sunchao commented on code in PR #45267: URL: https://github.com/apache/spark/pull/45267#discussion_r1538630610
########## sql/catalyst/src/main/java/org/apache/spark/sql/connector/catalog/functions/ReducibleFunction.java: ########## @@ -0,0 +1,106 @@ +/* + * 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.spark.sql.connector.catalog.functions; + +import org.apache.spark.annotation.Evolving; + +/** + * Base class for user-defined functions that can be 'reduced' on another function. + * + * A function f_source(x) is 'reducible' on another function f_target(x) if + * <ul> + * <li> There exists a reducer function r(x) such that r(f_source(x)) = f_target(x) + * for all input x, or </li> + * <li> More generally, there exists reducer functions r1(x) and r2(x) such that + * r1(f_source(x)) = r2(f_target(x)) for all input x. </li> + * </ul> + * <p> + * Examples: + * <ul> + * <li>Bucket functions where one side has reducer + * <ul> + * <li>f_source(x) = bucket(4, x)</li> + * <li>f_target(x) = bucket(2, x)</li> + * <li>r(x) = x % 2</li> + * </ul> + * + * <li>Bucket functions where both sides have reducer + * <ul> + * <li>f_source(x) = bucket(16, x)</li> + * <li>f_target(x) = bucket(12, x)</li> + * <li>r1(x) = x % 4</li> + * <li>r2(x) = x % 4</li> + * </ul> + * + * <li>Date functions + * <ul> + * <li>f_source(x) = days(x)</li> + * <li>f_target(x) = hours(x)</li> + * <li>r(x) = x / 24</li> + * </ul> + * </ul> + * @param <I> reducer function input type + * @param <O> reducer function output type + * @since 4.0.0 + */ +@Evolving +public interface ReducibleFunction<I, O> { + + /** + * This method is for parameterized functions. + * + * If this parameterized function is 'reducible' on another bucket function, + * return the {@link Reducer} function. + * <p> + * Example to return reducer for reducing f_source = bucket(4, x) on f_target = bucket(2, x) + * <ul> + * <li>thisBucketFunction = bucket</li> + * <li>thisNumBuckets = 4</li> + * <li>otherBucketFunction = bucket</li> + * <li>otherNumBuckets = 2</li> + * </ul> + * + * @param thisNumBuckets parameter for this function + * @param otherBucketFunction the other parameterized function + * @param otherNumBuckets parameter for the other function + * @return a reduction function if it is reducible, null if not + */ + default Reducer<I, O> bucketReducer( + int thisNumBuckets, + ReducibleFunction<?, ?> otherBucketFunction, + int otherNumBuckets) { + throw new UnsupportedOperationException(); + } + + /** + * This method is for all other functions. + * + * If this function is 'reducible' on another function, return the {@link Reducer} function. + * <p> + * Example of reducing f_source = days(x) on f_target = hours(x) + * <ul> + * <li>thisFunction = days</li> + * <li>otherFunction = hours</li> + * </ul> + * + * @param otherFunction the other function + * @return a reduction function if it is reducible, null if not. + */ + default Reducer<I, O> bucketReducer(ReducibleFunction<?, ?> otherFunction) { Review Comment: should this just be `reducer`? ########## sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/EnsureRequirements.scala: ########## @@ -527,25 +545,38 @@ case class EnsureRequirements( joinType == LeftAnti || joinType == LeftOuter } - // Populate the common partition values down to the scan nodes - private def populatePartitionValues( + // Populate the common partition information down to the scan nodes + private def populateCommonPartitionInfo( plan: SparkPlan, values: Seq[(InternalRow, Int)], joinKeyPositions: Option[Seq[Int]], + reducers: Option[Seq[Option[Reducer[_, _]]]], applyPartialClustering: Boolean, replicatePartitions: Boolean): SparkPlan = plan match { case scan: BatchScanExec => scan.copy( spjParams = scan.spjParams.copy( commonPartitionValues = Some(values), joinKeyPositions = joinKeyPositions, + reducers = reducers, applyPartialClustering = applyPartialClustering, replicatePartitions = replicatePartitions ) ) case node => - node.mapChildren(child => populatePartitionValues( - child, values, joinKeyPositions, applyPartialClustering, replicatePartitions)) + node.mapChildren(child => populateCommonPartitionInfo( + child, values, joinKeyPositions, reducers, applyPartialClustering, replicatePartitions)) + } + + private def reduceCommonPartValues(commonPartValues: Seq[(InternalRow, Int)], Review Comment: ditto, style ########## sql/catalyst/src/main/java/org/apache/spark/sql/connector/catalog/functions/ReducibleFunction.java: ########## @@ -0,0 +1,106 @@ +/* + * 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.spark.sql.connector.catalog.functions; + +import org.apache.spark.annotation.Evolving; + +/** + * Base class for user-defined functions that can be 'reduced' on another function. + * + * A function f_source(x) is 'reducible' on another function f_target(x) if + * <ul> + * <li> There exists a reducer function r(x) such that r(f_source(x)) = f_target(x) + * for all input x, or </li> + * <li> More generally, there exists reducer functions r1(x) and r2(x) such that + * r1(f_source(x)) = r2(f_target(x)) for all input x. </li> + * </ul> + * <p> + * Examples: + * <ul> + * <li>Bucket functions where one side has reducer + * <ul> + * <li>f_source(x) = bucket(4, x)</li> + * <li>f_target(x) = bucket(2, x)</li> + * <li>r(x) = x % 2</li> + * </ul> + * + * <li>Bucket functions where both sides have reducer + * <ul> + * <li>f_source(x) = bucket(16, x)</li> + * <li>f_target(x) = bucket(12, x)</li> + * <li>r1(x) = x % 4</li> + * <li>r2(x) = x % 4</li> + * </ul> + * + * <li>Date functions + * <ul> + * <li>f_source(x) = days(x)</li> + * <li>f_target(x) = hours(x)</li> + * <li>r(x) = x / 24</li> + * </ul> + * </ul> + * @param <I> reducer function input type + * @param <O> reducer function output type + * @since 4.0.0 + */ +@Evolving +public interface ReducibleFunction<I, O> { + + /** + * This method is for parameterized functions. + * + * If this parameterized function is 'reducible' on another bucket function, + * return the {@link Reducer} function. + * <p> + * Example to return reducer for reducing f_source = bucket(4, x) on f_target = bucket(2, x) + * <ul> + * <li>thisBucketFunction = bucket</li> + * <li>thisNumBuckets = 4</li> + * <li>otherBucketFunction = bucket</li> + * <li>otherNumBuckets = 2</li> + * </ul> + * + * @param thisNumBuckets parameter for this function + * @param otherBucketFunction the other parameterized function + * @param otherNumBuckets parameter for the other function + * @return a reduction function if it is reducible, null if not + */ + default Reducer<I, O> bucketReducer( + int thisNumBuckets, Review Comment: I think we may need 4 space indentation here too ########## sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/physical/partitioning.scala: ########## @@ -846,6 +879,21 @@ case class KeyGroupedShuffleSpec( } } +object KeyGroupedShuffleSpec { + def reducePartitionValue( + row: InternalRow, Review Comment: nit: indentation is off: should be: ```scala def reducePartitionValue( row: InternalRow, expressions: Seq[Expression], reducers: Seq[Option[Reducer[_, _]]]): InternalRowComparableWrapper = { val partitionVals = row.toSeq(expressions.map(_.dataType)) val reducedRow = partitionVals.zip(reducers).map{ case (v, Some(reducer: Reducer[Any, Any])) => reducer.reduce(v) case (v, _) => v ``` 4 space indentation for method parameters, see https://github.com/databricks/scala-style-guide?tab=readme-ov-file#indent ########## sql/core/src/test/scala/org/apache/spark/sql/connector/catalog/functions/transformFunctions.scala: ########## @@ -85,6 +85,34 @@ object BucketFunction extends ScalarFunction[Int] { override def produceResult(input: InternalRow): Int = { (input.getLong(1) % input.getInt(0)).toInt } + + override def bucketReducer( Review Comment: ditto -- This is an automated message from the Apache Git Service. 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