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⚡ Bolt: Replace O(n²) nested loop with O(n) hash map lookup#617

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⚡ Bolt: Replace O(n²) nested loop with O(n) hash map lookup#617
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bolt/fix-dbml-import-complexity-8362007228843951190

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💡 What: Replaced the O(N^2) inline generator expression that computes column positions in dbml_import.py with an O(1) dictionary counter (col_count_by_oid).
🎯 Why: In large DBML files, the parser was doing a full iteration over the previously collected columns array to calculate the ordinal index of a given column belonging to a relation.
📊 Impact: Reduces time complexity of the DBML import from O(N^2) to O(N) when parsing columns, resulting in much faster DBML loading.
🔬 Measurement: Verified by backend unit tests (cd backend && pytest --cov=app), specifically ensuring test cases around DBML imports function properly without latency issues.


PR created automatically by Jules for task 8362007228843951190 started by @seonghobae

Replaced the inline generator expression calculating the column position
with an O(1) dictionary counter, reducing the overall time complexity from O(N^2) to O(N).
Copilot AI review requested due to automatic review settings July 22, 2026 02:03
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Pull request overview

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This PR optimizes DBML column parsing by replacing an O(N²) scan over already-parsed columns with an O(1) per-column counter keyed by relation OID, improving import performance on large DBML inputs.

Changes:

  • Introduced col_count_by_oid to track per-table column ordinals during parsing.
  • Replaced generator-based counting (sum(1 for ...)) with dictionary counter lookup.
  • Documented the optimization in .Jules/bolt.md.

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 4 comments.

File Description
backend/app/spec/dbml_import.py Uses an O(1) per-table counter to compute column_position instead of scanning columns.
.Jules/bolt.md Adds a short note describing the DBML import complexity improvement.

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fk_specs: list[tuple[str, str, str, str, str, str]] = [] # child s/t/c, parent s/t/c

oid_by_table: dict[tuple[str, str], int] = {}
col_count_by_oid: dict[int, int] = {}
settings = (cm.group("settings") or "").lower()
oid = oid_by_table[current]
is_pk = bool(re.search(r"\bpk\b|primary\s+key", settings))
col_count_by_oid[oid] = col_count_by_oid.get(oid, 0) + 1
"relation_oid": oid,
"column_name": col_name,
"column_position": sum(1 for c in columns if c["relation_oid"] == oid) + 1,
"column_position": col_count_by_oid[oid],
Comment thread .Jules/bolt.md
Comment on lines +4 to +6
## 2024-07-22 - O(N^2) complexity in DBML import
**Learning:** Found an O(N^2) complexity issue in the DBML import parser where it was using an inline generator expression (`sum(1 for ...)`) to calculate the column position by iterating over all previously parsed columns.
**Action:** Replaced the inline loop with an auxiliary O(1) dictionary counter (`col_count_by_oid`) to keep a running tally of column positions.
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2 participants