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Original file line number Diff line number Diff line change
@@ -0,0 +1,196 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

package org.apache.paimon.predicate;

import org.apache.paimon.data.InternalRow;
import org.apache.paimon.types.DataType;
import org.apache.paimon.types.RowType;

import org.apache.paimon.shade.jackson2.com.fasterxml.jackson.annotation.JsonCreator;
import org.apache.paimon.shade.jackson2.com.fasterxml.jackson.annotation.JsonIgnore;
import org.apache.paimon.shade.jackson2.com.fasterxml.jackson.annotation.JsonProperty;

import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import java.util.Objects;

import static org.apache.paimon.utils.InternalRowUtils.get;
import static org.apache.paimon.utils.Preconditions.checkArgument;

/**
* Transform that extracts a field nested inside a row-typed column, for example {@code addr.city}.
*
* <p>The transform keeps the enclosing top-level column as its only {@link #inputs() input}, so
* anything that rewrites field indices (schema projection, for instance) keeps working without
* knowing about nesting. The positions below that column are held separately in {@link #path()}.
*
* <p>Deliberately <b>not</b> a {@link FieldTransform}: {@link LeafPredicate#fieldRefOptional()}
* returns empty for it, which is what keeps every consumer that equates a leaf with a top-level
* column — min/max pruning, file index lookup, ORC pushdown, schema evolution — from silently
* reading the enclosing column's metadata as if it belonged to the nested field. Those consumers
* give up on this transform instead, which costs pruning but never rows.
*/
public class NestedFieldTransform implements Transform {

private static final long serialVersionUID = 1L;

public static final String NAME = "NESTED_FIELD_REF";

public static final String FIELD_FIELD_REF = "fieldRef";
public static final String FIELD_PATH = "path";

/** The top-level row-typed column the nested field lives in. */
private final FieldRef fieldRef;

/**
* Names of the fields to descend into, relative to {@code fieldRef}'s row type. Never empty.
*
* <p>Deliberately names rather than positions: {@link #copyWithNewInputs} may be handed a
* structurally different row type — column masking and row filters remap that way — and a bare
* position would stay in range while silently addressing whatever now sits there. Names are
* re-resolved on every remap, so a reference either finds the same field or fails.
*/
private final List<String> path;

/** {@link #path} resolved to positions against {@code fieldRef}'s row type. */
private final int[] positions;

private final String name;
private final DataType outputType;

@JsonCreator
public NestedFieldTransform(
@JsonProperty(FIELD_FIELD_REF) FieldRef fieldRef,
@JsonProperty(FIELD_PATH) List<String> path) {
checkArgument(path != null && !path.isEmpty(), "Nested field path must not be empty.");
this.fieldRef = fieldRef;
this.path = Collections.unmodifiableList(new ArrayList<>(path));
this.positions = new int[this.path.size()];

StringBuilder nameBuilder = new StringBuilder(fieldRef.name());
DataType current = fieldRef.type();
for (int i = 0; i < this.path.size(); i++) {
checkArgument(
current instanceof RowType,
"Nested field path of '%s' descends into a non-row type %s.",
fieldRef.name(),
current);
RowType rowType = (RowType) current;
String component = this.path.get(i);
int position = rowType.getFieldIndex(component);
checkArgument(
position >= 0,
"Nested field '%s' does not contain a field named '%s'.",
nameBuilder,
component);
positions[i] = position;
nameBuilder.append('.').append(component);
current = rowType.getTypeAt(position);
}
this.name = nameBuilder.toString();
this.outputType = current;
}

@Override
public String name() {
return NAME;
}

@JsonProperty(FIELD_FIELD_REF)
public FieldRef fieldRef() {
return fieldRef;
}

@JsonProperty(FIELD_PATH)
public List<String> path() {
return path;
}

/** Dot-separated name from the top-level column down to the nested field, {@code addr.city}. */
@JsonIgnore
public String fieldName() {
return name;
}

@Override
@JsonIgnore
public List<Object> inputs() {
return Collections.singletonList(fieldRef);
}

@Override
@JsonIgnore
public DataType outputType() {
return outputType;
}

/**
* Reads the nested field out of {@code row}, which must match the row type {@link #fieldRef}
* was built against. A null anywhere along the path yields null, matching SQL semantics for
* field access on a null struct.
*/
@Override
public Object transform(InternalRow row) {
int position = fieldRef.index();
if (row.isNullAt(position)) {
return null;
}
RowType currentType = (RowType) fieldRef.type();
InternalRow current = row.getRow(position, currentType.getFieldCount());

for (int i = 0; i < positions.length - 1; i++) {
position = positions[i];
if (current.isNullAt(position)) {
return null;
}
RowType nextType = (RowType) currentType.getTypeAt(position);
current = current.getRow(position, nextType.getFieldCount());
currentType = nextType;
}

int leaf = positions[positions.length - 1];
return get(current, leaf, currentType.getTypeAt(leaf));
}

@Override
public Transform copyWithNewInputs(List<Object> inputs) {
checkArgument(inputs.size() == 1);

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[P1] Re-resolve nested identity when inputs are remapped

This preserves an ordinal path even when the replacement FieldRef has a different nested RowType. Nested transforms are now JSON-serializable and can be used by REST row filters, so a policy on info.secret with path [0] against ROW<secret, region> can be remapped against a Spark-pruned ROW and silently evaluate info.region instead. With same-typed fields this does not fail closed and can admit unauthorized rows. Please persist stable nested names or field IDs and re-resolve them during remapping, while ensuring auth reads the full nested dependencies; alternatively, reject nested transforms in row filters until their identity can be preserved.

return new NestedFieldTransform((FieldRef) inputs.get(0), path);
}

@Override
public boolean equals(Object o) {
if (o == null || getClass() != o.getClass()) {
return false;
}
NestedFieldTransform that = (NestedFieldTransform) o;
return Objects.equals(fieldRef, that.fieldRef) && Objects.equals(path, that.path);
}

@Override
public int hashCode() {
return Objects.hash(fieldRef, path);
}

@Override
public String toString() {
return name;
}
}
Original file line number Diff line number Diff line change
Expand Up @@ -278,6 +278,10 @@ public Predicate notIn(int idx, List<Object> literals) {
return in(idx, literals).negate().get();
}

public Predicate notIn(Transform transform, List<Object> literals) {
return in(transform, literals).negate().get();
}

public Predicate between(int idx, Object includedLowerBound, Object includedUpperBound) {
DataField field = rowType.getFields().get(idx);
return new LeafPredicate(
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Original file line number Diff line number Diff line change
Expand Up @@ -34,6 +34,7 @@
property = Transform.FIELD_NAME)
@JsonSubTypes({
@JsonSubTypes.Type(value = FieldTransform.class, name = FieldTransform.NAME),
@JsonSubTypes.Type(value = NestedFieldTransform.class, name = NestedFieldTransform.NAME),
@JsonSubTypes.Type(value = CastTransform.class, name = CastTransform.NAME),
@JsonSubTypes.Type(value = ConcatTransform.class, name = ConcatTransform.NAME),
@JsonSubTypes.Type(value = ConcatWsTransform.class, name = ConcatWsTransform.NAME),
Expand Down
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