cloud-fan commented on a change in pull request #35395: URL: https://github.com/apache/spark/pull/35395#discussion_r824424955
########## File path: sql/catalyst/src/test/scala/org/apache/spark/sql/connector/catalog/InMemoryRowLevelOperationTable.scala ########## @@ -0,0 +1,96 @@ +/* + * 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 + +import java.util + +import org.apache.spark.sql.connector.distributions.{Distribution, Distributions} +import org.apache.spark.sql.connector.expressions.{FieldReference, LogicalExpressions, NamedReference, SortDirection, SortOrder, Transform} +import org.apache.spark.sql.connector.read.{Scan, ScanBuilder} +import org.apache.spark.sql.connector.write.{BatchWrite, LogicalWriteInfo, RequiresDistributionAndOrdering, RowLevelOperation, RowLevelOperationBuilder, RowLevelOperationInfo, Write, WriteBuilder, WriterCommitMessage} +import org.apache.spark.sql.connector.write.RowLevelOperation.Command +import org.apache.spark.sql.types.StructType +import org.apache.spark.sql.util.CaseInsensitiveStringMap + +class InMemoryRowLevelOperationTable( + name: String, + schema: StructType, + partitioning: Array[Transform], + properties: util.Map[String, String]) + extends InMemoryTable(name, schema, partitioning, properties) with SupportsRowLevelOperations { + + override def newRowLevelOperationBuilder( + info: RowLevelOperationInfo): RowLevelOperationBuilder = { + () => PartitionBasedOperation(info.command) + } + + case class PartitionBasedOperation(command: Command) extends RowLevelOperation { + private final val PARTITION_COLUMN_REF = FieldReference(PartitionKeyColumn.name) + + var configuredScan: InMemoryBatchScan = _ + + override def requiredMetadataAttributes(): Array[NamedReference] = { + Array(PARTITION_COLUMN_REF) + } + + override def newScanBuilder(options: CaseInsensitiveStringMap): ScanBuilder = { + new InMemoryScanBuilder(schema) { + override def build: Scan = { + val scan = super.build() + configuredScan = scan.asInstanceOf[InMemoryBatchScan] + scan + } + } + } + + override def newWriteBuilder(info: LogicalWriteInfo): WriteBuilder = new WriteBuilder { + + override def build(): Write = new Write with RequiresDistributionAndOrdering { + override def requiredDistribution(): Distribution = { + Distributions.clustered(Array(PARTITION_COLUMN_REF)) + } + + override def requiredOrdering(): Array[SortOrder] = { + Array[SortOrder]( + LogicalExpressions.sort( + PARTITION_COLUMN_REF, + SortDirection.ASCENDING, + SortDirection.ASCENDING.defaultNullOrdering()) + ) + } + + override def toBatch: BatchWrite = PartitionBasedReplaceData(configuredScan) + + override def description(): String = "InMemoryWrite" + } + } + + override def description(): String = "InMemoryPartitionReplaceOperation" + } + + private case class PartitionBasedReplaceData(scan: InMemoryBatchScan) extends TestBatchWrite { + + override def commit(messages: Array[WriterCommitMessage]): Unit = dataMap.synchronized { + val newData = messages.map(_.asInstanceOf[BufferedRows]) + val readRows = scan.data.flatMap(_.asInstanceOf[BufferedRows].rows) Review comment: Yea we agree on the algorithm, the question is how the affected "groups" are determined and passed around. BTW, Delta does want to support conditions with subqueries, and we want to make sure the newly proposed API here can work with subqueries: https://github.com/delta-io/delta/issues/826 > Spark executes the filtering subquery via the existing runtime filtering mechanism, collects unique values for the filtering attributes ... This is the key problem. How does Spark know how to get the file name column? There is no DS v2 API for Delta to tell Spark: hey you can select `_file_name` column to get the "group id". Are we going to add an implicit assumption that, the `Scan` will add an extra column silently like my proposal? If yes, I think this solves the problem and is actually very similar to my proposal with the difference that we use the existing hidden column and runtime filter API to report "group id" from the source and use it to determine the final affected "groups". -- This is an automated message from the Apache Git Service. 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