dilipbiswal commented on a change in pull request #1947: URL: https://github.com/apache/iceberg/pull/1947#discussion_r559092106
########## File path: spark3-extensions/src/main/scala/org/apache/spark/sql/execution/datasources/v2/MergeIntoExec.scala ########## @@ -0,0 +1,111 @@ +/* + * 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.execution.datasources.v2 + +import org.apache.spark.rdd.RDD +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.catalyst.expressions.{Attribute, BasePredicate, Expression, UnsafeProjection} +import org.apache.spark.sql.catalyst.expressions.codegen.GeneratePredicate +import org.apache.spark.sql.catalyst.plans.logical.MergeIntoParams +import org.apache.spark.sql.execution.{SparkPlan, UnaryExecNode} + +case class MergeIntoExec(mergeIntoProcessor: MergeIntoParams, + @transient targetRelation: DataSourceV2Relation, + override val child: SparkPlan) extends UnaryExecNode { + + override def output: Seq[Attribute] = targetRelation.output + + protected override def doExecute(): RDD[InternalRow] = { + child.execute().mapPartitions { + processPartition(mergeIntoProcessor, _) + } + } + + private def generateProjection(exprs: Seq[Expression], attrs: Seq[Attribute]): UnsafeProjection = { + UnsafeProjection.create(exprs, attrs) + } + + private def generatePredicate(expr: Expression, attrs: Seq[Attribute]): BasePredicate = { + GeneratePredicate.generate(expr, attrs) + } + + def applyProjection(predicates: Seq[BasePredicate], + projections: Seq[UnsafeProjection], + projectTargetCols: UnsafeProjection, + projectDeleteRow: UnsafeProjection, + inputRow: InternalRow, + targetRowNotPresent: Boolean): InternalRow = { + // Find the first combination where the predicate evaluates to true + val pair = (predicates zip projections).find { + case (predicate, _) => predicate.eval(inputRow) + } + + // Now apply the appropriate projection to either : + // - Insert a row into target + // - Update a row of target + // - Delete a row in target. The projected row will have the deleted bit set. + pair match { + case Some((_, projection)) => + projection.apply(inputRow) + case None => + if (targetRowNotPresent) { + projectDeleteRow.apply(inputRow) + } else { + projectTargetCols.apply(inputRow) + } + } + } + + def processPartition(params: MergeIntoParams, + rowIterator: Iterator[InternalRow]): Iterator[InternalRow] = { + val joinedAttrs = params.joinedAttributes + val isSourceRowNotPresentPred = generatePredicate(params.isSourceRowNotPresent, joinedAttrs) + val isTargetRowNotPresentPred = generatePredicate(params.isTargetRowNotPresent, joinedAttrs) + val matchedPreds = params.matchedConditions.map(generatePredicate(_, joinedAttrs)) + val matchedProjs = params.matchedOutputs.map(generateProjection(_, joinedAttrs)) + val notMatchedPreds = params.notMatchedConditions.map(generatePredicate(_, joinedAttrs)) + val notMatchedProjs = params.notMatchedOutputs.map(generateProjection(_, joinedAttrs)) + val projectTargetCols = generateProjection(params.targetOutput, joinedAttrs) + val projectDeletedRow = generateProjection(params.deleteOutput, joinedAttrs) Review comment: @rdblue 1. ```projectTargetCols``` represents the expression that needs to be applied on the output of outer join which has columns from both the tables to only project the target output columns plus the deleted flag set to false. 2. ```projectDeletedRow ``` does the same but with the "deleted flag". I think in the earlier comment we discussed possible ideas to optimize this (will address in follow-up) 3. ``matchedPreds``` and ```notMatchedPred``` go hand in hand with their corresponding projections that is specified by the user in the `WHEN MATCHED ` and `WHEN NOT MATCHED` clauses. Given this background, can you please explain your idea a little bit ? ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
