e+03, 0.924), (1.49e+03, 0.895), (1.98e+03, 0.889), (2.29e+03, 0.875), (2.97e+03, 0.856)
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|
-| cpu | 104 | 11 | 32 | 2.71 | 3.04 | 10.9% |
-| fargate | 104 | 11 | 32 | 0.187 | 0.207 | 9.8% |
+| cpu | 104 | 11 | 32 | 2.68 | 3.01 | 11.0% |
+| fargate | 104 | 11 | 32 | 0.165 | 0.185 | 10.7% |
 
 ## mixed
 
-42 RQEs on 6 streams; dropped: 0; sanity violations: 0. AutoSketch: 150 probes, 10 distinct (metric, config); measured benchmark 212 s at N = 1e+08 (paper rate 600 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 87.7 ms.
+42 RQEs on 6 streams; dropped: 0; sanity violations: 0. AutoSketch: 100 probes, 8 distinct (metric, config); measured benchmark 169 s at N = 1e+08 (paper rate 480 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 87.7 ms.
 
 | weights | method | cost (unbounded) | CPU (vCPU) | GiB | latency (ms) | median latency (ms) | planning (s) | cost at AutoSketch's latency |
 |---|---|---|---|---|---|---|---|---|
-| cpu | ASAP | 2.38 | 2.38 | 21.4 | 1.34e+04 | 97.4 | 0.436 | 4.22 |
-| cpu | ASAP (no roll-ups) | 2.38 | 2.38 | 21.4 | 1.34e+04 | 97.4 | 0.436 | 4.22 |
-| cpu | PerQuery-CostAware | 7.77 | 7.77 | 72.8 | 3.33e+03 | 324 | 0.492 | 10.5 |
-| cpu | AutoSketch-Adapted | 2.74e+03 | 2.74e+03 | 5.62e+03 | 1.01e+03 | 10.3 | 212 | 2.74e+03 |
-| fargate | ASAP | 0.17 | 2.41 | 16.3 | 2.68e+03 | 51.1 | 0.476 | 0.242 |
-| fargate | ASAP (no roll-ups) | 0.17 | 2.41 | 16.3 | 2.68e+03 | 51.1 | 0.475 | 0.242 |
-| fargate | PerQuery-CostAware | 0.623 | 7.92 | 67.9 | 3.26e+03 | 269 | 0.499 | 0.732 |
-| fargate | AutoSketch-Adapted | 136 | 2.74e+03 | 5.62e+03 | 1.01e+03 | 10.3 | 212 | 136 |
+| cpu | ASAP | 2.35 | 2.35 | 16.8 | 1.34e+04 | 97.4 | 0.991 | 4.12 |
+| cpu | ASAP (no roll-ups) | 2.35 | 2.35 | 16.8 | 1.34e+04 | 97.4 | 0.993 | 4.12 |
+| cpu | PerQuery-CostAware | 7.67 | 7.67 | 39.8 | 3.33e+03 | 245 | 1.65 | 10.1 |
+| cpu | AutoSketch-Adapted | 2.7e+03 | 2.7e+03 | 4e+03 | 1.01e+03 | 9.45 | 169 | 2.7e+03 |
+| fargate | ASAP | 0.149 | 2.38 | 11.8 | 2.68e+03 | 46.7 | 1.06 | 0.215 |
+| fargate | ASAP (no roll-ups) | 0.149 | 2.38 | 11.8 | 2.68e+03 | 46.7 | 1.06 | 0.215 |
+| fargate | PerQuery-CostAware | 0.487 | 7.78 | 38.5 | 2.97e+03 | 245 | 1.65 | 0.576 |
+| fargate | AutoSketch-Adapted | 127 | 2.7e+03 | 4e+03 | 1.01e+03 | 9.45 | 169 | 127 |
 
 Frontier points (latency ms, cost), by weights:
 
-- cpu, ASAP: (87.7, 44.5), (138, 21.8), (206, 14.1), (342, 9.69), (541, 5.83), (813, 4.99), (980, 4.22), (1.3e+03, 4.1), (1.48e+03, 3.83), (2.68e+03, 2.41), (1.34e+04, 2.38)
-- cpu, ASAP (no roll-ups): (87.7, 44.5), (138, 21.8), (206, 14.1), (342, 9.69), (541, 5.83), (813, 4.99), (980, 4.22), (1.3e+03, 4.1), (1.48e+03, 3.83), (2.68e+03, 2.41), (1.34e+04, 2.38)
-- cpu, PerQuery-CostAware: (87.7, 73.3), (118, 47.1), (164, 32.7), (235, 24.7), (324, 19.6), (452, 15.8), (575, 13.4), (829, 11), (980, 10.5), (1.14e+03, 9.86), (1.63e+03, 8.87), (2.29e+03, 8.36), (3.33e+03, 7.77)
-- fargate, ASAP: (87.7, 1.89), (115, 1.14), (163, 0.755), (219, 0.628), (291, 0.499), (386, 0.418), (541, 0.305), (765, 0.272), (896, 0.242), (1.3e+03, 0.234), (1.48e+03, 0.228), (2.68e+03, 0.17)
-- fargate, ASAP (no roll-ups): (87.7, 1.89), (115, 1.14), (163, 0.755), (219, 0.628), (291, 0.499), (386, 0.418), (541, 0.305), (765, 0.272), (896, 0.242), (1.3e+03, 0.234), (1.48e+03, 0.228), (2.68e+03, 0.17)
-- fargate, PerQuery-CostAware: (87.7, 3.31), (118, 2.22), (164, 1.63), (233, 1.33), (323, 1.09), (452, 0.938), (575, 0.841), (829, 0.747), (896, 0.732), (1.14e+03, 0.701), (1.63e+03, 0.663), (2.29e+03, 0.642), (3.26e+03, 0.623)
+- cpu, ASAP: (87.7, 44.1), (137, 21.3), (206, 13.7), (342, 9.55), (539, 5.77), (765, 4.94), (989, 4.12), (1.19e+03, 4.07), (1.48e+03, 3.8), (2.68e+03, 2.38), (1.34e+04, 2.35)
+- cpu, ASAP (no roll-ups): (87.7, 44.1), (137, 21.3), (206, 13.7), (342, 9.55), (539, 5.77), (765, 4.94), (989, 4.12), (1.19e+03, 4.07), (1.48e+03, 3.8), (2.68e+03, 2.38), (1.34e+04, 2.35)
+- cpu, PerQuery-CostAware: (87.7, 69.2), (121, 44.8), (167, 30.7), (235, 23.9), (328, 18.7), (452, 15.4), (592, 12.7), (829, 10.8), (989, 10.1), (1.19e+03, 9.53), (1.49e+03, 8.74), (2.29e+03, 8.24), (3.33e+03, 7.67)
+- fargate, ASAP: (87.7, 1.85), (112, 1.11), (163, 0.718), (206, 0.602), (295, 0.466), (394, 0.386), (539, 0.282), (765, 0.249), (989, 0.215), (1.19e+03, 0.213), (1.48e+03, 0.206), (2.68e+03, 0.149)
+- fargate, ASAP (no roll-ups): (87.7, 1.85), (112, 1.11), (163, 0.718), (206, 0.602), (295, 0.466), (394, 0.386), (539, 0.282), (765, 0.249), (989, 0.215), (1.19e+03, 0.213), (1.48e+03, 0.206), (2.68e+03, 0.149)
+- fargate, PerQuery-CostAware: (87.7, 2.99), (118, 2.02), (163, 1.44), (227, 1.21), (305, 0.936), (394, 0.82), (592, 0.681), (765, 0.614), (989, 0.576), (1.49e+03, 0.525), (1.98e+03, 0.519), (2.97e+03, 0.487)
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|
-| cpu | 0 | 6 | 6 | 2.38 | 2.38 | 0.0% |
-| fargate | 0 | 6 | 6 | 0.17 | 0.17 | 0.0% |
+| cpu | 0 | 6 | 6 | 2.35 | 2.35 | 0.0% |
+| fargate | 0 | 6 | 6 | 0.149 | 0.149 | 0.0% |
 
 ## mixed, m = 8
 
-336 RQEs on 48 streams; dropped: 0; sanity violations: 0. AutoSketch: 1200 probes, 80 distinct (metric, config); measured benchmark 1.7e+03 s at N = 1e+08 (paper rate 4.8e+03 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 87.7 ms.
+336 RQEs on 48 streams; dropped: 0; sanity violations: 0. AutoSketch: 800 probes, 64 distinct (metric, config); measured benchmark 1.36e+03 s at N = 1e+08 (paper rate 3.84e+03 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 87.7 ms.
 
 | weights | method | cost (unbounded) | CPU (vCPU) | GiB | latency (ms) | median latency (ms) | planning (s) | cost at AutoSketch's latency |
 |---|---|---|---|---|---|---|---|---|
-| cpu | ASAP | 19.1 | 19.1 | 171 | 1.34e+04 | 97.4 | 3.74 | 33.8 |
-| cpu | ASAP (no roll-ups) | 19.1 | 19.1 | 171 | 1.34e+04 | 97.4 | 3.74 | 33.8 |
-| cpu | PerQuery-CostAware | 62.2 | 62.2 | 582 | 3.33e+03 | 324 | 4.2 | 83.7 |
-| cpu | AutoSketch-Adapted | 2.19e+04 | 2.19e+04 | 4.49e+04 | 1.01e+03 | 10.3 | 1.7e+03 | 2.19e+04 |
-| fargate | ASAP | 1.36 | 19.3 | 131 | 2.68e+03 | 51.1 | 4.04 | 1.93 |
-| fargate | ASAP (no roll-ups) | 1.36 | 19.3 | 131 | 2.68e+03 | 51.1 | 4.04 | 1.93 |
-| fargate | PerQuery-CostAware | 4.98 | 63.4 | 543 | 3.26e+03 | 269 | 4.26 | 5.85 |
-| fargate | AutoSketch-Adapted | 1.09e+03 | 2.19e+04 | 4.49e+04 | 1.01e+03 | 10.3 | 1.7e+03 | 1.09e+03 |
+| cpu | ASAP | 18.8 | 18.8 | 135 | 1.34e+04 | 97.4 | 8.6 | 33 |
+| cpu | ASAP (no roll-ups) | 18.8 | 18.8 | 135 | 1.34e+04 | 97.4 | 8.6 | 33 |
+| cpu | PerQuery-CostAware | 61.3 | 61.3 | 318 | 3.33e+03 | 245 | 14 | 80.5 |
+| cpu | AutoSketch-Adapted | 2.16e+04 | 2.16e+04 | 3.2e+04 | 1.01e+03 | 9.45 | 1.36e+03 | 2.16e+04 |
+| fargate | ASAP | 1.19 | 19.1 | 94.5 | 2.68e+03 | 46.7 | 9.01 | 1.72 |
+| fargate | ASAP (no roll-ups) | 1.19 | 19.1 | 94.5 | 2.68e+03 | 46.7 | 9.04 | 1.72 |
+| fargate | PerQuery-CostAware | 3.89 | 62.3 | 308 | 2.97e+03 | 245 | 14.1 | 4.61 |
+| fargate | AutoSketch-Adapted | 1.02e+03 | 2.16e+04 | 3.2e+04 | 1.01e+03 | 9.45 | 1.36e+03 | 1.02e+03 |
 
 Frontier points (latency ms, cost), by weights:
 
-- cpu, ASAP: (87.7, 356), (138, 174), (206, 113), (342, 77.5), (541, 46.6), (813, 39.9), (980, 33.8), (1.3e+03, 32.8), (1.48e+03, 30.6), (2.68e+03, 19.3), (1.34e+04, 19.1)
-- cpu, ASAP (no roll-ups): (87.7, 356), (138, 174), (206, 113), (342, 77.5), (541, 46.6), (813, 39.9), (980, 33.8), (1.3e+03, 32.8), (1.48e+03, 30.6), (2.68e+03, 19.3), (1.34e+04, 19.1)
-- cpu, PerQuery-CostAware: (87.7, 586), (118, 377), (164, 261), (235, 197), (324, 157), (452, 127), (575, 107), (829, 88.1), (980, 83.7), (1.14e+03, 78.9), (1.63e+03, 71), (2.29e+03, 66.9), (3.33e+03, 62.2)
-- fargate, ASAP: (87.7, 15.1), (115, 9.14), (163, 6.04), (219, 5.02), (291, 4), (386, 3.35), (541, 2.44), (765, 2.18), (896, 1.93), (1.3e+03, 1.87), (1.48e+03, 1.82), (2.68e+03, 1.36)
-- fargate, ASAP (no roll-ups): (87.7, 15.1), (115, 9.14), (163, 6.04), (219, 5.02), (291, 4), (386, 3.35), (541, 2.44), (765, 2.18), (896, 1.93), (1.3e+03, 1.87), (1.48e+03, 1.82), (2.68e+03, 1.36)
-- fargate, PerQuery-CostAware: (87.7, 26.5), (118, 17.8), (164, 13), (233, 10.6), (323, 8.71), (452, 7.5), (575, 6.73), (829, 5.98), (896, 5.85), (1.14e+03, 5.61), (1.63e+03, 5.3), (2.29e+03, 5.14), (3.26e+03, 4.98)
+- cpu, ASAP: (87.7, 353), (137, 170), (206, 110), (342, 76.4), (539, 46.2), (765, 39.5), (989, 33), (1.19e+03, 32.5), (1.48e+03, 30.4), (2.68e+03, 19.1), (1.34e+04, 18.8)
+- cpu, ASAP (no roll-ups): (87.7, 353), (137, 170), (206, 110), (342, 76.4), (539, 46.2), (765, 39.5), (989, 33), (1.19e+03, 32.5), (1.48e+03, 30.4), (2.68e+03, 19.1), (1.34e+04, 18.8)
+- cpu, PerQuery-CostAware: (87.7, 553), (121, 358), (167, 246), (235, 191), (328, 149), (452, 123), (592, 102), (829, 86.3), (989, 80.5), (1.19e+03, 76.2), (1.49e+03, 69.9), (2.29e+03, 65.9), (3.33e+03, 61.3)
+- fargate, ASAP: (87.7, 14.8), (112, 8.88), (163, 5.74), (206, 4.82), (295, 3.73), (394, 3.09), (539, 2.26), (765, 1.99), (989, 1.72), (1.19e+03, 1.7), (1.48e+03, 1.65), (2.68e+03, 1.19)
+- fargate, ASAP (no roll-ups): (87.7, 14.8), (112, 8.88), (163, 5.74), (206, 4.82), (295, 3.73), (394, 3.09), (539, 2.26), (765, 1.99), (989, 1.72), (1.19e+03, 1.7), (1.48e+03, 1.65), (2.68e+03, 1.19)
+- fargate, PerQuery-CostAware: (87.7, 23.9), (118, 16.1), (163, 11.5), (227, 9.68), (305, 7.48), (394, 6.56), (592, 5.45), (765, 4.91), (989, 4.61), (1.49e+03, 4.2), (1.98e+03, 4.15), (2.97e+03, 3.89)
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|
-| cpu | 0 | 48 | 48 | 19.1 | 19.1 | 0.0% |
-| fargate | 0 | 48 | 48 | 1.36 | 1.36 | 0.0% |
+| cpu | 0 | 48 | 48 | 18.8 | 18.8 | 0.0% |
+| fargate | 0 | 48 | 48 | 1.19 | 1.19 | 0.0% |
 
 ## mixed, m = 16
 
-672 RQEs on 96 streams; dropped: 0; sanity violations: 0. AutoSketch: 2400 probes, 160 distinct (metric, config); measured benchmark 3.39e+03 s at N = 1e+08 (paper rate 9.6e+03 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 87.7 ms.
+672 RQEs on 96 streams; dropped: 0; sanity violations: 0. AutoSketch: 1600 probes, 128 distinct (metric, config); measured benchmark 2.71e+03 s at N = 1e+08 (paper rate 7.68e+03 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 87.7 ms.
 
 | weights | method | cost (unbounded) | CPU (vCPU) | GiB | latency (ms) | median latency (ms) | planning (s) | cost at AutoSketch's latency |
 |---|---|---|---|---|---|---|---|---|
-| cpu | ASAP | 38.1 | 38.1 | 342 | 1.34e+04 | 97.4 | 8.12 | 67.6 |
-| cpu | ASAP (no roll-ups) | 38.1 | 38.1 | 342 | 1.34e+04 | 97.4 | 8.13 | 67.6 |
-| cpu | PerQuery-CostAware | 124 | 124 | 1.16e+03 | 3.33e+03 | 324 | 8.87 | 167 |
-| cpu | AutoSketch-Adapted | 4.38e+04 | 4.38e+04 | 8.99e+04 | 1.01e+03 | 10.3 | 3.39e+03 | 4.38e+04 |
-| fargate | ASAP | 2.73 | 38.6 | 261 | 2.68e+03 | 51.1 | 10.6 | 3.86 |
-| fargate | ASAP (no roll-ups) | 2.73 | 38.6 | 261 | 2.68e+03 | 51.1 | 10.6 | 3.86 |
-| fargate | PerQuery-CostAware | 9.97 | 127 | 1.09e+03 | 3.26e+03 | 269 | 9.01 | 11.7 |
-| fargate | AutoSketch-Adapted | 2.17e+03 | 4.38e+04 | 8.99e+04 | 1.01e+03 | 10.3 | 3.39e+03 | 2.17e+03 |
+| cpu | ASAP | 37.6 | 37.6 | 270 | 1.34e+04 | 97.4 | 7.36 | 66 |
+| cpu | ASAP (no roll-ups) | 37.6 | 37.6 | 270 | 1.34e+04 | 97.4 | 7.36 | 66 |
+| cpu | PerQuery-CostAware | 123 | 123 | 636 | 3.33e+03 | 245 | 12 | 161 |
+| cpu | AutoSketch-Adapted | 4.32e+04 | 4.32e+04 | 6.4e+04 | 1.01e+03 | 9.45 | 2.71e+03 | 4.32e+04 |
+| fargate | ASAP | 2.38 | 38.1 | 189 | 2.68e+03 | 46.7 | 8.21 | 3.45 |
+| fargate | ASAP (no roll-ups) | 2.38 | 38.1 | 189 | 2.68e+03 | 46.7 | 8.26 | 3.45 |
+| fargate | PerQuery-CostAware | 7.78 | 125 | 616 | 2.97e+03 | 245 | 12.2 | 9.22 |
+| fargate | AutoSketch-Adapted | 2.04e+03 | 4.32e+04 | 6.4e+04 | 1.01e+03 | 9.45 | 2.71e+03 | 2.04e+03 |
 
 Frontier points (latency ms, cost), by weights:
 
-- cpu, ASAP: (87.7, 712), (138, 349), (206, 226), (342, 155), (541, 93.2), (813, 79.8), (980, 67.6), (1.3e+03, 65.6), (1.48e+03, 61.3), (2.68e+03, 38.6), (1.34e+04, 38.1)
-- cpu, ASAP (no roll-ups): (87.7, 712), (138, 349), (206, 226), (342, 155), (541, 93.2), (813, 79.8), (980, 67.6), (1.3e+03, 65.6), (1.48e+03, 61.3), (2.68e+03, 38.6), (1.34e+04, 38.1)
-- cpu, PerQuery-CostAware: (87.7, 1.17e+03), (118, 753), (164, 523), (235, 395), (324, 313), (452, 253), (575, 214), (829, 176), (980, 167), (1.14e+03, 158), (1.63e+03, 142), (2.29e+03, 134), (3.33e+03, 124)
-- fargate, ASAP: (87.7, 30.2), (115, 18.3), (163, 12.1), (219, 10), (291, 7.99), (386, 6.69), (541, 4.88), (765, 4.36), (896, 3.86), (1.3e+03, 3.75), (1.48e+03, 3.65), (2.68e+03, 2.73)
-- fargate, ASAP (no roll-ups): (87.7, 30.2), (115, 18.3), (163, 12.1), (219, 10), (291, 7.99), (386, 6.69), (541, 4.88), (765, 4.36), (896, 3.86), (1.3e+03, 3.75), (1.48e+03, 3.65), (2.68e+03, 2.73)
-- fargate, PerQuery-CostAware: (87.7, 53), (118, 35.6), (164, 26), (233, 21.3), (323, 17.4), (452, 15), (575, 13.5), (829, 12), (896, 11.7), (1.14e+03, 11.2), (1.63e+03, 10.6), (2.29e+03, 10.3), (3.26e+03, 9.97)
+- cpu, ASAP: (87.7, 706), (137, 341), (206, 219), (342, 153), (539, 92.3), (765, 79), (989, 66), (1.19e+03, 65), (1.48e+03, 60.8), (2.68e+03, 38.1), (1.34e+04, 37.6)
+- cpu, ASAP (no roll-ups): (87.7, 706), (137, 341), (206, 219), (342, 153), (539, 92.3), (765, 79), (989, 66), (1.19e+03, 65), (1.48e+03, 60.8), (2.68e+03, 38.1), (1.34e+04, 37.6)
+- cpu, PerQuery-CostAware: (87.7, 1.11e+03), (121, 717), (167, 491), (235, 382), (328, 299), (452, 247), (592, 203), (829, 173), (989, 161), (1.19e+03, 152), (1.49e+03, 140), (2.29e+03, 132), (3.33e+03, 123)
+- fargate, ASAP: (87.7, 29.6), (112, 17.8), (163, 11.5), (206, 9.63), (295, 7.46), (394, 6.18), (539, 4.51), (765, 3.99), (989, 3.45), (1.19e+03, 3.4), (1.48e+03, 3.3), (2.68e+03, 2.38)
+- fargate, ASAP (no roll-ups): (87.7, 29.6), (112, 17.8), (163, 11.5), (206, 9.63), (295, 7.46), (394, 6.18), (539, 4.51), (765, 3.99), (989, 3.45), (1.19e+03, 3.4), (1.48e+03, 3.3), (2.68e+03, 2.38)
+- fargate, PerQuery-CostAware: (87.7, 47.9), (118, 32.3), (163, 23.1), (227, 19.4), (305, 15), (394, 13.1), (592, 10.9), (765, 9.83), (989, 9.22), (1.49e+03, 8.4), (1.98e+03, 8.31), (2.97e+03, 7.78)
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|
-| cpu | 0 | 96 | 96 | 38.1 | 38.1 | 0.0% |
-| fargate | 0 | 96 | 96 | 2.73 | 2.73 | 0.0% |
+| cpu | 0 | 96 | 96 | 37.6 | 37.6 | 0.0% |
+| fargate | 0 | 96 | 96 | 2.38 | 2.38 | 0.0% |
 
 ## mixed, r = 8
 
-76 RQEs on 6 streams; dropped: 0; sanity violations: 0. AutoSketch: 264 probes, 10 distinct (metric, config); measured benchmark 212 s at N = 1e+08 (paper rate 600 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 87.7 ms.
+76 RQEs on 6 streams; dropped: 0; sanity violations: 0. AutoSketch: 178 probes, 8 distinct (metric, config); measured benchmark 169 s at N = 1e+08 (paper rate 480 s). AutoSketch latency 1.01e+03 ms; tightest feasible bound 87.7 ms.
 
 | weights | method | cost (unbounded) | CPU (vCPU) | GiB | latency (ms) | median latency (ms) | planning (s) | cost at AutoSketch's latency |
 |---|---|---|---|---|---|---|---|---|
-| cpu | ASAP | 2.47 | 2.47 | 16.3 | 2.68e+03 | 97.4 | 1.01 | 4.25 |
-| cpu | ASAP (no roll-ups) | 2.47 | 2.47 | 16.3 | 2.68e+03 | 97.4 | 1.01 | 4.25 |
-| cpu | PerQuery-CostAware | 13.6 | 13.6 | 103 | 3.33e+03 | 77.9 | 0.949 | 16.5 |
-| cpu | AutoSketch-Adapted | 3.28e+03 | 3.28e+03 | 5.85e+03 | 1.01e+03 | 10.1 | 212 | 3.28e+03 |
-| fargate | ASAP | 0.173 | 2.47 | 16.3 | 2.68e+03 | 97.4 | 1.24 | 0.243 |
-| fargate | ASAP (no roll-ups) | 0.173 | 2.47 | 16.3 | 2.68e+03 | 97.4 | 1.24 | 0.243 |
-| fargate | PerQuery-CostAware | 0.919 | 13.8 | 80.9 | 3.26e+03 | 64.7 | 0.959 | 1.04 |
-| fargate | AutoSketch-Adapted | 159 | 3.28e+03 | 5.85e+03 | 1.01e+03 | 10.1 | 212 | 159 |
+| cpu | ASAP | 2.43 | 2.43 | 11.8 | 2.68e+03 | 97.4 | 1.06 | 4.16 |
+| cpu | ASAP (no roll-ups) | 2.43 | 2.43 | 11.8 | 2.68e+03 | 97.4 | 1.06 | 4.16 |
+| cpu | PerQuery-CostAware | 13.5 | 13.5 | 47 | 3.33e+03 | 59.1 | 1.51 | 16 |
+| cpu | AutoSketch-Adapted | 3.24e+03 | 3.24e+03 | 4.16e+03 | 1.01e+03 | 9.45 | 169 | 3.24e+03 |
+| fargate | ASAP | 0.151 | 2.43 | 11.8 | 2.68e+03 | 97.4 | 1.23 | 0.217 |
+| fargate | ASAP (no roll-ups) | 0.151 | 2.43 | 11.8 | 2.68e+03 | 97.4 | 1.23 | 0.217 |
+| fargate | PerQuery-CostAware | 0.754 | 13.6 | 45.8 | 2.97e+03 | 59.1 | 1.52 | 0.851 |
+| fargate | AutoSketch-Adapted | 150 | 3.24e+03 | 4.16e+03 | 1.01e+03 | 9.45 | 169 | 150 |
 
 Frontier points (latency ms, cost), by weights:
 
-- cpu, ASAP: (87.7, 44.5), (115, 26.4), (163, 16.9), (219, 13.8), (291, 10.6), (389, 8.6), (541, 5.85), (765, 5.04), (980, 4.25), (1.3e+03, 4.14), (1.48e+03, 3.87), (2.68e+03, 2.47)
-- cpu, ASAP (no roll-ups): (87.7, 44.5), (115, 26.4), (163, 16.9), (219, 13.8), (291, 10.6), (389, 8.6), (541, 5.85), (765, 5.04), (980, 4.25), (1.3e+03, 4.14), (1.48e+03, 3.87), (2.68e+03, 2.47)
-- cpu, PerQuery-CostAware: (87.7, 88.3), (118, 59.2), (164, 42.1), (235, 32.9), (324, 26.9), (452, 22.9), (575, 19.6), (829, 17), (980, 16.5), (1.14e+03, 15.8), (1.63e+03, 14.7), (2.29e+03, 14.2), (3.33e+03, 13.6)
-- fargate, ASAP: (87.7, 1.89), (115, 1.14), (163, 0.755), (219, 0.628), (291, 0.5), (386, 0.419), (541, 0.306), (765, 0.273), (896, 0.243), (1.3e+03, 0.236), (1.48e+03, 0.23), (2.68e+03, 0.173)
-- fargate, ASAP (no roll-ups): (87.7, 1.89), (115, 1.14), (163, 0.755), (219, 0.628), (291, 0.5), (386, 0.419), (541, 0.306), (765, 0.273), (896, 0.243), (1.3e+03, 0.236), (1.48e+03, 0.23), (2.68e+03, 0.173)
-- fargate, PerQuery-CostAware: (87.7, 3.98), (118, 2.77), (164, 2.07), (233, 1.72), (323, 1.44), (452, 1.29), (575, 1.15), (829, 1.05), (896, 1.04), (1.14e+03, 1), (1.63e+03, 0.959), (2.29e+03, 0.938), (3.26e+03, 0.919)
+- cpu, ASAP: (87.7, 44.1), (112, 26.2), (163, 16.5), (206, 13.7), (295, 10.4), (394, 8.37), (539, 5.79), (765, 4.96), (989, 4.16), (1.19e+03, 4.1), (1.48e+03, 3.84), (2.68e+03, 2.43)
+- cpu, ASAP (no roll-ups): (87.7, 44.1), (112, 26.2), (163, 16.5), (206, 13.7), (295, 10.4), (394, 8.37), (539, 5.79), (765, 4.96), (989, 4.16), (1.19e+03, 4.1), (1.48e+03, 3.84), (2.68e+03, 2.43)
+- cpu, PerQuery-CostAware: (87.7, 83.8), (121, 56.6), (167, 40), (235, 32), (328, 25.9), (452, 22.5), (592, 18.7), (829, 16.8), (989, 16), (1.19e+03, 15.3), (1.49e+03, 14.5), (2.29e+03, 14), (3.33e+03, 13.5)
+- fargate, ASAP: (87.7, 1.85), (112, 1.11), (163, 0.718), (206, 0.602), (295, 0.467), (394, 0.387), (539, 0.283), (765, 0.25), (989, 0.217), (1.19e+03, 0.214), (1.48e+03, 0.208), (2.68e+03, 0.151)
+- fargate, ASAP (no roll-ups): (87.7, 1.85), (112, 1.11), (163, 0.718), (206, 0.602), (295, 0.467), (394, 0.387), (539, 0.283), (765, 0.25), (989, 0.217), (1.19e+03, 0.214), (1.48e+03, 0.208), (2.68e+03, 0.151)
+- fargate, PerQuery-CostAware: (87.7, 3.62), (118, 2.53), (163, 1.85), (227, 1.59), (305, 1.26), (394, 1.14), (592, 0.955), (765, 0.889), (989, 0.851), (1.49e+03, 0.793), (1.98e+03, 0.787), (2.97e+03, 0.754)
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|
-| cpu | 0 | 6 | 6 | 2.47 | 2.47 | 0.0% |
-| fargate | 0 | 6 | 6 | 0.173 | 0.173 | 0.0% |
+| cpu | 0 | 6 | 6 | 2.43 | 2.43 | 0.0% |
+| fargate | 0 | 6 | 6 | 0.151 | 0.151 | 0.0% |
 
 ## multi-grouping
 
-62 RQEs on 3 streams; dropped: 0; sanity violations: 0. AutoSketch: 166 probes, 9 distinct (metric, config); measured benchmark 269 s at N = 1e+08 (paper rate 540 s). AutoSketch latency 490 ms; tightest feasible bound 490 ms.
+62 RQEs on 3 streams; dropped: 0; sanity violations: 0. AutoSketch: 138 probes, 7 distinct (metric, config); measured benchmark 227 s at N = 1e+08 (paper rate 420 s). AutoSketch latency 490 ms; tightest feasible bound 490 ms.
 
 | weights | method | cost (unbounded) | CPU (vCPU) | GiB | latency (ms) | median latency (ms) | planning (s) | cost at AutoSketch's latency |
 |---|---|---|---|---|---|---|---|---|
-| cpu | ASAP | 0.221 | 0.221 | 1.06 | 557 | 24.6 | 0.412 | 0.324 |
-| cpu | ASAP (no roll-ups) | 0.551 | 0.551 | 2.6 | 959 | 19.5 | 0.381 | 0.823 |
-| cpu | PerQuery-CostAware | 1.07 | 1.07 | 3.69 | 959 | 19.5 | 0.224 | 1.33 |
-| cpu | AutoSketch-Adapted | 10.2 | 10.2 | 3.55 | 490 | 4.9 | 269 | 10.2 |
-| fargate | ASAP | 0.0137 | 0.224 | 1.03 | 557 | 24.6 | 0.436 | 0.0187 |
-| fargate | ASAP (no roll-ups) | 0.0339 | 0.559 | 2.52 | 959 | 16.2 | 0.386 | 0.0469 |
-| fargate | PerQuery-CostAware | 0.0597 | 1.08 | 3.61 | 959 | 16.2 | 0.225 | 0.0701 |
-| fargate | AutoSketch-Adapted | 0.43 | 10.2 | 3.55 | 490 | 4.9 | 269 | 0.43 |
+| cpu | ASAP | 0.22 | 0.22 | 1.01 | 557 | 24.6 | 0.523 | 0.323 |
+| cpu | ASAP (no roll-ups) | 0.55 | 0.55 | 2.47 | 959 | 14.8 | 0.499 | 0.822 |
+| cpu | PerQuery-CostAware | 1.07 | 1.07 | 3.51 | 959 | 14.8 | 0.281 | 1.32 |
+| cpu | AutoSketch-Adapted | 9.65 | 9.65 | 3.51 | 490 | 4.9 | 227 | 9.65 |
+| fargate | ASAP | 0.0134 | 0.22 | 1.01 | 557 | 24.6 | 0.553 | 0.0185 |
+| fargate | ASAP (no roll-ups) | 0.0333 | 0.55 | 2.47 | 959 | 14.8 | 0.507 | 0.0463 |
+| fargate | PerQuery-CostAware | 0.0589 | 1.07 | 3.51 | 959 | 14.8 | 0.283 | 0.0693 |
+| fargate | AutoSketch-Adapted | 0.406 | 9.65 | 3.51 | 490 | 4.9 | 227 | 0.406 |
 
 Frontier points (latency ms, cost), by weights:
 
-- cpu, ASAP: (490, 0.324), (557, 0.221)
-- cpu, ASAP (no roll-ups): (490, 0.823), (557, 0.594), (624, 0.586), (959, 0.551)
-- cpu, PerQuery-CostAware: (490, 1.33), (557, 1.17), (624, 1.09), (959, 1.07)
-- fargate, ASAP: (490, 0.0187), (557, 0.0137)
-- fargate, ASAP (no roll-ups): (490, 0.0469), (557, 0.0356), (959, 0.0339)
-- fargate, PerQuery-CostAware: (490, 0.0701), (557, 0.0639), (624, 0.0605), (959, 0.0597)
+- cpu, ASAP: (490, 0.323), (557, 0.22)
+- cpu, ASAP (no roll-ups): (490, 0.822), (557, 0.594), (624, 0.585), (959, 0.55)
+- cpu, PerQuery-CostAware: (490, 1.32), (557, 1.17), (624, 1.09), (959, 1.07)
+- fargate, ASAP: (490, 0.0185), (557, 0.0134)
+- fargate, ASAP (no roll-ups): (490, 0.0463), (557, 0.035), (959, 0.0333)
+- fargate, PerQuery-CostAware: (490, 0.0693), (557, 0.0631), (624, 0.0597), (959, 0.0589)
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|
-| cpu | 52 | 5 | 26 | 0.221 | 0.551 | 59.9% |
-| fargate | 52 | 5 | 26 | 0.0137 | 0.0339 | 59.7% |
+| cpu | 52 | 5 | 26 | 0.22 | 0.55 | 60.0% |
+| fargate | 52 | 5 | 26 | 0.0134 | 0.0333 | 59.7% |
 
 ## multi-grouping, m = 8
 
-496 RQEs on 24 streams; dropped: 0; sanity violations: 0. AutoSketch: 1328 probes, 72 distinct (metric, config); measured benchmark 2.15e+03 s at N = 1e+08 (paper rate 4.32e+03 s). AutoSketch latency 490 ms; tightest feasible bound 490 ms.
+496 RQEs on 24 streams; dropped: 0; sanity violations: 0. AutoSketch: 1104 probes, 56 distinct (metric, config); measured benchmark 1.81e+03 s at N = 1e+08 (paper rate 3.36e+03 s). AutoSketch latency 490 ms; tightest feasible bound 490 ms.
 
 | weights | method | cost (unbounded) | CPU (vCPU) | GiB | latency (ms) | median latency (ms) | planning (s) | cost at AutoSketch's latency |
 |---|---|---|---|---|---|---|---|---|
-| cpu | ASAP | 1.77 | 1.77 | 8.52 | 557 | 24.6 | 3.4 | 2.59 |
-| cpu | ASAP (no roll-ups) | 4.41 | 4.41 | 20.8 | 959 | 19.5 | 3.1 | 6.58 |
-| cpu | PerQuery-CostAware | 8.55 | 8.55 | 29.5 | 959 | 19.5 | 1.93 | 10.6 |
-| cpu | AutoSketch-Adapted | 81.7 | 81.7 | 28.4 | 490 | 4.9 | 2.15e+03 | 81.7 |
-| fargate | ASAP | 0.109 | 1.79 | 8.22 | 557 | 24.6 | 3.63 | 0.15 |
-| fargate | ASAP (no roll-ups) | 0.271 | 4.47 | 20.2 | 959 | 16.2 | 3.21 | 0.375 |
-| fargate | PerQuery-CostAware | 0.477 | 8.61 | 28.9 | 959 | 16.2 | 1.93 | 0.56 |
-| fargate | AutoSketch-Adapted | 3.44 | 81.7 | 28.4 | 490 | 4.9 | 2.15e+03 | 3.44 |
+| cpu | ASAP | 1.76 | 1.76 | 8.12 | 557 | 24.6 | 3.69 | 2.59 |
+| cpu | ASAP (no roll-ups) | 4.4 | 4.4 | 19.8 | 959 | 14.8 | 3.48 | 6.58 |
+| cpu | PerQuery-CostAware | 8.54 | 8.54 | 28.1 | 959 | 14.8 | 2.15 | 10.6 |
+| cpu | AutoSketch-Adapted | 77.2 | 77.2 | 28.1 | 490 | 4.9 | 1.81e+03 | 77.2 |
+| fargate | ASAP | 0.107 | 1.76 | 8.12 | 557 | 24.6 | 4.37 | 0.148 |
+| fargate | ASAP (no roll-ups) | 0.266 | 4.4 | 19.8 | 959 | 14.8 | 3.54 | 0.371 |
+| fargate | PerQuery-CostAware | 0.471 | 8.54 | 28.1 | 959 | 14.8 | 2.16 | 0.554 |
+| fargate | AutoSketch-Adapted | 3.25 | 77.2 | 28.1 | 490 | 4.9 | 1.81e+03 | 3.25 |
 
 Frontier points (latency ms, cost), by weights:
 
-- cpu, ASAP: (490, 2.59), (557, 1.77)
-- cpu, ASAP (no roll-ups): (490, 6.58), (557, 4.76), (624, 4.69), (959, 4.41)
-- cpu, PerQuery-CostAware: (490, 10.6), (557, 9.39), (624, 8.71), (959, 8.55)
-- fargate, ASAP: (490, 0.15), (557, 0.109)
-- fargate, ASAP (no roll-ups): (490, 0.375), (557, 0.285), (959, 0.271)
-- fargate, PerQuery-CostAware: (490, 0.56), (557, 0.511), (624, 0.484), (959, 0.477)
+- cpu, ASAP: (490, 2.59), (557, 1.76)
+- cpu, ASAP (no roll-ups): (490, 6.58), (557, 4.75), (624, 4.68), (959, 4.4)
+- cpu, PerQuery-CostAware: (490, 10.6), (557, 9.38), (624, 8.7), (959, 8.54)
+- fargate, ASAP: (490, 0.148), (557, 0.107)
+- fargate, ASAP (no roll-ups): (490, 0.371), (557, 0.28), (959, 0.266)
+- fargate, PerQuery-CostAware: (490, 0.554), (557, 0.505), (624, 0.477), (959, 0.471)
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|
-| cpu | 416 | 40 | 208 | 1.77 | 4.41 | 59.9% |
-| fargate | 416 | 40 | 208 | 0.109 | 0.271 | 59.7% |
+| cpu | 416 | 40 | 208 | 1.76 | 4.4 | 60.0% |
+| fargate | 416 | 40 | 208 | 0.107 | 0.266 | 59.7% |
 
 ## multi-grouping, m = 16
 
-992 RQEs on 48 streams; dropped: 0; sanity violations: 0. AutoSketch: 2656 probes, 144 distinct (metric, config); measured benchmark 4.31e+03 s at N = 1e+08 (paper rate 8.64e+03 s). AutoSketch latency 490 ms; tightest feasible bound 490 ms.
+992 RQEs on 48 streams; dropped: 0; sanity violations: 0. AutoSketch: 2208 probes, 112 distinct (metric, config); measured benchmark 3.62e+03 s at N = 1e+08 (paper rate 6.72e+03 s). AutoSketch latency 490 ms; tightest feasible bound 490 ms.
 
 | weights | method | cost (unbounded) | CPU (vCPU) | GiB | latency (ms) | median latency (ms) | planning (s) | cost at AutoSketch's latency |
 |---|---|---|---|---|---|---|---|---|
-| cpu | ASAP | 3.53 | 3.53 | 17 | 557 | 24.6 | 7.01 | 5.18 |
-| cpu | ASAP (no roll-ups) | 8.81 | 8.81 | 41.5 | 959 | 19.5 | 6.3 | 13.2 |
-| cpu | PerQuery-CostAware | 17.1 | 17.1 | 59 | 959 | 19.5 | 4.09 | 21.2 |
-| cpu | AutoSketch-Adapted | 163 | 163 | 56.8 | 490 | 4.9 | 4.31e+03 | 163 |
-| fargate | ASAP | 0.218 | 3.59 | 16.4 | 557 | 24.6 | 9.83 | 0.3 |
-| fargate | ASAP (no roll-ups) | 0.542 | 8.94 | 40.4 | 959 | 16.2 | 6.48 | 0.75 |
-| fargate | PerQuery-CostAware | 0.955 | 17.2 | 57.8 | 959 | 16.2 | 4.07 | 1.12 |
-| fargate | AutoSketch-Adapted | 6.87 | 163 | 56.8 | 490 | 4.9 | 4.31e+03 | 6.87 |
+| cpu | ASAP | 3.52 | 3.52 | 16.2 | 557 | 24.6 | 8.52 | 5.17 |
+| cpu | ASAP (no roll-ups) | 8.8 | 8.8 | 39.5 | 959 | 14.8 | 7.96 | 13.2 |
+| cpu | PerQuery-CostAware | 17.1 | 17.1 | 56.2 | 959 | 14.8 | 4.96 | 21.2 |
+| cpu | AutoSketch-Adapted | 154 | 154 | 56.1 | 490 | 4.9 | 3.62e+03 | 154 |
+| fargate | ASAP | 0.215 | 3.52 | 16.2 | 557 | 24.6 | 9.26 | 0.296 |
+| fargate | ASAP (no roll-ups) | 0.532 | 8.8 | 39.5 | 959 | 14.8 | 8.23 | 0.741 |
+| fargate | PerQuery-CostAware | 0.942 | 17.1 | 56.2 | 959 | 14.8 | 4.98 | 1.11 |
+| fargate | AutoSketch-Adapted | 6.5 | 154 | 56.1 | 490 | 4.9 | 3.62e+03 | 6.5 |
 
 Frontier points (latency ms, cost), by weights:
 
-- cpu, ASAP: (490, 5.18), (557, 3.53)
-- cpu, ASAP (no roll-ups): (490, 13.2), (557, 9.51), (624, 9.37), (959, 8.81)
+- cpu, ASAP: (490, 5.17), (557, 3.52)
+- cpu, ASAP (no roll-ups): (490, 13.2), (557, 9.5), (624, 9.36), (959, 8.8)
 - cpu, PerQuery-CostAware: (490, 21.2), (557, 18.8), (624, 17.4), (959, 17.1)
-- fargate, ASAP: (490, 0.3), (557, 0.218)
-- fargate, ASAP (no roll-ups): (490, 0.75), (557, 0.57), (959, 0.542)
-- fargate, PerQuery-CostAware: (490, 1.12), (557, 1.02), (624, 0.967), (959, 0.955)
+- fargate, ASAP: (490, 0.296), (557, 0.215)
+- fargate, ASAP (no roll-ups): (490, 0.741), (557, 0.561), (959, 0.532)
+- fargate, PerQuery-CostAware: (490, 1.11), (557, 1.01), (624, 0.955), (959, 0.942)
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|
-| cpu | 832 | 80 | 416 | 3.53 | 8.81 | 59.9% |
-| fargate | 832 | 80 | 416 | 0.218 | 0.542 | 59.7% |
+| cpu | 832 | 80 | 416 | 3.52 | 8.8 | 60.0% |
+| fargate | 832 | 80 | 416 | 0.215 | 0.532 | 59.7% |
 
 ## multi-grouping, r = 8
 
-124 RQEs on 3 streams; dropped: 0; sanity violations: 0. AutoSketch: 332 probes, 9 distinct (metric, config); measured benchmark 269 s at N = 1e+08 (paper rate 540 s). AutoSketch latency 490 ms; tightest feasible bound 490 ms.
+124 RQEs on 3 streams; dropped: 0; sanity violations: 0. AutoSketch: 276 probes, 7 distinct (metric, config); measured benchmark 227 s at N = 1e+08 (paper rate 420 s). AutoSketch latency 490 ms; tightest feasible bound 490 ms.
 
 | weights | method | cost (unbounded) | CPU (vCPU) | GiB | latency (ms) | median latency (ms) | planning (s) | cost at AutoSketch's latency |
 |---|---|---|---|---|---|---|---|---|
-| cpu | ASAP | 0.242 | 0.242 | 1.06 | 557 | 24.6 | 0.917 | 0.344 |
-| cpu | ASAP (no roll-ups) | 0.573 | 0.573 | 2.6 | 959 | 19.5 | 0.851 | 0.841 |
-| cpu | PerQuery-CostAware | 2.04 | 2.04 | 4.69 | 959 | 19.5 | 0.453 | 2.33 |
-| cpu | AutoSketch-Adapted | 12.3 | 12.3 | 4.52 | 490 | 4.9 | 269 | 12.3 |
-| fargate | ASAP | 0.0145 | 0.245 | 1.03 | 557 | 24.6 | 1.02 | 0.0196 |
-| fargate | ASAP (no roll-ups) | 0.0347 | 0.581 | 2.52 | 959 | 16.2 | 0.875 | 0.0476 |
-| fargate | PerQuery-CostAware | 0.104 | 2.05 | 4.62 | 959 | 16.2 | 0.456 | 0.115 |
-| fargate | AutoSketch-Adapted | 0.517 | 12.3 | 4.52 | 490 | 4.9 | 269 | 0.517 |
+| cpu | ASAP | 0.241 | 0.241 | 1.01 | 557 | 24.6 | 1.22 | 0.343 |
+| cpu | ASAP (no roll-ups) | 0.572 | 0.572 | 2.47 | 959 | 14.8 | 1.17 | 0.84 |
+| cpu | PerQuery-CostAware | 2.04 | 2.04 | 4.47 | 959 | 14.8 | 0.575 | 2.33 |
+| cpu | AutoSketch-Adapted | 11.6 | 11.6 | 4.46 | 490 | 4.9 | 227 | 11.6 |
+| fargate | ASAP | 0.0143 | 0.241 | 1.01 | 557 | 24.6 | 1.32 | 0.0193 |
+| fargate | ASAP (no roll-ups) | 0.0342 | 0.572 | 2.47 | 959 | 14.8 | 1.18 | 0.0471 |
+| fargate | PerQuery-CostAware | 0.103 | 2.04 | 4.47 | 959 | 14.8 | 0.576 | 0.114 |
+| fargate | AutoSketch-Adapted | 0.489 | 11.6 | 4.46 | 490 | 4.9 | 227 | 0.489 |
 
 Frontier points (latency ms, cost), by weights:
 
-- cpu, ASAP: (490, 0.344), (557, 0.242)
-- cpu, ASAP (no roll-ups): (490, 0.841), (557, 0.613), (624, 0.606), (959, 0.573)
+- cpu, ASAP: (490, 0.343), (557, 0.241)
+- cpu, ASAP (no roll-ups): (490, 0.84), (557, 0.612), (624, 0.605), (959, 0.572)
 - cpu, PerQuery-CostAware: (490, 2.33), (557, 2.15), (624, 2.06), (959, 2.04)
-- fargate, ASAP: (490, 0.0196), (557, 0.0145)
-- fargate, ASAP (no roll-ups): (490, 0.0476), (557, 0.0364), (959, 0.0347)
-- fargate, PerQuery-CostAware: (490, 0.115), (557, 0.108), (624, 0.104), (959, 0.104)
+- fargate, ASAP: (490, 0.0193), (557, 0.0143)
+- fargate, ASAP (no roll-ups): (490, 0.0471), (557, 0.0358), (959, 0.0342)
+- fargate, PerQuery-CostAware: (490, 0.114), (557, 0.107), (624, 0.103), (959, 0.103)
 
 Roll-up ablation (ASAP vs. ASAP without roll-ups):
 
 | weights | RQEs rolled up | deployments with | deployments without | cost with | cost without | saving |
 |---|---|---|---|---|---|---|
-| cpu | 104 | 5 | 26 | 0.242 | 0.573 | 57.8% |
-| fargate | 104 | 5 | 26 | 0.0145 | 0.0347 | 58.2% |
+| cpu | 104 | 5 | 26 | 0.241 | 0.572 | 57.9% |
+| fargate | 104 | 5 | 26 | 0.0143 | 0.0342 | 58.2% |
diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared1-metrics16-tp95.json b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared1-metrics16-tp95.json
index eb9580ce..5d23f5b6 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared1-metrics16-tp95.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared1-metrics16-tp95.json
@@ -1,7 +1,7 @@
 {
  "autosketch": {
-  "benchmark_secs_paper_rate": 18240.0,
-  "distinct_probes": 304,
+  "benchmark_secs_paper_rate": 14400.0,
+  "distinct_probes": 240,
   "probed_configs": [
    {
     "distinct_keys": 10000.0,
@@ -43,27 +43,7 @@
     "distinct_keys": 0.0,
     "metric": "data_0",
     "params": {
-     "alpha": 0.01
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_0",
-    "params": {
-     "alpha": 0.02
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_0",
-    "params": {
-     "alpha": 0.05
+     "alpha": 0.1
     },
     "sketch": "dd",
     "tail_index": 2.0,
@@ -109,27 +89,7 @@
     "distinct_keys": 0.0,
     "metric": "data_0/http",
     "params": {
-     "alpha": 0.01
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_0/http",
-    "params": {
-     "alpha": 0.02
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_0/http",
-    "params": {
-     "alpha": 0.05
+     "alpha": 0.1
     },
     "sketch": "dd",
     "tail_index": 2.0,
@@ -159,7 +119,7 @@
     "distinct_keys": 0.0,
     "metric": "data_0/http",
     "params": {
-     "k": 200
+     "k": 25
     },
     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -179,7 +139,7 @@
     "distinct_keys": 0.0,
     "metric": "data_0",
     "params": {
-     "k": 200
+     "k": 25
     },
     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -235,27 +195,7 @@
     "distinct_keys": 0.0,
     "metric": "data_1",
     "params": {
-     "alpha": 0.01
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_1",
-    "params": {
-     "alpha": 0.02
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_1",
-    "params": {
-     "alpha": 0.05
+     "alpha": 0.1
     },
     "sketch": "dd",
     "tail_index": 2.0,
@@ -301,27 +241,7 @@
     "distinct_keys": 0.0,
     "metric": "data_1/http",
     "params": {
-     "alpha": 0.01
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_1/http",
-    "params": {
-     "alpha": 0.02
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_1/http",
-    "params": {
-     "alpha": 0.05
+     "alpha": 0.1
     },
     "sketch": "dd",
     "tail_index": 2.0,
@@ -351,7 +271,7 @@
     "distinct_keys": 0.0,
     "metric": "data_1/http",
     "params": {
-     "k": 200
+     "k": 25
     },
     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -371,7 +291,7 @@
     "distinct_keys": 0.0,
     "metric": "data_1",
     "params": {
-     "k": 200
+     "k": 25
     },
     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -427,27 +347,7 @@
     "distinct_keys": 0.0,
     "metric": "data_10",
     "params": {
-     "alpha": 0.01
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_10",
-    "params": {
-     "alpha": 0.02
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_10",
-    "params": {
-     "alpha": 0.05
+     "alpha": 0.1
     },
     "sketch": "dd",
     "tail_index": 2.0,
@@ -493,27 +393,7 @@
     "distinct_keys": 0.0,
     "metric": "data_10/http",
     "params": {
-     "alpha": 0.01
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_10/http",
-    "params": {
-     "alpha": 0.02
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_10/http",
-    "params": {
-     "alpha": 0.05
+     "alpha": 0.1
     },
     "sketch": "dd",
     "tail_index": 2.0,
@@ -543,7 +423,7 @@
     "distinct_keys": 0.0,
     "metric": "data_10/http",
     "params": {
-     "k": 200
+     "k": 25
     },
     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -563,7 +443,7 @@
     "distinct_keys": 0.0,
     "metric": "data_10",
     "params": {
-     "k": 200
+     "k": 25
     },
     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -619,27 +499,7 @@
     "distinct_keys": 0.0,
     "metric": "data_11",
     "params": {
-     "alpha": 0.01
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_11",
-    "params": {
-     "alpha": 0.02
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_11",
-    "params": {
-     "alpha": 0.05
+     "alpha": 0.1
     },
     "sketch": "dd",
     "tail_index": 2.0,
@@ -685,27 +545,7 @@
     "distinct_keys": 0.0,
     "metric": "data_11/http",
     "params": {
-     "alpha": 0.01
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_11/http",
-    "params": {
-     "alpha": 0.02
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_11/http",
-    "params": {
-     "alpha": 0.05
+     "alpha": 0.1
     },
     "sketch": "dd",
     "tail_index": 2.0,
@@ -735,7 +575,7 @@
     "distinct_keys": 0.0,
     "metric": "data_11/http",
     "params": {
-     "k": 200
+     "k": 25
     },
     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -755,7 +595,7 @@
     "distinct_keys": 0.0,
     "metric": "data_11",
     "params": {
-     "k": 200
+     "k": 25
     },
     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -811,27 +651,7 @@
     "distinct_keys": 0.0,
     "metric": "data_12",
     "params": {
-     "alpha": 0.01
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
-    "distinct_keys": 0.0,
-    "metric": "data_12",
-    "params": {
-     "alpha": 0.02
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
-   },
-   {
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-    "metric": "data_12",
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@@ -877,27 +697,7 @@
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-    "metric": "data_12/http",
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+     "alpha": 0.1
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@@ -927,7 +727,7 @@
     "distinct_keys": 0.0,
     "metric": "data_12/http",
     "params": {
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+     "k": 25
     },
     "sketch": "kll-percall",
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@@ -947,7 +747,7 @@
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     "metric": "data_12",
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@@ -1003,27 +803,7 @@
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@@ -1069,27 +849,7 @@
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+     "alpha": 0.1
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@@ -1119,7 +879,7 @@
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     "metric": "data_13/http",
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@@ -1139,7 +899,7 @@
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@@ -1195,27 +955,7 @@
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-    "metric": "data_14",
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@@ -1261,27 +1001,7 @@
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-    "metric": "data_14/http",
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+     "alpha": 0.1
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@@ -1311,7 +1031,7 @@
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     "metric": "data_14/http",
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@@ -1331,7 +1051,7 @@
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@@ -1387,27 +1107,7 @@
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-    "metric": "data_15",
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@@ -1453,27 +1153,7 @@
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+     "alpha": 0.1
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@@ -1503,7 +1183,7 @@
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     "metric": "data_15/http",
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@@ -1523,7 +1203,7 @@
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@@ -1579,27 +1259,7 @@
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@@ -1645,27 +1305,7 @@
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@@ -1695,7 +1335,7 @@
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@@ -1715,7 +1355,7 @@
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@@ -1771,27 +1411,7 @@
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@@ -1837,27 +1457,7 @@
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@@ -1887,7 +1487,7 @@
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@@ -1907,7 +1507,7 @@
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@@ -1953,37 +1553,17 @@
     "params": {
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      "heap": 32,
-     "rows": 5
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-    "sketch": "cms-heap-topk-fastpath-vector2d",
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-    "sketch": "dd",
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-    "zipf_s": null
+     "rows": 5
+    },
+    "sketch": "cms-heap-topk-fastpath-vector2d",
+    "tail_index": null,
+    "zipf_s": 1.1
    },
    {
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@@ -2029,27 +1609,7 @@
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+     "alpha": 0.1
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@@ -2079,7 +1639,7 @@
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     "metric": "data_4/http",
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     "sketch": "kll-percall",
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@@ -2099,7 +1659,7 @@
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@@ -2155,27 +1715,7 @@
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@@ -2221,27 +1761,7 @@
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@@ -2271,7 +1791,7 @@
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     "metric": "data_5/http",
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     "sketch": "kll-percall",
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@@ -2291,7 +1811,7 @@
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@@ -2347,27 +1867,7 @@
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-    "metric": "data_6",
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+     "alpha": 0.1
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@@ -2413,27 +1913,7 @@
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-    "metric": "data_6/http",
-    "params": {
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+     "alpha": 0.1
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     "sketch": "dd",
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@@ -2463,7 +1943,7 @@
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     "metric": "data_6/http",
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     "sketch": "kll-percall",
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@@ -2483,7 +1963,7 @@
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+     "k": 25
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@@ -2539,27 +2019,7 @@
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@@ -2605,27 +2065,7 @@
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-    "metric": "data_7/http",
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+     "alpha": 0.1
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@@ -2655,7 +2095,7 @@
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     "metric": "data_7/http",
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@@ -2675,7 +2115,7 @@
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@@ -2731,27 +2171,7 @@
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@@ -2797,27 +2217,7 @@
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+     "alpha": 0.1
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@@ -2847,7 +2247,7 @@
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@@ -2867,7 +2267,7 @@
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@@ -5525,26 +4885,26 @@
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@@ -5552,28 +4912,28 @@
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@@ -5581,26 +4941,26 @@
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@@ -5608,26 +4968,26 @@
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@@ -5635,26 +4995,26 @@
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@@ -5662,28 +5022,28 @@
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@@ -5691,26 +5051,26 @@
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@@ -5718,26 +5078,26 @@
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@@ -5745,26 +5105,26 @@
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@@ -5772,28 +5132,28 @@
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@@ -5825,28 +5185,28 @@
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@@ -5878,28 +5238,28 @@
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@@ -5907,26 +5267,26 @@
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@@ -5934,26 +5294,26 @@
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@@ -5961,26 +5321,26 @@
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@@ -5988,28 +5348,28 @@
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@@ -6017,26 +5377,26 @@
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@@ -6044,26 +5404,26 @@
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@@ -6071,26 +5431,26 @@
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@@ -6098,28 +5458,28 @@
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@@ -6127,26 +5487,26 @@
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@@ -6154,26 +5514,26 @@
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@@ -6181,26 +5541,26 @@
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@@ -6208,28 +5568,28 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared1-metrics8-tp95.json b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared1-metrics8-tp95.json
index bec7b583..a43956b9 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared1-metrics8-tp95.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared1-metrics8-tp95.json
@@ -1,7 +1,7 @@
 {
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+  "benchmark_secs_paper_rate": 7200.0,
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   "probed_configs": [
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@@ -43,27 +43,7 @@
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@@ -109,27 +89,7 @@
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@@ -159,7 +119,7 @@
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@@ -179,7 +139,7 @@
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@@ -235,27 +195,7 @@
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@@ -301,27 +241,7 @@
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@@ -351,7 +271,7 @@
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@@ -371,7 +291,7 @@
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@@ -427,27 +347,7 @@
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@@ -493,27 +393,7 @@
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@@ -543,7 +423,7 @@
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@@ -4045,26 +3725,26 @@
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@@ -4072,26 +3752,26 @@
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@@ -4155,26 +3835,26 @@
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@@ -4182,26 +3862,26 @@
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@@ -4209,26 +3889,26 @@
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@@ -4535,26 +4215,26 @@
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@@ -4562,28 +4242,28 @@
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@@ -4591,26 +4271,26 @@
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@@ -4618,26 +4298,26 @@
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@@ -4645,26 +4325,26 @@
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@@ -4672,28 +4352,28 @@
   },
   {
    "active_deployments": 832,
-   "benchmark_secs_paper_rate": 9120.0,
-   "cpu": 21997.345144536343,
+   "benchmark_secs_paper_rate": 7200.0,
+   "cpu": 21687.544557792826,
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-    "ingest": 21996.245280000057,
-    "query": 0.5472088371964985
+    "compaction": 0.5100779213114461,
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-   "gib": 44953.64132948295,
+   "gib": 32040.85645249659,
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    "hydra_rqes": 0,
    "latency_ms": 1014.5630284757121,
-   "median_latency_ms": 10.274587458745874,
+   "median_latency_ms": 9.454785478547855,
    "meets_sla": true,
    "method": "autosketch",
-   "objective": 1090.9361822699211,
-   "planning_secs": 0.028336821,
-   "probes": 2528,
+   "objective": 1020.9273658042193,
+   "planning_secs": 0.069505204,
+   "probes": 1904,
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared1-tp95.json b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared1-tp95.json
index 8547bac7..83a91f95 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared1-tp95.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared1-tp95.json
@@ -1,7 +1,7 @@
 {
  "autosketch": {
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-  "distinct_probes": 19,
+  "benchmark_secs_paper_rate": 900.0,
+  "distinct_probes": 15,
   "probed_configs": [
    {
     "distinct_keys": 10000.0,
@@ -43,27 +43,7 @@
     "distinct_keys": 0.0,
     "metric": "data",
     "params": {
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-    "sketch": "dd",
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-    "zipf_s": null
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-    "params": {
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-    "zipf_s": null
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-   {
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-    "metric": "data",
-    "params": {
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+     "alpha": 0.1
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     "tail_index": 2.0,
@@ -89,7 +69,7 @@
     "distinct_keys": 0.0,
     "metric": "data",
     "params": {
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+     "k": 25
     },
     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -129,27 +109,7 @@
     "distinct_keys": 0.0,
     "metric": "http",
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-    "sketch": "dd",
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-    "zipf_s": null
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-    "zipf_s": null
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-   {
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-    "metric": "http",
-    "params": {
-     "alpha": 0.05
+     "alpha": 0.1
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     "sketch": "dd",
     "tail_index": 2.0,
@@ -179,7 +139,7 @@
     "distinct_keys": 0.0,
     "metric": "http",
     "params": {
-     "k": 200
+     "k": 25
     },
     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -196,9 +156,9 @@
     "zipf_s": null
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-  "probes": 316,
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-  "benchmark_secs_measured": 481.3983948378009,
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+  "search_secs": 0.007462574,
+  "benchmark_secs_measured": 395.9548294044216,
   "benchmark_n": 100000000.0
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  "cost_model": "w_cpu * AUC(CPU) + w_mem * AUC(memory), billed by use; latency = longest chain, reported",
@@ -226,25 +186,25 @@
   {
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@@ -252,25 +212,25 @@
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@@ -278,25 +238,25 @@
   {
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@@ -304,51 +264,51 @@
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@@ -356,25 +316,25 @@
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@@ -382,25 +342,25 @@
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@@ -408,25 +368,25 @@
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@@ -434,25 +394,25 @@
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@@ -460,25 +420,25 @@
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@@ -486,25 +446,25 @@
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@@ -512,25 +472,25 @@
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@@ -2591,26 +2551,26 @@
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@@ -2618,26 +2578,26 @@
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@@ -2645,26 +2605,26 @@
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@@ -2672,28 +2632,28 @@
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@@ -2701,26 +2661,26 @@
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@@ -2728,26 +2688,26 @@
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@@ -2755,26 +2715,26 @@
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@@ -2782,28 +2742,28 @@
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@@ -2811,26 +2771,26 @@
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@@ -2838,26 +2798,26 @@
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@@ -2865,26 +2825,26 @@
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@@ -2892,28 +2852,28 @@
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@@ -2945,28 +2905,28 @@
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@@ -2998,28 +2958,28 @@
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@@ -3027,26 +2987,26 @@
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@@ -3054,26 +3014,26 @@
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@@ -3081,26 +3041,26 @@
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@@ -3108,28 +3068,28 @@
   },
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@@ -3137,26 +3097,26 @@
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@@ -3164,26 +3124,26 @@
   },
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@@ -3191,26 +3151,26 @@
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@@ -3218,28 +3178,28 @@
   },
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    "method": "autosketch",
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@@ -3247,26 +3207,26 @@
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    "hydra_rqes": 0,
    "infeasible": false,
    "latency_ms": 2677.0622579564497,
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    "method": "asap",
-   "milp_solve_secs": 0.204669814,
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    "sla_ms": 10000.0,
@@ -3274,26 +3234,26 @@
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   {
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    "hydra_rqes": 0,
    "infeasible": false,
    "latency_ms": 2677.0622579564497,
    "median_latency_ms": 39.001493326822924,
    "method": "asap-norollup",
-   "milp_solve_secs": 0.21425617,
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    "sla_ms": 10000.0,
@@ -3301,26 +3261,26 @@
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   {
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    "hydra_rqes": 0,
    "infeasible": false,
-   "latency_ms": 3260.6745874587455,
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    "method": "perquery",
-   "milp_solve_secs": 0.11811271,
-   "objective": 0.6827317048959917,
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@@ -3328,28 +3288,28 @@
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   {
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-   "benchmark_secs_paper_rate": 1140.0,
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+   "benchmark_secs_paper_rate": 900.0,
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    "hydra_rqes": 0,
    "latency_ms": 1014.5630284757121,
-   "median_latency_ms": 10.274587458745874,
+   "median_latency_ms": 9.454785478547855,
    "meets_sla": true,
    "method": "autosketch",
-   "objective": 136.3670227837398,
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared8-tp95.json b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared8-tp95.json
index 0fe85a50..96e1a4b0 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared8-tp95.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesall-shared8-tp95.json
@@ -1,7 +1,7 @@
 {
  "autosketch": {
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-  "distinct_probes": 19,
+  "benchmark_secs_paper_rate": 900.0,
+  "distinct_probes": 15,
   "probed_configs": [
    {
     "distinct_keys": 10000.0,
@@ -43,27 +43,7 @@
     "distinct_keys": 0.0,
     "metric": "data",
     "params": {
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-    "sketch": "dd",
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-    "zipf_s": null
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-   {
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-    "metric": "data",
-    "params": {
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+     "alpha": 0.1
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     "sketch": "dd",
     "tail_index": 2.0,
@@ -89,7 +69,7 @@
     "distinct_keys": 0.0,
     "metric": "data",
     "params": {
-     "k": 200
+     "k": 25
     },
     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -129,27 +109,7 @@
     "distinct_keys": 0.0,
     "metric": "http",
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-    "metric": "http",
-    "params": {
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+     "alpha": 0.1
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     "sketch": "dd",
     "tail_index": 2.0,
@@ -179,7 +139,7 @@
     "distinct_keys": 0.0,
     "metric": "http",
     "params": {
-     "k": 200
+     "k": 25
     },
     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -196,9 +156,9 @@
     "zipf_s": null
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   ],
-  "probes": 596,
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-  "benchmark_secs_measured": 481.3983948378009,
+  "probes": 454,
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+  "benchmark_secs_measured": 395.9548294044216,
   "benchmark_n": 100000000.0
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  "cost_model": "w_cpu * AUC(CPU) + w_mem * AUC(memory), billed by use; latency = longest chain, reported",
@@ -226,25 +186,25 @@
   {
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@@ -2701,26 +2661,26 @@
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@@ -2728,26 +2688,26 @@
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@@ -2755,26 +2715,26 @@
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@@ -2782,28 +2742,28 @@
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@@ -2811,26 +2771,26 @@
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@@ -2838,26 +2798,26 @@
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@@ -2865,26 +2825,26 @@
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@@ -2892,28 +2852,28 @@
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@@ -2945,28 +2905,28 @@
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@@ -2998,28 +2958,28 @@
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@@ -3027,26 +2987,26 @@
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@@ -3054,26 +3014,26 @@
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@@ -3081,26 +3041,26 @@
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@@ -3108,28 +3068,28 @@
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    "rqes": 200,
    "sla_ms": 1000.0,
@@ -3137,26 +3097,26 @@
   },
   {
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-    "query": 0.4657153866466019
+    "ingest": 2.2251736000000015,
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+    "ingest": 0.2400923411675434,
+    "query": 0.002213678856938029,
+    "storage": 12.586548483102167
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    "hydra_rqes": 0,
    "infeasible": false,
    "latency_ms": 2677.0622579564497,
-   "median_latency_ms": 51.074587458745874,
+   "median_latency_ms": 46.65478547854786,
    "method": "asap",
-   "milp_solve_secs": 0.604675908,
-   "objective": 0.1871837875704821,
+   "milp_solve_secs": 0.569476465,
+   "objective": 0.16546066255239014,
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    "rqes": 200,
    "sla_ms": 3000.0,
@@ -3164,26 +3124,26 @@
   },
   {
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+    "ingest": 2.5511467999999997,
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+    "ingest": 0.17835985527715492,
+    "query": 0.003767028025350117,
+    "storage": 14.10196744474634
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    "hydra_rqes": 0,
    "infeasible": false,
    "latency_ms": 2677.0622579564497,
    "median_latency_ms": 39.001493326822924,
    "method": "asap-norollup",
-   "milp_solve_secs": 0.472658501,
-   "objective": 0.20741835603687017,
+   "milp_solve_secs": 0.39965771,
+   "objective": 0.18535008020529384,
    "rolled_up_rqes": 0,
    "rqes": 200,
    "sla_ms": 3000.0,
@@ -3191,26 +3151,26 @@
   },
   {
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+    "ingest": 14.927826866666617,
+    "query": 0.6954424157724598
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+    "ingest": 0.8068229568888196,
+    "query": 0.004261383955694197,
+    "storage": 49.43127374859463
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    "hydra_rqes": 0,
    "infeasible": false,
-   "latency_ms": 2677.0622579564497,
+   "latency_ms": 2973.054785478548,
    "median_latency_ms": 33.96161525173612,
    "method": "perquery",
-   "milp_solve_secs": 0.224243816,
-   "objective": 1.0270510588111401,
+   "milp_solve_secs": 0.196043422,
+   "objective": 0.8563208994367867,
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@@ -3218,28 +3178,28 @@
   },
   {
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-   "benchmark_secs_paper_rate": 1140.0,
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+   "benchmark_secs_paper_rate": 900.0,
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+    "query": 0.082047081308615
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-   "gib": 5853.327783115489,
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-    "ingest": 5852.379183696825,
-    "query": 3.685740652345879e-06,
-    "storage": 0.909731121151591
+    "compaction": 0.03298054852991088,
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+    "query": 3.6851721630781865e-06,
+    "storage": 0.7828196299959668
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    "hydra_rqes": 0,
    "latency_ms": 1014.5630284757121,
    "median_latency_ms": 5.331095477386935,
    "meets_sla": true,
    "method": "autosketch",
-   "objective": 159.55438944980224,
-   "planning_secs": 0.007804312,
-   "probes": 596,
+   "objective": 150.17714711492874,
+   "planning_secs": 0.005825826,
+   "probes": 454,
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@@ -3247,26 +3207,26 @@
   },
   {
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+    "ingest": 2.2251736000000015,
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+    "ingest": 0.2400923411675434,
+    "query": 0.002213678856938029,
+    "storage": 12.586548483102167
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    "hydra_rqes": 0,
    "infeasible": false,
    "latency_ms": 2677.0622579564497,
-   "median_latency_ms": 51.074587458745874,
+   "median_latency_ms": 46.65478547854786,
    "method": "asap",
-   "milp_solve_secs": 0.572844605,
-   "objective": 0.1871837875704821,
+   "milp_solve_secs": 0.796466377,
+   "objective": 0.16546066255239014,
    "rolled_up_rqes": 104,
    "rqes": 200,
    "sla_ms": 10000.0,
@@ -3274,26 +3234,26 @@
   },
   {
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-   "cpu": 3.0506614695350494,
+   "cpu": 3.0070582826043575,
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-    "query": 0.47081146953505026
+    "ingest": 2.5511467999999997,
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-    "ingest": 0.1972989554830532,
-    "query": 0.00433985329697144,
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+    "ingest": 0.17835985527715492,
+    "query": 0.003767028025350117,
+    "storage": 14.10196744474634
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    "hydra_rqes": 0,
    "infeasible": false,
    "latency_ms": 2677.0622579564497,
    "median_latency_ms": 39.001493326822924,
    "method": "asap-norollup",
-   "milp_solve_secs": 0.441247043,
-   "objective": 0.20741835603687017,
+   "milp_solve_secs": 0.566294421,
+   "objective": 0.18535008020529384,
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    "sla_ms": 10000.0,
@@ -3301,26 +3261,26 @@
   },
   {
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-    "query": 0.7360380002213046
+    "ingest": 14.927826866666617,
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+    "ingest": 0.8068229568888196,
+    "query": 0.004261383955694197,
+    "storage": 49.43127374859463
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    "hydra_rqes": 0,
    "infeasible": false,
-   "latency_ms": 3260.6745874587455,
+   "latency_ms": 2973.054785478548,
    "median_latency_ms": 33.96161525173612,
    "method": "perquery",
-   "milp_solve_secs": 0.230732157,
-   "objective": 1.0222754509629204,
+   "milp_solve_secs": 0.19900549,
+   "objective": 0.8563208994367867,
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    "rqes": 200,
    "sla_ms": 10000.0,
@@ -3328,28 +3288,28 @@
   },
   {
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-   "benchmark_secs_paper_rate": 1140.0,
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+   "benchmark_secs_paper_rate": 900.0,
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-    "query": 3.685740652345879e-06,
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+    "storage": 0.7828196299959668
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    "hydra_rqes": 0,
    "latency_ms": 1014.5630284757121,
    "median_latency_ms": 5.331095477386935,
    "meets_sla": true,
    "method": "autosketch",
-   "objective": 159.55438944980224,
-   "planning_secs": 0.007804312,
-   "probes": 596,
+   "objective": 150.17714711492874,
+   "planning_secs": 0.005825826,
+   "probes": 454,
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared1-metrics16-tp95.json b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared1-metrics16-tp95.json
index 40b50fcd..d2639f19 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared1-metrics16-tp95.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared1-metrics16-tp95.json
@@ -1,7 +1,7 @@
 {
  "autosketch": {
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-  "distinct_probes": 160,
+  "benchmark_secs_paper_rate": 7680.0,
+  "distinct_probes": 128,
   "probed_configs": [
    {
     "distinct_keys": 10000.0,
@@ -43,27 +43,7 @@
     "distinct_keys": 0.0,
     "metric": "data_0",
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+     "alpha": 0.1
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@@ -89,7 +69,7 @@
     "distinct_keys": 0.0,
     "metric": "data_0",
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+     "k": 25
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     "sketch": "kll-percall",
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@@ -145,27 +125,7 @@
     "distinct_keys": 0.0,
     "metric": "data_1",
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-    "metric": "data_1",
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+     "alpha": 0.1
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@@ -191,7 +151,7 @@
     "distinct_keys": 0.0,
     "metric": "data_1",
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+     "k": 25
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     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -247,27 +207,7 @@
     "distinct_keys": 0.0,
     "metric": "data_10",
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-    "metric": "data_10",
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+     "alpha": 0.1
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     "tail_index": 2.0,
@@ -293,7 +233,7 @@
     "distinct_keys": 0.0,
     "metric": "data_10",
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@@ -349,27 +289,7 @@
     "distinct_keys": 0.0,
     "metric": "data_11",
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-    "metric": "data_11",
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@@ -395,7 +315,7 @@
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@@ -451,27 +371,7 @@
     "distinct_keys": 0.0,
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+     "alpha": 0.1
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@@ -497,7 +397,7 @@
     "distinct_keys": 0.0,
     "metric": "data_12",
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@@ -553,27 +453,7 @@
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@@ -599,7 +479,7 @@
     "distinct_keys": 0.0,
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@@ -655,27 +535,7 @@
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     "metric": "data_14",
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@@ -701,7 +561,7 @@
     "distinct_keys": 0.0,
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@@ -757,27 +617,7 @@
     "distinct_keys": 0.0,
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+     "alpha": 0.1
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@@ -803,7 +643,7 @@
     "distinct_keys": 0.0,
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@@ -859,27 +699,7 @@
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@@ -905,7 +725,7 @@
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@@ -961,27 +781,7 @@
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@@ -3865,25 +3545,25 @@
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@@ -3891,25 +3571,25 @@
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@@ -3917,27 +3597,27 @@
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@@ -3945,25 +3625,25 @@
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@@ -3971,25 +3651,25 @@
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@@ -3997,25 +3677,25 @@
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@@ -4023,27 +3703,27 @@
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@@ -4051,25 +3731,25 @@
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@@ -4077,25 +3757,25 @@
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@@ -4103,25 +3783,25 @@
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@@ -4129,27 +3809,27 @@
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@@ -4157,25 +3837,25 @@
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@@ -4183,25 +3863,25 @@
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@@ -4209,25 +3889,25 @@
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@@ -4235,27 +3915,27 @@
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@@ -4263,25 +3943,25 @@
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@@ -4289,25 +3969,25 @@
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@@ -4315,25 +3995,25 @@
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@@ -4341,27 +4021,27 @@
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@@ -4369,25 +4049,25 @@
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@@ -4395,25 +4075,25 @@
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@@ -4421,25 +4101,25 @@
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@@ -4447,27 +4127,27 @@
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@@ -4475,25 +4155,25 @@
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@@ -4501,25 +4181,25 @@
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@@ -4527,25 +4207,25 @@
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@@ -4553,27 +4233,27 @@
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@@ -4581,25 +4261,25 @@
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@@ -4607,25 +4287,25 @@
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@@ -4633,25 +4313,25 @@
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@@ -4659,27 +4339,27 @@
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@@ -4687,25 +4367,25 @@
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@@ -4713,25 +4393,25 @@
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@@ -4739,25 +4419,25 @@
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@@ -4765,27 +4445,27 @@
   },
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-   "median_latency_ms": 10.274587458745874,
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@@ -4793,25 +4473,25 @@
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   {
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    "infeasible": false,
    "latency_ms": 2677.0622579564497,
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@@ -4819,25 +4499,25 @@
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   {
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+    "ingest": 0.3865776707778624,
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    "infeasible": false,
    "latency_ms": 2677.0622579564497,
-   "median_latency_ms": 51.074587458745874,
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@@ -4845,25 +4525,25 @@
   },
   {
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+    "ingest": 1.5707128053933508,
+    "query": 0.024312806315510537,
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    "infeasible": false,
-   "latency_ms": 3260.6745874587455,
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    "method": "perquery",
-   "milp_solve_secs": 1.9532580130000001,
-   "objective": 9.969057925509304,
+   "milp_solve_secs": 1.134201813,
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    "sla_ms": 10000.0,
@@ -4871,27 +4551,27 @@
   },
   {
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    "method": "autosketch",
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+   "objective": 2035.3531206985958,
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared1-metrics8-tp95.json b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared1-metrics8-tp95.json
index 4f050fb8..90853c6b 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared1-metrics8-tp95.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared1-metrics8-tp95.json
@@ -1,7 +1,7 @@
 {
  "autosketch": {
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-  "distinct_probes": 80,
+  "benchmark_secs_paper_rate": 3840.0,
+  "distinct_probes": 64,
   "probed_configs": [
    {
     "distinct_keys": 10000.0,
@@ -43,27 +43,7 @@
     "distinct_keys": 0.0,
     "metric": "data_0",
     "params": {
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-    "metric": "data_0",
-    "params": {
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+     "alpha": 0.1
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     "tail_index": 2.0,
@@ -89,7 +69,7 @@
     "distinct_keys": 0.0,
     "metric": "data_0",
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+     "k": 25
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     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -145,27 +125,7 @@
     "distinct_keys": 0.0,
     "metric": "data_1",
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+     "alpha": 0.1
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     "tail_index": 2.0,
@@ -191,7 +151,7 @@
     "distinct_keys": 0.0,
     "metric": "data_1",
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+     "k": 25
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     "sketch": "kll-percall",
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@@ -247,27 +207,7 @@
     "distinct_keys": 0.0,
     "metric": "data_2",
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-    "metric": "data_2",
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+     "alpha": 0.1
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     "tail_index": 2.0,
@@ -293,7 +233,7 @@
     "distinct_keys": 0.0,
     "metric": "data_2",
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+     "k": 25
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@@ -349,27 +289,7 @@
     "distinct_keys": 0.0,
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@@ -3075,25 +2915,25 @@
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@@ -3101,27 +2941,27 @@
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@@ -3129,25 +2969,25 @@
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@@ -3155,25 +2995,25 @@
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@@ -3181,25 +3021,25 @@
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@@ -3207,27 +3047,27 @@
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@@ -3235,25 +3075,25 @@
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@@ -3261,25 +3101,25 @@
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@@ -3287,25 +3127,25 @@
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@@ -3313,27 +3153,27 @@
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@@ -3341,25 +3181,25 @@
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@@ -3367,25 +3207,25 @@
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@@ -3393,25 +3233,25 @@
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@@ -3419,27 +3259,27 @@
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@@ -3447,25 +3287,25 @@
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@@ -3473,25 +3313,25 @@
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@@ -3499,25 +3339,25 @@
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@@ -3553,25 +3393,25 @@
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@@ -3579,25 +3419,25 @@
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@@ -3605,25 +3445,25 @@
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@@ -3631,27 +3471,27 @@
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@@ -3659,25 +3499,25 @@
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@@ -3685,25 +3525,25 @@
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@@ -3711,25 +3551,25 @@
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@@ -3737,27 +3577,27 @@
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@@ -3765,25 +3605,25 @@
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@@ -3791,25 +3631,25 @@
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@@ -3817,25 +3657,25 @@
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@@ -3843,27 +3683,27 @@
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@@ -3871,25 +3711,25 @@
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+    "ingest": 0.19328883538893118,
+    "query": 0.0052263404875506165,
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@@ -3897,25 +3737,25 @@
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+    "ingest": 0.19328883538893118,
+    "query": 0.0052263404875506165,
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    "infeasible": false,
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@@ -3923,25 +3763,25 @@
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    "infeasible": false,
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@@ -3949,27 +3789,27 @@
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@@ -3977,25 +3817,25 @@
   },
   {
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+    "query": 0.0052263404875506165,
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    "infeasible": false,
    "latency_ms": 2677.0622579564497,
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    "method": "asap",
-   "milp_solve_secs": 1.322160461,
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+   "milp_solve_secs": 2.134302662,
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@@ -4003,25 +3843,25 @@
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   {
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+    "ingest": 0.19328883538893118,
+    "query": 0.0052263404875506165,
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    "infeasible": false,
    "latency_ms": 2677.0622579564497,
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-   "milp_solve_secs": 1.322800174,
-   "objective": 1.363364454853922,
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@@ -4029,25 +3869,25 @@
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   {
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+    "ingest": 0.785356402696677,
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    "infeasible": false,
-   "latency_ms": 3260.6745874587455,
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-   "milp_solve_secs": 0.776904374,
-   "objective": 4.984528962754636,
+   "milp_solve_secs": 1.085674712,
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@@ -4055,27 +3895,27 @@
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   {
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-   "median_latency_ms": 10.274587458745874,
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    "method": "autosketch",
-   "objective": 1087.4993251060878,
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared1-tp95.json b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared1-tp95.json
index 763ac6dc..11287cb7 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared1-tp95.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared1-tp95.json
@@ -1,7 +1,7 @@
 {
  "autosketch": {
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-  "distinct_probes": 10,
+  "benchmark_secs_paper_rate": 480.0,
+  "distinct_probes": 8,
   "probed_configs": [
    {
     "distinct_keys": 10000.0,
@@ -43,27 +43,7 @@
     "distinct_keys": 0.0,
     "metric": "data",
     "params": {
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-    "sketch": "dd",
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-    "zipf_s": null
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-    "zipf_s": null
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-    "metric": "data",
-    "params": {
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+     "alpha": 0.1
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     "sketch": "dd",
     "tail_index": 2.0,
@@ -89,7 +69,7 @@
     "distinct_keys": 0.0,
     "metric": "data",
     "params": {
-     "k": 200
+     "k": 25
     },
     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -106,9 +86,9 @@
     "zipf_s": null
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   ],
-  "probes": 150,
-  "search_secs": 0.001600582,
-  "benchmark_secs_measured": 212.11660946492339,
+  "probes": 100,
+  "search_secs": 0.003133721,
+  "benchmark_secs_measured": 169.39482674823375,
   "benchmark_n": 100000000.0
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  "cost_model": "w_cpu * AUC(CPU) + w_mem * AUC(memory), billed by use; latency = longest chain, reported",
@@ -136,24 +116,24 @@
   {
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@@ -161,24 +141,24 @@
   {
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@@ -186,24 +166,24 @@
   {
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@@ -211,24 +191,24 @@
   {
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@@ -2335,25 +2315,25 @@
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@@ -2361,25 +2341,25 @@
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@@ -2387,27 +2367,27 @@
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@@ -2415,25 +2395,25 @@
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@@ -2441,25 +2421,25 @@
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@@ -2467,25 +2447,25 @@
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@@ -2493,27 +2473,27 @@
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@@ -2521,25 +2501,25 @@
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@@ -2547,25 +2527,25 @@
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@@ -2573,25 +2553,25 @@
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@@ -2599,27 +2579,27 @@
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@@ -2627,25 +2607,25 @@
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@@ -2653,25 +2633,25 @@
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@@ -2679,25 +2659,25 @@
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@@ -2705,27 +2685,27 @@
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@@ -2733,25 +2713,25 @@
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@@ -2759,25 +2739,25 @@
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@@ -2785,25 +2765,25 @@
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@@ -2811,27 +2791,27 @@
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@@ -2839,25 +2819,25 @@
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@@ -2865,25 +2845,25 @@
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@@ -2891,25 +2871,25 @@
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@@ -2917,27 +2897,27 @@
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@@ -2945,25 +2925,25 @@
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@@ -2971,25 +2951,25 @@
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@@ -2997,25 +2977,25 @@
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@@ -3023,27 +3003,27 @@
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@@ -3051,25 +3031,25 @@
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@@ -3077,25 +3057,25 @@
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@@ -3103,25 +3083,25 @@
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@@ -3129,27 +3109,27 @@
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@@ -3157,25 +3137,25 @@
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@@ -3183,25 +3163,25 @@
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@@ -3209,25 +3189,25 @@
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@@ -3235,27 +3215,27 @@
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-    "storage": 0.13822956386972313
+    "compaction": 0.032722903306483954,
+    "ingest": 4001.4905987412562,
+    "query": 6.827698250652308e-08,
+    "storage": 0.07562904063630942
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    "latency_ms": 1014.5630284757121,
-   "median_latency_ms": 10.274587458745874,
+   "median_latency_ms": 9.454785478547855,
    "meets_sla": true,
    "method": "autosketch",
-   "objective": 135.93741563826123,
-   "planning_secs": 0.001600582,
-   "probes": 150,
+   "objective": 127.20957004366241,
+   "planning_secs": 0.003133721,
+   "probes": 100,
    "rolled_up_rqes": 0,
    "rqes": 42,
    "sla_ms": 3000.0,
@@ -3263,25 +3243,25 @@
   },
   {
    "active_deployments": 6,
-   "cpu": 2.414340249837069,
+   "cpu": 2.381591291421228,
    "cpu_parts": {
     "compaction": 0.0,
-    "ingest": 2.1309624000000014,
-    "query": 0.28337784983706765
+    "ingest": 2.1105876000000015,
+    "query": 0.27100369142122616
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-   "gib": 16.323545334458206,
+   "gib": 11.813800578927822,
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-    "ingest": 0.0398197661467533,
-    "query": 0.0011327742818952528,
-    "storage": 16.282592794029558
+    "ingest": 0.0241611044236164,
+    "query": 0.0006532925609438271,
+    "storage": 11.788986181943262
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    "infeasible": false,
    "latency_ms": 2677.0622579564497,
-   "median_latency_ms": 51.074587458745874,
+   "median_latency_ms": 46.65478547854786,
    "method": "asap",
-   "milp_solve_secs": 0.136346051,
-   "objective": 0.17042055685674032,
+   "milp_solve_secs": 0.221586276,
+   "objective": 0.14902585987878852,
    "rolled_up_rqes": 0,
    "rqes": 42,
    "sla_ms": 10000.0,
@@ -3289,25 +3269,25 @@
   },
   {
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-   "cpu": 2.414340249837069,
+   "cpu": 2.381591291421228,
    "cpu_parts": {
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-    "ingest": 2.1309624000000014,
-    "query": 0.28337784983706765
+    "ingest": 2.1105876000000015,
+    "query": 0.27100369142122616
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-   "gib": 16.323545334458206,
+   "gib": 11.813800578927822,
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-    "ingest": 0.0398197661467533,
-    "query": 0.0011327742818952528,
-    "storage": 16.282592794029558
+    "ingest": 0.0241611044236164,
+    "query": 0.0006532925609438271,
+    "storage": 11.788986181943262
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    "infeasible": false,
    "latency_ms": 2677.0622579564497,
-   "median_latency_ms": 51.074587458745874,
+   "median_latency_ms": 46.65478547854786,
    "method": "asap-norollup",
-   "milp_solve_secs": 0.137031268,
-   "objective": 0.17042055685674032,
+   "milp_solve_secs": 0.222229129,
+   "objective": 0.14902585987878852,
    "rolled_up_rqes": 0,
    "rqes": 42,
    "sla_ms": 10000.0,
@@ -3315,25 +3295,25 @@
   },
   {
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-   "cpu": 7.92168546709299,
+   "cpu": 7.7814373086771536,
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     "compaction": 0.0,
-    "ingest": 7.339645133333329,
-    "query": 0.5820403337596605
+    "ingest": 7.237771133333335,
+    "query": 0.543666175343819
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-   "gib": 67.91861998360977,
+   "gib": 38.51776471844535,
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-    "ingest": 0.17646285895276909,
-    "query": 0.0030044134614197267,
-    "storage": 67.73915271119556
+    "ingest": 0.09816955033708456,
+    "query": 0.0015195503947194005,
+    "storage": 38.41807561771355
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    "infeasible": false,
-   "latency_ms": 3260.6745874587455,
-   "median_latency_ms": 268.67458745874586,
+   "latency_ms": 2973.054785478548,
+   "median_latency_ms": 245.0547854785479,
    "method": "perquery",
-   "milp_solve_secs": 0.079554863,
-   "objective": 0.6230661203443296,
+   "milp_solve_secs": 0.110311811,
+   "objective": 0.4865522639985065,
    "rolled_up_rqes": 0,
    "rqes": 42,
    "sla_ms": 10000.0,
@@ -3341,27 +3321,27 @@
   },
   {
    "active_deployments": 42,
-   "benchmark_secs_paper_rate": 600.0,
-   "cpu": 2739.450843015953,
+   "benchmark_secs_paper_rate": 480.0,
+   "cpu": 2701.2951780940602,
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-    "ingest": 2739.3808280000003,
-    "query": 0.0009330535669634525
+    "compaction": 0.06375974016393078,
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-   "gib": 5615.653145194411,
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-    "query": 6.87687773814823e-08,
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+    "compaction": 0.032722903306483954,
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+    "query": 6.827698250652308e-08,
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    "latency_ms": 1014.5630284757121,
-   "median_latency_ms": 10.274587458745874,
+   "median_latency_ms": 9.454785478547855,
    "meets_sla": true,
    "method": "autosketch",
-   "objective": 135.93741563826123,
-   "planning_secs": 0.001600582,
-   "probes": 150,
+   "objective": 127.20957004366241,
+   "planning_secs": 0.003133721,
+   "probes": 100,
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared8-tp95.json b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared8-tp95.json
index 3660eef9..1616ca3c 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared8-tp95.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesclassic-shared8-tp95.json
@@ -1,7 +1,7 @@
 {
  "autosketch": {
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-  "distinct_probes": 10,
+  "benchmark_secs_paper_rate": 480.0,
+  "distinct_probes": 8,
   "probed_configs": [
    {
     "distinct_keys": 10000.0,
@@ -43,27 +43,7 @@
     "distinct_keys": 0.0,
     "metric": "data",
     "params": {
-     "alpha": 0.01
-    },
-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
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-   {
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-    "metric": "data",
-    "params": {
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-    "sketch": "dd",
-    "tail_index": 2.0,
-    "zipf_s": null
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-   {
-    "distinct_keys": 0.0,
-    "metric": "data",
-    "params": {
-     "alpha": 0.05
+     "alpha": 0.1
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     "sketch": "dd",
     "tail_index": 2.0,
@@ -89,7 +69,7 @@
     "distinct_keys": 0.0,
     "metric": "data",
     "params": {
-     "k": 200
+     "k": 25
     },
     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -106,9 +86,9 @@
     "zipf_s": null
    }
   ],
-  "probes": 264,
-  "search_secs": 0.002188334,
-  "benchmark_secs_measured": 212.11660946492339,
+  "probes": 178,
+  "search_secs": 0.002155445,
+  "benchmark_secs_measured": 169.39482674823375,
   "benchmark_n": 100000000.0
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  "cost_model": "w_cpu * AUC(CPU) + w_mem * AUC(memory), billed by use; latency = longest chain, reported",
@@ -136,24 +116,24 @@
   {
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-    "ingest": 44.4943444,
-    "query": 0.023292308530314196
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-   "objective": 44.518934789023895,
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@@ -161,24 +141,24 @@
   {
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@@ -186,24 +166,24 @@
   {
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-    "query": 0.047212346769513525
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+    "compaction": 4.061105507726677e-06,
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@@ -211,24 +191,24 @@
   {
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    "weights": "cpu"
@@ -236,49 +216,49 @@
   {
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@@ -286,24 +266,24 @@
   {
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@@ -311,24 +291,24 @@
   {
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@@ -336,24 +316,24 @@
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@@ -2273,24 +2253,24 @@
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@@ -2309,25 +2289,25 @@
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@@ -2335,25 +2315,25 @@
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@@ -2361,25 +2341,25 @@
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@@ -2387,27 +2367,27 @@
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@@ -2415,25 +2395,25 @@
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@@ -2441,25 +2421,25 @@
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@@ -2467,25 +2447,25 @@
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@@ -2493,27 +2473,27 @@
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@@ -2521,25 +2501,25 @@
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@@ -2547,25 +2527,25 @@
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@@ -2573,25 +2553,25 @@
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@@ -2599,27 +2579,27 @@
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@@ -2627,25 +2607,25 @@
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@@ -2653,25 +2633,25 @@
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@@ -2679,25 +2659,25 @@
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@@ -2705,27 +2685,27 @@
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@@ -2733,25 +2713,25 @@
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@@ -2759,25 +2739,25 @@
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@@ -2785,25 +2765,25 @@
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@@ -2811,27 +2791,27 @@
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@@ -2839,25 +2819,25 @@
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@@ -2865,25 +2845,25 @@
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@@ -2891,25 +2871,25 @@
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@@ -2917,27 +2897,27 @@
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@@ -2945,25 +2925,25 @@
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@@ -2971,25 +2951,25 @@
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@@ -2997,25 +2977,25 @@
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@@ -3023,27 +3003,27 @@
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@@ -3051,25 +3031,25 @@
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@@ -3077,25 +3057,25 @@
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@@ -3103,25 +3083,25 @@
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@@ -3129,27 +3109,27 @@
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@@ -3157,25 +3137,25 @@
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@@ -3183,25 +3163,25 @@
   },
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@@ -3209,25 +3189,25 @@
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@@ -3235,27 +3215,27 @@
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@@ -3263,25 +3243,25 @@
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+    "ingest": 0.0241611044236164,
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@@ -3289,25 +3269,25 @@
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   {
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@@ -3315,25 +3295,25 @@
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@@ -3341,27 +3321,27 @@
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   {
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared1-metrics16-tp95.json b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared1-metrics16-tp95.json
index b0a4b652..72cee1f6 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared1-metrics16-tp95.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared1-metrics16-tp95.json
@@ -1,7 +1,7 @@
 {
  "autosketch": {
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-  "distinct_probes": 144,
+  "benchmark_secs_paper_rate": 6720.0,
+  "distinct_probes": 112,
   "probed_configs": [
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     "distinct_keys": 1000000.0,
@@ -27,27 +27,7 @@
     "distinct_keys": 0.0,
     "metric": "data_0/http",
     "params": {
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-    "zipf_s": null
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-   {
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-    "metric": "data_0/http",
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-    "zipf_s": null
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-   {
-    "distinct_keys": 0.0,
-    "metric": "data_0/http",
-    "params": {
-     "alpha": 0.05
+     "alpha": 0.1
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     "sketch": "dd",
     "tail_index": 2.0,
@@ -77,7 +57,7 @@
     "distinct_keys": 0.0,
     "metric": "data_0/http",
     "params": {
-     "k": 200
+     "k": 25
     },
     "sketch": "kll-percall",
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@@ -117,27 +97,7 @@
     "distinct_keys": 0.0,
     "metric": "data_1/http",
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-    "zipf_s": null
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-   {
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-    "metric": "data_1/http",
-    "params": {
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+     "alpha": 0.1
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     "sketch": "dd",
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@@ -167,7 +127,7 @@
     "distinct_keys": 0.0,
     "metric": "data_1/http",
     "params": {
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+     "k": 25
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     "sketch": "kll-percall",
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@@ -207,27 +167,7 @@
     "distinct_keys": 0.0,
     "metric": "data_10/http",
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-   {
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-    "metric": "data_10/http",
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+     "alpha": 0.1
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@@ -257,7 +197,7 @@
     "distinct_keys": 0.0,
     "metric": "data_10/http",
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+     "k": 25
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@@ -297,27 +237,7 @@
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-    "metric": "data_11/http",
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+     "alpha": 0.1
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@@ -347,7 +267,7 @@
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     "metric": "data_11/http",
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@@ -387,27 +307,7 @@
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+     "alpha": 0.1
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@@ -437,7 +337,7 @@
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     "metric": "data_12/http",
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@@ -477,27 +377,7 @@
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     "metric": "data_13/http",
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-    "metric": "data_13/http",
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+     "alpha": 0.1
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@@ -527,7 +407,7 @@
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     "metric": "data_13/http",
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@@ -567,27 +447,7 @@
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-    "metric": "data_14/http",
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+     "alpha": 0.1
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@@ -617,7 +477,7 @@
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     "metric": "data_14/http",
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@@ -657,27 +517,7 @@
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+     "alpha": 0.1
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@@ -707,7 +547,7 @@
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     "metric": "data_15/http",
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@@ -747,27 +587,7 @@
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-    "metric": "data_2/http",
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+     "alpha": 0.1
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@@ -797,7 +617,7 @@
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     "metric": "data_2/http",
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@@ -837,27 +657,7 @@
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+     "alpha": 0.1
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@@ -887,7 +687,7 @@
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     "metric": "data_3/http",
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@@ -927,27 +727,7 @@
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     "metric": "data_4/http",
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+     "alpha": 0.1
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@@ -977,7 +757,7 @@
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     "metric": "data_4/http",
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     "sketch": "kll-percall",
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@@ -1017,27 +797,7 @@
     "distinct_keys": 0.0,
     "metric": "data_5/http",
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-    "metric": "data_5/http",
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+     "alpha": 0.1
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@@ -1067,7 +827,7 @@
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     "sketch": "kll-percall",
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@@ -1107,27 +867,7 @@
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     "metric": "data_6/http",
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+     "alpha": 0.1
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@@ -1157,7 +897,7 @@
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     "metric": "data_6/http",
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     "sketch": "kll-percall",
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@@ -1197,27 +937,7 @@
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     "metric": "data_7/http",
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-    "metric": "data_7/http",
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@@ -1247,7 +967,7 @@
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     "metric": "data_7/http",
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@@ -1287,27 +1007,7 @@
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@@ -1337,7 +1037,7 @@
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     "metric": "data_8/http",
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@@ -1377,27 +1077,7 @@
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+     "alpha": 0.1
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@@ -1427,7 +1107,7 @@
     "distinct_keys": 0.0,
     "metric": "data_9/http",
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@@ -1444,9 +1124,9 @@
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+  "benchmark_secs_measured": 3624.960042499006,
   "benchmark_n": 100000000.0
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  "cost_model": "w_cpu * AUC(CPU) + w_mem * AUC(memory), billed by use; latency = longest chain, reported",
@@ -1474,25 +1154,25 @@
   {
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@@ -1500,25 +1180,25 @@
   {
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@@ -1526,25 +1206,25 @@
   {
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@@ -1552,25 +1232,25 @@
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@@ -3696,25 +3376,25 @@
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@@ -3757,28 +3437,28 @@
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@@ -3810,28 +3490,28 @@
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@@ -3839,26 +3519,26 @@
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@@ -3866,26 +3546,26 @@
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@@ -3893,26 +3573,26 @@
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@@ -3920,28 +3600,28 @@
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@@ -3949,26 +3629,26 @@
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@@ -3976,26 +3656,26 @@
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@@ -4003,26 +3683,26 @@
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@@ -4030,28 +3710,28 @@
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@@ -4059,26 +3739,26 @@
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@@ -4086,26 +3766,26 @@
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@@ -4113,26 +3793,26 @@
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@@ -4140,28 +3820,28 @@
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@@ -4193,28 +3873,28 @@
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@@ -4246,28 +3926,28 @@
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@@ -4275,26 +3955,26 @@
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@@ -4302,26 +3982,26 @@
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@@ -4329,26 +4009,26 @@
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@@ -4356,28 +4036,28 @@
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@@ -4385,26 +4065,26 @@
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@@ -4412,26 +4092,26 @@
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@@ -4439,26 +4119,26 @@
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@@ -4466,28 +4146,28 @@
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@@ -4495,26 +4175,26 @@
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@@ -4522,26 +4202,26 @@
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@@ -4549,26 +4229,26 @@
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@@ -4576,28 +4256,28 @@
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    "hydra_rqes": 0,
    "latency_ms": 490.15722656250006,
    "median_latency_ms": 4.901572265625,
    "meets_sla": true,
    "method": "autosketch",
-   "objective": 6.873714327657627,
-   "planning_secs": 0.036724655,
-   "probes": 2656,
+   "objective": 6.501610909829353,
+   "planning_secs": 0.03699938,
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    "rqes": 992,
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared1-metrics8-tp95.json b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared1-metrics8-tp95.json
index ec76104d..63666e70 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared1-metrics8-tp95.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared1-metrics8-tp95.json
@@ -1,7 +1,7 @@
 {
  "autosketch": {
-  "benchmark_secs_paper_rate": 4320.0,
-  "distinct_probes": 72,
+  "benchmark_secs_paper_rate": 3360.0,
+  "distinct_probes": 56,
   "probed_configs": [
    {
     "distinct_keys": 1000000.0,
@@ -27,27 +27,7 @@
     "distinct_keys": 0.0,
     "metric": "data_0/http",
     "params": {
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-    "tail_index": 2.0,
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-   {
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-    "metric": "data_0/http",
-    "params": {
-     "alpha": 0.05
+     "alpha": 0.1
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     "tail_index": 2.0,
@@ -77,7 +57,7 @@
     "distinct_keys": 0.0,
     "metric": "data_0/http",
     "params": {
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+     "k": 25
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     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -117,27 +97,7 @@
     "distinct_keys": 0.0,
     "metric": "data_1/http",
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-    "metric": "data_1/http",
-    "params": {
-     "alpha": 0.05
+     "alpha": 0.1
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     "tail_index": 2.0,
@@ -167,7 +127,7 @@
     "distinct_keys": 0.0,
     "metric": "data_1/http",
     "params": {
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+     "k": 25
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     "sketch": "kll-percall",
     "tail_index": 2.0,
@@ -207,27 +167,7 @@
     "distinct_keys": 0.0,
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-    "metric": "data_2/http",
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+     "alpha": 0.1
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     "tail_index": 2.0,
@@ -257,7 +197,7 @@
     "distinct_keys": 0.0,
     "metric": "data_2/http",
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@@ -297,27 +237,7 @@
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+     "alpha": 0.1
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@@ -347,7 +267,7 @@
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@@ -387,27 +307,7 @@
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@@ -437,7 +337,7 @@
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@@ -477,27 +377,7 @@
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@@ -527,7 +407,7 @@
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@@ -567,27 +447,7 @@
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     "metric": "data_6/http",
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@@ -617,7 +477,7 @@
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     "metric": "data_6/http",
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@@ -657,27 +517,7 @@
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+     "alpha": 0.1
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@@ -707,7 +547,7 @@
     "distinct_keys": 0.0,
     "metric": "data_7/http",
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@@ -724,9 +564,9 @@
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   ],
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-  "search_secs": 0.019028717,
-  "benchmark_secs_measured": 2154.25428298302,
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+  "search_secs": 0.015570945,
+  "benchmark_secs_measured": 1812.480021249503,
   "benchmark_n": 100000000.0
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  "cost_model": "w_cpu * AUC(CPU) + w_mem * AUC(memory), billed by use; latency = longest chain, reported",
@@ -754,25 +594,25 @@
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@@ -780,25 +620,25 @@
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@@ -806,25 +646,25 @@
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@@ -832,25 +672,25 @@
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@@ -858,25 +698,25 @@
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@@ -884,25 +724,25 @@
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@@ -910,25 +750,25 @@
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@@ -936,25 +776,25 @@
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@@ -962,25 +802,25 @@
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@@ -988,25 +828,25 @@
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@@ -3119,26 +2959,26 @@
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@@ -3146,26 +2986,26 @@
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@@ -3173,26 +3013,26 @@
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@@ -3200,28 +3040,28 @@
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@@ -3229,26 +3069,26 @@
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@@ -3256,26 +3096,26 @@
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@@ -3283,26 +3123,26 @@
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@@ -3310,28 +3150,28 @@
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@@ -3339,26 +3179,26 @@
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@@ -3366,26 +3206,26 @@
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@@ -3393,26 +3233,26 @@
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@@ -3420,28 +3260,28 @@
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@@ -3473,28 +3313,28 @@
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@@ -3526,28 +3366,28 @@
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@@ -3555,26 +3395,26 @@
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@@ -3582,26 +3422,26 @@
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@@ -3609,26 +3449,26 @@
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@@ -3636,28 +3476,28 @@
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@@ -3665,26 +3505,26 @@
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@@ -3692,26 +3532,26 @@
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@@ -3719,26 +3559,26 @@
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@@ -3746,28 +3586,28 @@
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@@ -3775,26 +3615,26 @@
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    "infeasible": false,
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    "method": "asap",
-   "milp_solve_secs": 1.065013842,
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@@ -3802,26 +3642,26 @@
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    "latency_ms": 958.6905598958333,
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@@ -3829,26 +3669,26 @@
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    "latency_ms": 958.6905598958333,
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@@ -3856,28 +3696,28 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared1-tp95.json b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared1-tp95.json
index 200af282..7eaf4f96 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared1-tp95.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared1-tp95.json
@@ -1,7 +1,7 @@
 {
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-  "distinct_probes": 9,
+  "benchmark_secs_paper_rate": 420.0,
+  "distinct_probes": 7,
   "probed_configs": [
    {
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@@ -27,27 +27,7 @@
     "distinct_keys": 0.0,
     "metric": "http",
     "params": {
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-    "params": {
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+     "alpha": 0.1
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@@ -77,7 +57,7 @@
     "distinct_keys": 0.0,
     "metric": "http",
     "params": {
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+     "k": 25
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     "sketch": "kll-percall",
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@@ -94,9 +74,9 @@
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+  "benchmark_secs_measured": 226.56000265618786,
   "benchmark_n": 100000000.0
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  "cost_model": "w_cpu * AUC(CPU) + w_mem * AUC(memory), billed by use; latency = longest chain, reported",
@@ -124,25 +104,25 @@
   {
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@@ -150,25 +130,25 @@
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@@ -176,25 +156,25 @@
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@@ -202,25 +182,25 @@
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@@ -2346,25 +2326,25 @@
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@@ -2407,28 +2387,28 @@
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@@ -2460,28 +2440,28 @@
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@@ -2489,26 +2469,26 @@
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@@ -2516,26 +2496,26 @@
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@@ -2543,26 +2523,26 @@
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@@ -2570,28 +2550,28 @@
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@@ -2599,26 +2579,26 @@
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@@ -2626,26 +2606,26 @@
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@@ -2653,26 +2633,26 @@
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@@ -2680,28 +2660,28 @@
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@@ -2709,26 +2689,26 @@
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@@ -2736,26 +2716,26 @@
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@@ -2763,26 +2743,26 @@
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@@ -2790,28 +2770,28 @@
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@@ -2843,28 +2823,28 @@
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@@ -2896,28 +2876,28 @@
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@@ -2925,26 +2905,26 @@
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@@ -2952,26 +2932,26 @@
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@@ -2979,26 +2959,26 @@
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@@ -3006,28 +2986,28 @@
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@@ -3035,26 +3015,26 @@
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@@ -3062,26 +3042,26 @@
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@@ -3089,26 +3069,26 @@
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@@ -3116,28 +3096,28 @@
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@@ -3145,26 +3125,26 @@
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@@ -3172,26 +3152,26 @@
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@@ -3199,26 +3179,26 @@
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@@ -3226,28 +3206,28 @@
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    "method": "autosketch",
-   "objective": 0.4296071454786008,
-   "planning_secs": 0.002068572,
-   "probes": 166,
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared8-tp95.json b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared8-tp95.json
index 19260cda..aedc2296 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared8-tp95.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/synthetic-templatesmultigroup-shared8-tp95.json
@@ -1,7 +1,7 @@
 {
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-  "distinct_probes": 9,
+  "benchmark_secs_paper_rate": 420.0,
+  "distinct_probes": 7,
   "probed_configs": [
    {
     "distinct_keys": 1000000.0,
@@ -27,27 +27,7 @@
     "distinct_keys": 0.0,
     "metric": "http",
     "params": {
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-    "zipf_s": null
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-    "params": {
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+     "alpha": 0.1
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@@ -77,7 +57,7 @@
     "distinct_keys": 0.0,
     "metric": "http",
     "params": {
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+     "k": 25
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     "sketch": "kll-percall",
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@@ -94,9 +74,9 @@
     "zipf_s": null
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+  "benchmark_secs_measured": 226.56000265618786,
   "benchmark_n": 100000000.0
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  "cost_model": "w_cpu * AUC(CPU) + w_mem * AUC(memory), billed by use; latency = longest chain, reported",
@@ -124,25 +104,25 @@
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@@ -150,25 +130,25 @@
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@@ -176,25 +156,25 @@
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@@ -202,25 +182,25 @@
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@@ -228,25 +208,25 @@
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@@ -254,25 +234,25 @@
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@@ -280,25 +260,25 @@
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@@ -306,25 +286,25 @@
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@@ -332,25 +312,25 @@
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@@ -358,25 +338,25 @@
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@@ -384,25 +364,25 @@
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@@ -410,25 +390,25 @@
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@@ -2460,28 +2440,28 @@
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@@ -2489,26 +2469,26 @@
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@@ -2516,26 +2496,26 @@
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@@ -2543,26 +2523,26 @@
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@@ -2570,28 +2550,28 @@
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@@ -2599,26 +2579,26 @@
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@@ -2626,26 +2606,26 @@
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@@ -2653,26 +2633,26 @@
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@@ -2680,28 +2660,28 @@
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@@ -2709,26 +2689,26 @@
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@@ -2736,26 +2716,26 @@
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@@ -2763,26 +2743,26 @@
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@@ -2790,28 +2770,28 @@
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@@ -2843,28 +2823,28 @@
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@@ -2896,28 +2876,28 @@
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@@ -2925,26 +2905,26 @@
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@@ -2952,26 +2932,26 @@
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@@ -2979,26 +2959,26 @@
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@@ -3006,28 +2986,28 @@
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@@ -3035,26 +3015,26 @@
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@@ -3062,26 +3042,26 @@
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    "hydra_rqes": 0,
    "infeasible": false,
    "latency_ms": 958.6905598958333,
-   "median_latency_ms": 16.16864686468647,
+   "median_latency_ms": 14.763696369636964,
    "method": "asap-norollup",
-   "milp_solve_secs": 0.071560388,
-   "objective": 0.03474291529794566,
+   "milp_solve_secs": 0.06462501,
+   "objective": 0.03416639112415001,
    "rolled_up_rqes": 0,
    "rqes": 124,
    "sla_ms": 3000.0,
@@ -3089,26 +3069,26 @@
   },
   {
    "active_deployments": 124,
-   "cpu": 2.049516968372388,
+   "cpu": 2.040218599765127,
    "cpu_parts": {
     "compaction": 0.0,
-    "ingest": 1.9252280000000028,
-    "query": 0.12428896837238552
+    "ingest": 1.9160848000000026,
+    "query": 0.12413379976512476
    },
-   "gib": 4.615254931939094,
+   "gib": 4.467521953550475,
    "gib_parts": {
     "compaction": 0.0,
-    "ingest": 0.6649284660816193,
-    "query": 0.0026651852254555722,
-    "storage": 3.947661280632019
+    "ingest": 0.6378368735313416,
+    "query": 0.0026638388310841555,
+    "storage": 3.8270212411880493
    },
    "hydra_rqes": 0,
    "infeasible": false,
    "latency_ms": 958.6905598958333,
-   "median_latency_ms": 16.16864686468647,
+   "median_latency_ms": 14.763696369636964,
    "method": "perquery",
-   "milp_solve_secs": 0.087180406,
-   "objective": 0.10354332166621069,
+   "milp_solve_secs": 0.088878976,
+   "objective": 0.10250932598378726,
    "rolled_up_rqes": 0,
    "rqes": 124,
    "sla_ms": 3000.0,
@@ -3116,28 +3096,28 @@
   },
   {
    "active_deployments": 124,
-   "benchmark_secs_paper_rate": 540.0,
-   "cpu": 12.260760061299113,
+   "benchmark_secs_paper_rate": 420.0,
+   "cpu": 11.577469956031775,
    "cpu_parts": {
     "compaction": 0.0,
-    "ingest": 12.179798399999994,
-    "query": 0.08096166129911817
+    "ingest": 11.496508799999983,
+    "query": 0.08096115603179146
    },
-   "gib": 4.520753770003864,
+   "gib": 4.464861719729754,
    "gib_parts": {
     "compaction": 0.0,
-    "ingest": 3.8749287128448486,
-    "query": 3.6050182075261585e-06,
-    "storage": 0.6458214521408081
+    "ingest": 3.8270212411880493,
+    "query": 3.60501036338317e-06,
+    "storage": 0.6378368735313416
    },
    "hydra_rqes": 0,
    "latency_ms": 490.15722656250006,
    "median_latency_ms": 4.901572265625,
    "meets_sla": true,
    "method": "autosketch",
-   "objective": 0.5166781367591313,
-   "planning_secs": 0.00371294,
-   "probes": 332,
+   "objective": 0.4887561678720843,
+   "planning_secs": 0.004028628,
+   "probes": 276,
    "rolled_up_rqes": 0,
    "rqes": 124,
    "sla_ms": 3000.0,
@@ -3145,26 +3125,26 @@
   },
   {
    "active_deployments": 5,
-   "cpu": 0.2453387738324515,
+   "cpu": 0.2410012749651247,
    "cpu_parts": {
     "compaction": 0.0,
-    "ingest": 0.11865320000000001,
-    "query": 0.1266855738324515
+    "ingest": 0.11458600000000001,
+    "query": 0.1264152749651247
    },
-   "gib": 1.0274441553580245,
+   "gib": 1.014926255091841,
    "gib_parts": {
     "compaction": 0.0,
-    "ingest": 0.216713547706604,
-    "query": 0.0014336420523605052,
-    "storage": 0.8092969655990601
+    "ingest": 0.215931236743927,
+    "query": 0.0014327171890089407,
+    "storage": 0.797562301158905
    },
    "hydra_rqes": 0,
    "infeasible": false,
    "latency_ms": 557.0905598958334,
    "median_latency_ms": 24.64690559895833,
    "method": "asap",
-   "milp_solve_secs": 0.210505922,
-   "objective": 0.014508346831557495,
+   "milp_solve_secs": 0.214408106,
+   "objective": 0.014276973471246242,
    "rolled_up_rqes": 104,
    "rqes": 124,
    "sla_ms": 10000.0,
@@ -3172,26 +3152,26 @@
   },
   {
    "active_deployments": 26,
-   "cpu": 0.5806692567209003,
+   "cpu": 0.5722012856317912,
    "cpu_parts": {
     "compaction": 0.0,
-    "ingest": 0.44888759999999994,
-    "query": 0.13178165672090036
+    "ingest": 0.4405591999999998,
+    "query": 0.1316420856317914
    },
-   "gib": 2.5226540226402685,
+   "gib": 2.470166080014037,
    "gib_parts": {
     "compaction": 0.0,
-    "ingest": 0.1574791893362999,
-    "query": 0.002986993259470107,
-    "storage": 2.3621878400444984
+    "ingest": 0.1541987508535385,
+    "query": 0.0029860663574210267,
+    "storage": 2.3129812628030777
    },
    "hydra_rqes": 0,
    "infeasible": false,
    "latency_ms": 958.6905598958333,
-   "median_latency_ms": 16.16864686468647,
+   "median_latency_ms": 14.763696369636964,
    "method": "asap-norollup",
-   "milp_solve_secs": 0.085083542,
-   "objective": 0.03474291529794566,
+   "milp_solve_secs": 0.070345763,
+   "objective": 0.03416639112415001,
    "rolled_up_rqes": 0,
    "rqes": 124,
    "sla_ms": 10000.0,
@@ -3199,26 +3179,26 @@
   },
   {
    "active_deployments": 124,
-   "cpu": 2.049516968372388,
+   "cpu": 2.040218599765127,
    "cpu_parts": {
     "compaction": 0.0,
-    "ingest": 1.9252280000000028,
-    "query": 0.12428896837238552
+    "ingest": 1.9160848000000026,
+    "query": 0.12413379976512476
    },
-   "gib": 4.615254931939094,
+   "gib": 4.467521953550475,
    "gib_parts": {
     "compaction": 0.0,
-    "ingest": 0.6649284660816193,
-    "query": 0.0026651852254555722,
-    "storage": 3.947661280632019
+    "ingest": 0.6378368735313416,
+    "query": 0.0026638388310841555,
+    "storage": 3.8270212411880493
    },
    "hydra_rqes": 0,
    "infeasible": false,
    "latency_ms": 958.6905598958333,
-   "median_latency_ms": 16.16864686468647,
+   "median_latency_ms": 14.763696369636964,
    "method": "perquery",
-   "milp_solve_secs": 0.091291158,
-   "objective": 0.10354332166621069,
+   "milp_solve_secs": 0.09137734,
+   "objective": 0.10250932598378726,
    "rolled_up_rqes": 0,
    "rqes": 124,
    "sla_ms": 10000.0,
@@ -3226,28 +3206,28 @@
   },
   {
    "active_deployments": 124,
-   "benchmark_secs_paper_rate": 540.0,
-   "cpu": 12.260760061299113,
+   "benchmark_secs_paper_rate": 420.0,
+   "cpu": 11.577469956031775,
    "cpu_parts": {
     "compaction": 0.0,
-    "ingest": 12.179798399999994,
-    "query": 0.08096166129911817
+    "ingest": 11.496508799999983,
+    "query": 0.08096115603179146
    },
-   "gib": 4.520753770003864,
+   "gib": 4.464861719729754,
    "gib_parts": {
     "compaction": 0.0,
-    "ingest": 3.8749287128448486,
-    "query": 3.6050182075261585e-06,
-    "storage": 0.6458214521408081
+    "ingest": 3.8270212411880493,
+    "query": 3.60501036338317e-06,
+    "storage": 0.6378368735313416
    },
    "hydra_rqes": 0,
    "latency_ms": 490.15722656250006,
    "median_latency_ms": 4.901572265625,
    "meets_sla": true,
    "method": "autosketch",
-   "objective": 0.5166781367591313,
-   "planning_secs": 0.00371294,
-   "probes": 332,
+   "objective": 0.4887561678720843,
+   "planning_secs": 0.004028628,
+   "probes": 276,
    "rolled_up_rqes": 0,
    "rqes": 124,
    "sla_ms": 10000.0,
diff --git a/rqe-optimizer/results/autosketch-vs-asap-inputs/README.md b/rqe-optimizer/results/autosketch-vs-asap-inputs/README.md
index fb40de59..353d43c5 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-inputs/README.md
+++ b/rqe-optimizer/results/autosketch-vs-asap-inputs/README.md
@@ -15,6 +15,11 @@ and `../autosketch-vs-asap-synthetic-sla/`), as run on 2026-10-08.
     including the cost table's shape (Zipf 1.1 over 1e4 keys; Pareto a = 2),
     with merge curves for the sketches that lose accuracy when merged;
   - `out_1e9/`: the targeted points past 1e7 that the workloads read.
+- #213 (2026-10-14) appended the denser grid's new configs to both curve
+  directories: KLL `k` ∈ {25, 100, 400} and DDSketch α = 0.1, measured alone
+  (`study_saturation.py --sketches/--configs`) and merged with
+  `scripts/merge_study_parts.py`, which refuses a point measured twice. Their
+  raw records are `raw/dense_*`.
 - `tables/`: the synthetic mixed-set workloads from
   `scripts/export_autosketch_eval_table.py --synthetic` (RQEs, streams,
   targets, data shapes) and `plan.tsv` (one run per table).
diff --git a/rqe-optimizer/results/autosketch-vs-asap-inputs/raw/README.md b/rqe-optimizer/results/autosketch-vs-asap-inputs/raw/README.md
index 40c52c3e..e26b7d99 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-inputs/raw/README.md
+++ b/rqe-optimizer/results/autosketch-vs-asap-inputs/raw/README.md
@@ -29,3 +29,23 @@ Every accuracy run is `study_saturation.py --phase accuracy --seeds 3` plus:
 
 Run times are each file's first-to-last record timestamps; the refills ran
 about 40 minutes after their grids and are counted separately.
+
+## The denser grid (#213, 2026-10-14)
+
+Only the new configs, with the same arguments as the rows above plus
+`--sketches`/`--configs`; accuracy runs on clnode130, cost rows serially on
+idle clnode138.
+
+| File | Arguments | Feeds |
+|---|---|---|
+| `dense_grid_q.saturation_accuracy.jsonl.gz` | as `grid_quantile`, `--sketches kll-percall,dd --configs k=25,k=100,k=400,alpha=0.1` | `out_grid_1e7_cost/` |
+| `dense_kll_a2…`, `dense_kll_a3…` | as `kll_a2`, `kll_a3`, `--sketches kll-percall --configs k=25,k=100,k=400` | `out_1e9/` |
+| `dense_dd_a2…`, `dense_dd_a3…` | as `dd_a2`, `dd_a3`, `--sketches dd --configs alpha=0.1` | `out_1e9/` |
+| `dense_optimizer_cost_q.rqe_atomic_costs_raw.jsonl.gz` | `--phase optimizer-cost --seeds 3 --families quantile --sketches kll-percall,dd --configs k=25,k=100,k=400,alpha=0.1` | the cost table's 4 new rows |
+| `dense_optimizer_cost_h.rqe_atomic_costs_raw.jsonl.gz` | `--phase optimizer-cost --seeds 3 --families hydra --sketches hydra-hll,hydra-kll --hydra-variants hydra-hll,hydra-kll --hydra-ws 65536` (4-shard merges) | the cost table's 3 new Hydra rows |
+
+The Hydra W = 65536 accuracy rows (999 runs, `--phase hydra --hydra-sweeps eval
+--hydra-ws 65536 --hydra-variants hydra-hll,hydra-kll --hydra-shard i/4` on
+clnode109/155/167/178) are appended to
+`../../autosketch-vs-asap-hydra/inputs/saturation/hydra_saturation.csv`.
+
diff --git a/rqe-optimizer/results/autosketch-vs-asap-inputs/raw/dense_dd_a2.saturation_accuracy.jsonl.gz b/rqe-optimizer/results/autosketch-vs-asap-inputs/raw/dense_dd_a2.saturation_accuracy.jsonl.gz
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-inputs/raw/dense_kll_a2.saturation_accuracy.jsonl.gz b/rqe-optimizer/results/autosketch-vs-asap-inputs/raw/dense_kll_a2.saturation_accuracy.jsonl.gz
new file mode 100644
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-inputs/raw/dense_optimizer_cost_q.rqe_atomic_costs_raw.jsonl.gz b/rqe-optimizer/results/autosketch-vs-asap-inputs/raw/dense_optimizer_cost_q.rqe_atomic_costs_raw.jsonl.gz
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_1e9/saturation.csv b/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_1e9/saturation.csv
index d5f0d179..137394d8 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_1e9/saturation.csv
+++ b/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_1e9/saturation.csv
@@ -21,3 +21,11 @@ quantile,dd,alpha=0.005,pareto,3.0,,1000,0.0024845866734421245,mean_relative_val
 quantile,dd,alpha=0.01,pareto,3.0,,1000,0.005007220316037436,mean_relative_value_error,,,,
 quantile,dd,alpha=0.02,pareto,3.0,,1000,0.009765569868380548,mean_relative_value_error,,,,
 quantile,dd,alpha=0.05,pareto,3.0,,1000,0.024532785099746105,mean_relative_value_error,,,,
+quantile,kll-percall,k=25,pareto,2.0,,177828,0.021037581876412362,mean_rank_err,,,,
+quantile,kll-percall,k=100,pareto,2.0,,3162278,0.005018398557528588,mean_rank_err,,,,
+quantile,kll-percall,k=400,pareto,2.0,,not_saturated,0.0013976790339836655,mean_rank_err,,,,
+quantile,kll-percall,k=25,pareto,3.0,,31622777,0.018219169080907604,mean_rank_err,,,,
+quantile,kll-percall,k=100,pareto,3.0,,not_saturated,0.006330232515384681,mean_rank_err,,,,
+quantile,kll-percall,k=400,pareto,3.0,,not_saturated,0.0008376651920667641,mean_rank_err,,,,
+quantile,dd,alpha=0.1,pareto,2.0,,1000,0.04837114085833779,mean_relative_value_error,,,,
+quantile,dd,alpha=0.1,pareto,3.0,,1000,0.04790406646749001,mean_relative_value_error,,,,
diff --git a/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_1e9/saturation_curve.csv b/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_1e9/saturation_curve.csv
index 7e6d992f..df577a58 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_1e9/saturation_curve.csv
+++ b/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_1e9/saturation_curve.csv
@@ -493,3 +493,171 @@ quantile,dd,alpha=0.05,pareto,3.0,,56234133,0.02453459431054833,9.00989506916387
 quantile,dd,alpha=0.05,pareto,3.0,,100000000,0.024529602734025113,2.330330399161457e-06
 quantile,dd,alpha=0.05,pareto,3.0,,177827941,0.024532286264359455,3.3530398959089658e-06
 quantile,dd,alpha=0.05,pareto,3.0,,316227766,0.024532785099746105,2.45937547900963e-06
+quantile,kll-percall,k=25,pareto,2.0,,1000,0.01849504950495049,0.0013163601230159851
+quantile,kll-percall,k=25,pareto,2.0,,1778,0.018888876514198107,0.00216595134171788
+quantile,kll-percall,k=25,pareto,2.0,,3162,0.018296812603461485,0.002740830336767253
+quantile,kll-percall,k=25,pareto,2.0,,5623,0.0266839577430978,0.005437023534165254
+quantile,kll-percall,k=25,pareto,2.0,,10000,0.025872607260726075,0.002061402175217592
+quantile,kll-percall,k=25,pareto,2.0,,17783,0.023333778747047507,0.00224033433235879
+quantile,kll-percall,k=25,pareto,2.0,,31623,0.025052355154877973,0.0006740900797869597
+quantile,kll-percall,k=25,pareto,2.0,,56234,0.020705924595375926,0.004187786537372281
+quantile,kll-percall,k=25,pareto,2.0,,100000,0.016114686468646864,0.0011591836688819319
+quantile,kll-percall,k=25,pareto,2.0,,177828,0.017763685471725525,0.0011385552586071761
+quantile,kll-percall,k=25,pareto,2.0,,316228,0.027737448156948712,0.004304416582044165
+quantile,kll-percall,k=25,pareto,2.0,,562341,0.018101541256784027,0.0019586795830258113
+quantile,kll-percall,k=25,pareto,2.0,,1000000,0.0197743201320132,0.0026002626547492152
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+quantile,kll-percall,k=400,pareto,3.0,,1000000,0.0008566765676567657,5.268697132252204e-05
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+quantile,kll-percall,k=400,pareto,3.0,,316227766,0.0008376651920667641,7.367554965069229e-05
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+quantile,dd,alpha=0.1,pareto,2.0,,1778,0.04879801440596865,0.0005839216116838237
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+quantile,dd,alpha=0.1,pareto,3.0,,10000000,0.047907961496741557,5.862788126295711e-06
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+quantile,dd,alpha=0.1,pareto,3.0,,31622777,0.047902170806603916,7.4870657015191175e-06
+quantile,dd,alpha=0.1,pareto,3.0,,56234133,0.04789881567773546,3.6609499643166115e-06
+quantile,dd,alpha=0.1,pareto,3.0,,100000000,0.047910686099160375,2.8885801860708874e-06
+quantile,dd,alpha=0.1,pareto,3.0,,177827941,0.04790505136820932,4.942407342018589e-06
+quantile,dd,alpha=0.1,pareto,3.0,,316227766,0.04790406646749001,7.2913552106492534e-06
diff --git a/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_1e9/saturation_merge_curve.csv b/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_1e9/saturation_merge_curve.csv
index 62a27291..c0f72c36 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_1e9/saturation_merge_curve.csv
+++ b/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_1e9/saturation_merge_curve.csv
@@ -1121,3 +1121,1125 @@ quantile,kll-percall,k=800,pareto,3.0,,316227766,256,0.00033653064646275494,4.08
 quantile,kll-percall,k=800,pareto,3.0,,316227766,1024,0.000449404844794719,9.424668130001135e-05
 quantile,kll-percall,k=800,pareto,3.0,,316227766,3600,0.00037699261949498806,4.7339997931694936e-05
 quantile,kll-percall,k=800,pareto,3.0,,316227766,4096,0.0003684441459669862,4.028242796860756e-05
+quantile,kll-percall,k=25,pareto,2.0,,1000,1,0.01849504950495049,0.0013163601230159851
+quantile,kll-percall,k=25,pareto,2.0,,1000,4,0.025732673267326714,0.0012835823192293588
+quantile,kll-percall,k=25,pareto,2.0,,1000,16,0.021379537953795366,0.0021405865285748565
+quantile,kll-percall,k=25,pareto,2.0,,1000,64,0.025452145214521438,0.0048213326256549595
+quantile,kll-percall,k=25,pareto,2.0,,1000,256,0.020422442244224414,0.0023747955837116427
+quantile,kll-percall,k=25,pareto,2.0,,1000,1024,0.020514851485148505,0.0017220134135325388
+quantile,kll-percall,k=25,pareto,2.0,,1000,4096,0.021643564356435625,0.0031816910378508526
+quantile,kll-percall,k=25,pareto,2.0,,1000,16384,0.030115511551155095,0.0007997633324186309
+quantile,kll-percall,k=25,pareto,2.0,,1000,65536,0.029587458745874578,0.007497887890758386
+quantile,kll-percall,k=25,pareto,2.0,,1000,86400,0.021115511551155094,0.0029345836127256915
+quantile,kll-percall,k=25,pareto,2.0,,1778,1,0.018888876514198107,0.00216595134171788
+quantile,kll-percall,k=25,pareto,2.0,,1778,4,0.023177709221990816,0.004220129443932733
+quantile,kll-percall,k=25,pareto,2.0,,1778,16,0.02187524826723392,0.004302126411554758
+quantile,kll-percall,k=25,pareto,2.0,,1778,64,0.026575230076438472,0.0035464191649236974
+quantile,kll-percall,k=25,pareto,2.0,,1778,256,0.014994709819688382,0.0012836956749214768
+quantile,kll-percall,k=25,pareto,2.0,,1778,1024,0.018600459596015848,0.0005434667281896066
+quantile,kll-percall,k=25,pareto,2.0,,1778,4096,0.02392420006905077,0.0037427562465290986
+quantile,kll-percall,k=25,pareto,2.0,,1778,16384,0.02018398690262727,0.0024119663815017063
+quantile,kll-percall,k=25,pareto,2.0,,1778,65536,0.028682763664442928,0.006019327305903568
+quantile,kll-percall,k=25,pareto,2.0,,1778,86400,0.022415663388611073,0.0039972327506989525
+quantile,kll-percall,k=25,pareto,2.0,,3162,1,0.018296812603461485,0.002740830336767253
+quantile,kll-percall,k=25,pareto,2.0,,3162,4,0.014068152545804869,0.00041733746296122664
+quantile,kll-percall,k=25,pareto,2.0,,3162,16,0.017921397452838262,0.0013292287226628135
+quantile,kll-percall,k=25,pareto,2.0,,3162,64,0.023099241612965848,0.0052127942857269054
+quantile,kll-percall,k=25,pareto,2.0,,3162,256,0.015594800466763946,0.001012130120294926
+quantile,kll-percall,k=25,pareto,2.0,,3162,1024,0.021562448464960346,0.00029864331005145344
+quantile,kll-percall,k=25,pareto,2.0,,3162,4096,0.015552236438065055,0.001421839851193135
+quantile,kll-percall,k=25,pareto,2.0,,3162,16384,0.01811517963940607,0.000500298882611196
+quantile,kll-percall,k=25,pareto,2.0,,3162,65536,0.019198652313049142,0.002207949576987375
+quantile,kll-percall,k=25,pareto,2.0,,3162,86400,0.017644052830330468,0.0027803412853683322
+quantile,kll-percall,k=25,pareto,2.0,,5623,1,0.0266839577430978,0.005437023534165254
+quantile,kll-percall,k=25,pareto,2.0,,5623,4,0.018365271348404624,0.0009766121851907622
+quantile,kll-percall,k=25,pareto,2.0,,5623,16,0.021306544490479636,0.004056216922762774
+quantile,kll-percall,k=25,pareto,2.0,,5623,64,0.01859957541192497,0.002531957218368759
+quantile,kll-percall,k=25,pareto,2.0,,5623,256,0.018634163434127514,0.0007983404947131182
+quantile,kll-percall,k=25,pareto,2.0,,5623,1024,0.0222913493554584,0.006282945051435586
+quantile,kll-percall,k=25,pareto,2.0,,5623,4096,0.01808423559766611,0.002084318106777067
+quantile,kll-percall,k=25,pareto,2.0,,5623,16384,0.0209601301584898,0.0032766948825232183
+quantile,kll-percall,k=25,pareto,2.0,,5623,65536,0.020309261408089946,0.0024622639850043265
+quantile,kll-percall,k=25,pareto,2.0,,5623,86400,0.017550618657811008,0.0016039393462838603
+quantile,kll-percall,k=25,pareto,2.0,,10000,1,0.025872607260726075,0.002061402175217592
+quantile,kll-percall,k=25,pareto,2.0,,10000,4,0.01725511551155116,0.00042368885783618146
+quantile,kll-percall,k=25,pareto,2.0,,10000,16,0.02251815181518152,0.0022121856671734287
+quantile,kll-percall,k=25,pareto,2.0,,10000,64,0.019464686468646866,0.0009633584221406443
+quantile,kll-percall,k=25,pareto,2.0,,10000,256,0.025213861386138615,0.004739632089300524
+quantile,kll-percall,k=25,pareto,2.0,,10000,1024,0.021645874587458747,0.0016172982026326234
+quantile,kll-percall,k=25,pareto,2.0,,10000,4096,0.019159405940594062,0.0006287224863483426
+quantile,kll-percall,k=25,pareto,2.0,,10000,16384,0.022162376237623762,0.0007852186385309382
+quantile,kll-percall,k=25,pareto,2.0,,10000,65536,0.02497821782178218,0.0034806547310990083
+quantile,kll-percall,k=25,pareto,2.0,,10000,86400,0.02125808580858085,0.0031996939151502746
+quantile,kll-percall,k=25,pareto,2.0,,17783,1,0.023333778747047507,0.00224033433235879
+quantile,kll-percall,k=25,pareto,2.0,,17783,4,0.01853842315008086,0.0007703775836345264
+quantile,kll-percall,k=25,pareto,2.0,,17783,16,0.023846817398379332,0.003358007453901617
+quantile,kll-percall,k=25,pareto,2.0,,17783,64,0.023635290425516698,0.004776193513478754
+quantile,kll-percall,k=25,pareto,2.0,,17783,256,0.02278654531370024,0.0024050665106373843
+quantile,kll-percall,k=25,pareto,2.0,,17783,1024,0.019913207426011676,0.002441267542357342
+quantile,kll-percall,k=25,pareto,2.0,,17783,4096,0.016659996596296873,0.0010082450322287013
+quantile,kll-percall,k=25,pareto,2.0,,17783,16384,0.025426582921464835,0.0020143261811769123
+quantile,kll-percall,k=25,pareto,2.0,,17783,65536,0.020038955141085717,0.002246832519104237
+quantile,kll-percall,k=25,pareto,2.0,,17783,86400,0.019464119048692805,0.00258034656478524
+quantile,kll-percall,k=25,pareto,2.0,,31623,1,0.025052355154877973,0.0006740900797869597
+quantile,kll-percall,k=25,pareto,2.0,,31623,4,0.027575543722667493,0.00664303827989772
+quantile,kll-percall,k=25,pareto,2.0,,31623,16,0.015931603026539256,0.001981516003987543
+quantile,kll-percall,k=25,pareto,2.0,,31623,64,0.022425407041225896,0.003600833546214377
+quantile,kll-percall,k=25,pareto,2.0,,31623,256,0.017010504010272005,0.002669106568887947
+quantile,kll-percall,k=25,pareto,2.0,,31623,1024,0.02913073880198949,0.0034830406224217996
+quantile,kll-percall,k=25,pareto,2.0,,31623,4096,0.025269931888360072,0.0064398691577200054
+quantile,kll-percall,k=25,pareto,2.0,,31623,16384,0.020472335536371213,0.00047705034118534714
+quantile,kll-percall,k=25,pareto,2.0,,31623,65536,0.021517115472101247,0.004521788333805245
+quantile,kll-percall,k=25,pareto,2.0,,31623,86400,0.01578804394052914,0.0016568112526750471
+quantile,kll-percall,k=25,pareto,2.0,,56234,1,0.020705924595375926,0.004187786537372281
+quantile,kll-percall,k=25,pareto,2.0,,56234,4,0.021105579455765397,0.002641196710617246
+quantile,kll-percall,k=25,pareto,2.0,,56234,16,0.01809880707101902,4.757222437197747e-05
+quantile,kll-percall,k=25,pareto,2.0,,56234,64,0.017301280328978947,0.0028305604129455755
+quantile,kll-percall,k=25,pareto,2.0,,56234,256,0.022249183662186686,0.0017028821234889332
+quantile,kll-percall,k=25,pareto,2.0,,56234,1024,0.019348427498438573,0.0039712322659592285
+quantile,kll-percall,k=25,pareto,2.0,,56234,4096,0.02053623408362817,0.0020094815585423404
+quantile,kll-percall,k=25,pareto,2.0,,56234,16384,0.028548424070987677,0.00825595738394375
+quantile,kll-percall,k=25,pareto,2.0,,56234,65536,0.029839387537999806,0.0027673403760800196
+quantile,kll-percall,k=25,pareto,2.0,,56234,86400,0.0200218476519203,0.00285023754906197
+quantile,kll-percall,k=25,pareto,2.0,,100000,1,0.016114686468646864,0.0011591836688819319
+quantile,kll-percall,k=25,pareto,2.0,,100000,4,0.016401353135313535,0.001100508380401929
+quantile,kll-percall,k=25,pareto,2.0,,100000,16,0.021667260726072602,0.0019415722145279153
+quantile,kll-percall,k=25,pareto,2.0,,100000,64,0.018685445544554452,0.0008093722462481397
+quantile,kll-percall,k=25,pareto,2.0,,100000,256,0.01626788778877888,0.000588347038573357
+quantile,kll-percall,k=25,pareto,2.0,,100000,1024,0.01877046204620462,0.0028366318238973237
+quantile,kll-percall,k=25,pareto,2.0,,100000,4096,0.019619537953795382,0.001058286948490037
+quantile,kll-percall,k=25,pareto,2.0,,100000,16384,0.02129227722772278,0.00312997811238692
+quantile,kll-percall,k=25,pareto,2.0,,100000,65536,0.021198415841584158,0.00435071302167971
+quantile,kll-percall,k=25,pareto,2.0,,100000,86400,0.02006313531353135,0.0015013170337335913
+quantile,kll-percall,k=25,pareto,2.0,,177828,1,0.017763685471725525,0.0011385552586071761
+quantile,kll-percall,k=25,pareto,2.0,,177828,4,0.018143316592270604,0.0023964092510626676
+quantile,kll-percall,k=25,pareto,2.0,,177828,16,0.019038542156395267,0.0017173644938997868
+quantile,kll-percall,k=25,pareto,2.0,,177828,64,0.0172490182414557,0.0014413843809789042
+quantile,kll-percall,k=25,pareto,2.0,,177828,256,0.021591888657790808,0.00205650463183398
+quantile,kll-percall,k=25,pareto,2.0,,177828,1024,0.022067653016735644,0.006472681867272843
+quantile,kll-percall,k=25,pareto,2.0,,177828,4096,0.018204093977114828,0.0011753612491032697
+quantile,kll-percall,k=25,pareto,2.0,,177828,16384,0.020270398859846845,0.001681249193054621
+quantile,kll-percall,k=25,pareto,2.0,,177828,65536,0.02259572957768143,0.006146081310206339
+quantile,kll-percall,k=25,pareto,2.0,,177828,86400,0.01624336298263067,0.00200071095335496
+quantile,kll-percall,k=25,pareto,2.0,,316228,1,0.027737448156948712,0.004304416582044165
+quantile,kll-percall,k=25,pareto,2.0,,316228,4,0.01894056930390409,0.0012781958487989833
+quantile,kll-percall,k=25,pareto,2.0,,316228,16,0.019506359429598174,0.001435315707928531
+quantile,kll-percall,k=25,pareto,2.0,,316228,64,0.017048224093315134,0.001448174642456587
+quantile,kll-percall,k=25,pareto,2.0,,316228,256,0.01879527830339733,0.001287361892737761
+quantile,kll-percall,k=25,pareto,2.0,,316228,1024,0.0240160963362233,0.000866037290557924
+quantile,kll-percall,k=25,pareto,2.0,,316228,4096,0.021820956271221947,0.0031006709619701136
+quantile,kll-percall,k=25,pareto,2.0,,316228,16384,0.02577535463300051,0.006245942715711217
+quantile,kll-percall,k=25,pareto,2.0,,316228,65536,0.01943428626986811,0.001026355933171436
+quantile,kll-percall,k=25,pareto,2.0,,316228,86400,0.02880714132356606,0.004561369680308303
+quantile,kll-percall,k=25,pareto,2.0,,562341,1,0.018101541256784027,0.0019586795830258113
+quantile,kll-percall,k=25,pareto,2.0,,562341,4,0.018713298250501286,0.001752958613378695
+quantile,kll-percall,k=25,pareto,2.0,,562341,16,0.019367170383087908,0.002201511719600193
+quantile,kll-percall,k=25,pareto,2.0,,562341,64,0.02619242063659118,0.005264784235328293
+quantile,kll-percall,k=25,pareto,2.0,,562341,256,0.020074190035956656,0.0003992112274276659
+quantile,kll-percall,k=25,pareto,2.0,,562341,1024,0.021595906335046582,0.002835377551246985
+quantile,kll-percall,k=25,pareto,2.0,,562341,4096,0.01884493290697563,0.0021815540940154613
+quantile,kll-percall,k=25,pareto,2.0,,562341,16384,0.025406739775590284,0.0019774024681572847
+quantile,kll-percall,k=25,pareto,2.0,,562341,65536,0.025000639212587272,0.0023487272161303177
+quantile,kll-percall,k=25,pareto,2.0,,562341,86400,0.017193084099524244,0.001179184033674721
+quantile,kll-percall,k=25,pareto,2.0,,1000000,1,0.0197743201320132,0.0026002626547492152
+quantile,kll-percall,k=25,pareto,2.0,,1000000,4,0.02044617821782178,0.0009660181581561479
+quantile,kll-percall,k=25,pareto,2.0,,1000000,16,0.021635006600660072,0.0028632719591643995
+quantile,kll-percall,k=25,pareto,2.0,,1000000,64,0.027132432343234324,0.006411340175690602
+quantile,kll-percall,k=25,pareto,2.0,,1000000,256,0.02014967656765677,0.003105677793675017
+quantile,kll-percall,k=25,pareto,2.0,,1000000,1024,0.02794889108910892,0.0035538487706474288
+quantile,kll-percall,k=25,pareto,2.0,,1000000,4096,0.016702547854785477,0.0017216093399921421
+quantile,kll-percall,k=25,pareto,2.0,,1000000,16384,0.017868297029702974,0.0029019236691495563
+quantile,kll-percall,k=25,pareto,2.0,,1000000,65536,0.015434782178217817,0.0015205078216554671
+quantile,kll-percall,k=25,pareto,2.0,,1000000,86400,0.018457561056105614,0.00468072946355517
+quantile,kll-percall,k=25,pareto,2.0,,1778279,1,0.02410264660215281,0.0034207810014537576
+quantile,kll-percall,k=25,pareto,2.0,,1778279,4,0.02233308125774448,0.000915796210867699
+quantile,kll-percall,k=25,pareto,2.0,,1778279,16,0.01908964518420048,0.0047362018347092
+quantile,kll-percall,k=25,pareto,2.0,,1778279,64,0.0211304962397758,0.004525055993165642
+quantile,kll-percall,k=25,pareto,2.0,,1778279,256,0.01878439471728866,0.003957089729123466
+quantile,kll-percall,k=25,pareto,2.0,,1778279,1024,0.025215428677799922,0.005937884624516237
+quantile,kll-percall,k=25,pareto,2.0,,1778279,4096,0.01569998865870496,0.0018507295397458862
+quantile,kll-percall,k=25,pareto,2.0,,1778279,16384,0.01800766010023148,0.001170291463793272
+quantile,kll-percall,k=25,pareto,2.0,,1778279,65536,0.024858957051806112,0.00018619315165521494
+quantile,kll-percall,k=25,pareto,2.0,,1778279,86400,0.017876401512890047,0.0015113615058669969
+quantile,kll-percall,k=25,pareto,2.0,,3162278,1,0.01840451946245702,0.0026042207073947448
+quantile,kll-percall,k=25,pareto,2.0,,3162278,4,0.014232515910111225,0.00022289151420515222
+quantile,kll-percall,k=25,pareto,2.0,,3162278,16,0.02147389646420596,0.006086875049259655
+quantile,kll-percall,k=25,pareto,2.0,,3162278,64,0.018247681632740015,0.002219933809893205
+quantile,kll-percall,k=25,pareto,2.0,,3162278,256,0.020336808959982786,0.0035199731086534617
+quantile,kll-percall,k=25,pareto,2.0,,3162278,1024,0.015430171545070146,0.002128507038324917
+quantile,kll-percall,k=25,pareto,2.0,,3162278,4096,0.01875234331272286,0.0004455236904459832
+quantile,kll-percall,k=25,pareto,2.0,,3162278,16384,0.01979460582992813,0.0036152069537529015
+quantile,kll-percall,k=25,pareto,2.0,,3162278,65536,0.022186474120839784,0.004675283271782067
+quantile,kll-percall,k=25,pareto,2.0,,3162278,86400,0.023695068886892604,0.005710632136862706
+quantile,kll-percall,k=25,pareto,2.0,,5623413,1,0.017371619581584823,0.0015186611954321298
+quantile,kll-percall,k=25,pareto,2.0,,5623413,4,0.017543147596917694,0.001902955165437072
+quantile,kll-percall,k=25,pareto,2.0,,5623413,16,0.018968612403918828,0.0006713305243421987
+quantile,kll-percall,k=25,pareto,2.0,,5623413,64,0.024431517925422013,0.0015924477494973432
+quantile,kll-percall,k=25,pareto,2.0,,5623413,256,0.02873421279489476,0.004173945233924692
+quantile,kll-percall,k=25,pareto,2.0,,5623413,1024,0.018296206716396254,0.0005914305463639901
+quantile,kll-percall,k=25,pareto,2.0,,5623413,4096,0.0179692727084379,0.0031824691147186897
+quantile,kll-percall,k=25,pareto,2.0,,5623413,16384,0.02099028525386576,0.003411347512733595
+quantile,kll-percall,k=25,pareto,2.0,,5623413,65536,0.023699738062189557,0.003041456815371185
+quantile,kll-percall,k=25,pareto,2.0,,5623413,86400,0.0207441570993044,0.0039098607007624665
+quantile,kll-percall,k=25,pareto,2.0,,10000000,1,0.01906626402640264,0.0006173444314025458
+quantile,kll-percall,k=25,pareto,2.0,,10000000,4,0.019123254455445552,0.0006180884127088195
+quantile,kll-percall,k=25,pareto,2.0,,10000000,16,0.02578861320132013,0.0025291253134224366
+quantile,kll-percall,k=25,pareto,2.0,,10000000,64,0.028385615511551162,0.00487348337801791
+quantile,kll-percall,k=25,pareto,2.0,,10000000,256,0.021534262706270624,0.00498059093016087
+quantile,kll-percall,k=25,pareto,2.0,,10000000,1024,0.020576325082508253,0.0015506896181061598
+quantile,kll-percall,k=25,pareto,2.0,,10000000,4096,0.022169254455445542,0.0009505812388368525
+quantile,kll-percall,k=25,pareto,2.0,,10000000,16384,0.020788267326732664,0.0022989838564834086
+quantile,kll-percall,k=25,pareto,2.0,,10000000,65536,0.021919184488448845,0.0020213906547081367
+quantile,kll-percall,k=25,pareto,2.0,,10000000,86400,0.02103215280528052,0.0007300837143993475
+quantile,kll-percall,k=25,pareto,2.0,,17782794,1,0.017360257128527175,0.0019410483791542437
+quantile,kll-percall,k=25,pareto,2.0,,17782794,4,0.021264076845956565,0.0002846120895899259
+quantile,kll-percall,k=25,pareto,2.0,,17782794,16,0.018487032923612298,0.00023901457849444856
+quantile,kll-percall,k=25,pareto,2.0,,17782794,64,0.018577581502911656,0.0008163609181031596
+quantile,kll-percall,k=25,pareto,2.0,,17782794,256,0.01733844290991926,0.0016290442764138626
+quantile,kll-percall,k=25,pareto,2.0,,17782794,1024,0.022958172037554733,0.0022825878677143452
+quantile,kll-percall,k=25,pareto,2.0,,17782794,4096,0.023448266012552125,0.0025691615412131866
+quantile,kll-percall,k=25,pareto,2.0,,17782794,16384,0.025702839672006,0.001672155982403143
+quantile,kll-percall,k=25,pareto,2.0,,17782794,65536,0.020144278318534294,0.0017462077817376976
+quantile,kll-percall,k=25,pareto,2.0,,17782794,86400,0.02303315218418693,0.0025888478747428363
+quantile,kll-percall,k=25,pareto,2.0,,31622777,1,0.021037581876412362,0.0012500232501003422
+quantile,kll-percall,k=25,pareto,2.0,,31622777,4,0.02013540622501578,0.0005819374212652783
+quantile,kll-percall,k=25,pareto,2.0,,31622777,16,0.022971784026569086,0.0036411837905186385
+quantile,kll-percall,k=25,pareto,2.0,,31622777,64,0.023502299545822693,0.004666139967648592
+quantile,kll-percall,k=25,pareto,2.0,,31622777,256,0.022054224184685934,0.0037468396869664257
+quantile,kll-percall,k=25,pareto,2.0,,31622777,1024,0.025703565628040704,0.0010948252783512232
+quantile,kll-percall,k=25,pareto,2.0,,31622777,4096,0.020634057848050266,0.000989446566634142
+quantile,kll-percall,k=25,pareto,2.0,,31622777,16384,0.01926852139565483,0.0022006808549172954
+quantile,kll-percall,k=25,pareto,2.0,,31622777,65536,0.026629614362067466,0.008763664918179374
+quantile,kll-percall,k=25,pareto,2.0,,31622777,86400,0.022309057992395714,0.0018384091177549647
+quantile,kll-percall,k=100,pareto,2.0,,1000,1,0.0035181518151815206,0.0003450857656384679
+quantile,kll-percall,k=100,pareto,2.0,,1000,4,0.004844884488448848,0.0006777499128701017
+quantile,kll-percall,k=100,pareto,2.0,,1000,16,0.005511551155115515,0.0006947723849623664
+quantile,kll-percall,k=100,pareto,2.0,,1000,64,0.006264026402640268,0.0016169899551810672
+quantile,kll-percall,k=100,pareto,2.0,,1000,256,0.0049042904290429075,0.0008377964332423972
+quantile,kll-percall,k=100,pareto,2.0,,1000,1024,0.0038910891089108932,0.000698166077878396
+quantile,kll-percall,k=100,pareto,2.0,,1000,4096,0.004429042904290432,0.0006168439555415397
+quantile,kll-percall,k=100,pareto,2.0,,1000,16384,0.004719471947194722,0.00039737124858600593
+quantile,kll-percall,k=100,pareto,2.0,,1000,65536,0.003594059405940596,0.00043993535512380327
+quantile,kll-percall,k=100,pareto,2.0,,1000,86400,0.004204620462046207,0.0006203567075808113
+quantile,kll-percall,k=100,pareto,2.0,,1778,1,0.006385785935173941,0.001227207384651351
+quantile,kll-percall,k=100,pareto,2.0,,1778,4,0.005736448785485973,0.00040303112567731186
+quantile,kll-percall,k=100,pareto,2.0,,1778,16,0.004310364669762812,0.0005993558727300302
+quantile,kll-percall,k=100,pareto,2.0,,1778,64,0.0045323666224890225,0.0009328143411925359
+quantile,kll-percall,k=100,pareto,2.0,,1778,256,0.00460175151373405,0.0003569859542729296
+quantile,kll-percall,k=100,pareto,2.0,,1778,1024,0.005498483481643998,0.001129613753613313
+quantile,kll-percall,k=100,pareto,2.0,,1778,4096,0.005906699781339214,0.0009091200709844801
+quantile,kll-percall,k=100,pareto,2.0,,1778,16384,0.004927589496857446,0.00015567940239589475
+quantile,kll-percall,k=100,pareto,2.0,,1778,65536,0.005490241937579581,0.0006753046349755076
+quantile,kll-percall,k=100,pareto,2.0,,1778,86400,0.006794930336678213,0.0008150266659108927
+quantile,kll-percall,k=100,pareto,2.0,,3162,1,0.0066916957350384,0.00026432323430634924
+quantile,kll-percall,k=100,pareto,2.0,,3162,4,0.004503812810123521,0.0008942332338070251
+quantile,kll-percall,k=100,pareto,2.0,,3162,16,0.004366622620516318,0.00046890221251994163
+quantile,kll-percall,k=100,pareto,2.0,,3162,64,0.00575933684450039,0.0010810466975296877
+quantile,kll-percall,k=100,pareto,2.0,,3162,256,0.004077024400732292,0.00038139015907477403
+quantile,kll-percall,k=100,pareto,2.0,,3162,1024,0.004808587120571643,0.000775136472022824
+quantile,kll-percall,k=100,pareto,2.0,,3162,4096,0.004922480862887044,0.0005727108797008017
+quantile,kll-percall,k=100,pareto,2.0,,3162,16384,0.004612988813112811,0.00010718926029554691
+quantile,kll-percall,k=100,pareto,2.0,,3162,65536,0.005657675824508446,0.0015569051667340898
+quantile,kll-percall,k=100,pareto,2.0,,3162,86400,0.0046406272505808465,0.00033803892845387675
+quantile,kll-percall,k=100,pareto,2.0,,5623,1,0.005741770157808954,0.0011765365721794871
+quantile,kll-percall,k=100,pareto,2.0,,5623,4,0.0043256039991336846,0.00040667050990359426
+quantile,kll-percall,k=100,pareto,2.0,,5623,16,0.004238391472083363,0.0004914198467948488
+quantile,kll-percall,k=100,pareto,2.0,,5623,64,0.004853962010108179,0.0005620246413633128
+quantile,kll-percall,k=100,pareto,2.0,,5623,256,0.006365610596272148,0.0005362826598201446
+quantile,kll-percall,k=100,pareto,2.0,,5623,1024,0.00530298414867274,0.00043665874454786274
+quantile,kll-percall,k=100,pareto,2.0,,5623,4096,0.005617281450713094,0.0006992038932868138
+quantile,kll-percall,k=100,pareto,2.0,,5623,16384,0.004719642158062506,0.0003277739195070778
+quantile,kll-percall,k=100,pareto,2.0,,5623,65536,0.004991686079509602,9.294713712409934e-05
+quantile,kll-percall,k=100,pareto,2.0,,5623,86400,0.006186560502039887,0.000959637010220305
+quantile,kll-percall,k=100,pareto,2.0,,10000,1,0.00519075907590759,0.0001284795210622958
+quantile,kll-percall,k=100,pareto,2.0,,10000,4,0.005140594059405941,0.0011288188242784096
+quantile,kll-percall,k=100,pareto,2.0,,10000,16,0.00457986798679868,0.0003322871862571343
+quantile,kll-percall,k=100,pareto,2.0,,10000,64,0.007746534653465344,0.0019322137533314512
+quantile,kll-percall,k=100,pareto,2.0,,10000,256,0.0057947194719471925,0.0009878694919713703
+quantile,kll-percall,k=100,pareto,2.0,,10000,1024,0.005346864686468646,0.00020713456040983454
+quantile,kll-percall,k=100,pareto,2.0,,10000,4096,0.00580990099009901,0.00039563139027907254
+quantile,kll-percall,k=100,pareto,2.0,,10000,16384,0.005635313531353135,0.0010497114083829128
+quantile,kll-percall,k=100,pareto,2.0,,10000,65536,0.005893399339933996,0.00037091084709880073
+quantile,kll-percall,k=100,pareto,2.0,,10000,86400,0.006864356435643562,0.0017192847177034717
+quantile,kll-percall,k=100,pareto,2.0,,17783,1,0.006150235447545206,0.0009119453158373458
+quantile,kll-percall,k=100,pareto,2.0,,17783,4,0.006205798952498294,0.000986892797312598
+quantile,kll-percall,k=100,pareto,2.0,,17783,16,0.007264502809725386,0.0016064766377821048
+quantile,kll-percall,k=100,pareto,2.0,,17783,64,0.0065428045363159736,0.0011312884905010684
+quantile,kll-percall,k=100,pareto,2.0,,17783,256,0.005337912186315072,0.000892444838284613
+quantile,kll-percall,k=100,pareto,2.0,,17783,1024,0.00686328155955673,0.000515047720785158
+quantile,kll-percall,k=100,pareto,2.0,,17783,4096,0.006981449817927862,0.0008976866656387566
+quantile,kll-percall,k=100,pareto,2.0,,17783,16384,0.007964479741006772,0.0010022885966343672
+quantile,kll-percall,k=100,pareto,2.0,,17783,65536,0.004995225721751166,0.0007059372910743975
+quantile,kll-percall,k=100,pareto,2.0,,17783,86400,0.005022269757763609,0.000804878578890231
+quantile,kll-percall,k=100,pareto,2.0,,31623,1,0.0063372911619973315,0.000409265543110719
+quantile,kll-percall,k=100,pareto,2.0,,31623,4,0.005697782945925747,0.0008935515044003551
+quantile,kll-percall,k=100,pareto,2.0,,31623,16,0.005055790846137077,0.0006260973653114363
+quantile,kll-percall,k=100,pareto,2.0,,31623,64,0.003943951268288767,0.0004987487070482244
+quantile,kll-percall,k=100,pareto,2.0,,31623,256,0.005783337085250126,0.0006829042727094066
+quantile,kll-percall,k=100,pareto,2.0,,31623,1024,0.004551773268589542,0.0003348798139510535
+quantile,kll-percall,k=100,pareto,2.0,,31623,4096,0.006958186948568683,0.0015430396762609157
+quantile,kll-percall,k=100,pareto,2.0,,31623,16384,0.005810469862089141,0.0006699874473629523
+quantile,kll-percall,k=100,pareto,2.0,,31623,65536,0.006850168272685346,0.0009136062289163234
+quantile,kll-percall,k=100,pareto,2.0,,31623,86400,0.006200737045528859,0.0007293833390140433
+quantile,kll-percall,k=100,pareto,2.0,,56234,1,0.004809960172316268,0.0006800239223097685
+quantile,kll-percall,k=100,pareto,2.0,,56234,4,0.005324313738056593,0.0006529102296580225
+quantile,kll-percall,k=100,pareto,2.0,,56234,16,0.006987363387617349,0.0015758461544133789
+quantile,kll-percall,k=100,pareto,2.0,,56234,64,0.0036203189618673765,0.00018685547668807856
+quantile,kll-percall,k=100,pareto,2.0,,56234,256,0.004605932940984111,0.0002404110049442604
+quantile,kll-percall,k=100,pareto,2.0,,56234,1024,0.005465252397132162,0.0009688769028108989
+quantile,kll-percall,k=100,pareto,2.0,,56234,4096,0.007021289282607532,0.00032466911994507035
+quantile,kll-percall,k=100,pareto,2.0,,56234,16384,0.0053408558837887525,0.0004107500086538316
+quantile,kll-percall,k=100,pareto,2.0,,56234,65536,0.007014860464600356,0.0012169669819771724
+quantile,kll-percall,k=100,pareto,2.0,,56234,86400,0.005750953905363149,0.00027639850481110965
+quantile,kll-percall,k=100,pareto,2.0,,100000,1,0.006087557755775577,0.0009638847599440256
+quantile,kll-percall,k=100,pareto,2.0,,100000,4,0.0033940594059405933,9.165195956081578e-05
+quantile,kll-percall,k=100,pareto,2.0,,100000,16,0.005222244224422443,0.00038282820773129103
+quantile,kll-percall,k=100,pareto,2.0,,100000,64,0.00424907590759076,9.82922229202483e-05
+quantile,kll-percall,k=100,pareto,2.0,,100000,256,0.00554161716171617,0.0005789956292947217
+quantile,kll-percall,k=100,pareto,2.0,,100000,1024,0.005894389438943896,0.000536995838634247
+quantile,kll-percall,k=100,pareto,2.0,,100000,4096,0.005045148514851486,0.00031649144788548013
+quantile,kll-percall,k=100,pareto,2.0,,100000,16384,0.005022838283828382,0.00020526228522507666
+quantile,kll-percall,k=100,pareto,2.0,,100000,65536,0.005413465346534654,0.0003692116379592459
+quantile,kll-percall,k=100,pareto,2.0,,100000,86400,0.00575049504950495,0.0004355255728302227
+quantile,kll-percall,k=100,pareto,2.0,,177828,1,0.004713104686539912,4.154259592838538e-05
+quantile,kll-percall,k=100,pareto,2.0,,177828,4,0.0047230887472308886,0.0002052291360341778
+quantile,kll-percall,k=100,pareto,2.0,,177828,16,0.004596588344980661,9.571579013423467e-05
+quantile,kll-percall,k=100,pareto,2.0,,177828,64,0.005848410200356028,0.0004227945290175876
+quantile,kll-percall,k=100,pareto,2.0,,177828,256,0.0053814317257354985,0.000810284205759827
+quantile,kll-percall,k=100,pareto,2.0,,177828,1024,0.0057072377053482394,0.00018366370270161468
+quantile,kll-percall,k=100,pareto,2.0,,177828,4096,0.005927354730209504,0.00034190907184116756
+quantile,kll-percall,k=100,pareto,2.0,,177828,16384,0.005806335947718529,0.0006004969951676443
+quantile,kll-percall,k=100,pareto,2.0,,177828,65536,0.005273793321703452,0.0005860877888842598
+quantile,kll-percall,k=100,pareto,2.0,,177828,86400,0.005765866687215314,0.0006851415147021483
+quantile,kll-percall,k=100,pareto,2.0,,316228,1,0.006248558346860147,0.0002894852293704948
+quantile,kll-percall,k=100,pareto,2.0,,316228,4,0.005578007779906978,0.0006264866567894653
+quantile,kll-percall,k=100,pareto,2.0,,316228,16,0.005121282129604355,0.00040452876825089
+quantile,kll-percall,k=100,pareto,2.0,,316228,64,0.006350864111038905,0.00041756404322366845
+quantile,kll-percall,k=100,pareto,2.0,,316228,256,0.005320457884107596,7.47495794235486e-05
+quantile,kll-percall,k=100,pareto,2.0,,316228,1024,0.0057707295705221005,0.0005784154579843227
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+quantile,kll-percall,k=100,pareto,2.0,,316228,16384,0.005414844392467632,0.00012945271632034856
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+quantile,kll-percall,k=100,pareto,2.0,,316228,86400,0.005087215970797021,0.0003701223485407449
+quantile,kll-percall,k=100,pareto,2.0,,562341,1,0.007819249331720153,0.0010804875480349312
+quantile,kll-percall,k=100,pareto,2.0,,562341,4,0.006524809303925694,0.0011366983521405305
+quantile,kll-percall,k=100,pareto,2.0,,562341,16,0.004588261143569421,0.0010117209950054706
+quantile,kll-percall,k=100,pareto,2.0,,562341,64,0.007404312475612104,0.0012607599999718154
+quantile,kll-percall,k=100,pareto,2.0,,562341,256,0.004473652729989431,0.0004111453049540663
+quantile,kll-percall,k=100,pareto,2.0,,562341,1024,0.0054563373081774605,0.00021681085581974545
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+quantile,kll-percall,k=100,pareto,2.0,,562341,16384,0.0071847653857982675,0.002508913000533083
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+quantile,kll-percall,k=100,pareto,2.0,,562341,86400,0.008763198208141247,0.0010416628806860788
+quantile,kll-percall,k=100,pareto,2.0,,1000000,1,0.00627282508250825,0.0006129676561824788
+quantile,kll-percall,k=100,pareto,2.0,,1000000,4,0.0043312409240924095,0.00020447158426729648
+quantile,kll-percall,k=100,pareto,2.0,,1000000,16,0.00431613201320132,0.0006100368897372419
+quantile,kll-percall,k=100,pareto,2.0,,1000000,64,0.005957772277227723,0.0010880263559642056
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+quantile,kll-percall,k=100,pareto,2.0,,1000000,1024,0.0040609141914191415,0.0002866977626495114
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+quantile,kll-percall,k=100,pareto,2.0,,1000000,16384,0.00610541914191419,0.0011238805821190282
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+quantile,kll-percall,k=100,pareto,2.0,,1000000,86400,0.007579432343234323,0.0016904018731184415
+quantile,kll-percall,k=100,pareto,2.0,,1778279,1,0.0062023453918401495,0.00016168476572926466
+quantile,kll-percall,k=100,pareto,2.0,,1778279,4,0.006768490390671171,0.0009972000895553741
+quantile,kll-percall,k=100,pareto,2.0,,1778279,16,0.005592804688529113,0.0005617982674792556
+quantile,kll-percall,k=100,pareto,2.0,,1778279,64,0.0036523310073127663,0.0003274462437449177
+quantile,kll-percall,k=100,pareto,2.0,,1778279,256,0.0054799358359862846,0.0008240063574059125
+quantile,kll-percall,k=100,pareto,2.0,,1778279,1024,0.0062151389754432325,0.0005164903387101303
+quantile,kll-percall,k=100,pareto,2.0,,1778279,4096,0.0050241702244924824,0.0007662648493851924
+quantile,kll-percall,k=100,pareto,2.0,,1778279,16384,0.004990194593101017,0.0011721438056799846
+quantile,kll-percall,k=100,pareto,2.0,,1778279,65536,0.006873281310290184,0.0009991861989892307
+quantile,kll-percall,k=100,pareto,2.0,,1778279,86400,0.005352757045179385,0.0005332296715186713
+quantile,kll-percall,k=100,pareto,2.0,,3162278,1,0.0053568473929445845,0.0004555014530807334
+quantile,kll-percall,k=100,pareto,2.0,,3162278,4,0.00472734486970089,7.822813042495614e-05
+quantile,kll-percall,k=100,pareto,2.0,,3162278,16,0.004526363255822031,0.0007267205769921675
+quantile,kll-percall,k=100,pareto,2.0,,3162278,64,0.004622382289533743,0.00041003273075969837
+quantile,kll-percall,k=100,pareto,2.0,,3162278,256,0.005519760406165991,0.0007853157058664282
+quantile,kll-percall,k=100,pareto,2.0,,3162278,1024,0.005908221899533564,0.001837762266413325
+quantile,kll-percall,k=100,pareto,2.0,,3162278,4096,0.004954483255216625,0.00020946774911360835
+quantile,kll-percall,k=100,pareto,2.0,,3162278,16384,0.006173558299036034,0.0009546530538121424
+quantile,kll-percall,k=100,pareto,2.0,,3162278,65536,0.007101434795771375,0.0024748883966420427
+quantile,kll-percall,k=100,pareto,2.0,,3162278,86400,0.007005487085502596,0.0016177117054306039
+quantile,kll-percall,k=100,pareto,2.0,,5623413,1,0.00664918141959757,0.0015505354302325944
+quantile,kll-percall,k=100,pareto,2.0,,5623413,4,0.0049726651063971995,0.00038485611920785083
+quantile,kll-percall,k=100,pareto,2.0,,5623413,16,0.005030326646366849,0.00038101757831530584
+quantile,kll-percall,k=100,pareto,2.0,,5623413,64,0.005477262111763154,0.0003165038427778238
+quantile,kll-percall,k=100,pareto,2.0,,5623413,256,0.005248793370020509,0.00010892140523874773
+quantile,kll-percall,k=100,pareto,2.0,,5623413,1024,0.004959352512920404,0.0007182442597671057
+quantile,kll-percall,k=100,pareto,2.0,,5623413,4096,0.005247150081311473,0.0004229250830167246
+quantile,kll-percall,k=100,pareto,2.0,,5623413,16384,0.005899525551452109,0.0004886712947171303
+quantile,kll-percall,k=100,pareto,2.0,,5623413,65536,0.0055011923425601975,0.00023770625441128364
+quantile,kll-percall,k=100,pareto,2.0,,5623413,86400,0.0053485454004487286,0.0003595063398564991
+quantile,kll-percall,k=100,pareto,2.0,,10000000,1,0.0057056471947194735,0.0003856848606207295
+quantile,kll-percall,k=100,pareto,2.0,,10000000,4,0.004222331353135315,0.0002604034390347345
+quantile,kll-percall,k=100,pareto,2.0,,10000000,16,0.006666103300330031,0.0011119441305615823
+quantile,kll-percall,k=100,pareto,2.0,,10000000,64,0.004871658745874588,0.00018375958458561229
+quantile,kll-percall,k=100,pareto,2.0,,10000000,256,0.0061879574257425775,0.0004290353214373073
+quantile,kll-percall,k=100,pareto,2.0,,10000000,1024,0.005397137953795382,0.00017571074770646988
+quantile,kll-percall,k=100,pareto,2.0,,10000000,4096,0.004766963366336633,0.000219085468685827
+quantile,kll-percall,k=100,pareto,2.0,,10000000,16384,0.005820232343234324,0.0002878055982519602
+quantile,kll-percall,k=100,pareto,2.0,,10000000,65536,0.005915424752475247,0.0009884822842431012
+quantile,kll-percall,k=100,pareto,2.0,,10000000,86400,0.007036566336633663,0.00047278898297407407
+quantile,kll-percall,k=100,pareto,2.0,,17782794,1,0.005234879859993683,0.00031267623542819643
+quantile,kll-percall,k=100,pareto,2.0,,17782794,4,0.006785984364785679,0.0012456904840911387
+quantile,kll-percall,k=100,pareto,2.0,,17782794,16,0.005257590109191214,0.00032287021650220674
+quantile,kll-percall,k=100,pareto,2.0,,17782794,64,0.0066467452815463755,0.0012677430195115042
+quantile,kll-percall,k=100,pareto,2.0,,17782794,256,0.007689741052846117,0.0015333874614688247
+quantile,kll-percall,k=100,pareto,2.0,,17782794,1024,0.0068915384897857285,0.0010926873518851841
+quantile,kll-percall,k=100,pareto,2.0,,17782794,4096,0.006121971805912491,0.0013444808849925774
+quantile,kll-percall,k=100,pareto,2.0,,17782794,16384,0.005520381547173381,0.0008067390026028935
+quantile,kll-percall,k=100,pareto,2.0,,17782794,65536,0.0052231263694572615,0.0005857698543738109
+quantile,kll-percall,k=100,pareto,2.0,,17782794,86400,0.007356408753998117,0.0014182479871669086
+quantile,kll-percall,k=100,pareto,2.0,,31622777,1,0.005018398557528588,0.0004769419494658104
+quantile,kll-percall,k=100,pareto,2.0,,31622777,4,0.006186233003277142,0.0009878193466825982
+quantile,kll-percall,k=100,pareto,2.0,,31622777,16,0.0050439073287797155,0.0005016876864800526
+quantile,kll-percall,k=100,pareto,2.0,,31622777,64,0.0045900298706562795,0.0004758169817539701
+quantile,kll-percall,k=100,pareto,2.0,,31622777,256,0.005878192850778675,0.0012274995373534787
+quantile,kll-percall,k=100,pareto,2.0,,31622777,1024,0.006670026410260414,0.0007146684058690032
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+quantile,kll-percall,k=100,pareto,2.0,,31622777,65536,0.006679647660793404,0.0013849915377608787
+quantile,kll-percall,k=100,pareto,2.0,,31622777,86400,0.005668735679267691,0.0003576427860725719
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+quantile,kll-percall,k=400,pareto,2.0,,1000,4,0.0010363036303630369,0.0005304914810136671
+quantile,kll-percall,k=400,pareto,2.0,,1000,16,0.00021122112211221134,1.1899509159947171e-05
+quantile,kll-percall,k=400,pareto,2.0,,1000,64,0.0014026402640264035,0.0003868713253625597
+quantile,kll-percall,k=400,pareto,2.0,,1000,256,0.0005610561056105614,3.7192830592688567e-05
+quantile,kll-percall,k=400,pareto,2.0,,1000,1024,0.0008448844884488453,0.00027830609062949667
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+quantile,kll-percall,k=400,pareto,2.0,,1000,16384,0.0007425742574257431,4.464603715666233e-05
+quantile,kll-percall,k=400,pareto,2.0,,1000,65536,0.0006303630363036308,6.270627062706269e-05
+quantile,kll-percall,k=400,pareto,2.0,,1000,86400,0.0007359735973597363,6.600660066006643e-06
+quantile,kll-percall,k=400,pareto,2.0,,1778,1,0.0004526909383851755,8.128667250837818e-05
+quantile,kll-percall,k=400,pareto,2.0,,1778,4,0.0009394246511265337,9.414057952014607e-05
+quantile,kll-percall,k=400,pareto,2.0,,1778,16,0.0010672428322697283,0.00010911378742445777
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+quantile,kll-percall,k=400,pareto,2.0,,1778,1024,0.0005443502730475531,5.043494809660715e-05
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+quantile,kll-percall,k=400,pareto,2.0,,3162,1,0.0013513400675930988,0.0003023399316671258
+quantile,kll-percall,k=400,pareto,2.0,,3162,4,0.0006008646405437501,0.00013034099355167054
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+quantile,kll-percall,k=400,pareto,2.0,,3162,64,0.0008872898675066732,0.00019624012836087695
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+quantile,kll-percall,k=400,pareto,2.0,,3162,1024,0.000899543464782911,0.00015875511926438516
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+quantile,kll-percall,k=400,pareto,2.0,,3162,65536,0.0009036975803842274,0.00020603487756876826
+quantile,kll-percall,k=400,pareto,2.0,,3162,86400,0.0007482835570084544,2.2542320141029916e-05
+quantile,kll-percall,k=400,pareto,2.0,,5623,1,0.001067122362245117,0.00031167766260208643
+quantile,kll-percall,k=400,pareto,2.0,,5623,4,0.0006669800894370053,7.643757928676501e-05
+quantile,kll-percall,k=400,pareto,2.0,,5623,16,0.0008766446625100016,9.851249729632206e-05
+quantile,kll-percall,k=400,pareto,2.0,,5623,64,0.0007888334627522849,6.55620314839836e-05
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+quantile,kll-percall,k=400,pareto,2.0,,5623,1024,0.0009114028955803255,6.197919303106343e-05
+quantile,kll-percall,k=400,pareto,2.0,,5623,4096,0.0010952130247703763,0.00019094487795327545
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+quantile,kll-percall,k=400,pareto,2.0,,5623,65536,0.000799081330861164,6.476485241774856e-05
+quantile,kll-percall,k=400,pareto,2.0,,5623,86400,0.00105172121338045,0.00019537093575357017
+quantile,kll-percall,k=400,pareto,2.0,,10000,1,0.0011709570957095727,0.0001399293230430547
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+quantile,kll-percall,k=400,pareto,2.0,,10000,16,0.001446204620462047,0.00031615766451916166
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+quantile,kll-percall,k=400,pareto,2.0,,10000,1024,0.0010112211221122124,0.0001691663026770398
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+quantile,kll-percall,k=400,pareto,2.0,,17783,1,0.0013322082925269418,0.00016390293168219657
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+quantile,kll-percall,k=400,pareto,2.0,,17783,16,0.0012913137458940777,0.0001724823049101733
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+quantile,kll-percall,k=400,pareto,2.0,,17783,65536,0.0012990992064397886,0.00011995811822458873
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+quantile,kll-percall,k=400,pareto,2.0,,31623,64,0.0009676209059099611,0.00016829901780933377
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+quantile,kll-percall,k=400,pareto,2.0,,177828,1,0.0017035974465926251,0.0002996323029236052
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+quantile,kll-percall,k=400,pareto,2.0,,177828,86400,0.0011243014442479389,3.9297386811385724e-05
+quantile,kll-percall,k=400,pareto,2.0,,316228,1,0.001367044732857868,0.000193561208203407
+quantile,kll-percall,k=400,pareto,2.0,,316228,4,0.0008433731921960833,2.6300430961469987e-05
+quantile,kll-percall,k=400,pareto,2.0,,316228,16,0.0012100030094841926,0.00023653424223863719
+quantile,kll-percall,k=400,pareto,2.0,,316228,64,0.0009267295172539367,3.6590059726507926e-05
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+quantile,kll-percall,k=400,pareto,2.0,,316228,65536,0.001181219833406747,0.00015005817702002863
+quantile,kll-percall,k=400,pareto,2.0,,316228,86400,0.001714996461382605,0.0002195061371964983
+quantile,kll-percall,k=400,pareto,2.0,,562341,1,0.0014032758378880368,0.00011177125492045308
+quantile,kll-percall,k=400,pareto,2.0,,562341,4,0.0009785121336505333,5.687179102726935e-05
+quantile,kll-percall,k=400,pareto,2.0,,562341,16,0.001198698700152708,0.00016474718872939144
+quantile,kll-percall,k=400,pareto,2.0,,562341,64,0.0014622496622044782,0.00021628768937522876
+quantile,kll-percall,k=400,pareto,2.0,,562341,256,0.0009271640805803321,0.0001466408113669354
+quantile,kll-percall,k=400,pareto,2.0,,562341,1024,0.0013308468864566122,0.00010511794083646942
+quantile,kll-percall,k=400,pareto,2.0,,562341,4096,0.001488455001373532,0.00022136148465862383
+quantile,kll-percall,k=400,pareto,2.0,,562341,16384,0.0017805163766041836,0.00021458146424674203
+quantile,kll-percall,k=400,pareto,2.0,,562341,65536,0.0020776440317214,0.00014710050229506535
+quantile,kll-percall,k=400,pareto,2.0,,562341,86400,0.0016978760459069372,0.0004944550274054064
+quantile,kll-percall,k=400,pareto,2.0,,1000000,1,0.001335059405940594,0.000287296006288333
+quantile,kll-percall,k=400,pareto,2.0,,1000000,4,0.0014732409240924094,0.00028533057291624535
+quantile,kll-percall,k=400,pareto,2.0,,1000000,16,0.0009325544554455446,0.0001937754434681004
+quantile,kll-percall,k=400,pareto,2.0,,1000000,64,0.0013664521452145216,0.00010600175131422438
+quantile,kll-percall,k=400,pareto,2.0,,1000000,256,0.0018023696369636967,0.00018932481690615862
+quantile,kll-percall,k=400,pareto,2.0,,1000000,1024,0.0012752904290429044,0.00012094575388407732
+quantile,kll-percall,k=400,pareto,2.0,,1000000,4096,0.0013473168316831682,0.00012638429956816444
+quantile,kll-percall,k=400,pareto,2.0,,1000000,16384,0.0009784917491749176,6.20428737431888e-05
+quantile,kll-percall,k=400,pareto,2.0,,1000000,65536,0.0009586732673267326,9.06924202276915e-05
+quantile,kll-percall,k=400,pareto,2.0,,1000000,86400,0.001953125412541254,0.0003014134046949396
+quantile,kll-percall,k=400,pareto,2.0,,1778279,1,0.00116915721479716,0.00018117326497806235
+quantile,kll-percall,k=400,pareto,2.0,,1778279,4,0.0013741707627998709,0.0002097313195320002
+quantile,kll-percall,k=400,pareto,2.0,,1778279,16,0.001290489955804921,0.00024297165366023388
+quantile,kll-percall,k=400,pareto,2.0,,1778279,64,0.0010970523087256011,3.026878880366761e-05
+quantile,kll-percall,k=400,pareto,2.0,,1778279,256,0.0014630905320913272,0.0004596609289766178
+quantile,kll-percall,k=400,pareto,2.0,,1778279,1024,0.0012558212339305616,7.106396206281877e-05
+quantile,kll-percall,k=400,pareto,2.0,,1778279,4096,0.0010921564860713016,9.440962741174063e-05
+quantile,kll-percall,k=400,pareto,2.0,,1778279,16384,0.0011586860642843805,0.0001828970176515605
+quantile,kll-percall,k=400,pareto,2.0,,1778279,65536,0.0008828659322832466,4.944298784778516e-05
+quantile,kll-percall,k=400,pareto,2.0,,1778279,86400,0.0012134613698340506,0.0001633100031263813
+quantile,kll-percall,k=400,pareto,2.0,,3162278,1,0.0009627573966151789,2.0225354125748613e-05
+quantile,kll-percall,k=400,pareto,2.0,,3162278,4,0.0009897067622745615,0.0002853295122781982
+quantile,kll-percall,k=400,pareto,2.0,,3162278,16,0.0009398476889024276,2.7077439628033042e-05
+quantile,kll-percall,k=400,pareto,2.0,,3162278,64,0.0010691344435982545,0.0001409051386659486
+quantile,kll-percall,k=400,pareto,2.0,,3162278,256,0.0009634445187743137,5.836694861570501e-05
+quantile,kll-percall,k=400,pareto,2.0,,3162278,1024,0.0009229699782137049,0.00010808249193894836
+quantile,kll-percall,k=400,pareto,2.0,,3162278,4096,0.001192140351961716,6.618205031684029e-05
+quantile,kll-percall,k=400,pareto,2.0,,3162278,16384,0.0010013165781561921,4.8021193342615335e-05
+quantile,kll-percall,k=400,pareto,2.0,,3162278,65536,0.0012641103605812941,0.00015849076213373165
+quantile,kll-percall,k=400,pareto,2.0,,3162278,86400,0.0011604264258536768,7.700518600841162e-05
+quantile,kll-percall,k=400,pareto,2.0,,5623413,1,0.0010830830846586988,0.00011051963410355253
+quantile,kll-percall,k=400,pareto,2.0,,5623413,4,0.0011127763025893013,0.00029609528322295644
+quantile,kll-percall,k=400,pareto,2.0,,5623413,16,0.0010338312924967413,0.0001362375737721458
+quantile,kll-percall,k=400,pareto,2.0,,5623413,64,0.0010185050351886943,4.406253869900057e-05
+quantile,kll-percall,k=400,pareto,2.0,,5623413,256,0.0014103136192547235,0.00020445233531569138
+quantile,kll-percall,k=400,pareto,2.0,,5623413,1024,0.001510600031472966,0.0002846174477865853
+quantile,kll-percall,k=400,pareto,2.0,,5623413,4096,0.0010897183325542293,0.00016093116494593198
+quantile,kll-percall,k=400,pareto,2.0,,5623413,16384,0.0014583603248135802,0.0001849486306485462
+quantile,kll-percall,k=400,pareto,2.0,,5623413,65536,0.001356726217367427,0.0003580586283461228
+quantile,kll-percall,k=400,pareto,2.0,,5623413,86400,0.0013487066346438085,0.00033345550451350305
+quantile,kll-percall,k=400,pareto,2.0,,10000000,1,0.001609415511551155,0.0004591711084548267
+quantile,kll-percall,k=400,pareto,2.0,,10000000,4,0.001119720462046205,0.00014029234905157747
+quantile,kll-percall,k=400,pareto,2.0,,10000000,16,0.0010705267326732671,0.00015408257969633948
+quantile,kll-percall,k=400,pareto,2.0,,10000000,64,0.0008355600660065991,1.6373341950039228e-05
+quantile,kll-percall,k=400,pareto,2.0,,10000000,256,0.0010705214521452148,9.893037405505497e-05
+quantile,kll-percall,k=400,pareto,2.0,,10000000,1024,0.001207791089108911,8.798324329037088e-05
+quantile,kll-percall,k=400,pareto,2.0,,10000000,4096,0.0011219280528052807,7.527984926764027e-05
+quantile,kll-percall,k=400,pareto,2.0,,10000000,16384,0.0012933399339933995,7.366740354619852e-05
+quantile,kll-percall,k=400,pareto,2.0,,10000000,65536,0.0015106544554455454,0.0004207836830488294
+quantile,kll-percall,k=400,pareto,2.0,,10000000,86400,0.001667099669966996,0.0004956790367926722
+quantile,kll-percall,k=400,pareto,2.0,,17782794,1,0.0011301145770159628,0.00010999263829837947
+quantile,kll-percall,k=400,pareto,2.0,,17782794,4,0.0014071862146216951,0.00028814545276843376
+quantile,kll-percall,k=400,pareto,2.0,,17782794,16,0.0013339919267109015,0.00026670647287249075
+quantile,kll-percall,k=400,pareto,2.0,,17782794,64,0.0010872365072824755,9.32617435405949e-05
+quantile,kll-percall,k=400,pareto,2.0,,17782794,256,0.0016954766693712093,0.0006769499411509295
+quantile,kll-percall,k=400,pareto,2.0,,17782794,1024,0.0013461932673659598,0.0002174386103241476
+quantile,kll-percall,k=400,pareto,2.0,,17782794,4096,0.0014809985249319283,0.0003542665479394137
+quantile,kll-percall,k=400,pareto,2.0,,17782794,16384,0.001461341752029178,0.00014501169171680044
+quantile,kll-percall,k=400,pareto,2.0,,17782794,65536,0.0019075257034222722,0.0003233104438492387
+quantile,kll-percall,k=400,pareto,2.0,,17782794,86400,0.0009474172474007331,0.00020838235234190913
+quantile,kll-percall,k=400,pareto,2.0,,31622777,1,0.0013976790339836655,0.00018497364143600504
+quantile,kll-percall,k=400,pareto,2.0,,31622777,4,0.0010954505758279031,0.00010916022778326082
+quantile,kll-percall,k=400,pareto,2.0,,31622777,16,0.0008452282403413148,0.0001111264821658867
+quantile,kll-percall,k=400,pareto,2.0,,31622777,64,0.0012035326181935163,0.00022635679375969294
+quantile,kll-percall,k=400,pareto,2.0,,31622777,256,0.0015710345420801679,0.0001978820224159242
+quantile,kll-percall,k=400,pareto,2.0,,31622777,1024,0.001531092288321171,0.00021269514385782566
+quantile,kll-percall,k=400,pareto,2.0,,31622777,4096,0.001806106385658263,0.00024635780303660146
+quantile,kll-percall,k=400,pareto,2.0,,31622777,16384,0.0018309478015293408,0.00041150259391514385
+quantile,kll-percall,k=400,pareto,2.0,,31622777,65536,0.001723408131521856,0.00029952073359580905
+quantile,kll-percall,k=400,pareto,2.0,,31622777,86400,0.0010616014653817487,0.0001720314815509679
+quantile,kll-percall,k=25,pareto,3.0,,1000,1,0.022900990099009894,0.0008532294666879214
+quantile,kll-percall,k=25,pareto,3.0,,1000,4,0.020495049504950482,0.0033353456005052375
+quantile,kll-percall,k=25,pareto,3.0,,1000,16,0.018600660066006584,0.003371876306490161
+quantile,kll-percall,k=25,pareto,3.0,,1000,64,0.021646864686468637,0.0015358382877963584
+quantile,kll-percall,k=25,pareto,3.0,,1000,256,0.02175247524752474,0.001555821224219075
+quantile,kll-percall,k=25,pareto,3.0,,1000,1024,0.019290429042904275,0.0021807990506557463
+quantile,kll-percall,k=25,pareto,3.0,,1000,3600,0.019854785478547837,0.0026741798548464944
+quantile,kll-percall,k=25,pareto,3.0,,1000,4096,0.01969966996699669,0.0026078872957278412
+quantile,kll-percall,k=25,pareto,3.0,,1778,1,0.01989427064191233,0.0009768714484827351
+quantile,kll-percall,k=25,pareto,3.0,,1778,4,0.01964011924252043,0.0013265921627985328
+quantile,kll-percall,k=25,pareto,3.0,,1778,16,0.019507660552331944,0.0026277846273929893
+quantile,kll-percall,k=25,pareto,3.0,,1778,64,0.022034324917306124,0.003470970168271628
+quantile,kll-percall,k=25,pareto,3.0,,1778,256,0.021619166416079184,0.004903835377560618
+quantile,kll-percall,k=25,pareto,3.0,,1778,1024,0.02284396381145426,0.007966151093445789
+quantile,kll-percall,k=25,pareto,3.0,,1778,3600,0.02393210749646393,0.00688401852016076
+quantile,kll-percall,k=25,pareto,3.0,,1778,4096,0.01665538094866854,0.0015237327528893167
+quantile,kll-percall,k=25,pareto,3.0,,3162,1,0.01941176470588236,0.0011687970209988863
+quantile,kll-percall,k=25,pareto,3.0,,3162,4,0.015096932843189442,0.0011909079362475432
+quantile,kll-percall,k=25,pareto,3.0,,3162,16,0.016175708652459177,0.00015331248482230948
+quantile,kll-percall,k=25,pareto,3.0,,3162,64,0.01948804178330546,0.0011950754875109557
+quantile,kll-percall,k=25,pareto,3.0,,3162,256,0.018778460388733372,0.0011006027161167243
+quantile,kll-percall,k=25,pareto,3.0,,3162,1024,0.030968514308736383,0.005239983536239732
+quantile,kll-percall,k=25,pareto,3.0,,3162,3600,0.020189043572288914,0.003458130833190131
+quantile,kll-percall,k=25,pareto,3.0,,3162,4096,0.017790845498212065,0.001484504792143686
+quantile,kll-percall,k=25,pareto,3.0,,5623,1,0.01786239801287616,0.001046383893627967
+quantile,kll-percall,k=25,pareto,3.0,,5623,4,0.01806662170752021,0.0011759975180144111
+quantile,kll-percall,k=25,pareto,3.0,,5623,16,0.02469617653566886,0.002877327199838244
+quantile,kll-percall,k=25,pareto,3.0,,5623,64,0.01575717717601389,0.0017557776315756796
+quantile,kll-percall,k=25,pareto,3.0,,5623,256,0.016990971193864893,0.0011977169552700008
+quantile,kll-percall,k=25,pareto,3.0,,5623,1024,0.02039254147716034,0.003128613885005007
+quantile,kll-percall,k=25,pareto,3.0,,5623,3600,0.017647756239255442,0.0015884717329104413
+quantile,kll-percall,k=25,pareto,3.0,,5623,4096,0.02079763160381484,0.003492545969507754
+quantile,kll-percall,k=25,pareto,3.0,,10000,1,0.025379537953795384,0.002633252054368548
+quantile,kll-percall,k=25,pareto,3.0,,10000,4,0.016457755775577555,0.0007800778779800959
+quantile,kll-percall,k=25,pareto,3.0,,10000,16,0.01711650165016501,0.001261273877494768
+quantile,kll-percall,k=25,pareto,3.0,,10000,64,0.022465676567656773,0.0038664049779219716
+quantile,kll-percall,k=25,pareto,3.0,,10000,256,0.024837623762376238,0.002506016092372491
+quantile,kll-percall,k=25,pareto,3.0,,10000,1024,0.017584818481848185,0.001452791672788244
+quantile,kll-percall,k=25,pareto,3.0,,10000,3600,0.022476237623762375,0.0017106868116955399
+quantile,kll-percall,k=25,pareto,3.0,,10000,4096,0.018438613861386136,0.002351546429634006
+quantile,kll-percall,k=25,pareto,3.0,,17783,1,0.021626890294045437,0.004163482337492693
+quantile,kll-percall,k=25,pareto,3.0,,17783,4,0.025420328570561604,0.002336042451148316
+quantile,kll-percall,k=25,pareto,3.0,,17783,16,0.021972579589399077,0.0016828248943873932
+quantile,kll-percall,k=25,pareto,3.0,,17783,64,0.024877398947227566,0.0018481209049425382
+quantile,kll-percall,k=25,pareto,3.0,,17783,256,0.019218018692157692,0.0005591043634851356
+quantile,kll-percall,k=25,pareto,3.0,,17783,1024,0.020160592058756005,0.00435923053828227
+quantile,kll-percall,k=25,pareto,3.0,,17783,3600,0.025573450670152768,0.0020743227681945444
+quantile,kll-percall,k=25,pareto,3.0,,17783,4096,0.025396227976843686,0.003811408570145491
+quantile,kll-percall,k=25,pareto,3.0,,31623,1,0.022368872595446624,0.0040628519843259
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+quantile,kll-percall,k=25,pareto,3.0,,31623,16,0.022831323735731893,0.004297818183327837
+quantile,kll-percall,k=25,pareto,3.0,,31623,64,0.022693854339423128,0.005001426278119968
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+quantile,kll-percall,k=25,pareto,3.0,,31623,3600,0.0324473226186104,0.006309954305874128
+quantile,kll-percall,k=25,pareto,3.0,,31623,4096,0.02412294535591496,0.008283455881269565
+quantile,kll-percall,k=25,pareto,3.0,,56234,1,0.016324029564815854,0.0022236186596893753
+quantile,kll-percall,k=25,pareto,3.0,,56234,4,0.022121126114816553,0.002826647440970992
+quantile,kll-percall,k=25,pareto,3.0,,56234,16,0.02008740704066494,0.002683135026424274
+quantile,kll-percall,k=25,pareto,3.0,,56234,64,0.016700652424669154,0.001884167792620259
+quantile,kll-percall,k=25,pareto,3.0,,56234,256,0.023684812554236174,0.005827102991004844
+quantile,kll-percall,k=25,pareto,3.0,,56234,1024,0.01659832423474236,0.0013098847678221573
+quantile,kll-percall,k=25,pareto,3.0,,56234,3600,0.02339489363809945,0.006211256326493162
+quantile,kll-percall,k=25,pareto,3.0,,56234,4096,0.014866610536289251,0.0011140702889618295
+quantile,kll-percall,k=25,pareto,3.0,,100000,1,0.017717293729372932,0.0019439729494343076
+quantile,kll-percall,k=25,pareto,3.0,,100000,4,0.017395478547854785,0.001050179735642265
+quantile,kll-percall,k=25,pareto,3.0,,100000,16,0.018464983498349838,0.0014010655314837539
+quantile,kll-percall,k=25,pareto,3.0,,100000,64,0.024272079207920783,0.001315412863776746
+quantile,kll-percall,k=25,pareto,3.0,,100000,256,0.022068877887788774,0.003864541351312645
+quantile,kll-percall,k=25,pareto,3.0,,100000,1024,0.019396996699669957,0.0013710019616672018
+quantile,kll-percall,k=25,pareto,3.0,,100000,3600,0.021957854785478546,0.003610264261728888
+quantile,kll-percall,k=25,pareto,3.0,,100000,4096,0.014874191419141902,0.000832806232017601
+quantile,kll-percall,k=25,pareto,3.0,,177828,1,0.016893372176815493,0.0012986181238184328
+quantile,kll-percall,k=25,pareto,3.0,,177828,4,0.02066523434852426,0.003248961462544313
+quantile,kll-percall,k=25,pareto,3.0,,177828,16,0.01647336607606371,0.0006824261281743875
+quantile,kll-percall,k=25,pareto,3.0,,177828,64,0.026406523572932227,0.005293982874471152
+quantile,kll-percall,k=25,pareto,3.0,,177828,256,0.023979761360979877,0.003729540276477207
+quantile,kll-percall,k=25,pareto,3.0,,177828,1024,0.019854353273912995,0.0006176894829041083
+quantile,kll-percall,k=25,pareto,3.0,,177828,3600,0.019748695498472173,0.0018108545808801898
+quantile,kll-percall,k=25,pareto,3.0,,177828,4096,0.02235685003145026,0.0044738341918796705
+quantile,kll-percall,k=25,pareto,3.0,,316228,1,0.02847299924092868,0.004492369682860354
+quantile,kll-percall,k=25,pareto,3.0,,316228,4,0.020630401568054398,0.0027706884389044704
+quantile,kll-percall,k=25,pareto,3.0,,316228,16,0.01870445650381095,0.00031778866900958146
+quantile,kll-percall,k=25,pareto,3.0,,316228,64,0.02387236079945827,0.0009115328779704078
+quantile,kll-percall,k=25,pareto,3.0,,316228,256,0.02138913181703589,0.006299845773660699
+quantile,kll-percall,k=25,pareto,3.0,,316228,1024,0.020493128344419253,0.0015848995629329408
+quantile,kll-percall,k=25,pareto,3.0,,316228,3600,0.02374372361404779,0.002129366613422044
+quantile,kll-percall,k=25,pareto,3.0,,316228,4096,0.02499451559181241,0.002979720780396673
+quantile,kll-percall,k=25,pareto,3.0,,562341,1,0.01516166978373404,0.0017036595615406538
+quantile,kll-percall,k=25,pareto,3.0,,562341,4,0.02017482040233237,0.0018340251489052327
+quantile,kll-percall,k=25,pareto,3.0,,562341,16,0.01636677610368814,0.0007360166448043581
+quantile,kll-percall,k=25,pareto,3.0,,562341,64,0.019960498815996822,0.000828942563937672
+quantile,kll-percall,k=25,pareto,3.0,,562341,256,0.02214959413859517,0.003028306647904783
+quantile,kll-percall,k=25,pareto,3.0,,562341,1024,0.022225728545209374,0.0032459277655843156
+quantile,kll-percall,k=25,pareto,3.0,,562341,3600,0.019473368527909464,0.0005521395215672112
+quantile,kll-percall,k=25,pareto,3.0,,562341,4096,0.022261942668790353,0.0020211451279348977
+quantile,kll-percall,k=25,pareto,3.0,,1000000,1,0.03139640924092408,0.008417502271890538
+quantile,kll-percall,k=25,pareto,3.0,,1000000,4,0.021753260726072605,0.0035361956755959457
+quantile,kll-percall,k=25,pareto,3.0,,1000000,16,0.02144522772277227,0.0017967394119877494
+quantile,kll-percall,k=25,pareto,3.0,,1000000,64,0.0284192508250825,0.007732456800451185
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+quantile,kll-percall,k=25,pareto,3.0,,1000000,1024,0.025800544554455445,0.004660680355965808
+quantile,kll-percall,k=25,pareto,3.0,,1000000,3600,0.01717607920792079,0.0014687675879888915
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+quantile,kll-percall,k=25,pareto,3.0,,1778279,1,0.026491826765046873,0.008724568343226585
+quantile,kll-percall,k=25,pareto,3.0,,1778279,4,0.024383615647581177,0.007457179029056081
+quantile,kll-percall,k=25,pareto,3.0,,1778279,16,0.018631719661864568,0.0016907356559039512
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+quantile,kll-percall,k=25,pareto,3.0,,1778279,1024,0.02407834127651774,0.0018449113792968765
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+quantile,kll-percall,k=25,pareto,3.0,,3162278,1,0.024483190155122268,0.003430826757143817
+quantile,kll-percall,k=25,pareto,3.0,,3162278,4,0.013642766865579753,0.0007222225907968048
+quantile,kll-percall,k=25,pareto,3.0,,3162278,16,0.017191823118145415,0.0025056665882188653
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+quantile,kll-percall,k=25,pareto,3.0,,3162278,1024,0.018609990633459816,0.0018941689674240683
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+quantile,kll-percall,k=25,pareto,3.0,,5623413,1,0.021811513132976388,0.003818587787246179
+quantile,kll-percall,k=25,pareto,3.0,,5623413,4,0.018707134129064575,0.002097366240193472
+quantile,kll-percall,k=25,pareto,3.0,,5623413,16,0.020458594828231872,0.0026852145729476294
+quantile,kll-percall,k=25,pareto,3.0,,5623413,64,0.02285806361940892,0.006861919404914459
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+quantile,kll-percall,k=25,pareto,3.0,,5623413,3600,0.014363802339483254,0.00038894304182124286
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+quantile,kll-percall,k=25,pareto,3.0,,17782794,1,0.01732887648173131,0.0004920120809006046
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+quantile,kll-percall,k=25,pareto,3.0,,177827941,1,0.020063515511734267,0.002385558083084665
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+quantile,kll-percall,k=100,pareto,3.0,,1000,16,0.006128712871287133,0.001108306648198888
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+quantile,kll-percall,k=100,pareto,3.0,,1000,1024,0.004854785478547858,0.0015629179722846927
+quantile,kll-percall,k=100,pareto,3.0,,1000,3600,0.003947194719471949,0.0007678712713480102
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+quantile,kll-percall,k=100,pareto,3.0,,3162,1,0.00806000713923385,0.0005047832098192195
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+quantile,kll-percall,k=100,pareto,3.0,,56234,1,0.005582511126597241,0.0006594345035359743
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+quantile,kll-percall,k=100,pareto,3.0,,56234,16,0.005245718298045263,0.00017465021476697763
+quantile,kll-percall,k=100,pareto,3.0,,56234,64,0.004791291128970631,0.0006607899268744152
+quantile,kll-percall,k=100,pareto,3.0,,56234,256,0.004629888709964998,0.0007305567639941616
+quantile,kll-percall,k=100,pareto,3.0,,56234,1024,0.005517360214877695,0.0008427451905978547
+quantile,kll-percall,k=100,pareto,3.0,,56234,3600,0.0074191705545345555,0.0005170350045300752
+quantile,kll-percall,k=100,pareto,3.0,,56234,4096,0.008130519208338656,0.0010395611618070582
+quantile,kll-percall,k=100,pareto,3.0,,100000,1,0.005223399339933994,0.0006817125191313643
+quantile,kll-percall,k=100,pareto,3.0,,100000,4,0.003608415841584158,0.0003747947493497166
+quantile,kll-percall,k=100,pareto,3.0,,100000,16,0.003862706270627063,0.00013681542334045542
+quantile,kll-percall,k=100,pareto,3.0,,100000,64,0.0059604620462046206,0.0008621024303276661
+quantile,kll-percall,k=100,pareto,3.0,,100000,256,0.005087359735973594,0.0009534029540901375
+quantile,kll-percall,k=100,pareto,3.0,,100000,1024,0.0074605940594059394,0.0011193075875475928
+quantile,kll-percall,k=100,pareto,3.0,,100000,3600,0.004796765676567657,0.0005063616995894736
+quantile,kll-percall,k=100,pareto,3.0,,100000,4096,0.00511079207920792,0.00016146685503018554
+quantile,kll-percall,k=100,pareto,3.0,,177828,1,0.005111640862446458,0.0003187766485080669
+quantile,kll-percall,k=100,pareto,3.0,,177828,4,0.004501099479001145,0.0003721879264691678
+quantile,kll-percall,k=100,pareto,3.0,,177828,16,0.004753798883498577,0.0007004634369545249
+quantile,kll-percall,k=100,pareto,3.0,,177828,64,0.004708528751518791,0.0002329624612845283
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+quantile,kll-percall,k=100,pareto,3.0,,562341,1,0.005178236314724953,0.00035149693999916154
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+quantile,kll-percall,k=400,pareto,3.0,,10000,16,0.0007392739273927385,5.0460524446768295e-05
+quantile,kll-percall,k=400,pareto,3.0,,10000,64,0.00093795379537954,0.000155216595109407
+quantile,kll-percall,k=400,pareto,3.0,,10000,256,0.0011323432343234323,0.0003687735968493492
+quantile,kll-percall,k=400,pareto,3.0,,10000,1024,0.001276897689768978,0.00022808432579138335
+quantile,kll-percall,k=400,pareto,3.0,,10000,3600,0.0009122112211221111,0.00015389626855598072
+quantile,kll-percall,k=400,pareto,3.0,,10000,4096,0.0008976897689768976,0.0001337883944440036
+quantile,kll-percall,k=400,pareto,3.0,,17783,1,0.0012635589038294253,0.00011375921414977325
+quantile,kll-percall,k=400,pareto,3.0,,17783,4,0.0007929069350729731,0.0001186740241048963
+quantile,kll-percall,k=400,pareto,3.0,,17783,16,0.000940570860774995,0.00014865546077330588
+quantile,kll-percall,k=400,pareto,3.0,,17783,64,0.001089697228171896,0.00015083565564375819
+quantile,kll-percall,k=400,pareto,3.0,,17783,256,0.001046445700634845,0.0003029705317146476
+quantile,kll-percall,k=400,pareto,3.0,,17783,1024,0.0010440293312354344,0.00011000675885671414
+quantile,kll-percall,k=400,pareto,3.0,,17783,3600,0.0014311402461170606,0.00015462456326044012
+quantile,kll-percall,k=400,pareto,3.0,,17783,4096,0.001344048873762144,0.00012913783246171136
+quantile,kll-percall,k=400,pareto,3.0,,31623,1,0.001151174694359675,9.94706472884383e-05
+quantile,kll-percall,k=400,pareto,3.0,,31623,4,0.001183989094289375,9.930280247749043e-05
+quantile,kll-percall,k=400,pareto,3.0,,31623,16,0.0010611474770472968,7.649984149529603e-05
+quantile,kll-percall,k=400,pareto,3.0,,31623,64,0.0009148394205704583,0.00010401778171095941
+quantile,kll-percall,k=400,pareto,3.0,,31623,256,0.0013710547603474892,0.00010464603024175074
+quantile,kll-percall,k=400,pareto,3.0,,31623,1024,0.0010135612745412644,5.075112913053307e-05
+quantile,kll-percall,k=400,pareto,3.0,,31623,3600,0.0009777213372603743,3.7203522988067644e-05
+quantile,kll-percall,k=400,pareto,3.0,,31623,4096,0.0008949318231320317,0.00016741164394976107
+quantile,kll-percall,k=400,pareto,3.0,,56234,1,0.001379311882890107,0.00018491290426226416
+quantile,kll-percall,k=400,pareto,3.0,,56234,4,0.000748751298645887,0.0002299553489074828
+quantile,kll-percall,k=400,pareto,3.0,,56234,16,0.0010765494161536935,0.00021756100364155403
+quantile,kll-percall,k=400,pareto,3.0,,56234,64,0.0006377817068259464,6.42910657874417e-05
+quantile,kll-percall,k=400,pareto,3.0,,56234,256,0.001131344026745384,0.00037228601709573265
+quantile,kll-percall,k=400,pareto,3.0,,56234,1024,0.0015252813825679613,0.00011052499534914425
+quantile,kll-percall,k=400,pareto,3.0,,56234,3600,0.0008116062877760594,0.00012476979376001269
+quantile,kll-percall,k=400,pareto,3.0,,56234,4096,0.0008777537425827094,5.589502817366861e-05
+quantile,kll-percall,k=400,pareto,3.0,,100000,1,0.0009634983498349835,5.706682914821483e-05
+quantile,kll-percall,k=400,pareto,3.0,,100000,4,0.000649537953795379,4.858586885838992e-05
+quantile,kll-percall,k=400,pareto,3.0,,100000,16,0.0008120462046204618,2.687326028233121e-05
+quantile,kll-percall,k=400,pareto,3.0,,100000,64,0.0009371287128712868,7.86361998671692e-05
+quantile,kll-percall,k=400,pareto,3.0,,100000,256,0.0013874257425742582,0.0003192703640125894
+quantile,kll-percall,k=400,pareto,3.0,,100000,1024,0.0012548184818481863,7.637175490757825e-05
+quantile,kll-percall,k=400,pareto,3.0,,100000,3600,0.0010842244224422443,0.00011401703141939701
+quantile,kll-percall,k=400,pareto,3.0,,100000,4096,0.0010259075907590764,0.0001763978054766943
+quantile,kll-percall,k=400,pareto,3.0,,177828,1,0.0009295510156994542,2.5914489765304412e-05
+quantile,kll-percall,k=400,pareto,3.0,,177828,4,0.0006796480984220971,9.999081928017054e-06
+quantile,kll-percall,k=400,pareto,3.0,,177828,16,0.0009997178272385572,0.0002276942754242146
+quantile,kll-percall,k=400,pareto,3.0,,177828,64,0.0010952787025784048,0.0002923834145594723
+quantile,kll-percall,k=400,pareto,3.0,,177828,256,0.0013334507754034746,0.0002884198249673658
+quantile,kll-percall,k=400,pareto,3.0,,177828,1024,0.0012359671759064753,5.4464038496867856e-05
+quantile,kll-percall,k=400,pareto,3.0,,177828,3600,0.0009534380794851207,9.114249030227085e-05
+quantile,kll-percall,k=400,pareto,3.0,,177828,4096,0.0009699133757089846,4.201698692351195e-05
+quantile,kll-percall,k=400,pareto,3.0,,316228,1,0.001062740752995571,7.486683303428501e-05
+quantile,kll-percall,k=400,pareto,3.0,,316228,4,0.0009926083745149241,0.00017368069071526743
+quantile,kll-percall,k=400,pareto,3.0,,316228,16,0.0008445930164186563,1.9608800024943807e-05
+quantile,kll-percall,k=400,pareto,3.0,,316228,64,0.0009556199810881319,0.00011894730017619176
+quantile,kll-percall,k=400,pareto,3.0,,316228,256,0.00110122741785797,0.00023306141758601837
+quantile,kll-percall,k=400,pareto,3.0,,316228,1024,0.0012192961330361504,0.00017740619896048897
+quantile,kll-percall,k=400,pareto,3.0,,316228,3600,0.0010559624210647036,0.00020599586683022795
+quantile,kll-percall,k=400,pareto,3.0,,316228,4096,0.0010896440972885382,0.00022878752477786278
+quantile,kll-percall,k=400,pareto,3.0,,562341,1,0.0011572845441729948,0.00024193166010826248
+quantile,kll-percall,k=400,pareto,3.0,,562341,4,0.0011724631360851175,0.00023189160952239043
+quantile,kll-percall,k=400,pareto,3.0,,562341,16,0.0010676060964218983,0.00028954042720947566
+quantile,kll-percall,k=400,pareto,3.0,,562341,64,0.0009192821313105413,2.565772191315744e-06
+quantile,kll-percall,k=400,pareto,3.0,,562341,256,0.001162836183109901,0.0001339112615862666
+quantile,kll-percall,k=400,pareto,3.0,,562341,1024,0.0008893213925147184,3.9532003427434775e-05
+quantile,kll-percall,k=400,pareto,3.0,,562341,3600,0.0016115056105950936,0.00026065025675441994
+quantile,kll-percall,k=400,pareto,3.0,,562341,4096,0.0011899513210695733,0.0002197877282817929
+quantile,kll-percall,k=400,pareto,3.0,,1000000,1,0.0008566765676567657,5.268697132252204e-05
+quantile,kll-percall,k=400,pareto,3.0,,1000000,4,0.0011673432343234323,0.00025537380425907534
+quantile,kll-percall,k=400,pareto,3.0,,1000000,16,0.0006427062706270627,4.43405080776089e-05
+quantile,kll-percall,k=400,pareto,3.0,,1000000,64,0.001034118811881188,9.609283356975374e-05
+quantile,kll-percall,k=400,pareto,3.0,,1000000,256,0.0011566204620462046,0.00010458597608631154
+quantile,kll-percall,k=400,pareto,3.0,,1000000,1024,0.001197745874587459,0.00011097378522074252
+quantile,kll-percall,k=400,pareto,3.0,,1000000,3600,0.0008600264026402642,0.00017315218789541118
+quantile,kll-percall,k=400,pareto,3.0,,1000000,4096,0.0013740198019801975,0.0004068572476339731
+quantile,kll-percall,k=400,pareto,3.0,,1778279,1,0.0013211135867064675,0.00017190253739284884
+quantile,kll-percall,k=400,pareto,3.0,,1778279,4,0.0011419656298870028,0.00012360336265885161
+quantile,kll-percall,k=400,pareto,3.0,,1778279,16,0.0010586655818784483,0.0002144751325917775
+quantile,kll-percall,k=400,pareto,3.0,,1778279,64,0.001147919563873502,0.0004968970657310647
+quantile,kll-percall,k=400,pareto,3.0,,1778279,256,0.0011913750101734141,0.00017822747175145868
+quantile,kll-percall,k=400,pareto,3.0,,1778279,1024,0.001173864922171376,0.00015845031619110265
+quantile,kll-percall,k=400,pareto,3.0,,1778279,3600,0.0010857640556638836,0.00033113421410631744
+quantile,kll-percall,k=400,pareto,3.0,,1778279,4096,0.0010681433367241407,0.000249305599513986
+quantile,kll-percall,k=400,pareto,3.0,,3162278,1,0.0008775197456196487,0.0001636285479863047
+quantile,kll-percall,k=400,pareto,3.0,,3162278,4,0.0006315525138719785,1.897793254703903e-05
+quantile,kll-percall,k=400,pareto,3.0,,3162278,16,0.001000855219637305,0.0003037292969546795
+quantile,kll-percall,k=400,pareto,3.0,,3162278,64,0.0009700494411309427,0.00017894951622920055
+quantile,kll-percall,k=400,pareto,3.0,,3162278,256,0.0009730545021293151,8.16892876015971e-05
+quantile,kll-percall,k=400,pareto,3.0,,3162278,1024,0.0009126435042230707,0.0002367000341887584
+quantile,kll-percall,k=400,pareto,3.0,,3162278,3600,0.0010917791253365109,0.00014438173138759186
+quantile,kll-percall,k=400,pareto,3.0,,3162278,4096,0.0009567061963229426,8.759649274513246e-05
+quantile,kll-percall,k=400,pareto,3.0,,5623413,1,0.0009764715377074228,0.00011585392682355553
+quantile,kll-percall,k=400,pareto,3.0,,5623413,4,0.000751868558425742,3.330218208413047e-05
+quantile,kll-percall,k=400,pareto,3.0,,5623413,16,0.0006671173953724121,0.00013037036642418712
+quantile,kll-percall,k=400,pareto,3.0,,5623413,64,0.0011476546313773075,0.0002717248515962897
+quantile,kll-percall,k=400,pareto,3.0,,5623413,256,0.0014004795400026874,0.00017177320611885176
+quantile,kll-percall,k=400,pareto,3.0,,5623413,1024,0.0010772253909372704,8.599073117119708e-05
+quantile,kll-percall,k=400,pareto,3.0,,5623413,3600,0.0014510444888618738,6.442797294563158e-05
+quantile,kll-percall,k=400,pareto,3.0,,5623413,4096,0.0009405739789330887,0.0001042996409962532
+quantile,kll-percall,k=400,pareto,3.0,,10000000,1,0.0011651049504950502,0.00019597739287259254
+quantile,kll-percall,k=400,pareto,3.0,,10000000,4,0.0009015214521452122,4.380260960363659e-05
+quantile,kll-percall,k=400,pareto,3.0,,10000000,16,0.0008337528052805293,9.599679986948664e-05
+quantile,kll-percall,k=400,pareto,3.0,,10000000,64,0.0009526023102310249,0.00011309784263086278
+quantile,kll-percall,k=400,pareto,3.0,,10000000,256,0.0011963821782178224,0.00034541228831224194
+quantile,kll-percall,k=400,pareto,3.0,,10000000,1024,0.0013468910891089117,0.00012780563019764788
+quantile,kll-percall,k=400,pareto,3.0,,10000000,3600,0.0009976201320132016,8.4315656140382e-05
+quantile,kll-percall,k=400,pareto,3.0,,10000000,4096,0.00098096204620462,9.20546576188613e-05
+quantile,kll-percall,k=400,pareto,3.0,,17782794,1,0.0008278494243130495,0.00011357619656698122
+quantile,kll-percall,k=400,pareto,3.0,,17782794,4,0.0011353109560896784,6.707353748401271e-05
+quantile,kll-percall,k=400,pareto,3.0,,17782794,16,0.0018988802121626292,0.0004042317520856561
+quantile,kll-percall,k=400,pareto,3.0,,17782794,64,0.000994275227568575,5.911793178804448e-05
+quantile,kll-percall,k=400,pareto,3.0,,17782794,256,0.000892698745078462,5.276563035550128e-05
+quantile,kll-percall,k=400,pareto,3.0,,17782794,1024,0.0009368453603413115,0.00029522460818408146
+quantile,kll-percall,k=400,pareto,3.0,,17782794,3600,0.0013526292731486586,0.00023089995798079014
+quantile,kll-percall,k=400,pareto,3.0,,17782794,4096,0.0012150856694294,0.00012940544758825547
+quantile,kll-percall,k=400,pareto,3.0,,31622777,1,0.0016319123229420116,0.0005245864579253513
+quantile,kll-percall,k=400,pareto,3.0,,31622777,4,0.0008138233054070651,7.462833773130836e-05
+quantile,kll-percall,k=400,pareto,3.0,,31622777,16,0.0006718392715904306,5.974559243114416e-05
+quantile,kll-percall,k=400,pareto,3.0,,31622777,64,0.001162477027719022,9.519084980081185e-05
+quantile,kll-percall,k=400,pareto,3.0,,31622777,256,0.001327407234674455,0.00017051354927971312
+quantile,kll-percall,k=400,pareto,3.0,,31622777,1024,0.0013032398828040678,0.0003308937597865969
+quantile,kll-percall,k=400,pareto,3.0,,31622777,3600,0.0011405405865228964,0.00016473265278720359
+quantile,kll-percall,k=400,pareto,3.0,,31622777,4096,0.0012331549678402862,0.0001285106834558406
+quantile,kll-percall,k=400,pareto,3.0,,56234133,1,0.0009173520143276372,1.900299154083551e-05
+quantile,kll-percall,k=400,pareto,3.0,,56234133,4,0.0009981122520144985,0.00025199920634362056
+quantile,kll-percall,k=400,pareto,3.0,,56234133,16,0.0011165972480062117,0.00011725116869148036
+quantile,kll-percall,k=400,pareto,3.0,,56234133,64,0.0009253782613563591,0.00019703941767482475
+quantile,kll-percall,k=400,pareto,3.0,,56234133,256,0.0008175014666736377,0.00010509668905424328
+quantile,kll-percall,k=400,pareto,3.0,,56234133,1024,0.0010801970613563356,0.00017228609024189535
+quantile,kll-percall,k=400,pareto,3.0,,56234133,3600,0.0007629414526958595,1.8754420081172095e-05
+quantile,kll-percall,k=400,pareto,3.0,,56234133,4096,0.0014681489473362525,0.00039347593557613177
+quantile,kll-percall,k=400,pareto,3.0,,100000000,1,0.0009369878877887797,0.00010292853239930828
+quantile,kll-percall,k=400,pareto,3.0,,100000000,4,0.001069737194719472,0.00042028162614814895
+quantile,kll-percall,k=400,pareto,3.0,,100000000,16,0.0006669842244224427,4.858866209345623e-05
+quantile,kll-percall,k=400,pareto,3.0,,100000000,64,0.0006331475907590771,3.2757512239452676e-05
+quantile,kll-percall,k=400,pareto,3.0,,100000000,256,0.0012814514851485152,0.00022462567520659135
+quantile,kll-percall,k=400,pareto,3.0,,100000000,1024,0.0013809952805280527,0.0004609846117578078
+quantile,kll-percall,k=400,pareto,3.0,,100000000,3600,0.0011145100660065997,5.6359704435481735e-05
+quantile,kll-percall,k=400,pareto,3.0,,100000000,4096,0.0012191763696369651,0.0002751739708106477
+quantile,kll-percall,k=400,pareto,3.0,,177827941,1,0.0014351942602260869,0.00033099428535826977
+quantile,kll-percall,k=400,pareto,3.0,,177827941,4,0.000843520625589449,6.732179208662477e-05
+quantile,kll-percall,k=400,pareto,3.0,,177827941,16,0.0010482350373884027,3.952378993918109e-05
+quantile,kll-percall,k=400,pareto,3.0,,177827941,64,0.0011547887041989432,0.0001107394277995711
+quantile,kll-percall,k=400,pareto,3.0,,177827941,256,0.0009603029681986653,8.121179346720052e-06
+quantile,kll-percall,k=400,pareto,3.0,,177827941,1024,0.0011658237297610238,0.0001946039292991763
+quantile,kll-percall,k=400,pareto,3.0,,177827941,3600,0.0010556022367555153,9.506692893958561e-05
+quantile,kll-percall,k=400,pareto,3.0,,177827941,4096,0.0012318210510468578,6.666083779640154e-05
+quantile,kll-percall,k=400,pareto,3.0,,316227766,1,0.0008376651920667641,7.367554965069229e-05
+quantile,kll-percall,k=400,pareto,3.0,,316227766,4,0.0009819766064275703,0.00013147030173344028
+quantile,kll-percall,k=400,pareto,3.0,,316227766,16,0.0009048786176555313,6.507202812467395e-05
+quantile,kll-percall,k=400,pareto,3.0,,316227766,64,0.0009546581754374213,9.184658321629123e-05
+quantile,kll-percall,k=400,pareto,3.0,,316227766,256,0.0010892369754132776,7.517058047676803e-05
+quantile,kll-percall,k=400,pareto,3.0,,316227766,1024,0.001344114915879049,0.0003710505745548158
+quantile,kll-percall,k=400,pareto,3.0,,316227766,3600,0.0013269873938770709,0.00015820248821045655
+quantile,kll-percall,k=400,pareto,3.0,,316227766,4096,0.0010934956113987577,0.00011209280260556443
diff --git a/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_grid_1e7_cost/saturation.csv b/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_grid_1e7_cost/saturation.csv
index fc4e6f02..17ca7566 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_grid_1e7_cost/saturation.csv
+++ b/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_grid_1e7_cost/saturation.csv
@@ -379,3 +379,19 @@ quantile,dd,alpha=0.05,pareto,1.1,,1000,0.024921173898693156,mean_relative_value
 quantile,dd,alpha=0.05,pareto,1.5,,1000,0.024473440529436702,mean_relative_value_error,,,,
 quantile,dd,alpha=0.05,pareto,2.0,,1000,0.02463159649785922,mean_relative_value_error,,,,
 quantile,dd,alpha=0.05,pareto,3.0,,1000,0.024517607831075105,mean_relative_value_error,,,,
+quantile,kll-percall,k=25,pareto,1.1,,1000000,0.02030838448844884,mean_rank_err,,,,
+quantile,kll-percall,k=25,pareto,1.5,,not_saturated,0.0181633597359736,mean_rank_err,,,,
+quantile,kll-percall,k=25,pareto,2.0,,not_saturated,0.02521805247524753,mean_rank_err,,,,
+quantile,kll-percall,k=25,pareto,3.0,,not_saturated,0.02907483432343234,mean_rank_err,,,,
+quantile,kll-percall,k=100,pareto,1.1,,1778279,0.006491249834983499,mean_rank_err,,,,
+quantile,kll-percall,k=100,pareto,1.5,,not_saturated,0.009550481518151814,mean_rank_err,,,,
+quantile,kll-percall,k=100,pareto,2.0,,316228,0.006240266996699671,mean_rank_err,,,,
+quantile,kll-percall,k=100,pareto,3.0,,not_saturated,0.005473811881188122,mean_rank_err,,,,
+quantile,kll-percall,k=400,pareto,1.1,,17783,0.0014099495049504954,mean_rank_err,,,,
+quantile,kll-percall,k=400,pareto,1.5,,not_saturated,0.0013603006600660052,mean_rank_err,,,,
+quantile,kll-percall,k=400,pareto,2.0,,562341,0.0013665326732673266,mean_rank_err,,,,
+quantile,kll-percall,k=400,pareto,3.0,,not_saturated,0.001084203630363035,mean_rank_err,,,,
+quantile,dd,alpha=0.1,pareto,1.1,,1000,0.04929709657564954,mean_relative_value_error,,,,
+quantile,dd,alpha=0.1,pareto,1.5,,1000,0.04821490712888921,mean_relative_value_error,,,,
+quantile,dd,alpha=0.1,pareto,2.0,,1000,0.04837709996663131,mean_relative_value_error,,,,
+quantile,dd,alpha=0.1,pareto,3.0,,1000,0.047907961496741557,mean_relative_value_error,,,,
diff --git a/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_grid_1e7_cost/saturation_curve.csv b/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_grid_1e7_cost/saturation_curve.csv
index 71d65126..70f852cf 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_grid_1e7_cost/saturation_curve.csv
+++ b/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_grid_1e7_cost/saturation_curve.csv
@@ -6459,3 +6459,275 @@ quantile,dd,alpha=0.05,pareto,3.0,,1778279,0.024483762920530523,1.61982086252439
 quantile,dd,alpha=0.05,pareto,3.0,,3162278,0.024511203757437098,1.7663396942931932e-06
 quantile,dd,alpha=0.05,pareto,3.0,,5623413,0.024515803174319496,9.275022080026896e-06
 quantile,dd,alpha=0.05,pareto,3.0,,10000000,0.024517607831075105,5.393056150724128e-06
+quantile,kll-percall,k=25,pareto,1.1,,1000,0.02323762376237623,0.0025527343448472186
+quantile,kll-percall,k=25,pareto,1.1,,1778,0.01972750930886114,0.006231576556347655
+quantile,kll-percall,k=25,pareto,1.1,,3162,0.018794095728358412,0.0017081702012475973
+quantile,kll-percall,k=25,pareto,1.1,,5623,0.019386389821624883,0.001735730478286327
+quantile,kll-percall,k=25,pareto,1.1,,10000,0.023120132013201317,0.0015687377895113807
+quantile,kll-percall,k=25,pareto,1.1,,17783,0.02354842547179983,0.005945388136388003
+quantile,kll-percall,k=25,pareto,1.1,,31623,0.018386562022106773,0.0018207550748105261
+quantile,kll-percall,k=25,pareto,1.1,,56234,0.02780949382771261,0.004613162394430273
+quantile,kll-percall,k=25,pareto,1.1,,100000,0.01830795379537954,0.0008933451644772697
+quantile,kll-percall,k=25,pareto,1.1,,177828,0.026686105482132,0.003660714095747814
+quantile,kll-percall,k=25,pareto,1.1,,316228,0.01911897715442895,0.001940701996137877
+quantile,kll-percall,k=25,pareto,1.1,,562341,0.029130915145428444,0.0010014072280946763
+quantile,kll-percall,k=25,pareto,1.1,,1000000,0.020028676567656774,0.0033054075452412374
+quantile,kll-percall,k=25,pareto,1.1,,1778279,0.02528497470754239,0.005343075170713607
+quantile,kll-percall,k=25,pareto,1.1,,3162278,0.01813395203007318,0.0024109693230621385
+quantile,kll-percall,k=25,pareto,1.1,,5623413,0.021643873451929283,0.0021275910541365484
+quantile,kll-percall,k=25,pareto,1.1,,10000000,0.02030838448844884,0.0013264735250949921
+quantile,kll-percall,k=25,pareto,1.5,,1000,0.021435643564356427,0.001024421591643348
+quantile,kll-percall,k=25,pareto,1.5,,1778,0.022573217951716434,0.002664452001503276
+quantile,kll-percall,k=25,pareto,1.5,,3162,0.021619854585078997,0.0025767222768517052
+quantile,kll-percall,k=25,pareto,1.5,,5623,0.020265481999026863,0.003787303281565204
+quantile,kll-percall,k=25,pareto,1.5,,10000,0.02472706270627063,0.00896169722939947
+quantile,kll-percall,k=25,pareto,1.5,,17783,0.023701905758252817,0.003225969460758555
+quantile,kll-percall,k=25,pareto,1.5,,31623,0.01959610902746664,0.003383845441246047
+quantile,kll-percall,k=25,pareto,1.5,,56234,0.025577784296194672,0.0033472562270050045
+quantile,kll-percall,k=25,pareto,1.5,,100000,0.02064508250825083,0.003909356619357436
+quantile,kll-percall,k=25,pareto,1.5,,177828,0.01913550684307921,0.0018471775414590989
+quantile,kll-percall,k=25,pareto,1.5,,316228,0.022047838567076414,0.003485416488819395
+quantile,kll-percall,k=25,pareto,1.5,,562341,0.02316705208107435,0.0022718049368826167
+quantile,kll-percall,k=25,pareto,1.5,,1000000,0.020326356435643556,0.00294145074013735
+quantile,kll-percall,k=25,pareto,1.5,,1778279,0.02340222389193711,0.001061586581086085
+quantile,kll-percall,k=25,pareto,1.5,,3162278,0.016708488274746396,0.0008904777263801567
+quantile,kll-percall,k=25,pareto,1.5,,5623413,0.022116006409949863,0.005360352684931015
+quantile,kll-percall,k=25,pareto,1.5,,10000000,0.0181633597359736,0.0006991133664433392
+quantile,kll-percall,k=25,pareto,2.0,,1000,0.021458745874587442,0.0019622064958520337
+quantile,kll-percall,k=25,pareto,2.0,,1778,0.019413291160387126,0.002952063505538851
+quantile,kll-percall,k=25,pareto,2.0,,3162,0.01714457783539265,0.002739447347879492
+quantile,kll-percall,k=25,pareto,2.0,,5623,0.022341596777497415,0.0021346667927643263
+quantile,kll-percall,k=25,pareto,2.0,,10000,0.02577656765676567,0.004217870989863619
+quantile,kll-percall,k=25,pareto,2.0,,17783,0.02529261917925471,0.005876861114168365
+quantile,kll-percall,k=25,pareto,2.0,,31623,0.022970804242932602,0.001305660172703887
+quantile,kll-percall,k=25,pareto,2.0,,56234,0.026684897888373315,0.0027492475227679676
+quantile,kll-percall,k=25,pareto,2.0,,100000,0.017136864686468647,0.002935692529789011
+quantile,kll-percall,k=25,pareto,2.0,,177828,0.022515662592644314,0.0030749104097267236
+quantile,kll-percall,k=25,pareto,2.0,,316228,0.01886305160361591,0.0010052568623516503
+quantile,kll-percall,k=25,pareto,2.0,,562341,0.023398636427471458,0.005299029497269334
+quantile,kll-percall,k=25,pareto,2.0,,1000000,0.03222734323432344,0.006085860675760331
+quantile,kll-percall,k=25,pareto,2.0,,1778279,0.017519499426575963,0.0011517574297584324
+quantile,kll-percall,k=25,pareto,2.0,,3162278,0.01901771513390595,0.002208647820969057
+quantile,kll-percall,k=25,pareto,2.0,,5623413,0.02057647233916567,0.004274165922370207
+quantile,kll-percall,k=25,pareto,2.0,,10000000,0.02521805247524753,0.0029852749414234765
+quantile,kll-percall,k=25,pareto,3.0,,1000,0.021204620462046197,0.0020209044856567262
+quantile,kll-percall,k=25,pareto,3.0,,1778,0.022712915836015552,0.007954180194527862
+quantile,kll-percall,k=25,pareto,3.0,,3162,0.02417281955899575,0.005135511223654562
+quantile,kll-percall,k=25,pareto,3.0,,5623,0.017494584066267197,0.0013649139020483008
+quantile,kll-percall,k=25,pareto,3.0,,10000,0.027070297029702973,0.0037211514711288697
+quantile,kll-percall,k=25,pareto,3.0,,17783,0.018956031913150265,0.0010751886672771295
+quantile,kll-percall,k=25,pareto,3.0,,31623,0.025521702725248327,0.001869901619704034
+quantile,kll-percall,k=25,pareto,3.0,,56234,0.021412965459863553,0.0020201907669135087
+quantile,kll-percall,k=25,pareto,3.0,,100000,0.01903524752475248,0.002099391895778144
+quantile,kll-percall,k=25,pareto,3.0,,177828,0.02030726171341744,0.004148239279453307
+quantile,kll-percall,k=25,pareto,3.0,,316228,0.02480846693268186,0.004713855043450952
+quantile,kll-percall,k=25,pareto,3.0,,562341,0.02327928769339614,0.004349610811730328
+quantile,kll-percall,k=25,pareto,3.0,,1000000,0.025791224422442246,0.0013532526741385654
+quantile,kll-percall,k=25,pareto,3.0,,1778279,0.01598180522508638,0.0021208494296767813
+quantile,kll-percall,k=25,pareto,3.0,,3162278,0.016483298102537375,0.0011634662201352676
+quantile,kll-percall,k=25,pareto,3.0,,5623413,0.017333707214541926,0.0010767359053110704
+quantile,kll-percall,k=25,pareto,3.0,,10000000,0.02907483432343234,0.004844340470457982
+quantile,kll-percall,k=100,pareto,1.1,,1000,0.005646864686468651,0.0010526500811561031
+quantile,kll-percall,k=100,pareto,1.1,,1778,0.004669688566156951,0.0005295817678984481
+quantile,kll-percall,k=100,pareto,1.1,,3162,0.006294048759714681,0.0008877350212098461
+quantile,kll-percall,k=100,pareto,1.1,,5623,0.00525149829583705,0.0012342309436665351
+quantile,kll-percall,k=100,pareto,1.1,,10000,0.005731353135313534,0.0007465472010337657
+quantile,kll-percall,k=100,pareto,1.1,,17783,0.0059829232093765545,0.00023216475461357297
+quantile,kll-percall,k=100,pareto,1.1,,31623,0.00484805989374196,0.0003505789000308527
+quantile,kll-percall,k=100,pareto,1.1,,56234,0.00890686618187017,0.0006089650892783793
+quantile,kll-percall,k=100,pareto,1.1,,100000,0.006705676567656767,0.0010651963994430555
+quantile,kll-percall,k=100,pareto,1.1,,177828,0.005552317361434505,0.00027244680152573226
+quantile,kll-percall,k=100,pareto,1.1,,316228,0.006127489331651963,0.0003623304308862384
+quantile,kll-percall,k=100,pareto,1.1,,562341,0.007114364495714322,0.0012060704494416261
+quantile,kll-percall,k=100,pareto,1.1,,1000000,0.006991475247524752,0.0003289219938000866
+quantile,kll-percall,k=100,pareto,1.1,,1778279,0.007087735253622128,0.0007947173154838602
+quantile,kll-percall,k=100,pareto,1.1,,3162278,0.006594477678170074,0.0006283412954928877
+quantile,kll-percall,k=100,pareto,1.1,,5623413,0.005258149585078185,0.0008440978882402405
+quantile,kll-percall,k=100,pareto,1.1,,10000000,0.006491249834983499,0.001252406947417045
+quantile,kll-percall,k=100,pareto,1.5,,1000,0.0054455445544554495,0.0006083270162101241
+quantile,kll-percall,k=100,pareto,1.5,,1778,0.004936090909428401,0.00045353238477597327
+quantile,kll-percall,k=100,pareto,1.5,,3162,0.00564940934321136,0.0007390565068350542
+quantile,kll-percall,k=100,pareto,1.5,,5623,0.005493209466776308,0.0004481332344989288
+quantile,kll-percall,k=100,pareto,1.5,,10000,0.00555313531353135,0.0004497478056589133
+quantile,kll-percall,k=100,pareto,1.5,,17783,0.004222716878897022,0.000438537861497696
+quantile,kll-percall,k=100,pareto,1.5,,31623,0.007235249566129175,0.0010783064401803908
+quantile,kll-percall,k=100,pareto,1.5,,56234,0.007180841817154647,0.001647467367952644
+quantile,kll-percall,k=100,pareto,1.5,,100000,0.007121749174917491,0.001189317932200217
+quantile,kll-percall,k=100,pareto,1.5,,177828,0.0059809564194154745,0.0004416542912774705
+quantile,kll-percall,k=100,pareto,1.5,,316228,0.005473238571944018,0.00019576678235259714
+quantile,kll-percall,k=100,pareto,1.5,,562341,0.005992363676449369,0.00025490098926229834
+quantile,kll-percall,k=100,pareto,1.5,,1000000,0.006221003300330032,0.0004527444361910532
+quantile,kll-percall,k=100,pareto,1.5,,1778279,0.006138230170058161,0.0003718115763282885
+quantile,kll-percall,k=100,pareto,1.5,,3162278,0.007914798572212795,0.0014417787194718765
+quantile,kll-percall,k=100,pareto,1.5,,5623413,0.0063789711703445195,0.0009707705057430869
+quantile,kll-percall,k=100,pareto,1.5,,10000000,0.009550481518151814,0.0017109176471526819
+quantile,kll-percall,k=100,pareto,2.0,,1000,0.005178217821782182,0.00043956381941431946
+quantile,kll-percall,k=100,pareto,2.0,,1778,0.006026759031358704,0.0012954124239312182
+quantile,kll-percall,k=100,pareto,2.0,,3162,0.004910707389524533,0.0010736403038225568
+quantile,kll-percall,k=100,pareto,2.0,,5623,0.005099899106040788,0.0004727933480902764
+quantile,kll-percall,k=100,pareto,2.0,,10000,0.005860396039603965,0.0007163421646028494
+quantile,kll-percall,k=100,pareto,2.0,,17783,0.004236990532545921,0.00039652320331718977
+quantile,kll-percall,k=100,pareto,2.0,,31623,0.00609143050724767,0.0009306020352155627
+quantile,kll-percall,k=100,pareto,2.0,,56234,0.005495708584978068,0.000531128784011349
+quantile,kll-percall,k=100,pareto,2.0,,100000,0.005969504950495049,0.0011193197655606482
+quantile,kll-percall,k=100,pareto,2.0,,177828,0.004975195002461311,0.00030331175360508275
+quantile,kll-percall,k=100,pareto,2.0,,316228,0.007102573900078194,0.0004473827854108379
+quantile,kll-percall,k=100,pareto,2.0,,562341,0.006700356864496726,0.0002689297338270232
+quantile,kll-percall,k=100,pareto,2.0,,1000000,0.006149953795379537,0.0007418704003334213
+quantile,kll-percall,k=100,pareto,2.0,,1778279,0.005532909885763638,0.000543991313285548
+quantile,kll-percall,k=100,pareto,2.0,,3162278,0.006432218202261545,0.00023922224696710454
+quantile,kll-percall,k=100,pareto,2.0,,5623413,0.006724333741017702,0.0013404648299858162
+quantile,kll-percall,k=100,pareto,2.0,,10000000,0.006240266996699671,0.000949493802460623
+quantile,kll-percall,k=100,pareto,3.0,,1000,0.004042904290429045,0.0005430923465764267
+quantile,kll-percall,k=100,pareto,3.0,,1778,0.004821971510986868,0.0008358297711728816
+quantile,kll-percall,k=100,pareto,3.0,,3162,0.005583674116937312,0.0003703088245348024
+quantile,kll-percall,k=100,pareto,3.0,,5623,0.004869304465570157,0.00019298403762648837
+quantile,kll-percall,k=100,pareto,3.0,,10000,0.005677227722772275,0.0006806215984080919
+quantile,kll-percall,k=100,pareto,3.0,,17783,0.005933086982431585,0.0016612473290252287
+quantile,kll-percall,k=100,pareto,3.0,,31623,0.005963448920549009,0.0010315191303900705
+quantile,kll-percall,k=100,pareto,3.0,,56234,0.006042931639609175,0.0013801992222532327
+quantile,kll-percall,k=100,pareto,3.0,,100000,0.004871848184818484,0.0005206231211244522
+quantile,kll-percall,k=100,pareto,3.0,,177828,0.005321845093612539,0.0005276253313783397
+quantile,kll-percall,k=100,pareto,3.0,,316228,0.005250735453397851,0.0006109641391467222
+quantile,kll-percall,k=100,pareto,3.0,,562341,0.00553093089054647,0.0015411704882016565
+quantile,kll-percall,k=100,pareto,3.0,,1000000,0.007164333333333334,0.0014071160138622023
+quantile,kll-percall,k=100,pareto,3.0,,1778279,0.004261362633854593,0.00046277358006381917
+quantile,kll-percall,k=100,pareto,3.0,,3162278,0.005040820355936875,0.0008668857148539208
+quantile,kll-percall,k=100,pareto,3.0,,5623413,0.005198454491543974,0.0006976964019339257
+quantile,kll-percall,k=100,pareto,3.0,,10000000,0.005473811881188122,0.0007479520458950124
+quantile,kll-percall,k=400,pareto,1.1,,1000,0.0007689768976897694,6.425056875885078e-05
+quantile,kll-percall,k=400,pareto,1.1,,1778,0.0009372343308571566,7.600331285349055e-05
+quantile,kll-percall,k=400,pareto,1.1,,3162,0.0012822230989702364,0.00045063972875900124
+quantile,kll-percall,k=400,pareto,1.1,,5623,0.0012156929724628145,0.00021806165412687238
+quantile,kll-percall,k=400,pareto,1.1,,10000,0.0013066006600660075,3.774660046840334e-05
+quantile,kll-percall,k=400,pareto,1.1,,17783,0.0014745903539350148,0.00021288954494241754
+quantile,kll-percall,k=400,pareto,1.1,,31623,0.0023933075406013214,0.0005592467054018927
+quantile,kll-percall,k=400,pareto,1.1,,56234,0.0012191149406223488,0.00013879641873095215
+quantile,kll-percall,k=400,pareto,1.1,,100000,0.001514191419141913,0.0004205623925001738
+quantile,kll-percall,k=400,pareto,1.1,,177828,0.0014607826259378741,0.00010964789400804908
+quantile,kll-percall,k=400,pareto,1.1,,316228,0.0017098984143579226,0.0005291948321576935
+quantile,kll-percall,k=400,pareto,1.1,,562341,0.0015813298348512134,0.00022875108062877885
+quantile,kll-percall,k=400,pareto,1.1,,1000000,0.0016314290429042904,0.00021639130690471076
+quantile,kll-percall,k=400,pareto,1.1,,1778279,0.0015792234891131814,0.0002261565890286192
+quantile,kll-percall,k=400,pareto,1.1,,3162278,0.0013403975352463346,0.00014743407401473583
+quantile,kll-percall,k=400,pareto,1.1,,5623413,0.0017324733810825076,0.0003461498900347397
+quantile,kll-percall,k=400,pareto,1.1,,10000000,0.0014099495049504954,0.00011915018655674588
+quantile,kll-percall,k=400,pareto,1.5,,1000,0.0006567656765676572,8.861862430427434e-05
+quantile,kll-percall,k=400,pareto,1.5,,1778,0.0008451666313987975,0.0001438852371355671
+quantile,kll-percall,k=400,pareto,1.5,,3162,0.0013933822224727222,0.000287048337682376
+quantile,kll-percall,k=400,pareto,1.5,,5623,0.001038433027012462,5.834346153452067e-05
+quantile,kll-percall,k=400,pareto,1.5,,10000,0.0014468646864686475,0.0001756901175217578
+quantile,kll-percall,k=400,pareto,1.5,,17783,0.001518270592171967,0.00020942321391337877
+quantile,kll-percall,k=400,pareto,1.5,,31623,0.0015657004463372028,0.00015891879080850372
+quantile,kll-percall,k=400,pareto,1.5,,56234,0.0016867671402769977,0.0005209400013177305
+quantile,kll-percall,k=400,pareto,1.5,,100000,0.0012206270627062707,0.00020266649027779436
+quantile,kll-percall,k=400,pareto,1.5,,177828,0.0011629764096593176,8.745181880693319e-05
+quantile,kll-percall,k=400,pareto,1.5,,316228,0.0015480625563599958,0.00017481657325350389
+quantile,kll-percall,k=400,pareto,1.5,,562341,0.0013744563090963187,4.6365288261299834e-05
+quantile,kll-percall,k=400,pareto,1.5,,1000000,0.001051171617161716,0.0001366013847572348
+quantile,kll-percall,k=400,pareto,1.5,,1778279,0.0011681167531918091,8.809910349648186e-05
+quantile,kll-percall,k=400,pareto,1.5,,3162278,0.0011675616088904714,0.00015638375072308063
+quantile,kll-percall,k=400,pareto,1.5,,5623413,0.0015310344288941788,7.050604451890734e-05
+quantile,kll-percall,k=400,pareto,1.5,,10000000,0.0013603006600660052,0.00018246916577142333
+quantile,kll-percall,k=400,pareto,2.0,,1000,0.0006501650165016506,0.00010070063565935556
+quantile,kll-percall,k=400,pareto,2.0,,1778,0.0004449320072614637,6.398712693967644e-05
+quantile,kll-percall,k=400,pareto,2.0,,3162,0.0011936506743653503,0.00042702939013992774
+quantile,kll-percall,k=400,pareto,2.0,,5623,0.0014083540667778303,0.00033824353997846484
+quantile,kll-percall,k=400,pareto,2.0,,10000,0.001117161716171619,0.00012006535342746387
+quantile,kll-percall,k=400,pareto,2.0,,17783,0.001108315521424493,0.00015189064361392736
+quantile,kll-percall,k=400,pareto,2.0,,31623,0.0018451738922113442,0.00027408875197623575
+quantile,kll-percall,k=400,pareto,2.0,,56234,0.001260718560386108,0.00019555222705721766
+quantile,kll-percall,k=400,pareto,2.0,,100000,0.0013521452145214524,0.00022381062984294165
+quantile,kll-percall,k=400,pareto,2.0,,177828,0.0017470814494905216,0.0003615920345762457
+quantile,kll-percall,k=400,pareto,2.0,,316228,0.00208327024437521,0.00029041916686753133
+quantile,kll-percall,k=400,pareto,2.0,,562341,0.0013667228433086708,0.00014136826821005023
+quantile,kll-percall,k=400,pareto,2.0,,1000000,0.0013276072607260724,0.00015394651039792173
+quantile,kll-percall,k=400,pareto,2.0,,1778279,0.001911022411613875,0.0005011550395932183
+quantile,kll-percall,k=400,pareto,2.0,,3162278,0.0012482992244570183,0.0003791657494265309
+quantile,kll-percall,k=400,pareto,2.0,,5623413,0.0011727715849605355,0.00011852017863912354
+quantile,kll-percall,k=400,pareto,2.0,,10000000,0.0013665326732673266,0.0001568462499777369
+quantile,kll-percall,k=400,pareto,3.0,,1000,0.0006171617161716175,4.8616897236489204e-05
+quantile,kll-percall,k=400,pareto,3.0,,1778,0.0004435955406564258,1.9650490753921204e-05
+quantile,kll-percall,k=400,pareto,3.0,,3162,0.0008780005135238388,3.407484855739936e-05
+quantile,kll-percall,k=400,pareto,3.0,,5623,0.0006933392965830467,5.173707689919844e-05
+quantile,kll-percall,k=400,pareto,3.0,,10000,0.0010198019801980198,7.980181640976107e-05
+quantile,kll-percall,k=400,pareto,3.0,,17783,0.0011416788645068159,8.488672679066145e-05
+quantile,kll-percall,k=400,pareto,3.0,,31623,0.0014709851594209781,0.0004469436970294926
+quantile,kll-percall,k=400,pareto,3.0,,56234,0.0009812334151578545,0.00011963075307030836
+quantile,kll-percall,k=400,pareto,3.0,,100000,0.0009146534653465344,0.00010485921368188979
+quantile,kll-percall,k=400,pareto,3.0,,177828,0.0010429984222526483,0.0001952704540683916
+quantile,kll-percall,k=400,pareto,3.0,,316228,0.0013552852432870946,0.0002520946714085965
+quantile,kll-percall,k=400,pareto,3.0,,562341,0.0014638379659504843,5.8681626301226094e-05
+quantile,kll-percall,k=400,pareto,3.0,,1000000,0.0009432739273927392,0.00020027068906421672
+quantile,kll-percall,k=400,pareto,3.0,,1778279,0.0008421077762586299,0.00010323972106542633
+quantile,kll-percall,k=400,pareto,3.0,,3162278,0.0008838683252187072,0.00016817036665650592
+quantile,kll-percall,k=400,pareto,3.0,,5623413,0.0012247762418061824,0.00035436850024614906
+quantile,kll-percall,k=400,pareto,3.0,,10000000,0.001084203630363035,0.00019954471859933494
+quantile,dd,alpha=0.1,pareto,1.1,,1000,0.04966205141826915,0.00037316500749312776
+quantile,dd,alpha=0.1,pareto,1.1,,1778,0.04938663093189283,0.0005952104958461708
+quantile,dd,alpha=0.1,pareto,1.1,,3162,0.04876829003840194,7.749500197564912e-06
+quantile,dd,alpha=0.1,pareto,1.1,,5623,0.04991889037973194,0.00040330491195378533
+quantile,dd,alpha=0.1,pareto,1.1,,10000,0.04891946571822738,0.0007477850163904845
+quantile,dd,alpha=0.1,pareto,1.1,,17783,0.04944057977040789,0.0006648071112527539
+quantile,dd,alpha=0.1,pareto,1.1,,31623,0.04967973711686292,0.00017834870944200958
+quantile,dd,alpha=0.1,pareto,1.1,,56234,0.049824816422823735,0.0003640394304384578
+quantile,dd,alpha=0.1,pareto,1.1,,100000,0.04954351893831512,0.00038630363918339757
+quantile,dd,alpha=0.1,pareto,1.1,,177828,0.04888207520745023,0.0004686937266327248
+quantile,dd,alpha=0.1,pareto,1.1,,316228,0.04900398557602018,0.0002744334282859706
+quantile,dd,alpha=0.1,pareto,1.1,,562341,0.04904849084189566,0.0001738533497194691
+quantile,dd,alpha=0.1,pareto,1.1,,1000000,0.04906520788791091,8.582734738367153e-05
+quantile,dd,alpha=0.1,pareto,1.1,,1778279,0.049142856525489664,9.977230452430167e-05
+quantile,dd,alpha=0.1,pareto,1.1,,3162278,0.049161324941796064,0.00010782798437686576
+quantile,dd,alpha=0.1,pareto,1.1,,5623413,0.04935094855918182,3.041566727816725e-05
+quantile,dd,alpha=0.1,pareto,1.1,,10000000,0.04929709657564954,3.6635993752430935e-05
+quantile,dd,alpha=0.1,pareto,1.5,,1000,0.04886891288669959,0.0008372852688485456
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+quantile,dd,alpha=0.1,pareto,1.5,,3162,0.04941312301805323,0.00031078224455605656
+quantile,dd,alpha=0.1,pareto,1.5,,5623,0.04843961758890051,0.00019283810855155056
+quantile,dd,alpha=0.1,pareto,1.5,,10000,0.048622827061632845,0.00020757512344772298
+quantile,dd,alpha=0.1,pareto,1.5,,17783,0.048490050236762394,0.00037819549604931486
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+quantile,dd,alpha=0.1,pareto,1.5,,56234,0.04819449709400785,8.250641442654972e-05
+quantile,dd,alpha=0.1,pareto,1.5,,100000,0.04823031204223116,0.0002593270769954371
+quantile,dd,alpha=0.1,pareto,1.5,,177828,0.04814562868398262,0.00012698271105589527
+quantile,dd,alpha=0.1,pareto,1.5,,316228,0.04816354090046009,8.639720132364197e-05
+quantile,dd,alpha=0.1,pareto,1.5,,562341,0.04817937180760434,5.1459215889339415e-05
+quantile,dd,alpha=0.1,pareto,1.5,,1000000,0.048129034244712376,1.841326206841574e-05
+quantile,dd,alpha=0.1,pareto,1.5,,1778279,0.04815989156527572,3.625711302300438e-05
+quantile,dd,alpha=0.1,pareto,1.5,,3162278,0.04818986936626588,5.955019609656601e-05
+quantile,dd,alpha=0.1,pareto,1.5,,5623413,0.048273852866074836,5.32209815449222e-06
+quantile,dd,alpha=0.1,pareto,1.5,,10000000,0.04821490712888921,6.672729476498839e-06
+quantile,dd,alpha=0.1,pareto,2.0,,1000,0.0479083322184796,0.00042501642911604664
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+quantile,dd,alpha=0.1,pareto,2.0,,56234,0.048222766756323,5.6173832733196966e-05
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+quantile,dd,alpha=0.1,pareto,2.0,,177828,0.04825214331846647,3.2277895671728526e-05
+quantile,dd,alpha=0.1,pareto,2.0,,316228,0.04831233773626455,4.0143644174075496e-05
+quantile,dd,alpha=0.1,pareto,2.0,,562341,0.048337479744294316,4.828799497456752e-05
+quantile,dd,alpha=0.1,pareto,2.0,,1000000,0.04830375834163406,3.659243375458483e-06
+quantile,dd,alpha=0.1,pareto,2.0,,1778279,0.04830942799032912,2.4783446215328894e-05
+quantile,dd,alpha=0.1,pareto,2.0,,3162278,0.04835202981725525,2.601130920776609e-05
+quantile,dd,alpha=0.1,pareto,2.0,,5623413,0.048400135938572286,2.6966850976433785e-05
+quantile,dd,alpha=0.1,pareto,2.0,,10000000,0.04837709996663131,2.3565771347070403e-05
+quantile,dd,alpha=0.1,pareto,3.0,,1000,0.04737218836620722,0.0004945811177315289
+quantile,dd,alpha=0.1,pareto,3.0,,1778,0.047857402160851936,0.0006760563822894943
+quantile,dd,alpha=0.1,pareto,3.0,,3162,0.04763471068838443,0.0004470931390722623
+quantile,dd,alpha=0.1,pareto,3.0,,5623,0.047646361061305736,0.0005838573954635599
+quantile,dd,alpha=0.1,pareto,3.0,,10000,0.047817543259386176,0.0003005441595673318
+quantile,dd,alpha=0.1,pareto,3.0,,17783,0.0479324329027803,0.00013783436117957982
+quantile,dd,alpha=0.1,pareto,3.0,,31623,0.04801405439277551,9.63660215958414e-05
+quantile,dd,alpha=0.1,pareto,3.0,,56234,0.04821639015454274,7.238807805665859e-05
+quantile,dd,alpha=0.1,pareto,3.0,,100000,0.04811531581997181,0.00010653927606329438
+quantile,dd,alpha=0.1,pareto,3.0,,177828,0.04793665929630873,0.00010871775330850251
+quantile,dd,alpha=0.1,pareto,3.0,,316228,0.04791854250823327,3.5777609694733156e-05
+quantile,dd,alpha=0.1,pareto,3.0,,562341,0.04793622289385819,2.851877622889069e-06
+quantile,dd,alpha=0.1,pareto,3.0,,1000000,0.04792490056891215,8.891133140547888e-06
+quantile,dd,alpha=0.1,pareto,3.0,,1778279,0.047921872070835723,9.28892296610222e-06
+quantile,dd,alpha=0.1,pareto,3.0,,3162278,0.04789885358918111,9.343143765979885e-06
+quantile,dd,alpha=0.1,pareto,3.0,,5623413,0.047920380813021614,1.1661174159887452e-05
+quantile,dd,alpha=0.1,pareto,3.0,,10000000,0.047907961496741557,5.862788126295711e-06
diff --git a/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_grid_1e7_cost/saturation_merge_curve.csv b/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_grid_1e7_cost/saturation_merge_curve.csv
index 9759d7b8..98632c71 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_grid_1e7_cost/saturation_merge_curve.csv
+++ b/rqe-optimizer/results/autosketch-vs-asap-inputs/saturation/out_grid_1e7_cost/saturation_merge_curve.csv
@@ -1903,3 +1903,1091 @@ quantile,dd,alpha=0.05,pareto,3.0,,10000000,1,0.024517607831075105,5.39305615072
 quantile,dd,alpha=0.05,pareto,3.0,,10000000,4,0.024517607831075105,5.393056150724128e-06
 quantile,dd,alpha=0.05,pareto,3.0,,10000000,16,0.024517607831075105,5.393056150724128e-06
 quantile,dd,alpha=0.05,pareto,3.0,,10000000,64,0.024517607831075105,5.393056150724128e-06
+quantile,kll-percall,k=25,pareto,1.1,,1000,1,0.02323762376237623,0.0025527343448472186
+quantile,kll-percall,k=25,pareto,1.1,,1000,4,0.01697689768976897,0.0021534318371758967
+quantile,kll-percall,k=25,pareto,1.1,,1000,16,0.021537953795379528,0.0018738464811755482
+quantile,kll-percall,k=25,pareto,1.1,,1000,64,0.022333333333333316,0.002369643858526238
+quantile,kll-percall,k=25,pareto,1.1,,1778,1,0.01972750930886114,0.006231576556347655
+quantile,kll-percall,k=25,pareto,1.1,,1778,4,0.02158122561412497,0.0022308393591253333
+quantile,kll-percall,k=25,pareto,1.1,,1778,16,0.021789268915642968,0.0009861855442138399
+quantile,kll-percall,k=25,pareto,1.1,,1778,64,0.023403609202315056,0.003965332232659372
+quantile,kll-percall,k=25,pareto,1.1,,3162,1,0.018794095728358412,0.0017081702012475973
+quantile,kll-percall,k=25,pareto,1.1,,3162,4,0.021086750041228033,0.00485335056620219
+quantile,kll-percall,k=25,pareto,1.1,,3162,16,0.018487359172349876,0.0014066135916217361
+quantile,kll-percall,k=25,pareto,1.1,,3162,64,0.016766386316050957,0.0009456060530867661
+quantile,kll-percall,k=25,pareto,1.1,,5623,1,0.019386389821624883,0.001735730478286327
+quantile,kll-percall,k=25,pareto,1.1,,5623,4,0.016479176461128234,0.0018953739141280219
+quantile,kll-percall,k=25,pareto,1.1,,5623,16,0.02547826025711231,0.0037527799601097525
+quantile,kll-percall,k=25,pareto,1.1,,5623,64,0.018017025782250996,0.0023509737182160102
+quantile,kll-percall,k=25,pareto,1.1,,10000,1,0.023120132013201317,0.0015687377895113807
+quantile,kll-percall,k=25,pareto,1.1,,10000,4,0.02482409240924092,0.005263654031544265
+quantile,kll-percall,k=25,pareto,1.1,,10000,16,0.01816468646864686,0.0011640518075119936
+quantile,kll-percall,k=25,pareto,1.1,,10000,64,0.01894158415841584,0.0011920879795298087
+quantile,kll-percall,k=25,pareto,1.1,,17783,1,0.02354842547179983,0.005945388136388003
+quantile,kll-percall,k=25,pareto,1.1,,17783,4,0.017330034302423664,0.0023399939499036434
+quantile,kll-percall,k=25,pareto,1.1,,17783,16,0.0225476439563205,0.0013446826245810356
+quantile,kll-percall,k=25,pareto,1.1,,17783,64,0.022703945196296604,0.0033948074383012166
+quantile,kll-percall,k=25,pareto,1.1,,31623,1,0.018386562022106773,0.0018207550748105261
+quantile,kll-percall,k=25,pareto,1.1,,31623,4,0.02273683492056634,0.0013633439828927372
+quantile,kll-percall,k=25,pareto,1.1,,31623,16,0.020457653487576253,0.0067745792302653296
+quantile,kll-percall,k=25,pareto,1.1,,31623,64,0.019788567225947528,0.0002507346996027797
+quantile,kll-percall,k=25,pareto,1.1,,56234,1,0.02780949382771261,0.004613162394430273
+quantile,kll-percall,k=25,pareto,1.1,,56234,4,0.024579911311186597,0.0011834979227864561
+quantile,kll-percall,k=25,pareto,1.1,,56234,16,0.026994805181695395,0.0023685396033063105
+quantile,kll-percall,k=25,pareto,1.1,,56234,64,0.02130489863724788,0.0008752008442347163
+quantile,kll-percall,k=25,pareto,1.1,,100000,1,0.01830795379537954,0.0008933451644772697
+quantile,kll-percall,k=25,pareto,1.1,,100000,4,0.02157135313531353,0.00397315068484919
+quantile,kll-percall,k=25,pareto,1.1,,100000,16,0.01757567656765677,0.001604589185649983
+quantile,kll-percall,k=25,pareto,1.1,,100000,64,0.02223023102310232,0.0012702594436268695
+quantile,kll-percall,k=25,pareto,1.1,,177828,1,0.026686105482132,0.003660714095747814
+quantile,kll-percall,k=25,pareto,1.1,,177828,4,0.019452975326549455,0.002664216726139938
+quantile,kll-percall,k=25,pareto,1.1,,177828,16,0.023059716323207996,0.0005441655545630017
+quantile,kll-percall,k=25,pareto,1.1,,177828,64,0.024211420669700418,0.004468975682324813
+quantile,kll-percall,k=25,pareto,1.1,,316228,1,0.01911897715442895,0.001940701996137877
+quantile,kll-percall,k=25,pareto,1.1,,316228,4,0.021536006251244296,0.0012396220043146
+quantile,kll-percall,k=25,pareto,1.1,,316228,16,0.02443668104113876,0.0022902215883634103
+quantile,kll-percall,k=25,pareto,1.1,,316228,64,0.023503436193069705,0.0042114538600691994
+quantile,kll-percall,k=25,pareto,1.1,,562341,1,0.029130915145428444,0.0010014072280946763
+quantile,kll-percall,k=25,pareto,1.1,,562341,4,0.018168611304359726,0.0010112280617497543
+quantile,kll-percall,k=25,pareto,1.1,,562341,16,0.03157477308598732,0.00262862766796993
+quantile,kll-percall,k=25,pareto,1.1,,562341,64,0.020652076304100344,0.0003041410549228582
+quantile,kll-percall,k=25,pareto,1.1,,1000000,1,0.020028676567656774,0.0033054075452412374
+quantile,kll-percall,k=25,pareto,1.1,,1000000,4,0.021998313531353137,0.002855535433843824
+quantile,kll-percall,k=25,pareto,1.1,,1000000,16,0.017946108910891087,0.0009402721355820648
+quantile,kll-percall,k=25,pareto,1.1,,1000000,64,0.022094270627062707,0.0017514092317913493
+quantile,kll-percall,k=25,pareto,1.1,,1778279,1,0.02528497470754239,0.005343075170713607
+quantile,kll-percall,k=25,pareto,1.1,,1778279,4,0.019288142642353078,0.0004128225028958336
+quantile,kll-percall,k=25,pareto,1.1,,1778279,16,0.026886999657920088,0.002316889869088004
+quantile,kll-percall,k=25,pareto,1.1,,1778279,64,0.01740660622446254,0.0013786517111033184
+quantile,kll-percall,k=25,pareto,1.1,,3162278,1,0.01813395203007318,0.0024109693230621385
+quantile,kll-percall,k=25,pareto,1.1,,3162278,4,0.015977952786206045,0.0008885329691140015
+quantile,kll-percall,k=25,pareto,1.1,,3162278,16,0.01868501366950207,0.0014270592457396789
+quantile,kll-percall,k=25,pareto,1.1,,3162278,64,0.01861894586886113,0.0007986431749659726
+quantile,kll-percall,k=25,pareto,1.1,,5623413,1,0.021643873451929283,0.0021275910541365484
+quantile,kll-percall,k=25,pareto,1.1,,5623413,4,0.0237397728380824,0.0037471341636394714
+quantile,kll-percall,k=25,pareto,1.1,,5623413,16,0.019035945072876384,0.0022591307852041793
+quantile,kll-percall,k=25,pareto,1.1,,5623413,64,0.01967792157538491,0.0019326502201177972
+quantile,kll-percall,k=25,pareto,1.1,,10000000,1,0.02030838448844884,0.0013264735250949921
+quantile,kll-percall,k=25,pareto,1.1,,10000000,4,0.02139792013201321,0.0022910134958208667
+quantile,kll-percall,k=25,pareto,1.1,,10000000,16,0.019942670627062713,0.0013324071929080366
+quantile,kll-percall,k=25,pareto,1.1,,10000000,64,0.024577299009900994,0.0029343105761575855
+quantile,kll-percall,k=25,pareto,1.5,,1000,1,0.021435643564356427,0.001024421591643348
+quantile,kll-percall,k=25,pareto,1.5,,1000,4,0.020924092409240907,0.0020119673759940245
+quantile,kll-percall,k=25,pareto,1.5,,1000,16,0.020514851485148502,0.002453868065622521
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+quantile,kll-percall,k=25,pareto,1.5,,1778,1,0.022573217951716434,0.002664452001503276
+quantile,kll-percall,k=25,pareto,1.5,,1778,4,0.01999480262986929,0.0027788173426413296
+quantile,kll-percall,k=25,pareto,1.5,,1778,16,0.026761518671552197,0.005544004269813043
+quantile,kll-percall,k=25,pareto,1.5,,1778,64,0.025814260841157243,0.006175326375276604
+quantile,kll-percall,k=25,pareto,1.5,,3162,1,0.021619854585078997,0.0025767222768517052
+quantile,kll-percall,k=25,pareto,1.5,,3162,4,0.02197840277386372,0.0010502234480196917
+quantile,kll-percall,k=25,pareto,1.5,,3162,16,0.018595929801708825,0.0027242290030775993
+quantile,kll-percall,k=25,pareto,1.5,,3162,64,0.024632987017866873,0.0016087852494223846
+quantile,kll-percall,k=25,pareto,1.5,,5623,1,0.020265481999026863,0.003787303281565204
+quantile,kll-percall,k=25,pareto,1.5,,5623,4,0.018752788670295093,0.0020630832351091004
+quantile,kll-percall,k=25,pareto,1.5,,5623,16,0.019081506941375278,0.002505011675282412
+quantile,kll-percall,k=25,pareto,1.5,,5623,64,0.021901889281939046,0.005187435449283877
+quantile,kll-percall,k=25,pareto,1.5,,10000,1,0.02472706270627063,0.00896169722939947
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+quantile,kll-percall,k=25,pareto,1.5,,562341,1,0.02316705208107435,0.0022718049368826167
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+quantile,kll-percall,k=25,pareto,1.5,,1778279,16,0.024895390152473537,0.005856159806270706
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+quantile,kll-percall,k=25,pareto,1.5,,3162278,4,0.01987365203415409,0.0033497512491121894
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+quantile,kll-percall,k=25,pareto,2.0,,10000,1,0.02577656765676567,0.004217870989863619
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+quantile,kll-percall,k=25,pareto,2.0,,10000,16,0.022347524752475242,0.0025347455763997354
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+quantile,kll-percall,k=25,pareto,2.0,,3162278,4,0.017801972504188645,0.0026250874647591083
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+quantile,kll-percall,k=25,pareto,2.0,,3162278,64,0.020789233513175496,0.002184720679364275
+quantile,kll-percall,k=25,pareto,2.0,,5623413,1,0.02057647233916567,0.004274165922370207
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+quantile,kll-percall,k=25,pareto,2.0,,5623413,16,0.022677941232122512,0.0041879325809386645
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+quantile,kll-percall,k=25,pareto,2.0,,10000000,1,0.02521805247524753,0.0029852749414234765
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+quantile,kll-percall,k=25,pareto,2.0,,10000000,16,0.020479714521452152,0.00027298820390523254
+quantile,kll-percall,k=25,pareto,2.0,,10000000,64,0.02213914356435644,0.004253654868021596
+quantile,kll-percall,k=25,pareto,3.0,,1000,1,0.021204620462046197,0.0020209044856567262
+quantile,kll-percall,k=25,pareto,3.0,,1000,4,0.027947194719471935,0.002330208297522623
+quantile,kll-percall,k=25,pareto,3.0,,1000,16,0.017039603960396027,0.002522849214674607
+quantile,kll-percall,k=25,pareto,3.0,,1000,64,0.02044884488448843,0.0013713774777319786
+quantile,kll-percall,k=25,pareto,3.0,,1778,1,0.022712915836015552,0.007954180194527862
+quantile,kll-percall,k=25,pareto,3.0,,1778,4,0.02650929772392312,0.004948960882001717
+quantile,kll-percall,k=25,pareto,3.0,,1778,16,0.025046312280271904,0.004464866446884659
+quantile,kll-percall,k=25,pareto,3.0,,1778,64,0.021701544732650988,0.0012932391138588705
+quantile,kll-percall,k=25,pareto,3.0,,3162,1,0.02417281955899575,0.005135511223654562
+quantile,kll-percall,k=25,pareto,3.0,,3162,4,0.013000356961692374,0.00027603737090550274
+quantile,kll-percall,k=25,pareto,3.0,,3162,16,0.016810265466774384,0.002546254103486205
+quantile,kll-percall,k=25,pareto,3.0,,3162,64,0.017260663447748955,0.0007339168029963307
+quantile,kll-percall,k=25,pareto,3.0,,5623,1,0.017494584066267197,0.0013649139020483008
+quantile,kll-percall,k=25,pareto,3.0,,5623,4,0.017802554219498067,0.002927525022851814
+quantile,kll-percall,k=25,pareto,3.0,,5623,16,0.01692472395025382,0.0014435257340881242
+quantile,kll-percall,k=25,pareto,3.0,,5623,64,0.02012012191793606,0.0027390272019124865
+quantile,kll-percall,k=25,pareto,3.0,,10000,1,0.027070297029702973,0.0037211514711288697
+quantile,kll-percall,k=25,pareto,3.0,,10000,4,0.022138943894389442,0.003164309673738286
+quantile,kll-percall,k=25,pareto,3.0,,10000,16,0.0197023102310231,0.0012667841677563333
+quantile,kll-percall,k=25,pareto,3.0,,10000,64,0.019223762376237626,0.0002929092641236235
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+quantile,kll-percall,k=25,pareto,3.0,,17783,4,0.021096029526475116,0.0029488222551200998
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+quantile,kll-percall,k=25,pareto,3.0,,17783,64,0.020248451769767875,0.003945663580274214
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+quantile,kll-percall,k=25,pareto,3.0,,56234,1,0.021412965459863553,0.0020201907669135087
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+quantile,kll-percall,k=100,pareto,1.5,,31623,64,0.004606509507795478,0.0005580199483399043
+quantile,kll-percall,k=100,pareto,1.5,,56234,1,0.007180841817154647,0.001647467367952644
+quantile,kll-percall,k=100,pareto,1.5,,56234,4,0.003953311076030602,0.0006831339287341027
+quantile,kll-percall,k=100,pareto,1.5,,56234,16,0.005751755600214142,0.0011450121543556328
+quantile,kll-percall,k=100,pareto,1.5,,56234,64,0.006963291413965525,0.0013839489536850394
+quantile,kll-percall,k=100,pareto,1.5,,100000,1,0.007121749174917491,0.001189317932200217
+quantile,kll-percall,k=100,pareto,1.5,,100000,4,0.004554026402640262,0.0008591226478931344
+quantile,kll-percall,k=100,pareto,1.5,,100000,16,0.005179108910891089,0.0007212318409692766
+quantile,kll-percall,k=100,pareto,1.5,,100000,64,0.0049110561056105615,0.00031312239961071267
+quantile,kll-percall,k=100,pareto,1.5,,177828,1,0.0059809564194154745,0.0004416542912774705
+quantile,kll-percall,k=100,pareto,1.5,,177828,4,0.004678060626090948,0.00043502983522340153
+quantile,kll-percall,k=100,pareto,1.5,,177828,16,0.005457894530933629,0.0006642146838325713
+quantile,kll-percall,k=100,pareto,1.5,,177828,64,0.004541602888273173,0.00019214529258950407
+quantile,kll-percall,k=100,pareto,1.5,,316228,1,0.005473238571944018,0.00019576678235259714
+quantile,kll-percall,k=100,pareto,1.5,,316228,4,0.006240167358881425,0.0016392313934894646
+quantile,kll-percall,k=100,pareto,1.5,,316228,16,0.00429766157358744,0.0002665230828407216
+quantile,kll-percall,k=100,pareto,1.5,,316228,64,0.00548975378962691,0.00046469434488991316
+quantile,kll-percall,k=100,pareto,1.5,,562341,1,0.005992363676449369,0.00025490098926229834
+quantile,kll-percall,k=100,pareto,1.5,,562341,4,0.005505677254202131,0.0006164354156051886
+quantile,kll-percall,k=100,pareto,1.5,,562341,16,0.006689335399260904,0.001576021776941051
+quantile,kll-percall,k=100,pareto,1.5,,562341,64,0.005573550345053022,0.00011038094133136302
+quantile,kll-percall,k=100,pareto,1.5,,1000000,1,0.006221003300330032,0.0004527444361910532
+quantile,kll-percall,k=100,pareto,1.5,,1000000,4,0.006556122112211221,0.000586370264754231
+quantile,kll-percall,k=100,pareto,1.5,,1000000,16,0.004834026402640264,0.000519283243924376
+quantile,kll-percall,k=100,pareto,1.5,,1000000,64,0.004407072607260726,0.0001591620335712654
+quantile,kll-percall,k=100,pareto,1.5,,1778279,1,0.006138230170058161,0.0003718115763282885
+quantile,kll-percall,k=100,pareto,1.5,,1778279,4,0.006058695527024898,0.0016195105645785833
+quantile,kll-percall,k=100,pareto,1.5,,1778279,16,0.005483348060833323,0.0007037392375844682
+quantile,kll-percall,k=100,pareto,1.5,,1778279,64,0.004352533049545027,0.0009587366526441523
+quantile,kll-percall,k=100,pareto,1.5,,3162278,1,0.007914798572212795,0.0014417787194718765
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+quantile,kll-percall,k=100,pareto,1.5,,5623413,1,0.0063789711703445195,0.0009707705057430869
+quantile,kll-percall,k=100,pareto,1.5,,5623413,4,0.004696321477281634,0.00024930574265010554
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+quantile,kll-percall,k=100,pareto,1.5,,10000000,1,0.009550481518151814,0.0017109176471526819
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+quantile,kll-percall,k=100,pareto,1.5,,10000000,16,0.005297834323432344,0.000548927561597189
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+quantile,kll-percall,k=100,pareto,2.0,,1000,4,0.006148514851485153,0.001611926597425586
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+quantile,kll-percall,k=100,pareto,2.0,,1778,4,0.00707540270337495,0.0015868534679624716
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+quantile,kll-percall,k=100,pareto,2.0,,100000,1,0.005969504950495049,0.0011193197655606482
+quantile,kll-percall,k=100,pareto,2.0,,100000,4,0.0040694719471947175,0.0003615225626730363
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+quantile,kll-percall,k=100,pareto,3.0,,562341,1,0.00553093089054647,0.0015411704882016565
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+quantile,kll-percall,k=100,pareto,3.0,,1778279,16,0.006010170359079535,0.002385029552511593
+quantile,kll-percall,k=100,pareto,3.0,,1778279,64,0.0045004333249210405,0.0006941976549501829
+quantile,kll-percall,k=100,pareto,3.0,,3162278,1,0.005040820355936875,0.0008668857148539208
+quantile,kll-percall,k=100,pareto,3.0,,3162278,4,0.0034945172174906027,0.0002144225023588014
+quantile,kll-percall,k=100,pareto,3.0,,3162278,16,0.004379072205659856,0.0001601251025903905
+quantile,kll-percall,k=100,pareto,3.0,,3162278,64,0.004941902046186916,0.0009001301281203167
+quantile,kll-percall,k=100,pareto,3.0,,5623413,1,0.005198454491543974,0.0006976964019339257
+quantile,kll-percall,k=100,pareto,3.0,,5623413,4,0.004513379401911305,0.00023000096047385456
+quantile,kll-percall,k=100,pareto,3.0,,5623413,16,0.0043462089049418375,0.00011171213004719395
+quantile,kll-percall,k=100,pareto,3.0,,5623413,64,0.00589416606943326,0.0012272441938251293
+quantile,kll-percall,k=100,pareto,3.0,,10000000,1,0.005473811881188122,0.0007479520458950124
+quantile,kll-percall,k=100,pareto,3.0,,10000000,4,0.004565303960396041,0.00017514287982789862
+quantile,kll-percall,k=100,pareto,3.0,,10000000,16,0.005342753465346534,0.0002482530654917026
+quantile,kll-percall,k=100,pareto,3.0,,10000000,64,0.005193402310231022,0.0009551484686530788
+quantile,kll-percall,k=400,pareto,1.1,,1000,1,0.0007689768976897694,6.425056875885078e-05
+quantile,kll-percall,k=400,pareto,1.1,,1000,4,0.0005445544554455449,6.592404077702374e-05
+quantile,kll-percall,k=400,pareto,1.1,,1000,16,0.00021452145214521465,8.731852511764334e-06
+quantile,kll-percall,k=400,pareto,1.1,,1000,64,0.0006864686468646868,8.009677293406997e-05
+quantile,kll-percall,k=400,pareto,1.1,,1778,1,0.0009372343308571566,7.600331285349055e-05
+quantile,kll-percall,k=400,pareto,1.1,,1778,4,0.001215590625429252,0.00036849912430048955
+quantile,kll-percall,k=400,pareto,1.1,,1778,16,0.0011118659672491452,2.0393621823234606e-05
+quantile,kll-percall,k=400,pareto,1.1,,1778,64,0.0009782193067450731,0.00018563549667848726
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+quantile,kll-percall,k=400,pareto,1.1,,3162,16,0.0008293618735687574,0.00015907970293909548
+quantile,kll-percall,k=400,pareto,1.1,,3162,64,0.0010773980623868826,0.00030863229395913073
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+quantile,kll-percall,k=400,pareto,1.1,,5623,16,0.0010317948031687385,3.589107429154017e-05
+quantile,kll-percall,k=400,pareto,1.1,,5623,64,0.0010842960518708791,0.0001671975134096957
+quantile,kll-percall,k=400,pareto,1.1,,10000,1,0.0013066006600660075,3.774660046840334e-05
+quantile,kll-percall,k=400,pareto,1.1,,10000,4,0.0011442244224422454,0.00022355661947848253
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+quantile,kll-percall,k=400,pareto,1.1,,10000,64,0.001183168316831682,0.0001300401231067519
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+quantile,kll-percall,k=400,pareto,1.1,,56234,1,0.0012191149406223488,0.00013879641873095215
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+quantile,kll-percall,k=400,pareto,1.1,,5623413,1,0.0017324733810825076,0.0003461498900347397
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+quantile,kll-percall,k=400,pareto,2.0,,3162,64,0.0006961587999407167,4.855550361451459e-05
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/README.md b/rqe-optimizer/results/autosketch-vs-asap-targets/README.md
index 7c063693..b4fb4dbc 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/README.md
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/README.md
@@ -11,11 +11,15 @@ applies in each sketch family's own metric:
 | 99% (`acc99`) | ≤ 0.01 | ≤ 0.01 | ≥ 0.99 |
 
 Exact accumulators (sum, increase) have zero error at every level. Everything
-else is unchanged: the same tables, cost table, curves and Hydra study, and
+else is the 95% runs': the same tables (#210's, without classic templates 7
+and 9), the cost table, curves and Hydra study with #213's denser grid, and
 the same runner (`--target acc90` / `acc99`). The 95% results are
 `../autosketch-vs-asap-hydra/synthetic-*-tp95.json`.
 
-Every run: 0 RQEs dropped and 0 sanity violations.
+Every run: 0 RQEs dropped. One sanity check fails, by solver tolerance: in
+`synthetic-templatesall-shared8-tacc99.json`, ASAP's Fargate frontier is
+0.00004 $/h (0.01%) higher at the 2,100 ms bound than at 2,000 ms, inside
+HiGHS's gap.
 
 ## Results
 
@@ -24,45 +28,43 @@ Each method's cheapest plan (no latency bound), CPU only, in vCPU. The
 
 | Workload | Target | ASAP | ASAP (no roll-ups) | PerQuery | AutoSketch (latency) |
 |---|---|---|---|---|---|
-| mixed (50 RQEs) | 90% | 3.54 | 3.54 | 10.5 | 3,716 (1.0 s) |
-| | 95% | 3.54 | 3.54 | 10.5 | 3,716 (1.0 s) |
-| | 99% | 3.85 | 3.85 | 10.9 | 3,757 (1.0 s) |
-| multi-grouping (62 RQEs) | 90% | 0.221 | 0.551 | 1.07 | 10.2 (0.49 s) |
-| | 95% | 0.221 | 0.551 | 1.07 | 10.2 (0.49 s) |
-| | 99% | 0.627 | 0.979 | 1.49 | 9.94 (1.57 s) |
-| mixed + multi-grouping (112 RQEs) | 90% | 3.76 | 4.09 | 11.6 | 3,726 (1.0 s) |
-| | 95% | 3.76 | 4.09 | 11.6 | 3,726 (1.0 s) |
-| | 99% | 4.47 | 4.82 | 12.3 | 3,767 (1.57 s) |
-| multi-grouping, 16 metrics (992 RQEs) | 95% | 3.53 | 8.81 | 17.1 | 163 (0.49 s) |
-| | 99% | 10.0 | 15.7 | 23.8 | 159 (1.57 s) |
-
-**90% costs the same as 95%, for every method and workload.** At 95% the
-plans already use the cheapest measured config of each sketch that can
-serve them. On mixed + multi-grouping, for example, the plan uses HLL
-`lg_k = 12` (the smallest measured), DDSketch α = 0.05 and 0.02, and top-k
-3 × 1024. The measured grid has nothing cheaper for a looser target to
-switch to. Cost is also mostly ingest (CPU per sample), which barely depends
-on sketch size. A sweep below 95% would need smaller configs measured first
-(e.g. HLL `lg_k` 10, DDSketch α 0.1).
+| mixed (42 RQEs) | 90% | 2.35 | 2.35 | 7.67 | 2,701 (1.0 s) |
+| | 95% | 2.35 | 2.35 | 7.67 | 2,701 (1.0 s) |
+| | 99% | 2.54 | 2.54 | 7.95 | 2,741 (1.0 s) |
+| multi-grouping (62 RQEs) | 90% | 0.220 | 0.550 | 1.07 | 9.65 (0.49 s) |
+| | 95% | 0.220 | 0.550 | 1.07 | 9.65 (0.49 s) |
+| | 99% | 0.627 | 0.979 | 1.49 | 9.94 (1.6 s) |
+| mixed + multi-grouping (104 RQEs) | 90% | 2.57 | 2.90 | 8.74 | 2,711 (1.0 s) |
+| | 95% | 2.57 | 2.90 | 8.74 | 2,711 (1.0 s) |
+| | 99% | 3.17 | 3.52 | 9.44 | 2,751 (1.6 s) |
+| multi-grouping, 16 metrics (992 RQEs) | 95% | 3.52 | 8.80 | 17.1 | 154 (0.49 s) |
+| | 99% | 10.0 | 15.7 | 23.8 | 159 (1.6 s) |
+
+**90% costs the same as 95%, for every method and workload, even with the
+denser grid.** HLL, which multi-grouping is mostly made of, still bottoms out
+at `lg_k = 12` (asap_sketchlib builds 12, 14 and 16 only). DDSketch α = 0.1,
+the new coarsest config, reads 0.048 relative error, so it meets 95% as well
+as 90%. Cost is also mostly ingest (CPU per sample), which barely depends on
+sketch size (KLL ≈ 30 ns and DDSketch ≈ 19 ns per item at every config).
 
 **99% costs more, most where sketches dominate the cost.**
-- On the mixed set, ASAP's cost rises 9% (3.54 → 3.85 vCPU). Its cost is
+- On the mixed set, ASAP's cost rises 8% (2.35 → 2.54 vCPU). Its cost is
   mostly exact accumulators and per-series ingest, which the target doesn't
   touch.
-- On multi-grouping, which is all sketches, ASAP's cost rises 2.8× (0.221 →
-  0.627 vCPU, and 3.53 → 10.0 at 16 metrics). HLL moves to `lg_k` 14 and 16,
-  and quantiles to DDSketch α = 0.02.
+- On multi-grouping, which is all sketches, it rises 2.8× (0.220 → 0.627
+  vCPU, and 3.52 → 10.0 at 16 metrics). HLL moves to `lg_k` 14 and 16.
 - ASAP stays the cheapest at every target: 2.4× below PerQuery on
-  multi-grouping and 2.8× on mixed, and 16× (multi-grouping) to ~1,000× (mixed)
-  below AutoSketch.
+  multi-grouping and 3.1× on mixed at 99%, and 16× (multi-grouping) to
+  ~1,000× (mixed) below AutoSketch.
 
 **Roll-ups still help at 99%, but less.** On multi-grouping they save 36%
 (0.979 → 0.627 vCPU) at 99%, against 60% at 90% and 95%, and ASAP rolls up
 42 of the 62 RQEs, against 52.
 
 **AutoSketch's plan gets slower at 99%.** Its batch latency rises from 0.49 or
-1.0 s to 1.57 s. Its multi-grouping cost falls slightly (10.2 → 9.94 vCPU):
-it minimizes memory, not cost, so its cost need not rise with the target.
+1.0 s to 1.6 s on the workloads with multi-grouping templates. Its
+multi-grouping cost barely moves (9.65 → 9.94 vCPU): it minimizes memory, not
+cost.
 
 ## Figures
 
@@ -91,6 +93,7 @@ done
 python3 scripts/plot_autosketch_vs_asap_targets.py $D $H/synthetic-*-tp95.json $D/synthetic-*-tacc*.json
 ```
 
-Runs: 2026-10-11, one Xeon E5-2683 v3 node (56 cores), 6 runs at a time.
-Planning times are not compared here: the runs shared the machine.
-AutoSketch's benchmark time was not re-measured for the new targets' probes.
+Runs: 2026-10-14, the 4 CloudLab nodes clnode109/155/167/178 (Xeon E5-2683
+v3, 56 cores), each running its share serially, with the 95% runs. Planning
+times are not compared here. AutoSketch's benchmark time was not measured for
+the 90% and 99% probes.
diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/fig_cost_vs_target.png b/rqe-optimizer/results/autosketch-vs-asap-targets/fig_cost_vs_target.png
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/fig_cost_vs_target_at_autosketch_latency.png b/rqe-optimizer/results/autosketch-vs-asap-targets/fig_cost_vs_target_at_autosketch_latency.png
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/summary_targets.md b/rqe-optimizer/results/autosketch-vs-asap-targets/summary_targets.md
index 0f2097de..1c75a5ec 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/summary_targets.md
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/summary_targets.md
@@ -6,98 +6,98 @@ Cheapest plan of each method (no latency bound). Cost by use: CPU only in vCPU,
 
 | Target | Weights | RQEs | dropped | ASAP (latency, deployments, rolled up) | ASAP no roll-ups | PerQuery | AutoSketch (latency) |
 |---|---|---|---|---|---|---|---|
-| 90% | cpu | 112 | 0 | 3.76 (13.36 s, 13, 52) | 4.09 | 11.59 | 3726 (1015 ms) |
-| 90% | fargate | 112 | 0 | 0.2434 (2.68 s, 13, 52) | 0.2636 | 0.8119 | 175.9 (1015 ms) |
-| 95% | cpu | 112 | 0 | 3.76 (13.36 s, 13, 52) | 4.09 | 11.59 | 3726 (1015 ms) |
-| 95% | fargate | 112 | 0 | 0.2434 (2.68 s, 13, 52) | 0.2636 | 0.8119 | 175.9 (1015 ms) |
-| 99% | cpu | 112 | 0 | 4.473 (2.68 s, 16, 42) | 4.824 | 12.34 | 3767 (1569 ms) |
-| 99% | fargate | 112 | 0 | 0.3646 (2.68 s, 14, 51) | 0.4108 | 1.313 | 193.9 (1569 ms) |
+| 90% | cpu | 104 | 0 | 2.571 (13.36 s, 11, 52) | 2.901 | 8.736 | 2711 (1015 ms) |
+| 90% | fargate | 104 | 0 | 0.1624 (2.68 s, 11, 52) | 0.1823 | 0.5454 | 127.6 (1015 ms) |
+| 95% | cpu | 104 | 0 | 2.571 (13.36 s, 11, 52) | 2.901 | 8.736 | 2711 (1015 ms) |
+| 95% | fargate | 104 | 0 | 0.1624 (2.68 s, 11, 52) | 0.1823 | 0.5454 | 127.6 (1015 ms) |
+| 99% | cpu | 104 | 0 | 3.169 (2.68 s, 14, 42) | 3.52 | 9.442 | 2751 (1569 ms) |
+| 99% | fargate | 104 | 0 | 0.3003 (2.68 s, 12, 51) | 0.3465 | 1.178 | 152.7 (1569 ms) |
 
 ## mixed + multi-grouping, 8 metrics
 
 | Target | Weights | RQEs | dropped | ASAP (latency, deployments, rolled up) | ASAP no roll-ups | PerQuery | AutoSketch (latency) |
 |---|---|---|---|---|---|---|---|
-| 90% | cpu | 896 | 0 | 30.08 (13.36 s, 104, 416) | 32.72 | 92.68 | 2.981e+04 (1015 ms) |
-| 90% | fargate | 896 | 0 | 1.947 (2.68 s, 104, 416) | 2.108 | 6.495 | 1407 (1015 ms) |
-| 95% | cpu | 896 | 0 | 30.08 (13.36 s, 104, 416) | 32.72 | 92.68 | 2.981e+04 (1015 ms) |
-| 95% | fargate | 896 | 0 | 1.947 (2.68 s, 104, 416) | 2.108 | 6.495 | 1407 (1015 ms) |
-| 99% | cpu | 896 | 0 | 35.78 (2.68 s, 128, 336) | 38.59 | 98.72 | 3.014e+04 (1569 ms) |
-| 99% | fargate | 896 | 0 | 2.917 (2.68 s, 112, 408) | 3.287 | 10.51 | 1551 (1569 ms) |
+| 90% | cpu | 832 | 0 | 20.57 (13.36 s, 88, 416) | 23.21 | 69.89 | 2.169e+04 (1015 ms) |
+| 90% | fargate | 832 | 0 | 1.3 (2.68 s, 88, 416) | 1.458 | 4.363 | 1021 (1015 ms) |
+| 95% | cpu | 832 | 0 | 20.57 (13.36 s, 88, 416) | 23.21 | 69.89 | 2.169e+04 (1015 ms) |
+| 95% | fargate | 832 | 0 | 1.3 (2.68 s, 88, 416) | 1.458 | 4.363 | 1021 (1015 ms) |
+| 99% | cpu | 832 | 0 | 25.35 (2.68 s, 112, 336) | 28.16 | 75.54 | 2.201e+04 (1569 ms) |
+| 99% | fargate | 832 | 0 | 2.403 (2.68 s, 96, 408) | 2.772 | 9.424 | 1222 (1569 ms) |
 
 ## mixed + multi-grouping, 16 metrics
 
 | Target | Weights | RQEs | dropped | ASAP (latency, deployments, rolled up) | ASAP no roll-ups | PerQuery | AutoSketch (latency) |
 |---|---|---|---|---|---|---|---|
-| 90% | cpu | 1792 | 0 | 60.15 (13.36 s, 208, 832) | 65.43 | 185.4 | 5.962e+04 (1015 ms) |
-| 90% | fargate | 1792 | 0 | 3.894 (2.68 s, 208, 832) | 4.217 | 12.99 | 2815 (1015 ms) |
-| 95% | cpu | 1792 | 0 | 60.15 (13.36 s, 208, 832) | 65.43 | 185.4 | 5.962e+04 (1015 ms) |
-| 95% | fargate | 1792 | 0 | 3.894 (2.68 s, 208, 832) | 4.217 | 12.99 | 2815 (1015 ms) |
-| 99% | cpu | 1792 | 0 | 71.57 (2.68 s, 256, 672) | 77.19 | 197.4 | 6.028e+04 (1569 ms) |
-| 99% | fargate | 1792 | 0 | 5.834 (2.68 s, 224, 816) | 6.573 | 21.01 | 3103 (1569 ms) |
+| 90% | cpu | 1664 | 0 | 41.14 (13.36 s, 176, 832) | 46.42 | 139.8 | 4.338e+04 (1015 ms) |
+| 90% | fargate | 1664 | 0 | 2.599 (2.68 s, 176, 832) | 2.917 | 8.727 | 2042 (1015 ms) |
+| 95% | cpu | 1664 | 0 | 41.14 (13.36 s, 176, 832) | 46.42 | 139.8 | 4.338e+04 (1015 ms) |
+| 95% | fargate | 1664 | 0 | 2.599 (2.68 s, 176, 832) | 2.917 | 8.727 | 2042 (1015 ms) |
+| 99% | cpu | 1664 | 0 | 50.7 (2.68 s, 224, 672) | 56.32 | 151.1 | 4.402e+04 (1569 ms) |
+| 99% | fargate | 1664 | 0 | 4.805 (2.68 s, 192, 816) | 5.544 | 18.85 | 2444 (1569 ms) |
 
 ## mixed + multi-grouping, 8 users
 
 | Target | Weights | RQEs | dropped | ASAP (latency, deployments, rolled up) | ASAP no roll-ups | PerQuery | AutoSketch (latency) |
 |---|---|---|---|---|---|---|---|
-| 90% | cpu | 216 | 0 | 3.904 (2.68 s, 13, 104) | 4.234 | 20.54 | 4468 (1015 ms) |
-| 90% | fargate | 216 | 0 | 0.2467 (2.68 s, 13, 104) | 0.267 | 1.241 | 207 (1015 ms) |
-| 95% | cpu | 216 | 0 | 3.904 (2.68 s, 13, 104) | 4.234 | 20.54 | 4468 (1015 ms) |
-| 95% | fargate | 216 | 0 | 0.2467 (2.68 s, 13, 104) | 0.267 | 1.241 | 207 (1015 ms) |
-| 99% | cpu | 216 | 0 | 4.613 (2.68 s, 16, 84) | 4.985 | 21.39 | 4518 (1569 ms) |
-| 99% | fargate | 216 | 0 | 0.3705 (2.68 s, 15, 92) | 0.4174 | 1.842 | 226 (1569 ms) |
+| 90% | cpu | 200 | 0 | 2.676 (2.68 s, 11, 104) | 3.007 | 15.51 | 3250 (1015 ms) |
+| 90% | fargate | 200 | 0 | 0.1655 (2.68 s, 11, 104) | 0.1854 | 0.8563 | 150.2 (1015 ms) |
+| 95% | cpu | 200 | 0 | 2.676 (2.68 s, 11, 104) | 3.007 | 15.51 | 3250 (1015 ms) |
+| 95% | fargate | 200 | 0 | 0.1655 (2.68 s, 11, 104) | 0.1854 | 0.8563 | 150.2 (1015 ms) |
+| 99% | cpu | 200 | 0 | 3.303 (2.68 s, 14, 84) | 3.675 | 16.3 | 3299 (1569 ms) |
+| 99% | fargate | 200 | 0 | 0.3059 (2.68 s, 13, 92) | 0.3528 | 1.616 | 176.6 (1569 ms) |
 
 ## mixed
 
 | Target | Weights | RQEs | dropped | ASAP (latency, deployments, rolled up) | ASAP no roll-ups | PerQuery | AutoSketch (latency) |
 |---|---|---|---|---|---|---|---|
-| 90% | cpu | 50 | 0 | 3.539 (13.36 s, 8, 0) | 3.539 | 10.52 | 3716 (1015 ms) |
-| 90% | fargate | 50 | 0 | 0.2297 (2.68 s, 8, 0) | 0.2297 | 0.7522 | 175.5 (1015 ms) |
-| 95% | cpu | 50 | 0 | 3.539 (13.36 s, 8, 0) | 3.539 | 10.52 | 3716 (1015 ms) |
-| 95% | fargate | 50 | 0 | 0.2297 (2.68 s, 8, 0) | 0.2297 | 0.7522 | 175.5 (1015 ms) |
-| 99% | cpu | 50 | 0 | 3.846 (2.68 s, 8, 0) | 3.846 | 10.85 | 3757 (1015 ms) |
-| 99% | fargate | 50 | 0 | 0.2998 (2.68 s, 8, 0) | 0.2998 | 1.154 | 193.4 (1015 ms) |
+| 90% | cpu | 42 | 0 | 2.351 (13.36 s, 6, 0) | 2.351 | 7.668 | 2701 (1015 ms) |
+| 90% | fargate | 42 | 0 | 0.149 (2.68 s, 6, 0) | 0.149 | 0.4866 | 127.2 (1015 ms) |
+| 95% | cpu | 42 | 0 | 2.351 (13.36 s, 6, 0) | 2.351 | 7.668 | 2701 (1015 ms) |
+| 95% | fargate | 42 | 0 | 0.149 (2.68 s, 6, 0) | 0.149 | 0.4866 | 127.2 (1015 ms) |
+| 99% | cpu | 42 | 0 | 2.542 (2.68 s, 6, 0) | 2.542 | 7.953 | 2741 (1015 ms) |
+| 99% | fargate | 42 | 0 | 0.2355 (2.68 s, 6, 0) | 0.2355 | 1.018 | 152.2 (1015 ms) |
 
 ## mixed, 8 metrics
 
 | Target | Weights | RQEs | dropped | ASAP (latency, deployments, rolled up) | ASAP no roll-ups | PerQuery | AutoSketch (latency) |
 |---|---|---|---|---|---|---|---|
-| 90% | cpu | 400 | 0 | 28.31 (13.36 s, 64, 0) | 28.31 | 84.13 | 2.973e+04 (1015 ms) |
-| 90% | fargate | 400 | 0 | 1.838 (2.68 s, 64, 0) | 1.838 | 6.018 | 1404 (1015 ms) |
-| 95% | cpu | 400 | 0 | 28.31 (13.36 s, 64, 0) | 28.31 | 84.13 | 2.973e+04 (1015 ms) |
-| 95% | fargate | 400 | 0 | 1.838 (2.68 s, 64, 0) | 1.838 | 6.018 | 1404 (1015 ms) |
-| 99% | cpu | 400 | 0 | 30.77 (2.68 s, 64, 0) | 30.77 | 86.81 | 3.006e+04 (1015 ms) |
-| 99% | fargate | 400 | 0 | 2.399 (2.68 s, 64, 0) | 2.399 | 9.228 | 1547 (1015 ms) |
+| 90% | cpu | 336 | 0 | 18.81 (13.36 s, 48, 0) | 18.81 | 61.35 | 2.161e+04 (1015 ms) |
+| 90% | fargate | 336 | 0 | 1.192 (2.68 s, 48, 0) | 1.192 | 3.892 | 1018 (1015 ms) |
+| 95% | cpu | 336 | 0 | 18.81 (13.36 s, 48, 0) | 18.81 | 61.35 | 2.161e+04 (1015 ms) |
+| 95% | fargate | 336 | 0 | 1.192 (2.68 s, 48, 0) | 1.192 | 3.892 | 1018 (1015 ms) |
+| 99% | cpu | 336 | 0 | 20.33 (2.68 s, 48, 0) | 20.33 | 63.63 | 2.193e+04 (1015 ms) |
+| 99% | fargate | 336 | 0 | 1.884 (2.68 s, 48, 0) | 1.884 | 8.146 | 1218 (1015 ms) |
 
 ## mixed, 16 metrics
 
 | Target | Weights | RQEs | dropped | ASAP (latency, deployments, rolled up) | ASAP no roll-ups | PerQuery | AutoSketch (latency) |
 |---|---|---|---|---|---|---|---|
-| 90% | cpu | 800 | 0 | 56.62 (13.36 s, 128, 0) | 56.62 | 168.3 | 5.945e+04 (1015 ms) |
-| 90% | fargate | 800 | 0 | 3.675 (2.68 s, 128, 0) | 3.675 | 12.04 | 2808 (1015 ms) |
-| 95% | cpu | 800 | 0 | 56.62 (13.36 s, 128, 0) | 56.62 | 168.3 | 5.945e+04 (1015 ms) |
-| 95% | fargate | 800 | 0 | 3.675 (2.68 s, 128, 0) | 3.675 | 12.04 | 2808 (1015 ms) |
-| 99% | cpu | 800 | 0 | 61.53 (2.68 s, 128, 0) | 61.53 | 173.6 | 6.012e+04 (1015 ms) |
-| 99% | fargate | 800 | 0 | 4.797 (2.68 s, 128, 0) | 4.797 | 18.46 | 3095 (1015 ms) |
+| 90% | cpu | 672 | 0 | 37.62 (13.36 s, 96, 0) | 37.62 | 122.7 | 4.322e+04 (1015 ms) |
+| 90% | fargate | 672 | 0 | 2.384 (2.68 s, 96, 0) | 2.384 | 7.785 | 2035 (1015 ms) |
+| 95% | cpu | 672 | 0 | 37.62 (13.36 s, 96, 0) | 37.62 | 122.7 | 4.322e+04 (1015 ms) |
+| 95% | fargate | 672 | 0 | 2.384 (2.68 s, 96, 0) | 2.384 | 7.785 | 2035 (1015 ms) |
+| 99% | cpu | 672 | 0 | 40.67 (2.68 s, 96, 0) | 40.67 | 127.3 | 4.386e+04 (1015 ms) |
+| 99% | fargate | 672 | 0 | 3.768 (2.68 s, 96, 0) | 3.768 | 16.29 | 2436 (1015 ms) |
 
 ## mixed, 8 users
 
 | Target | Weights | RQEs | dropped | ASAP (latency, deployments, rolled up) | ASAP no roll-ups | PerQuery | AutoSketch (latency) |
 |---|---|---|---|---|---|---|---|
-| 90% | cpu | 92 | 0 | 3.662 (2.68 s, 8, 0) | 3.662 | 18.5 | 4456 (1015 ms) |
-| 90% | fargate | 92 | 0 | 0.2322 (2.68 s, 8, 0) | 0.2322 | 1.137 | 206.5 (1015 ms) |
-| 95% | cpu | 92 | 0 | 3.662 (2.68 s, 8, 0) | 3.662 | 18.5 | 4456 (1015 ms) |
-| 95% | fargate | 92 | 0 | 0.2322 (2.68 s, 8, 0) | 0.2322 | 1.137 | 206.5 (1015 ms) |
-| 99% | cpu | 92 | 0 | 3.914 (2.68 s, 8, 0) | 3.914 | 18.87 | 4506 (1015 ms) |
-| 99% | fargate | 92 | 0 | 0.3026 (2.68 s, 8, 0) | 0.3026 | 1.613 | 225.4 (1015 ms) |
+| 90% | cpu | 76 | 0 | 2.435 (2.68 s, 6, 0) | 2.435 | 13.47 | 3239 (1015 ms) |
+| 90% | fargate | 76 | 0 | 0.1512 (2.68 s, 6, 0) | 0.1512 | 0.7538 | 149.7 (1015 ms) |
+| 95% | cpu | 76 | 0 | 2.435 (2.68 s, 6, 0) | 2.435 | 13.47 | 3239 (1015 ms) |
+| 95% | fargate | 76 | 0 | 0.1512 (2.68 s, 6, 0) | 0.1512 | 0.7538 | 149.7 (1015 ms) |
+| 99% | cpu | 76 | 0 | 2.603 (2.68 s, 6, 0) | 2.603 | 13.78 | 3287 (1015 ms) |
+| 99% | fargate | 76 | 0 | 0.238 (2.68 s, 6, 0) | 0.238 | 1.387 | 176 (1015 ms) |
 
 ## multi-grouping
 
 | Target | Weights | RQEs | dropped | ASAP (latency, deployments, rolled up) | ASAP no roll-ups | PerQuery | AutoSketch (latency) |
 |---|---|---|---|---|---|---|---|
-| 90% | cpu | 62 | 0 | 0.2207 (0.56 s, 5, 52) | 0.5508 | 1.069 | 10.22 (490 ms) |
-| 90% | fargate | 62 | 0 | 0.01365 (0.56 s, 5, 52) | 0.03385 | 0.05967 | 0.4296 (490 ms) |
-| 95% | cpu | 62 | 0 | 0.2207 (0.56 s, 5, 52) | 0.5508 | 1.069 | 10.22 (490 ms) |
-| 95% | fargate | 62 | 0 | 0.01365 (0.56 s, 5, 52) | 0.03385 | 0.05967 | 0.4296 (490 ms) |
+| 90% | cpu | 62 | 0 | 0.2199 (0.56 s, 5, 52) | 0.5503 | 1.068 | 9.648 (490 ms) |
+| 90% | fargate | 62 | 0 | 0.01342 (0.56 s, 5, 52) | 0.03328 | 0.05887 | 0.4064 (490 ms) |
+| 95% | cpu | 62 | 0 | 0.2199 (0.56 s, 5, 52) | 0.5503 | 1.068 | 9.648 (490 ms) |
+| 95% | fargate | 62 | 0 | 0.01342 (0.56 s, 5, 52) | 0.03328 | 0.05887 | 0.4064 (490 ms) |
 | 99% | cpu | 62 | 0 | 0.6273 (1.84 s, 8, 42) | 0.9785 | 1.489 | 9.94 (1569 ms) |
 | 99% | fargate | 62 | 0 | 0.0648 (1.84 s, 6, 51) | 0.111 | 0.1598 | 0.5018 (1569 ms) |
 
@@ -105,10 +105,10 @@ Cheapest plan of each method (no latency bound). Cost by use: CPU only in vCPU,
 
 | Target | Weights | RQEs | dropped | ASAP (latency, deployments, rolled up) | ASAP no roll-ups | PerQuery | AutoSketch (latency) |
 |---|---|---|---|---|---|---|---|
-| 90% | cpu | 496 | 0 | 1.766 (0.56 s, 40, 416) | 4.406 | 8.548 | 81.74 (490 ms) |
-| 90% | fargate | 496 | 0 | 0.1092 (0.56 s, 40, 416) | 0.2708 | 0.4773 | 3.437 (490 ms) |
-| 95% | cpu | 496 | 0 | 1.766 (0.56 s, 40, 416) | 4.406 | 8.548 | 81.74 (490 ms) |
-| 95% | fargate | 496 | 0 | 0.1092 (0.56 s, 40, 416) | 0.2708 | 0.4773 | 3.437 (490 ms) |
+| 90% | cpu | 496 | 0 | 1.759 (0.56 s, 40, 416) | 4.402 | 8.542 | 77.18 (490 ms) |
+| 90% | fargate | 496 | 0 | 0.1074 (0.56 s, 40, 416) | 0.2662 | 0.4709 | 3.251 (490 ms) |
+| 95% | cpu | 496 | 0 | 1.759 (0.56 s, 40, 416) | 4.402 | 8.542 | 77.18 (490 ms) |
+| 95% | fargate | 496 | 0 | 0.1074 (0.56 s, 40, 416) | 0.2662 | 0.4709 | 3.251 (490 ms) |
 | 99% | cpu | 496 | 0 | 5.018 (1.84 s, 64, 336) | 7.828 | 11.91 | 79.52 (1569 ms) |
 | 99% | fargate | 496 | 0 | 0.5184 (1.84 s, 48, 408) | 0.8879 | 1.279 | 4.015 (1569 ms) |
 
@@ -116,10 +116,10 @@ Cheapest plan of each method (no latency bound). Cost by use: CPU only in vCPU,
 
 | Target | Weights | RQEs | dropped | ASAP (latency, deployments, rolled up) | ASAP no roll-ups | PerQuery | AutoSketch (latency) |
 |---|---|---|---|---|---|---|---|
-| 90% | cpu | 992 | 0 | 3.532 (0.56 s, 80, 832) | 8.813 | 17.1 | 163.5 (490 ms) |
-| 90% | fargate | 992 | 0 | 0.2184 (0.56 s, 80, 832) | 0.5416 | 0.9546 | 6.874 (490 ms) |
-| 95% | cpu | 992 | 0 | 3.532 (0.56 s, 80, 832) | 8.813 | 17.1 | 163.5 (490 ms) |
-| 95% | fargate | 992 | 0 | 0.2184 (0.56 s, 80, 832) | 0.5416 | 0.9546 | 6.874 (490 ms) |
+| 90% | cpu | 992 | 0 | 3.519 (0.56 s, 80, 832) | 8.804 | 17.08 | 154.4 (490 ms) |
+| 90% | fargate | 992 | 0 | 0.2148 (0.56 s, 80, 832) | 0.5324 | 0.9419 | 6.502 (490 ms) |
+| 95% | cpu | 992 | 0 | 3.519 (0.56 s, 80, 832) | 8.804 | 17.08 | 154.4 (490 ms) |
+| 95% | fargate | 992 | 0 | 0.2148 (0.56 s, 80, 832) | 0.5324 | 0.9419 | 6.502 (490 ms) |
 | 99% | cpu | 992 | 0 | 10.04 (1.84 s, 128, 672) | 15.66 | 23.82 | 159 (1569 ms) |
 | 99% | fargate | 992 | 0 | 1.037 (1.84 s, 96, 816) | 1.776 | 2.557 | 8.029 (1569 ms) |
 
@@ -127,9 +127,9 @@ Cheapest plan of each method (no latency bound). Cost by use: CPU only in vCPU,
 
 | Target | Weights | RQEs | dropped | ASAP (latency, deployments, rolled up) | ASAP no roll-ups | PerQuery | AutoSketch (latency) |
 |---|---|---|---|---|---|---|---|
-| 90% | cpu | 124 | 0 | 0.2419 (0.56 s, 5, 104) | 0.5728 | 2.042 | 12.26 (490 ms) |
-| 90% | fargate | 124 | 0 | 0.01451 (0.56 s, 5, 104) | 0.03474 | 0.1035 | 0.5167 (490 ms) |
-| 95% | cpu | 124 | 0 | 0.2419 (0.56 s, 5, 104) | 0.5728 | 2.042 | 12.26 (490 ms) |
-| 95% | fargate | 124 | 0 | 0.01451 (0.56 s, 5, 104) | 0.03474 | 0.1035 | 0.5167 (490 ms) |
+| 90% | cpu | 124 | 0 | 0.241 (0.56 s, 5, 104) | 0.5722 | 2.04 | 11.58 (490 ms) |
+| 90% | fargate | 124 | 0 | 0.01428 (0.56 s, 5, 104) | 0.03417 | 0.1025 | 0.4888 (490 ms) |
+| 95% | cpu | 124 | 0 | 0.241 (0.56 s, 5, 104) | 0.5722 | 2.04 | 11.58 (490 ms) |
+| 95% | fargate | 124 | 0 | 0.01428 (0.56 s, 5, 104) | 0.03417 | 0.1025 | 0.4888 (490 ms) |
 | 99% | cpu | 124 | 0 | 0.6992 (1.84 s, 8, 84) | 1.071 | 2.515 | 11.93 (1569 ms) |
 | 99% | fargate | 124 | 0 | 0.06787 (1.84 s, 7, 92) | 0.1148 | 0.2285 | 0.6095 (1569 ms) |
diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics16-tacc90.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics16-tacc90.json
index 8a8ed17c..08935ec3 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics16-tacc90.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics16-tacc90.json
@@ -1,7 +1,7 @@
 {
   "autosketch": {
-    "benchmark_secs_paper_rate": 18240.0,
-    "distinct_probes": 304,
+    "benchmark_secs_paper_rate": 14400.0,
+    "distinct_probes": 240,
     "probed_configs": [
       {
         "distinct_keys": 10000.0,
@@ -43,27 +43,7 @@
         "distinct_keys": 0.0,
         "metric": "data_0",
         "params": {
-          "alpha": 0.01
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_0",
-        "params": {
-          "alpha": 0.02
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_0",
-        "params": {
-          "alpha": 0.05
+          "alpha": 0.1
         },
         "sketch": "dd",
         "tail_index": 2.0,
@@ -109,27 +89,7 @@
         "distinct_keys": 0.0,
         "metric": "data_0/http",
         "params": {
-          "alpha": 0.01
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_0/http",
-        "params": {
-          "alpha": 0.02
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_0/http",
-        "params": {
-          "alpha": 0.05
+          "alpha": 0.1
         },
         "sketch": "dd",
         "tail_index": 2.0,
@@ -159,7 +119,7 @@
         "distinct_keys": 0.0,
         "metric": "data_0/http",
         "params": {
-          "k": 200
+          "k": 25
         },
         "sketch": "kll-percall",
         "tail_index": 2.0,
@@ -179,7 +139,7 @@
         "distinct_keys": 0.0,
         "metric": "data_0",
         "params": {
-          "k": 200
+          "k": 25
         },
         "sketch": "kll-percall",
         "tail_index": 2.0,
@@ -235,27 +195,7 @@
         "distinct_keys": 0.0,
         "metric": "data_1",
         "params": {
-          "alpha": 0.01
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_1",
-        "params": {
-          "alpha": 0.02
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_1",
-        "params": {
-          "alpha": 0.05
+          "alpha": 0.1
         },
         "sketch": "dd",
         "tail_index": 2.0,
@@ -301,27 +241,7 @@
         "distinct_keys": 0.0,
         "metric": "data_1/http",
         "params": {
-          "alpha": 0.01
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_1/http",
-        "params": {
-          "alpha": 0.02
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_1/http",
-        "params": {
-          "alpha": 0.05
+          "alpha": 0.1
         },
         "sketch": "dd",
         "tail_index": 2.0,
@@ -351,7 +271,7 @@
         "distinct_keys": 0.0,
         "metric": "data_1/http",
         "params": {
-          "k": 200
+          "k": 25
         },
         "sketch": "kll-percall",
         "tail_index": 2.0,
@@ -371,7 +291,7 @@
         "distinct_keys": 0.0,
         "metric": "data_1",
         "params": {
-          "k": 200
+          "k": 25
         },
         "sketch": "kll-percall",
         "tail_index": 2.0,
@@ -427,27 +347,7 @@
         "distinct_keys": 0.0,
         "metric": "data_10",
         "params": {
-          "alpha": 0.01
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_10",
-        "params": {
-          "alpha": 0.02
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_10",
-        "params": {
-          "alpha": 0.05
+          "alpha": 0.1
         },
         "sketch": "dd",
         "tail_index": 2.0,
@@ -493,27 +393,7 @@
         "distinct_keys": 0.0,
         "metric": "data_10/http",
         "params": {
-          "alpha": 0.01
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_10/http",
-        "params": {
-          "alpha": 0.02
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_10/http",
-        "params": {
-          "alpha": 0.05
+          "alpha": 0.1
         },
         "sketch": "dd",
         "tail_index": 2.0,
@@ -543,7 +423,7 @@
         "distinct_keys": 0.0,
         "metric": "data_10/http",
         "params": {
-          "k": 200
+          "k": 25
         },
         "sketch": "kll-percall",
         "tail_index": 2.0,
@@ -563,7 +443,7 @@
         "distinct_keys": 0.0,
         "metric": "data_10",
         "params": {
-          "k": 200
+          "k": 25
         },
         "sketch": "kll-percall",
         "tail_index": 2.0,
@@ -619,27 +499,7 @@
         "distinct_keys": 0.0,
         "metric": "data_11",
         "params": {
-          "alpha": 0.01
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_11",
-        "params": {
-          "alpha": 0.02
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_11",
-        "params": {
-          "alpha": 0.05
+          "alpha": 0.1
         },
         "sketch": "dd",
         "tail_index": 2.0,
@@ -685,27 +545,7 @@
         "distinct_keys": 0.0,
         "metric": "data_11/http",
         "params": {
-          "alpha": 0.01
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_11/http",
-        "params": {
-          "alpha": 0.02
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_11/http",
-        "params": {
-          "alpha": 0.05
+          "alpha": 0.1
         },
         "sketch": "dd",
         "tail_index": 2.0,
@@ -735,7 +575,7 @@
         "distinct_keys": 0.0,
         "metric": "data_11/http",
         "params": {
-          "k": 200
+          "k": 25
         },
         "sketch": "kll-percall",
         "tail_index": 2.0,
@@ -755,7 +595,7 @@
         "distinct_keys": 0.0,
         "metric": "data_11",
         "params": {
-          "k": 200
+          "k": 25
         },
         "sketch": "kll-percall",
         "tail_index": 2.0,
@@ -811,27 +651,7 @@
         "distinct_keys": 0.0,
         "metric": "data_12",
         "params": {
-          "alpha": 0.01
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_12",
-        "params": {
-          "alpha": 0.02
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
-        "zipf_s": null
-      },
-      {
-        "distinct_keys": 0.0,
-        "metric": "data_12",
-        "params": {
-          "alpha": 0.05
+          "alpha": 0.1
         },
         "sketch": "dd",
         "tail_index": 2.0,
@@ -877,27 +697,7 @@
         "distinct_keys": 0.0,
         "metric": "data_12/http",
         "params": {
-          "alpha": 0.01
-        },
-        "sketch": "dd",
-        "tail_index": 2.0,
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@@ -927,7 +727,7 @@
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@@ -947,7 +747,7 @@
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@@ -1003,27 +803,7 @@
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@@ -1069,27 +849,7 @@
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@@ -1119,7 +879,7 @@
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@@ -1139,7 +899,7 @@
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@@ -1195,27 +955,7 @@
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@@ -1261,27 +1001,7 @@
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@@ -1311,7 +1031,7 @@
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@@ -1331,7 +1051,7 @@
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@@ -1387,27 +1107,7 @@
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@@ -1453,27 +1153,7 @@
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@@ -1503,7 +1183,7 @@
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@@ -1523,7 +1203,7 @@
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@@ -1579,27 +1259,7 @@
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@@ -1645,27 +1305,7 @@
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@@ -1695,7 +1335,7 @@
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@@ -1963,27 +1563,7 @@
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@@ -2029,27 +1609,7 @@
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@@ -2079,7 +1639,7 @@
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@@ -2099,7 +1659,7 @@
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@@ -2221,27 +1761,7 @@
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@@ -2271,7 +1791,7 @@
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@@ -2291,7 +1811,7 @@
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@@ -2347,27 +1867,7 @@
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@@ -2399,41 +1899,21 @@
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@@ -2463,7 +1943,7 @@
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@@ -2483,7 +1963,7 @@
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@@ -2539,27 +2019,7 @@
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@@ -2605,27 +2065,7 @@
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@@ -2655,7 +2095,7 @@
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@@ -2675,7 +2115,7 @@
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@@ -2731,27 +2171,7 @@
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@@ -2797,27 +2217,7 @@
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@@ -2847,7 +2247,7 @@
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@@ -2867,7 +2267,7 @@
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@@ -2923,27 +2323,7 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics16-tacc99.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics16-tacc99.json
index 0a877f14..d530e5ad 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics16-tacc99.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics16-tacc99.json
@@ -1,7 +1,7 @@
 {
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@@ -55,7 +55,7 @@
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@@ -65,7 +65,7 @@
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@@ -75,7 +75,7 @@
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@@ -121,7 +121,7 @@
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@@ -181,7 +181,7 @@
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@@ -197,21 +197,11 @@
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@@ -289,7 +279,7 @@
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@@ -299,7 +289,7 @@
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@@ -345,7 +335,7 @@
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@@ -365,7 +355,7 @@
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@@ -405,7 +395,7 @@
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@@ -629,7 +609,7 @@
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@@ -727,7 +697,7 @@
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@@ -747,7 +717,7 @@
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@@ -793,7 +763,7 @@
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@@ -803,7 +773,7 @@
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@@ -813,7 +783,7 @@
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@@ -853,7 +823,7 @@
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@@ -869,21 +839,11 @@
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@@ -951,7 +911,7 @@
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@@ -961,7 +921,7 @@
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@@ -971,7 +931,7 @@
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@@ -1017,7 +977,7 @@
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@@ -1037,7 +997,7 @@
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@@ -1077,7 +1037,7 @@
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@@ -1093,21 +1053,11 @@
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@@ -1175,7 +1125,7 @@
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@@ -1185,7 +1135,7 @@
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@@ -1195,7 +1145,7 @@
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@@ -1241,7 +1191,7 @@
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@@ -1251,7 +1201,7 @@
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@@ -1261,7 +1211,7 @@
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@@ -1301,7 +1251,7 @@
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@@ -1317,21 +1267,11 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics8-tacc90.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics8-tacc90.json
index 18f8bbf9..4731a1eb 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics8-tacc90.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics8-tacc90.json
@@ -1,7 +1,7 @@
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@@ -43,27 +43,7 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics8-tacc99.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics8-tacc99.json
index c299f76f..0ebb08d9 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics8-tacc99.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-metrics8-tacc99.json
@@ -1,7 +1,7 @@
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@@ -55,7 +55,7 @@
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@@ -65,7 +65,7 @@
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@@ -75,7 +75,7 @@
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@@ -121,7 +121,7 @@
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@@ -181,7 +181,7 @@
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@@ -197,21 +197,11 @@
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@@ -405,7 +395,7 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-tacc90.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-tacc90.json
index 082a7693..9df524ad 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-tacc90.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-tacc90.json
@@ -1,7 +1,7 @@
 {
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+    "benchmark_secs_paper_rate": 900.0,
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     "probed_configs": [
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@@ -43,27 +43,7 @@
         "distinct_keys": 0.0,
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@@ -89,7 +69,7 @@
         "distinct_keys": 0.0,
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+          "k": 25
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@@ -129,27 +109,7 @@
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@@ -179,7 +139,7 @@
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+          "k": 25
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@@ -196,8 +156,8 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-tacc99.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-tacc99.json
index 6dcbef74..584df6e5 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-tacc99.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared1-tacc99.json
@@ -1,7 +1,7 @@
 {
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@@ -55,7 +55,7 @@
         "distinct_keys": 0.0,
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@@ -65,7 +65,7 @@
         "distinct_keys": 0.0,
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@@ -75,7 +75,7 @@
         "distinct_keys": 0.0,
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@@ -101,7 +101,7 @@
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@@ -141,7 +141,7 @@
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@@ -151,7 +151,7 @@
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@@ -161,7 +161,7 @@
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@@ -201,7 +201,7 @@
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+          "k": 100
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@@ -216,20 +216,10 @@
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@@ -254,2255 +244,2255 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared8-tacc90.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared8-tacc90.json
index c80d7566..4ed24ff1 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared8-tacc90.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared8-tacc90.json
@@ -1,7 +1,7 @@
 {
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     "probed_configs": [
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@@ -43,27 +43,7 @@
         "distinct_keys": 0.0,
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@@ -89,7 +69,7 @@
         "distinct_keys": 0.0,
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+          "k": 25
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@@ -129,27 +109,7 @@
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@@ -179,7 +139,7 @@
         "distinct_keys": 0.0,
         "metric": "http",
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+          "k": 25
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@@ -196,8 +156,8 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared8-tacc99.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared8-tacc99.json
index 3f105781..a696409a 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared8-tacc99.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesall-shared8-tacc99.json
@@ -1,7 +1,7 @@
 {
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@@ -55,7 +55,7 @@
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@@ -65,7 +65,7 @@
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@@ -75,7 +75,7 @@
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@@ -101,7 +101,7 @@
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@@ -141,7 +141,7 @@
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@@ -151,7 +151,7 @@
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@@ -161,7 +161,7 @@
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@@ -201,7 +201,7 @@
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@@ -216,20 +216,10 @@
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@@ -254,2257 +244,2264 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics16-tacc90.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics16-tacc90.json
index d1911fff..5fcc9209 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics16-tacc90.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics16-tacc90.json
@@ -1,7 +1,7 @@
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@@ -803,7 +643,7 @@
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@@ -905,7 +725,7 @@
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@@ -961,27 +781,7 @@
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@@ -1063,27 +863,7 @@
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@@ -1109,7 +889,7 @@
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@@ -1165,27 +945,7 @@
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@@ -1211,7 +971,7 @@
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@@ -1313,7 +1053,7 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics16-tacc99.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics16-tacc99.json
index fa69a93e..9a13923a 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics16-tacc99.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics16-tacc99.json
@@ -55,7 +55,7 @@
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@@ -65,7 +65,7 @@
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@@ -75,7 +75,7 @@
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@@ -101,7 +101,7 @@
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@@ -169,7 +169,7 @@
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@@ -189,7 +189,7 @@
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@@ -215,7 +215,7 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics8-tacc90.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics8-tacc90.json
index 358aebbe..128f67b4 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics8-tacc90.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics8-tacc90.json
@@ -1,7 +1,7 @@
 {
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@@ -43,27 +43,7 @@
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@@ -89,7 +69,7 @@
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@@ -145,27 +125,7 @@
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@@ -191,7 +151,7 @@
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@@ -293,7 +233,7 @@
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@@ -349,27 +289,7 @@
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@@ -395,7 +315,7 @@
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@@ -451,27 +371,7 @@
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@@ -497,7 +397,7 @@
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@@ -553,27 +453,7 @@
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@@ -599,7 +479,7 @@
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@@ -655,27 +535,7 @@
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@@ -701,7 +561,7 @@
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@@ -757,27 +617,7 @@
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@@ -803,7 +643,7 @@
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@@ -820,8 +660,8 @@
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@@ -846,2169 +686,2169 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics8-tacc99.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics8-tacc99.json
index 67448bd1..79f2334f 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics8-tacc99.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-metrics8-tacc99.json
@@ -55,7 +55,7 @@
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@@ -65,7 +65,7 @@
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@@ -75,7 +75,7 @@
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@@ -101,7 +101,7 @@
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@@ -169,7 +169,7 @@
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@@ -179,7 +179,7 @@
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@@ -189,7 +189,7 @@
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@@ -215,7 +215,7 @@
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@@ -283,7 +283,7 @@
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@@ -293,7 +293,7 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-tacc90.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-tacc90.json
index ae71d2bd..f1117fc0 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-tacc90.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-tacc90.json
@@ -1,7 +1,7 @@
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@@ -43,27 +43,7 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-tacc99.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-tacc99.json
index fa34ffc0..3c38c702 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-tacc99.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared1-tacc99.json
@@ -55,7 +55,7 @@
         "distinct_keys": 0.0,
         "metric": "data",
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+          "alpha": 0.02
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@@ -65,7 +65,7 @@
         "distinct_keys": 0.0,
         "metric": "data",
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+          "alpha": 0.05
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@@ -75,7 +75,7 @@
         "distinct_keys": 0.0,
         "metric": "data",
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+          "alpha": 0.1
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@@ -101,7 +101,7 @@
         "distinct_keys": 0.0,
         "metric": "data",
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+          "k": 100
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@@ -118,8 +118,8 @@
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-    "probes": 174,
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   "cost_model": "w_cpu * AUC(CPU) + w_mem * AUC(memory), billed by use; latency = longest chain, reported",
   "dropped_unservable": {
@@ -144,2169 +144,2169 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared8-tacc90.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared8-tacc90.json
index 1b00ba31..be65b5d7 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared8-tacc90.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared8-tacc90.json
@@ -1,7 +1,7 @@
 {
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@@ -43,27 +43,7 @@
         "distinct_keys": 0.0,
         "metric": "data",
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@@ -89,7 +69,7 @@
         "distinct_keys": 0.0,
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+          "k": 25
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@@ -106,8 +86,8 @@
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@@ -132,2169 +112,2169 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared8-tacc99.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared8-tacc99.json
index d5c0361c..f8c1fd9d 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared8-tacc99.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesclassic-shared8-tacc99.json
@@ -55,7 +55,7 @@
         "distinct_keys": 0.0,
         "metric": "data",
         "params": {
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+          "alpha": 0.02
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@@ -65,7 +65,7 @@
         "distinct_keys": 0.0,
         "metric": "data",
         "params": {
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+          "alpha": 0.05
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@@ -75,7 +75,7 @@
         "distinct_keys": 0.0,
         "metric": "data",
         "params": {
-          "alpha": 0.05
+          "alpha": 0.1
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         "sketch": "dd",
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@@ -101,7 +101,7 @@
         "distinct_keys": 0.0,
         "metric": "data",
         "params": {
-          "k": 200
+          "k": 100
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         "sketch": "kll-percall",
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@@ -118,8 +118,8 @@
         "zipf_s": null
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-    "probes": 312,
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+    "probes": 272,
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   "cost_model": "w_cpu * AUC(CPU) + w_mem * AUC(memory), billed by use; latency = longest chain, reported",
   "dropped_unservable": {
@@ -144,2169 +144,2169 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics16-tacc90.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics16-tacc90.json
index 7bbceea2..5380e6a2 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics16-tacc90.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics16-tacc90.json
@@ -1,7 +1,7 @@
 {
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@@ -27,27 +27,7 @@
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@@ -77,7 +57,7 @@
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@@ -117,27 +97,7 @@
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@@ -167,7 +127,7 @@
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@@ -207,27 +167,7 @@
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@@ -257,7 +197,7 @@
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@@ -347,7 +267,7 @@
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@@ -387,27 +307,7 @@
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@@ -437,7 +337,7 @@
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@@ -477,27 +377,7 @@
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@@ -527,7 +407,7 @@
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@@ -567,27 +447,7 @@
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@@ -657,27 +517,7 @@
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@@ -707,7 +547,7 @@
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@@ -887,7 +687,7 @@
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@@ -1444,8 +1124,8 @@
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@@ -4138,28 +3818,28 @@
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@@ -4191,28 +3871,28 @@
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@@ -4244,28 +3924,28 @@
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@@ -4273,26 +3953,26 @@
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@@ -4300,26 +3980,26 @@
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@@ -4327,26 +4007,26 @@
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@@ -4354,28 +4034,28 @@
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@@ -4383,26 +4063,26 @@
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       "method": "asap",
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@@ -4410,26 +4090,26 @@
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       "latency_ms": 958.6905598958333,
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@@ -4437,26 +4117,26 @@
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       "latency_ms": 958.6905598958333,
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       "method": "perquery",
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@@ -4464,28 +4144,28 @@
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@@ -4493,26 +4173,26 @@
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     {
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       "hydra_rqes": 0,
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       "method": "asap",
-      "milp_solve_secs": 3.688699435,
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       "sla_ms": 10000.0,
@@ -4520,26 +4200,26 @@
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     {
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       "latency_ms": 958.6905598958333,
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@@ -4547,26 +4227,26 @@
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       "hydra_rqes": 0,
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       "latency_ms": 958.6905598958333,
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       "method": "perquery",
-      "milp_solve_secs": 0.906925433,
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       "sla_ms": 10000.0,
@@ -4574,28 +4254,28 @@
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     {
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics16-tacc99.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics16-tacc99.json
index 73ddd74b..c9f9e57b 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics16-tacc99.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics16-tacc99.json
@@ -1,7 +1,7 @@
 {
   "autosketch": {
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-    "distinct_probes": 176,
+    "benchmark_secs_paper_rate": 9600.0,
+    "distinct_probes": 160,
     "probed_configs": [
       {
         "distinct_keys": 1000000.0,
@@ -27,7 +27,7 @@
         "distinct_keys": 0.0,
         "metric": "data_0/http",
         "params": {
-          "alpha": 0.01
+          "alpha": 0.02
         },
         "sketch": "dd",
         "tail_index": 2.0,
@@ -37,7 +37,7 @@
         "distinct_keys": 0.0,
         "metric": "data_0/http",
         "params": {
-          "alpha": 0.02
+          "alpha": 0.05
         },
         "sketch": "dd",
         "tail_index": 2.0,
@@ -47,7 +47,7 @@
         "distinct_keys": 0.0,
         "metric": "data_0/http",
         "params": {
-          "alpha": 0.05
+          "alpha": 0.1
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         "sketch": "dd",
         "tail_index": 2.0,
@@ -87,7 +87,7 @@
         "distinct_keys": 0.0,
         "metric": "data_0/http",
         "params": {
-          "k": 200
+          "k": 100
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         "sketch": "kll-percall",
         "tail_index": 2.0,
@@ -103,16 +103,6 @@
         "tail_index": 2.0,
         "zipf_s": null
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-      {
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       {
         "distinct_keys": 1000000.0,
         "metric": "data_1/flows",
@@ -137,7 +127,7 @@
         "distinct_keys": 0.0,
         "metric": "data_1/http",
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@@ -147,7 +137,7 @@
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@@ -157,7 +147,7 @@
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@@ -197,7 +187,7 @@
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@@ -213,16 +203,6 @@
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@@ -247,7 +227,7 @@
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@@ -257,7 +237,7 @@
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@@ -267,7 +247,7 @@
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@@ -307,7 +287,7 @@
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@@ -323,16 +303,6 @@
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@@ -357,7 +327,7 @@
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@@ -367,7 +337,7 @@
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@@ -377,7 +347,7 @@
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@@ -417,7 +387,7 @@
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@@ -433,16 +403,6 @@
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@@ -467,7 +427,7 @@
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@@ -477,7 +437,7 @@
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@@ -487,7 +447,7 @@
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@@ -527,7 +487,7 @@
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@@ -543,16 +503,6 @@
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@@ -577,7 +527,7 @@
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@@ -587,7 +537,7 @@
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@@ -597,7 +547,7 @@
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@@ -637,7 +587,7 @@
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@@ -653,16 +603,6 @@
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@@ -687,7 +627,7 @@
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@@ -697,7 +637,7 @@
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@@ -707,7 +647,7 @@
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@@ -747,7 +687,7 @@
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@@ -763,16 +703,6 @@
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@@ -797,7 +727,7 @@
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@@ -807,7 +737,7 @@
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@@ -817,7 +747,7 @@
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@@ -857,7 +787,7 @@
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@@ -873,16 +803,6 @@
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@@ -907,7 +827,7 @@
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@@ -917,7 +837,7 @@
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@@ -927,7 +847,7 @@
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@@ -967,7 +887,7 @@
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@@ -983,16 +903,6 @@
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@@ -1027,7 +937,7 @@
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@@ -1077,7 +987,7 @@
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@@ -1093,16 +1003,6 @@
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@@ -1187,7 +1087,7 @@
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@@ -1203,16 +1103,6 @@
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@@ -1237,7 +1127,7 @@
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@@ -1247,7 +1137,7 @@
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@@ -1257,7 +1147,7 @@
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@@ -1297,7 +1187,7 @@
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@@ -1313,16 +1203,6 @@
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@@ -1347,7 +1227,7 @@
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@@ -1357,7 +1237,7 @@
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@@ -1367,7 +1247,7 @@
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@@ -1407,7 +1287,7 @@
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@@ -1457,7 +1327,7 @@
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@@ -1467,7 +1337,7 @@
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@@ -1517,7 +1387,7 @@
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@@ -1533,16 +1403,6 @@
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@@ -1567,7 +1427,7 @@
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@@ -1577,7 +1437,7 @@
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@@ -1587,7 +1447,7 @@
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@@ -1627,7 +1487,7 @@
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@@ -1643,16 +1503,6 @@
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@@ -1677,7 +1527,7 @@
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@@ -1697,7 +1547,7 @@
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@@ -1737,7 +1587,7 @@
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@@ -1752,20 +1602,10 @@
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   "cost_model": "w_cpu * AUC(CPU) + w_mem * AUC(memory), billed by use; latency = longest chain, reported",
   "dropped_unservable": {
@@ -1809,7 +1649,7 @@
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@@ -4690,7 +4530,7 @@
       "meets_sla": true,
       "method": "autosketch",
       "objective": 8.029332476727905,
-      "planning_secs": 0.039573579,
+      "planning_secs": 0.077166333,
       "probes": 2656,
       "rolled_up_rqes": 0,
       "rqes": 992,
@@ -4717,7 +4557,7 @@
       "latency_ms": 1835.6486002604163,
       "median_latency_ms": 94.35648600260416,
       "method": "asap",
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+      "milp_solve_secs": 26.281954467,
       "objective": 1.0368179787827143,
       "rolled_up_rqes": 816,
       "rqes": 992,
@@ -4744,7 +4584,7 @@
       "latency_ms": 3335.11134765625,
       "median_latency_ms": 34.35648600260416,
       "method": "asap-norollup",
-      "milp_solve_secs": 0.653799285,
+      "milp_solve_secs": 1.594263735,
       "objective": 1.7757945350403683,
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@@ -4771,7 +4611,7 @@
       "latency_ms": 3335.11134765625,
       "median_latency_ms": 34.35648600260416,
       "method": "perquery",
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+      "milp_solve_secs": 1.428802922,
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@@ -4780,7 +4620,7 @@
     },
     {
       "active_deployments": 992,
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+      "benchmark_secs_paper_rate": 9600.0,
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@@ -4800,7 +4640,7 @@
       "meets_sla": true,
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-      "planning_secs": 0.039573579,
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics8-tacc90.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics8-tacc90.json
index d36dc0b7..703f83a4 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics8-tacc90.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics8-tacc90.json
@@ -1,7 +1,7 @@
 {
   "autosketch": {
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-    "distinct_probes": 72,
+    "benchmark_secs_paper_rate": 3360.0,
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     "probed_configs": [
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         "distinct_keys": 1000000.0,
@@ -27,27 +27,7 @@
         "distinct_keys": 0.0,
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+          "alpha": 0.1
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@@ -77,7 +57,7 @@
         "distinct_keys": 0.0,
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+          "k": 25
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@@ -117,27 +97,7 @@
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@@ -167,7 +127,7 @@
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@@ -207,27 +167,7 @@
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@@ -257,7 +197,7 @@
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@@ -297,27 +237,7 @@
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@@ -347,7 +267,7 @@
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@@ -387,27 +307,7 @@
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@@ -437,7 +337,7 @@
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@@ -477,27 +377,7 @@
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@@ -527,7 +407,7 @@
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@@ -567,27 +447,7 @@
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@@ -617,7 +477,7 @@
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@@ -657,27 +517,7 @@
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@@ -707,7 +547,7 @@
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@@ -724,8 +564,8 @@
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+    "probes": 1104,
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   "cost_model": "w_cpu * AUC(CPU) + w_mem * AUC(memory), billed by use; latency = longest chain, reported",
   "dropped_unservable": {
@@ -752,25 +592,25 @@
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@@ -778,25 +618,25 @@
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@@ -804,25 +644,25 @@
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@@ -830,25 +670,25 @@
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@@ -856,25 +696,25 @@
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@@ -882,25 +722,25 @@
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@@ -908,25 +748,25 @@
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@@ -934,25 +774,25 @@
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@@ -960,25 +800,25 @@
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@@ -3364,26 +3204,26 @@
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@@ -3391,26 +3231,26 @@
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@@ -3418,28 +3258,28 @@
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@@ -3471,28 +3311,28 @@
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@@ -3524,28 +3364,28 @@
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@@ -3553,26 +3393,26 @@
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@@ -3580,26 +3420,26 @@
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@@ -3607,26 +3447,26 @@
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@@ -3634,28 +3474,28 @@
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@@ -3663,26 +3503,26 @@
     },
     {
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       "method": "asap",
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@@ -3690,26 +3530,26 @@
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@@ -3717,26 +3557,26 @@
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@@ -3744,28 +3584,28 @@
     },
     {
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@@ -3773,26 +3613,26 @@
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       "method": "asap",
-      "milp_solve_secs": 0.947674117,
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@@ -3800,26 +3640,26 @@
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       "latency_ms": 958.6905598958333,
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@@ -3827,26 +3667,26 @@
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       "latency_ms": 958.6905598958333,
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       "method": "perquery",
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@@ -3854,28 +3694,28 @@
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     {
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics8-tacc99.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics8-tacc99.json
index 6c0b9da9..850515fd 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics8-tacc99.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-metrics8-tacc99.json
@@ -1,7 +1,7 @@
 {
   "autosketch": {
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-    "distinct_probes": 88,
+    "benchmark_secs_paper_rate": 4800.0,
+    "distinct_probes": 80,
     "probed_configs": [
       {
         "distinct_keys": 1000000.0,
@@ -27,7 +27,7 @@
         "distinct_keys": 0.0,
         "metric": "data_0/http",
         "params": {
-          "alpha": 0.01
+          "alpha": 0.02
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@@ -37,7 +37,7 @@
         "distinct_keys": 0.0,
         "metric": "data_0/http",
         "params": {
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+          "alpha": 0.05
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         "tail_index": 2.0,
@@ -47,7 +47,7 @@
         "distinct_keys": 0.0,
         "metric": "data_0/http",
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+          "alpha": 0.1
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@@ -87,7 +87,7 @@
         "distinct_keys": 0.0,
         "metric": "data_0/http",
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+          "k": 100
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         "sketch": "kll-percall",
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@@ -103,16 +103,6 @@
         "tail_index": 2.0,
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       {
         "distinct_keys": 1000000.0,
         "metric": "data_1/flows",
@@ -137,7 +127,7 @@
         "distinct_keys": 0.0,
         "metric": "data_1/http",
         "params": {
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+          "alpha": 0.02
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         "tail_index": 2.0,
@@ -147,7 +137,7 @@
         "distinct_keys": 0.0,
         "metric": "data_1/http",
         "params": {
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+          "alpha": 0.05
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@@ -157,7 +147,7 @@
         "distinct_keys": 0.0,
         "metric": "data_1/http",
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+          "alpha": 0.1
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@@ -197,7 +187,7 @@
         "distinct_keys": 0.0,
         "metric": "data_1/http",
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+          "k": 100
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         "sketch": "kll-percall",
         "tail_index": 2.0,
@@ -213,16 +203,6 @@
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       {
         "distinct_keys": 1000000.0,
         "metric": "data_2/flows",
@@ -247,7 +227,7 @@
         "distinct_keys": 0.0,
         "metric": "data_2/http",
         "params": {
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+          "alpha": 0.02
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@@ -257,7 +237,7 @@
         "distinct_keys": 0.0,
         "metric": "data_2/http",
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+          "alpha": 0.05
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@@ -267,7 +247,7 @@
         "distinct_keys": 0.0,
         "metric": "data_2/http",
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@@ -307,7 +287,7 @@
         "distinct_keys": 0.0,
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@@ -323,16 +303,6 @@
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@@ -357,7 +327,7 @@
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@@ -3348,7 +3268,7 @@
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@@ -3375,7 +3295,7 @@
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@@ -3402,7 +3322,7 @@
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@@ -3411,7 +3331,7 @@
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@@ -3431,7 +3351,7 @@
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@@ -3458,7 +3378,7 @@
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@@ -3485,7 +3405,7 @@
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@@ -3512,7 +3432,7 @@
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@@ -3521,7 +3441,7 @@
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@@ -3541,7 +3461,7 @@
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@@ -3574,7 +3494,7 @@
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@@ -3594,7 +3514,7 @@
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@@ -3627,7 +3547,7 @@
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@@ -3647,7 +3567,7 @@
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@@ -3680,7 +3600,7 @@
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@@ -3700,7 +3620,7 @@
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@@ -3727,7 +3647,7 @@
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@@ -3754,7 +3674,7 @@
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@@ -3781,7 +3701,7 @@
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@@ -3790,7 +3710,7 @@
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@@ -3810,7 +3730,7 @@
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@@ -3837,7 +3757,7 @@
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@@ -3864,7 +3784,7 @@
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@@ -3891,7 +3811,7 @@
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@@ -3900,7 +3820,7 @@
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@@ -3920,7 +3840,7 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-tacc90.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-tacc90.json
index 39a24498..4c4ea781 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-tacc90.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-tacc90.json
@@ -1,7 +1,7 @@
 {
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     "probed_configs": [
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@@ -27,27 +27,7 @@
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@@ -77,7 +57,7 @@
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@@ -94,8 +74,8 @@
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@@ -122,25 +102,25 @@
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@@ -148,25 +128,25 @@
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@@ -174,25 +154,25 @@
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@@ -200,25 +180,25 @@
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@@ -226,25 +206,25 @@
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@@ -252,25 +232,25 @@
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@@ -278,25 +258,25 @@
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@@ -304,25 +284,25 @@
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@@ -330,25 +310,25 @@
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@@ -2651,26 +2631,26 @@
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@@ -2734,26 +2714,26 @@
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@@ -2761,26 +2741,26 @@
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@@ -2788,28 +2768,28 @@
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@@ -2841,28 +2821,28 @@
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@@ -2894,28 +2874,28 @@
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@@ -2923,26 +2903,26 @@
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@@ -2950,26 +2930,26 @@
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@@ -2977,26 +2957,26 @@
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     {
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@@ -3004,28 +2984,28 @@
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     {
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@@ -3033,26 +3013,26 @@
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     {
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+        "ingest": 0.215931236743927,
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       "hydra_rqes": 0,
       "infeasible": false,
       "latency_ms": 557.0905598958334,
       "median_latency_ms": 24.64690559895833,
       "method": "asap",
-      "milp_solve_secs": 0.083472438,
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       "rolled_up_rqes": 52,
       "rqes": 62,
       "sla_ms": 3000.0,
@@ -3060,26 +3040,26 @@
     },
     {
       "active_deployments": 26,
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+        "ingest": 0.1541987508535385,
+        "query": 0.0024883886311841906,
+        "storage": 2.3129812628030777
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       "hydra_rqes": 0,
       "infeasible": false,
       "latency_ms": 958.6905598958333,
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       "method": "asap-norollup",
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@@ -3087,26 +3067,26 @@
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     {
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+        "ingest": 0.3189184367656708,
+        "query": 0.0024883886311841906,
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       "hydra_rqes": 0,
       "infeasible": false,
       "latency_ms": 958.6905598958333,
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       "method": "perquery",
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@@ -3114,28 +3094,28 @@
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     {
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+        "ingest": 3.1891843676567078,
+        "query": 3.0041753028193087e-6,
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       "meets_sla": true,
       "method": "autosketch",
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@@ -3143,26 +3123,26 @@
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     {
       "active_deployments": 5,
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+        "ingest": 0.215931236743927,
+        "query": 0.0011939309908407835,
+        "storage": 0.797562301158905
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       "hydra_rqes": 0,
       "infeasible": false,
       "latency_ms": 557.0905598958334,
       "median_latency_ms": 24.64690559895833,
       "method": "asap",
-      "milp_solve_secs": 0.086251812,
-      "objective": 0.013652155923666282,
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       "sla_ms": 10000.0,
@@ -3170,26 +3150,26 @@
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     {
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       "cpu_parts": {
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+        "ingest": 0.1541987508535385,
+        "query": 0.0024883886311841906,
+        "storage": 2.3129812628030777
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       "hydra_rqes": 0,
       "infeasible": false,
       "latency_ms": 958.6905598958333,
-      "median_latency_ms": 16.16864686468647,
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       "method": "asap-norollup",
-      "milp_solve_secs": 0.035655772,
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       "rolled_up_rqes": 0,
       "rqes": 62,
       "sla_ms": 10000.0,
@@ -3197,26 +3177,26 @@
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     {
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       "cpu_parts": {
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+        "ingest": 0.3189184367656708,
+        "query": 0.0024883886311841906,
+        "storage": 3.1891843676567078
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       "hydra_rqes": 0,
       "infeasible": false,
       "latency_ms": 958.6905598958333,
-      "median_latency_ms": 16.16864686468647,
+      "median_latency_ms": 14.763696369636964,
       "method": "perquery",
-      "milp_solve_secs": 0.042909183,
-      "objective": 0.059665584551662584,
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       "rolled_up_rqes": 0,
       "rqes": 62,
       "sla_ms": 10000.0,
@@ -3224,28 +3204,28 @@
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     {
       "active_deployments": 62,
-      "benchmark_secs_paper_rate": 540.0,
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+      "benchmark_secs_paper_rate": 420.0,
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+        "ingest": 3.1891843676567078,
+        "query": 3.0041753028193087e-6,
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       "hydra_rqes": 0,
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       "median_latency_ms": 4.901572265625,
       "meets_sla": true,
       "method": "autosketch",
-      "objective": 0.4296071454786008,
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-tacc99.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-tacc99.json
index ff28a352..c9356489 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-tacc99.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared1-tacc99.json
@@ -1,7 +1,7 @@
 {
   "autosketch": {
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-    "distinct_probes": 11,
+    "benchmark_secs_paper_rate": 600.0,
+    "distinct_probes": 10,
     "probed_configs": [
       {
         "distinct_keys": 1000000.0,
@@ -27,7 +27,7 @@
         "distinct_keys": 0.0,
         "metric": "http",
         "params": {
-          "alpha": 0.01
+          "alpha": 0.02
         },
         "sketch": "dd",
         "tail_index": 2.0,
@@ -37,7 +37,7 @@
         "distinct_keys": 0.0,
         "metric": "http",
         "params": {
-          "alpha": 0.02
+          "alpha": 0.05
         },
         "sketch": "dd",
         "tail_index": 2.0,
@@ -47,7 +47,7 @@
         "distinct_keys": 0.0,
         "metric": "http",
         "params": {
-          "alpha": 0.05
+          "alpha": 0.1
         },
         "sketch": "dd",
         "tail_index": 2.0,
@@ -87,7 +87,7 @@
         "distinct_keys": 0.0,
         "metric": "http",
         "params": {
-          "k": 200
+          "k": 100
         },
         "sketch": "kll-percall",
         "tail_index": 2.0,
@@ -102,20 +102,10 @@
         "sketch": "kll-percall",
         "tail_index": 2.0,
         "zipf_s": null
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-        "metric": "http",
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     ],
     "probes": 166,
-    "search_secs": 0.002251738
+    "search_secs": 0.002774706
   },
   "cost_model": "w_cpu * AUC(CPU) + w_mem * AUC(memory), billed by use; latency = longest chain, reported",
   "dropped_unservable": {
@@ -159,7 +149,7 @@
       "latency_ms": 1568.9819335937495,
       "median_latency_ms": 84.09261067708331,
       "method": "asap",
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+      "milp_solve_secs": 0.065344393,
       "objective": 0.7149272939485984,
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@@ -185,7 +175,7 @@
       "latency_ms": 1568.9819335937495,
       "median_latency_ms": 84.09261067708331,
       "method": "asap",
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+      "milp_solve_secs": 0.065197037,
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@@ -211,7 +201,7 @@
       "latency_ms": 1568.9819335937495,
       "median_latency_ms": 84.09261067708331,
       "method": "asap",
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+      "milp_solve_secs": 0.065734791,
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@@ -237,7 +227,7 @@
       "latency_ms": 1568.9819335937495,
       "median_latency_ms": 84.09261067708331,
       "method": "asap",
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+      "milp_solve_secs": 0.065745789,
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       "rolled_up_rqes": 47,
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@@ -263,7 +253,7 @@
       "latency_ms": 1568.9819335937495,
       "median_latency_ms": 84.09261067708331,
       "method": "asap",
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+      "milp_solve_secs": 0.072504764,
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@@ -289,7 +279,7 @@
       "latency_ms": 1568.9819335937495,
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@@ -315,7 +305,7 @@
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@@ -341,7 +331,7 @@
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@@ -2425,7 +2415,7 @@
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@@ -2478,7 +2468,7 @@
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@@ -2531,7 +2521,7 @@
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@@ -2804,7 +2794,7 @@
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@@ -2824,7 +2814,7 @@
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@@ -2857,7 +2847,7 @@
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@@ -2877,7 +2867,7 @@
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@@ -2910,7 +2900,7 @@
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@@ -2930,7 +2920,7 @@
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@@ -2984,7 +2974,7 @@
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@@ -3011,7 +3001,7 @@
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@@ -3020,7 +3010,7 @@
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@@ -3040,7 +3030,7 @@
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@@ -3067,7 +3057,7 @@
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@@ -3121,7 +3111,7 @@
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@@ -3130,7 +3120,7 @@
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@@ -3150,7 +3140,7 @@
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared8-tacc90.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared8-tacc90.json
index 31936530..2380dc20 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared8-tacc90.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared8-tacc90.json
@@ -1,7 +1,7 @@
 {
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@@ -27,27 +27,7 @@
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@@ -2651,26 +2631,26 @@
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@@ -2707,26 +2687,26 @@
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@@ -2734,26 +2714,26 @@
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@@ -2761,26 +2741,26 @@
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@@ -2923,26 +2903,26 @@
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@@ -2950,26 +2930,26 @@
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@@ -2977,26 +2957,26 @@
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@@ -3004,28 +2984,28 @@
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@@ -3033,26 +3013,26 @@
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@@ -3060,26 +3040,26 @@
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@@ -3087,26 +3067,26 @@
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@@ -3114,28 +3094,28 @@
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-        "query": 3.6050182075261585e-6,
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+        "ingest": 3.8270212411880493,
+        "query": 3.60501036338317e-6,
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       "hydra_rqes": 0,
       "latency_ms": 490.15722656250006,
       "median_latency_ms": 4.901572265625,
       "meets_sla": true,
       "method": "autosketch",
-      "objective": 0.5166781367591313,
-      "planning_secs": 0.003808329,
-      "probes": 332,
+      "objective": 0.4887561678720843,
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+      "probes": 276,
       "rolled_up_rqes": 0,
       "rqes": 124,
       "sla_ms": 3000.0,
@@ -3143,26 +3123,26 @@
     },
     {
       "active_deployments": 5,
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+      "cpu": 0.2410012749651247,
       "cpu_parts": {
         "compaction": 0.0,
-        "ingest": 0.11865320000000001,
-        "query": 0.1266855738324515
+        "ingest": 0.11458600000000001,
+        "query": 0.1264152749651247
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-      "gib": 1.0274441553580245,
+      "gib": 1.014926255091841,
       "gib_parts": {
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-        "ingest": 0.216713547706604,
-        "query": 0.0014336420523605052,
-        "storage": 0.8092969655990601
+        "ingest": 0.215931236743927,
+        "query": 0.0014327171890089407,
+        "storage": 0.797562301158905
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       "hydra_rqes": 0,
       "infeasible": false,
       "latency_ms": 557.0905598958334,
       "median_latency_ms": 24.64690559895833,
       "method": "asap",
-      "milp_solve_secs": 0.215816621,
-      "objective": 0.014508346831557495,
+      "milp_solve_secs": 0.207429973,
+      "objective": 0.014276973471246242,
       "rolled_up_rqes": 104,
       "rqes": 124,
       "sla_ms": 10000.0,
@@ -3170,26 +3150,26 @@
     },
     {
       "active_deployments": 26,
-      "cpu": 0.5806692567209003,
+      "cpu": 0.5722012856317912,
       "cpu_parts": {
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-        "ingest": 0.44888759999999994,
-        "query": 0.13178165672090036
+        "ingest": 0.4405591999999998,
+        "query": 0.1316420856317914
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+      "gib": 2.470166080014037,
       "gib_parts": {
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-        "storage": 2.3621878400444984
+        "ingest": 0.1541987508535385,
+        "query": 0.0029860663574210267,
+        "storage": 2.3129812628030777
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       "hydra_rqes": 0,
       "infeasible": false,
       "latency_ms": 958.6905598958333,
-      "median_latency_ms": 16.16864686468647,
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       "method": "asap-norollup",
-      "milp_solve_secs": 0.088251,
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       "rolled_up_rqes": 0,
       "rqes": 124,
       "sla_ms": 10000.0,
@@ -3197,26 +3177,26 @@
     },
     {
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       "cpu_parts": {
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-        "ingest": 1.9252280000000028,
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+        "ingest": 1.9160848000000026,
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-        "storage": 3.947661280632019
+        "ingest": 0.6378368735313416,
+        "query": 0.0026638388310841555,
+        "storage": 3.8270212411880493
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       "hydra_rqes": 0,
       "infeasible": false,
       "latency_ms": 958.6905598958333,
-      "median_latency_ms": 16.16864686468647,
+      "median_latency_ms": 14.763696369636964,
       "method": "perquery",
-      "milp_solve_secs": 0.092439764,
-      "objective": 0.10354332166621069,
+      "milp_solve_secs": 0.089071061,
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       "rolled_up_rqes": 0,
       "rqes": 124,
       "sla_ms": 10000.0,
@@ -3224,28 +3204,28 @@
     },
     {
       "active_deployments": 124,
-      "benchmark_secs_paper_rate": 540.0,
-      "cpu": 12.260760061299113,
+      "benchmark_secs_paper_rate": 420.0,
+      "cpu": 11.577469956031775,
       "cpu_parts": {
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-        "query": 0.08096166129911817
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+        "ingest": 3.8270212411880493,
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       "method": "autosketch",
-      "objective": 0.5166781367591313,
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-      "probes": 332,
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diff --git a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared8-tacc99.json b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared8-tacc99.json
index 8d859be9..a833e6a8 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared8-tacc99.json
+++ b/rqe-optimizer/results/autosketch-vs-asap-targets/synthetic-templatesmultigroup-shared8-tacc99.json
@@ -1,7 +1,7 @@
 {
   "autosketch": {
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-    "distinct_probes": 11,
+    "benchmark_secs_paper_rate": 600.0,
+    "distinct_probes": 10,
     "probed_configs": [
       {
         "distinct_keys": 1000000.0,
@@ -27,7 +27,7 @@
         "distinct_keys": 0.0,
         "metric": "http",
         "params": {
-          "alpha": 0.01
+          "alpha": 0.02
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         "tail_index": 2.0,
@@ -37,7 +37,7 @@
         "distinct_keys": 0.0,
         "metric": "http",
         "params": {
-          "alpha": 0.02
+          "alpha": 0.05
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         "sketch": "dd",
         "tail_index": 2.0,
@@ -47,7 +47,7 @@
         "distinct_keys": 0.0,
         "metric": "http",
         "params": {
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+          "alpha": 0.1
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         "sketch": "dd",
         "tail_index": 2.0,
@@ -87,7 +87,7 @@
         "distinct_keys": 0.0,
         "metric": "http",
         "params": {
-          "k": 200
+          "k": 100
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         "sketch": "kll-percall",
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@@ -102,20 +102,10 @@
         "sketch": "kll-percall",
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         "zipf_s": null
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     "probes": 332,
-    "search_secs": 0.003780365
+    "search_secs": 0.009112471
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   "cost_model": "w_cpu * AUC(CPU) + w_mem * AUC(memory), billed by use; latency = longest chain, reported",
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@@ -159,7 +149,7 @@
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@@ -185,7 +175,7 @@
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@@ -211,7 +201,7 @@
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@@ -237,7 +227,7 @@
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@@ -263,7 +253,7 @@
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@@ -289,7 +279,7 @@
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@@ -315,7 +305,7 @@
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@@ -341,7 +331,7 @@
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@@ -367,7 +357,7 @@
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@@ -393,7 +383,7 @@
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@@ -419,7 +409,7 @@
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@@ -445,7 +435,7 @@
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@@ -471,7 +461,7 @@
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@@ -497,7 +487,7 @@
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@@ -523,7 +513,7 @@
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@@ -549,7 +539,7 @@
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@@ -575,7 +565,7 @@
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@@ -601,7 +591,7 @@
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@@ -627,7 +617,7 @@
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@@ -653,7 +643,7 @@
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@@ -679,7 +669,7 @@
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@@ -705,7 +695,7 @@
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@@ -731,7 +721,7 @@
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@@ -757,7 +747,7 @@
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@@ -783,7 +773,7 @@
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@@ -809,7 +799,7 @@
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@@ -835,7 +825,7 @@
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@@ -861,7 +851,7 @@
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@@ -887,7 +877,7 @@
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@@ -913,7 +903,7 @@
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@@ -939,7 +929,7 @@
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@@ -965,7 +955,7 @@
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@@ -991,7 +981,7 @@
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@@ -1043,7 +1033,7 @@
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         "compaction": 0.0,
@@ -2445,7 +2435,7 @@
       "meets_sla": false,
       "method": "autosketch",
       "objective": 11.928364133538325,
-      "planning_secs": 0.003780365,
+      "planning_secs": 0.009112471,
       "probes": 332,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -2478,7 +2468,7 @@
     },
     {
       "active_deployments": 124,
-      "benchmark_secs_paper_rate": 660.0,
+      "benchmark_secs_paper_rate": 600.0,
       "cpu": 11.928364133538325,
       "cpu_parts": {
         "compaction": 0.0,
@@ -2498,7 +2488,7 @@
       "meets_sla": false,
       "method": "autosketch",
       "objective": 11.928364133538325,
-      "planning_secs": 0.003780365,
+      "planning_secs": 0.009112471,
       "probes": 332,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -2531,7 +2521,7 @@
     },
     {
       "active_deployments": 124,
-      "benchmark_secs_paper_rate": 660.0,
+      "benchmark_secs_paper_rate": 600.0,
       "cpu": 11.928364133538325,
       "cpu_parts": {
         "compaction": 0.0,
@@ -2551,7 +2541,7 @@
       "meets_sla": false,
       "method": "autosketch",
       "objective": 11.928364133538325,
-      "planning_secs": 0.003780365,
+      "planning_secs": 0.009112471,
       "probes": 332,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -2578,7 +2568,7 @@
       "latency_ms": 1835.6486002604163,
       "median_latency_ms": 84.09261067708331,
       "method": "asap",
-      "milp_solve_secs": 0.140538659,
+      "milp_solve_secs": 0.281182273,
       "objective": 0.6992298460716512,
       "rolled_up_rqes": 84,
       "rqes": 124,
@@ -2605,7 +2595,7 @@
       "latency_ms": 1835.6486002604163,
       "median_latency_ms": 34.35648600260416,
       "method": "asap-norollup",
-      "milp_solve_secs": 0.071085064,
+      "milp_solve_secs": 0.143043632,
       "objective": 1.0926536540716514,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -2632,7 +2622,7 @@
       "latency_ms": 2102.315266927083,
       "median_latency_ms": 34.35648600260416,
       "method": "perquery",
-      "milp_solve_secs": 0.083555534,
+      "milp_solve_secs": 0.169876065,
       "objective": 2.52400464856054,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -2641,7 +2631,7 @@
     },
     {
       "active_deployments": 124,
-      "benchmark_secs_paper_rate": 660.0,
+      "benchmark_secs_paper_rate": 600.0,
       "cpu": 11.928364133538325,
       "cpu_parts": {
         "compaction": 0.0,
@@ -2661,7 +2651,7 @@
       "meets_sla": true,
       "method": "autosketch",
       "objective": 11.928364133538325,
-      "planning_secs": 0.003780365,
+      "planning_secs": 0.009112471,
       "probes": 332,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -2688,7 +2678,7 @@
       "latency_ms": 1835.6486002604163,
       "median_latency_ms": 84.09261067708331,
       "method": "asap",
-      "milp_solve_secs": 0.150180987,
+      "milp_solve_secs": 0.308797258,
       "objective": 0.6992298460716512,
       "rolled_up_rqes": 84,
       "rqes": 124,
@@ -2715,7 +2705,7 @@
       "latency_ms": 3335.11134765625,
       "median_latency_ms": 34.35648600260416,
       "method": "asap-norollup",
-      "milp_solve_secs": 0.076966493,
+      "milp_solve_secs": 0.149992947,
       "objective": 1.0711944540716518,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -2742,7 +2732,7 @@
       "latency_ms": 3335.11134765625,
       "median_latency_ms": 34.35648600260416,
       "method": "perquery",
-      "milp_solve_secs": 0.084986194,
+      "milp_solve_secs": 0.168874993,
       "objective": 2.5154873152272073,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -2751,7 +2741,7 @@
     },
     {
       "active_deployments": 124,
-      "benchmark_secs_paper_rate": 660.0,
+      "benchmark_secs_paper_rate": 600.0,
       "cpu": 11.928364133538325,
       "cpu_parts": {
         "compaction": 0.0,
@@ -2771,7 +2761,7 @@
       "meets_sla": true,
       "method": "autosketch",
       "objective": 11.928364133538325,
-      "planning_secs": 0.003780365,
+      "planning_secs": 0.009112471,
       "probes": 332,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -2804,7 +2794,7 @@
     },
     {
       "active_deployments": 124,
-      "benchmark_secs_paper_rate": 660.0,
+      "benchmark_secs_paper_rate": 600.0,
       "cpu": 11.928364133538325,
       "cpu_parts": {
         "compaction": 0.0,
@@ -2824,7 +2814,7 @@
       "meets_sla": false,
       "method": "autosketch",
       "objective": 0.6094644827420113,
-      "planning_secs": 0.003780365,
+      "planning_secs": 0.009112471,
       "probes": 332,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -2857,7 +2847,7 @@
     },
     {
       "active_deployments": 124,
-      "benchmark_secs_paper_rate": 660.0,
+      "benchmark_secs_paper_rate": 600.0,
       "cpu": 11.928364133538325,
       "cpu_parts": {
         "compaction": 0.0,
@@ -2877,7 +2867,7 @@
       "meets_sla": false,
       "method": "autosketch",
       "objective": 0.6094644827420113,
-      "planning_secs": 0.003780365,
+      "planning_secs": 0.009112471,
       "probes": 332,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -2910,7 +2900,7 @@
     },
     {
       "active_deployments": 124,
-      "benchmark_secs_paper_rate": 660.0,
+      "benchmark_secs_paper_rate": 600.0,
       "cpu": 11.928364133538325,
       "cpu_parts": {
         "compaction": 0.0,
@@ -2930,7 +2920,7 @@
       "meets_sla": false,
       "method": "autosketch",
       "objective": 0.6094644827420113,
-      "planning_secs": 0.003780365,
+      "planning_secs": 0.009112471,
       "probes": 332,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -2957,7 +2947,7 @@
       "latency_ms": 1835.6486002604163,
       "median_latency_ms": 94.35648600260416,
       "method": "asap",
-      "milp_solve_secs": 0.760368069,
+      "milp_solve_secs": 1.356104214,
       "objective": 0.06786610578432939,
       "rolled_up_rqes": 92,
       "rqes": 124,
@@ -2984,7 +2974,7 @@
       "latency_ms": 1835.6486002604163,
       "median_latency_ms": 34.35648600260416,
       "method": "asap-norollup",
-      "milp_solve_secs": 0.079132898,
+      "milp_solve_secs": 0.154505235,
       "objective": 0.11553285338709168,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -3011,7 +3001,7 @@
       "latency_ms": 2102.315266927083,
       "median_latency_ms": 34.35648600260416,
       "method": "perquery",
-      "milp_solve_secs": 0.086591224,
+      "milp_solve_secs": 0.167275595,
       "objective": 0.22882448454617363,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -3020,7 +3010,7 @@
     },
     {
       "active_deployments": 124,
-      "benchmark_secs_paper_rate": 660.0,
+      "benchmark_secs_paper_rate": 600.0,
       "cpu": 11.928364133538325,
       "cpu_parts": {
         "compaction": 0.0,
@@ -3040,7 +3030,7 @@
       "meets_sla": true,
       "method": "autosketch",
       "objective": 0.6094644827420113,
-      "planning_secs": 0.003780365,
+      "planning_secs": 0.009112471,
       "probes": 332,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -3067,7 +3057,7 @@
       "latency_ms": 1835.6486002604163,
       "median_latency_ms": 94.35648600260416,
       "method": "asap",
-      "milp_solve_secs": 0.594611808,
+      "milp_solve_secs": 1.599110276,
       "objective": 0.06786610578432939,
       "rolled_up_rqes": 92,
       "rqes": 124,
@@ -3094,7 +3084,7 @@
       "latency_ms": 3335.11134765625,
       "median_latency_ms": 34.35648600260416,
       "method": "asap-norollup",
-      "milp_solve_secs": 0.079044816,
+      "milp_solve_secs": 0.156216614,
       "objective": 0.11478328246366784,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -3121,7 +3111,7 @@
       "latency_ms": 3335.11134765625,
       "median_latency_ms": 34.35648600260416,
       "method": "perquery",
-      "milp_solve_secs": 0.088830511,
+      "milp_solve_secs": 0.188806945,
       "objective": 0.2285246029886714,
       "rolled_up_rqes": 0,
       "rqes": 124,
@@ -3130,7 +3120,7 @@
     },
     {
       "active_deployments": 124,
-      "benchmark_secs_paper_rate": 660.0,
+      "benchmark_secs_paper_rate": 600.0,
       "cpu": 11.928364133538325,
       "cpu_parts": {
         "compaction": 0.0,
@@ -3150,7 +3140,7 @@
       "meets_sla": true,
       "method": "autosketch",
       "objective": 0.6094644827420113,
-      "planning_secs": 0.003780365,
+      "planning_secs": 0.009112471,
       "probes": 332,
       "rolled_up_rqes": 0,
       "rqes": 124,

From 85a99bd00ea74ca486394075dd3809ea3e2300b6 Mon Sep 17 00:00:00 2001
From: zz_y <zeyingz@umd.edu>
Date: Wed, 14 Oct 2026 02:32:32 +0000
Subject: [PATCH 4/5] review: one filter helper with name checks and tests;
 README provenance and claims

- filtered_configs()/check_filters(): --sketches or --configs skips the
  exact rows; a misspelled name exits; tests for both.
- The wide-merge comment says per fold, with operands 4x larger.
- rqe-optimizer README: the -hydra row's 2026-10-14 rerun, the one
  solver-tolerance violation, e2e-rate10 planned on the pre-#213 grid.
- -hydra README: rerun provenance moved to Reproduce; hydra-kll's figure
  marked unmerged, with the all-merge-counts value.
- raw README: measurement dates, clnode130.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 rqe-optimizer/README.md                       |  6 +--
 .../autosketch-vs-asap-hydra/README.md        | 20 +++++----
 .../autosketch-vs-asap-inputs/raw/README.md   |  7 +--
 scripts/study_saturation.py                   | 44 +++++++++++++++----
 scripts/test_study_saturation.py              | 22 +++++++++-
 5 files changed, 74 insertions(+), 25 deletions(-)

diff --git a/rqe-optimizer/README.md b/rqe-optimizer/README.md
index 830148e4..b91fbf60 100644
--- a/rqe-optimizer/README.md
+++ b/rqe-optimizer/README.md
@@ -17,8 +17,8 @@ ProjectASAP/ASAPQuery#777 (`docs/evaluation/autosketch-vs-planner.md`).
 | `examples/autosketch_vs_asap.rs` | the §6.3 runner: one workload in, one result JSON out | |
 | `examples/workload_scenarios.rs` | how the optimal plan moves as one knob of a workload changes (types, groupings, windows, SLAs) | |
 | `examples/small_problem.rs` | a toy instance solved end to end (brute force or MILP) | |
-| `results/autosketch-vs-asap-hydra/` | **the current §6.3 results** (2026-10-11; classic and all rerun 2026-10-13 without templates 7 and 9): roll-ups, the roll-up ablation, Hydra candidates, the classic, multi-grouping and mixed + multi-grouping workloads, and each plan | current |
-| `results/e2e-rate10/` | the classic, multi-grouping and all workloads (r = m = 1) re-planned at 10 samples/s per series, for the end-to-end run | current (e2e input) |
+| `results/autosketch-vs-asap-hydra/` | **the current §6.3 results** (2026-10-11; classic and all rerun 2026-10-13 without templates 7 and 9; all rerun 2026-10-14 on the denser grid, #213): roll-ups, the roll-up ablation, Hydra candidates, the classic, multi-grouping and mixed + multi-grouping workloads, and each plan | current |
+| `results/e2e-rate10/` | the classic, multi-grouping and all workloads (r = m = 1) re-planned at 10 samples/s per series, for the end-to-end run (on the grid before #213's denser one) | current (e2e input) |
 | `results/autosketch-vs-asap-inputs/` | the accuracy curves every run reads (#138's study), and #138's tables and raw records | current (shared input) |
 | `results/autosketch-vs-asap-synthetic/`, `results/autosketch-vs-asap-synthetic-sla/` | the 2026-10-08 results (#138): before roll-ups and the KLL footprint fix | superseded by `-hydra` |
 | `data/autosketch-eval/table.json` | the trace workloads (Alibaba 2022, Google 2011, BOOM) | not yet rerun on cost by use |
@@ -57,7 +57,7 @@ Start with the summaries and figures:
 | `sla_results` | version 2: each method's cheapest plan at each SLA (`sla_ms`); `infeasible` when no plan meets it; AutoSketch's has `meets_sla` |
 | `frontier` | each method's tightest feasible bound and AutoSketch's latency |
 | `autosketch` | AutoSketch's search: probes, `search_secs`, `benchmark_secs_measured` (its benchmark runs, timed) |
-| `dropped_unservable`, `sanity_violations` | RQEs no method could serve, and failed checks (ASAP ≤ no roll-ups ≤ PerQuery, ASAP ≤ AutoSketch); both are empty in every committed run |
+| `dropped_unservable`, `sanity_violations` | RQEs no method could serve, and failed checks (ASAP ≤ no roll-ups ≤ PerQuery, ASAP ≤ AutoSketch); both are empty in every committed run except one solver-tolerance frontier check in `autosketch-vs-asap-targets` (see its README) |
 | `notes` | what the runner assumed |
 
 Every entry of `results` and `sla_results` is one plan:
diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/README.md b/rqe-optimizer/results/autosketch-vs-asap-hydra/README.md
index f349452f..34174c65 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/README.md
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/README.md
@@ -135,7 +135,7 @@ than the grid at the W that needs.
 W = 65536 (#213) widens what Hydra is accurate for: on groups holding ≥ 1% of
 the records, the worst error at 1e7 records drops from 0.283 to 0.039
 (hydra-hll, `http`), 0.074 to 0.021 (hydra-hll, `flows`) and 0.054 to 0.017
-(hydra-kll). But it is the most expensive grid on every axis (3.3 GB per
+(hydra-kll, unmerged; 0.056 to 0.017 over every merge count). But it is the most expensive grid on every axis (3.3 GB per
 hydra-hll grid, 6.2 µs per insert on `http`), and it is never chosen either.
 
 hydra-univmon-cardinality reads ≈ 100% error at N ≥ 1e6 at every W
@@ -217,8 +217,8 @@ python3 scripts/plot_autosketch_vs_asap_synthetic.py $DIR
 python3 scripts/plot_autosketch_vs_asap_sla.py $DIR $DIR/synthetic-*-tp95.json
 ```
 
-Runs: Xeon E5-2683 v3, 56 cores, `--runs 3`, runner from sketch-bench
-`hydra/eval-integration` at 44ac160. Classic: one large table per CloudLab node
+Runs: Xeon E5-2683 v3, 56 cores, `--runs 3`. First run (superseded by the
+reruns below): runner from sketch-bench `hydra/eval-integration` at 44ac160. Classic: one large table per CloudLab node
 (clnode178, 167; the small ones serially on clnode138), 2026-10-10.
 Multigroup and all (with the cube template): serially on one idle node,
 2026-10-11.
@@ -233,6 +233,14 @@ benchmark times are reused: the dropped RQEs used exact accumulators or a
 top-k config already probed on the same metric, so every probe was already
 measured and each workload's benchmark time is unchanged.
 
+Denser grid (2026-10-14, #213, runner at sketch-bench eval/dense-grid):
+multi-grouping on the 4 CloudLab nodes clnode109/155/167/178, then classic and
+all on #210's tables on the same 4 nodes, each node running its share
+serially. Plans: `--runs 1`, without `--no-chosen`, extracted with
+`scripts/extract_autosketch_plans.py`.
+
+The JSONs, figures and plans here are from that last rerun.
+
 ## Caveats
 
 - The cost model charges a per-group sketch its insert only, not routing a
@@ -247,9 +255,3 @@ measured and each workload's benchmark time is unchanged.
 - Template 12 groups by (dst_subnet, proto) rather than (dst_subnet,
   dst_port): answering 1e6 groups every minute took ~49 s and set every
   plan's batch latency above the largest SLA.
-
-Denser grid (2026-10-14, #213, runner at sketch-bench eval/dense-grid):
-multi-grouping on the 4 CloudLab nodes clnode109/155/167/178, then classic and
-all on #210's tables on the same 4 nodes, each node running its share
-serially. Plans: `--runs 1`, without `--no-chosen`, extracted with
-`scripts/extract_autosketch_plans.py`.
diff --git a/rqe-optimizer/results/autosketch-vs-asap-inputs/raw/README.md b/rqe-optimizer/results/autosketch-vs-asap-inputs/raw/README.md
index e26b7d99..e1f3d5a6 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-inputs/raw/README.md
+++ b/rqe-optimizer/results/autosketch-vs-asap-inputs/raw/README.md
@@ -30,11 +30,12 @@ Every accuracy run is `study_saturation.py --phase accuracy --seeds 3` plus:
 Run times are each file's first-to-last record timestamps; the refills ran
 about 40 minutes after their grids and are counted separately.
 
-## The denser grid (#213, 2026-10-14)
+## The denser grid (#213, measured 2026-10-13/14 UTC)
 
 Only the new configs, with the same arguments as the rows above plus
-`--sketches`/`--configs`; accuracy runs on clnode130, cost rows serially on
-idle clnode138.
+`--sketches`/`--configs`; accuracy runs on clnode130 (the same Xeon
+E5-2683 v3 node type), cost rows serially on idle clnode138, where the
+existing cost rows were measured.
 
 | File | Arguments | Feeds |
 |---|---|---|
diff --git a/scripts/study_saturation.py b/scripts/study_saturation.py
index 6f96b82c..63a3fcd4 100644
--- a/scripts/study_saturation.py
+++ b/scripts/study_saturation.py
@@ -191,6 +191,30 @@
 # of them in a merge more than a machine holds, and its error has saturated
 # by 16384 anyway.
 HYDRA_MAX_W = {"hydra-univmon-cardinality": 16384}
+
+
+def filtered_configs(args, variant, configs):
+    """`configs` narrowed by --sketches/--configs (adding configs to an
+    existing study), or None when --sketches leaves `variant` out."""
+    if args.sketches and variant not in args.sketches.split(","):
+        return None
+    if args.configs:
+        configs = [c for c in configs if c in args.configs.split(",")]
+    return configs
+
+
+def check_filters(args):
+    """Exit on a --sketches or --configs name that matches nothing, so a typo
+    does not silently measure nothing."""
+    variants = {v for _, v, _, _, _ in SKETCHES} | set(HYDRA_CELLS)
+    configs = {c for _, _, cs, _, _ in SKETCHES for c in cs}
+    for name, known, flag in [(args.sketches, variants, "--sketches"),
+                              (args.configs, configs, "--configs")]:
+        unknown = sorted(set((name or "").split(",")) - known - {""})
+        if unknown:
+            sys.exit(f"{flag}: no such {unknown}")
+
+
 HYDRA_DATAGEN = os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", "configs",
                              "datagen")
 HYDRA_TABLE = "hydra_saturation.csv"
@@ -415,18 +439,19 @@ def optimizer_cost(args, families):
     for family, variant, configs, comparator, metric in SKETCHES:
         if family not in families or family not in OPTIMIZER_FAMILIES:
             continue
-        if args.sketches and variant not in args.sketches.split(","):
+        configs = filtered_configs(args, variant, configs)
+        if configs is None:
             continue
         metrics[variant] = metric
-        if args.configs:
-            configs = [c for c in configs if c in args.configs.split(",")]
         for config in configs[:1] if args.one_config else configs:
             heaps = [f" heap={h}" for h in TOPK_HEAPS] if family == "topk" else [""]
             for heap in heaps:
                 rows.append((variant, "lib", ["--config", config + heap], comparator,
                              cost_dataset(family)))
-    # --sketches adds rows to an existing table, which has the exact ones.
-    for variant, comparator, spec in [] if args.sketches else EXACT_COST_ROWS:
+    # --sketches/--configs add rows to an existing table, which has the exact
+    # ones.
+    narrowed = args.sketches or args.configs
+    for variant, comparator, spec in [] if narrowed else EXACT_COST_ROWS:
         metrics[variant] = EXACT_METRIC
         rows.append((variant, "exact", [], comparator, ["--spec", spec, "--dtype", "i64"]))
     # Hydra: each eval variant on its datasets at the full schema, at each
@@ -476,7 +501,8 @@ def sketchbench(variant, library, config, data, passes):
         runs, warmup = HYDRA_COST_RUNS if variant.startswith("hydra-") else \
             (COST_RUNS, COST_WARMUP)
         # A Hydra grid past 3 x 16384 holds GBs; 16 of them in one merge do
-        # not fit, so it merges 4 (merge CPU is per merge either way).
+        # not fit, so it merges 4. Merge CPU is per fold either way, though
+        # each fold's operand holds 4x the items (a quarter of COST_N).
         wide = variant.startswith("hydra-") and \
             int(re.search(r"cols=(\d+)", config[1]).group(1)) > 16384
         sketchbench(variant, library, config, data, [
@@ -875,6 +901,7 @@ def main():
                         help="hydra: only these groupings, ';'-separated, labels by name "
                              "joined by ',' in schema order")
     args = parser.parse_args()
+    check_filters(args)
     if args.phase == "hydra":
         return hydra(args)
 
@@ -900,10 +927,9 @@ def main():
     for family, variant, configs, comparator, metric in SKETCHES:
         if family not in families:
             continue
-        if args.sketches and variant not in args.sketches.split(","):
+        configs = filtered_configs(args, variant, configs)
+        if configs is None:
             continue
-        if args.configs:
-            configs = [c for c in configs if c in args.configs.split(",")]
         configs = configs[:1] if args.one_config else configs
         if family == "topk":
             configs = [c + ("" if k == TOPK_K else f" topk_k={k}")
diff --git a/scripts/test_study_saturation.py b/scripts/test_study_saturation.py
index e6668b32..dd98177f 100644
--- a/scripts/test_study_saturation.py
+++ b/scripts/test_study_saturation.py
@@ -18,7 +18,8 @@
 sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
 
 from study_saturation import (  # noqa: E402
-    HYDRA_COLUMNS, HYDRA_DATAGEN, HYDRA_SWEEPS, checkpoints, covered_max, hydra_groupings,
+    HYDRA_COLUMNS, HYDRA_DATAGEN, HYDRA_SWEEPS, check_filters, checkpoints, covered_max,
+    filtered_configs, hydra_groupings,
     hydra_jobs, hydra_labels, hydra_spec, n_saturation, n_star, read_curve, read_per_group)
 
 SCRIPT = os.path.join(os.path.dirname(os.path.abspath(__file__)), "study_saturation.py")
@@ -838,5 +839,24 @@ def test_univmon_stops_at_16384_and_the_others_reach_65536(self):
         self.assertEqual(max(widths["hydra-kll"]), 65536)
 
 
+class FilterTest(unittest.TestCase):
+    def args(self, sketches=None, configs=None):
+        return type("Args", (), {"sketches": sketches, "configs": configs})()
+
+    def test_sketches_and_configs_narrow_a_study_to_new_configs(self):
+        a = self.args("kll-percall", "k=25,k=100")
+        self.assertEqual(filtered_configs(a, "kll-percall", ["k=25", "k=50", "k=100"]),
+                         ["k=25", "k=100"])
+        self.assertIsNone(filtered_configs(a, "dd", ["alpha=0.1"]))
+        self.assertEqual(filtered_configs(self.args(), "dd", ["alpha=0.1"]), ["alpha=0.1"])
+
+    def test_a_misspelled_sketch_or_config_exits(self):
+        check_filters(self.args("kll-percall,hydra-hll", "k=25,alpha=0.1"))
+        with self.assertRaises(SystemExit):
+            check_filters(self.args("kll"))
+        with self.assertRaises(SystemExit):
+            check_filters(self.args(None, "k=26"))
+
+
 if __name__ == "__main__":
     unittest.main()

From 512361ec29691854d4f9cabab987f6dabfe1f21b Mon Sep 17 00:00:00 2001
From: zz_y <zeyingz@umd.edu>
Date: Wed, 14 Oct 2026 04:52:14 +0000
Subject: [PATCH 5/5] review round 2: --sketches help names the Hydra flags;
 planning-time comparability; rewrap

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 .../autosketch-vs-asap-hydra/README.md        | 36 ++++++++++---------
 scripts/study_saturation.py                   |  3 +-
 2 files changed, 22 insertions(+), 17 deletions(-)

diff --git a/rqe-optimizer/results/autosketch-vs-asap-hydra/README.md b/rqe-optimizer/results/autosketch-vs-asap-hydra/README.md
index 34174c65..7b80280d 100644
--- a/rqe-optimizer/results/autosketch-vs-asap-hydra/README.md
+++ b/rqe-optimizer/results/autosketch-vs-asap-hydra/README.md
@@ -84,10 +84,12 @@ plus its measured benchmark, approxbench accuracy runs at 1e8 items):
 | mixed + multi-grouping, m = 16 | 1664 | 16.1 s | 17.1 s | 0.064 s + 6,335 s |
 
 The denser grid gives ASAP and PerQuery more candidates (6 KLL and 5 DDSketch
-configs instead of 3 and 4), so their MILPs are larger than before
-(mixed + multi-grouping: 0.94 → 2.1 s). AutoSketch reaches a feasible config
-sooner (15 probes instead of 19 on mixed + multi-grouping), so its measured
-benchmark is shorter (481 → 396 s).
+configs instead of 3 and 4), so their MILPs are larger than before (mixed +
+multi-grouping: 0.94 → 2.1 s). The reruns also spread over 4 nodes and ran
+beside each other's shares, so planning times are not comparable across reruns
+to better than about 2×; within one rerun they are. AutoSketch reaches a
+feasible config sooner (15 probes instead of 19 on mixed + multi-grouping), so
+its measured benchmark is shorter (481 → 396 s).
 
 **What the denser grid changed** (95%, cheapest plans): CPU cost falls 0–1.4%
 (mixed 2.38 → 2.35 vCPU, mixed + multi-grouping 2.60 → 2.57), since insert
@@ -135,8 +137,9 @@ than the grid at the W that needs.
 W = 65536 (#213) widens what Hydra is accurate for: on groups holding ≥ 1% of
 the records, the worst error at 1e7 records drops from 0.283 to 0.039
 (hydra-hll, `http`), 0.074 to 0.021 (hydra-hll, `flows`) and 0.054 to 0.017
-(hydra-kll, unmerged; 0.056 to 0.017 over every merge count). But it is the most expensive grid on every axis (3.3 GB per
-hydra-hll grid, 6.2 µs per insert on `http`), and it is never chosen either.
+(hydra-kll, unmerged; 0.056 to 0.017 over every merge count). But it is the
+most expensive grid on every axis (3.3 GB per hydra-hll grid, 6.2 µs per
+insert on `http`), and it is never chosen either.
 
 hydra-univmon-cardinality reads ≈ 100% error at N ≥ 1e6 at every W
 (8 layers × a small heap saturate at ~1e6 distinct values per cell), so it is
@@ -184,15 +187,16 @@ zcat plans/synthetic-templatesmultigroup-shared1.plans.json.gz | jq '.plans[]
 
 ## Inputs
 
-- `inputs/saturation/optimizer_cost/rqe_atomic_costs.json`: the cost table,
-  63 rows (56, plus #213's KLL `k` 25/100/400, DDSketch α 0.1 and Hydra
-  W = 65536 rows), measured serially on idle clnode138 (`study_saturation.py --phase
+- `inputs/saturation/optimizer_cost/rqe_atomic_costs.json`: the cost table, 63
+  rows (56, plus #213's KLL `k` 25/100/400, DDSketch α 0.1 and Hydra W = 65536
+  rows), measured serially on idle clnode138 (`study_saturation.py --phase
   optimizer-cost --seeds 3 --hydra-variants hydra-hll,hydra-kll`), including
   Hydra rows per dataset (`measured_at.dataset`) and #192's KLL footprint.
 - `inputs/saturation/hydra_saturation.csv`: the Hydra study (`--phase hydra`,
-  #202), 7,778 runs on 4 CloudLab nodes (#213 added 999 at W = 65536); hydra-kll on `hydra_http_latency`
-  rerun with per-service latency scales (×1–10 log-uniform), so groups differ
-  in distribution as they do in practice.
+  #202), 7,778 runs on 4 CloudLab nodes (#213 added 999 at W = 65536);
+  hydra-kll on `hydra_http_latency` rerun with per-service latency scales
+  (×1–10 log-uniform), so groups differ in distribution as they do in
+  practice.
 - The accuracy curves (`out_grid_1e7_cost/`, `out_1e9/`) are the committed
   #138 study's, in `../autosketch-vs-asap-inputs/saturation/` (#194), with
   #213's new KLL and DDSketch configs appended.
@@ -218,10 +222,10 @@ python3 scripts/plot_autosketch_vs_asap_sla.py $DIR $DIR/synthetic-*-tp95.json
 ```
 
 Runs: Xeon E5-2683 v3, 56 cores, `--runs 3`. First run (superseded by the
-reruns below): runner from sketch-bench `hydra/eval-integration` at 44ac160. Classic: one large table per CloudLab node
-(clnode178, 167; the small ones serially on clnode138), 2026-10-10.
-Multigroup and all (with the cube template): serially on one idle node,
-2026-10-11.
+reruns below): runner from sketch-bench `hydra/eval-integration` at 44ac160.
+Classic: one large table per CloudLab node (clnode178, 167; the small ones
+serially on clnode138), 2026-10-10. Multigroup and all (with the cube
+template): serially on one idle node, 2026-10-11.
 
 Rerun without templates 7 and 9 (2026-10-13), runner at sketch-bench
 eval/drop-group-rate-templates: all serially on idle clnode109; classic
diff --git a/scripts/study_saturation.py b/scripts/study_saturation.py
index 63a3fcd4..f75c6e19 100644
--- a/scripts/study_saturation.py
+++ b/scripts/study_saturation.py
@@ -840,7 +840,8 @@ def main():
     parser.add_argument("--one-config", action="store_true",
                         help="only the first config of each sketch")
     parser.add_argument("--sketches",
-                        help="only these variants of --families (e.g. kll-percall)")
+                        help="only these variants of --families (e.g. kll-percall); Hydra "
+                             "cost rows are narrowed by --hydra-variants/--hydra-ws instead")
     parser.add_argument("--configs",
                         help="only these configs of them (e.g. k=25,k=100), to add new "
                              "configs to an existing study")