aokolnychyi commented on a change in pull request #29066: URL: https://github.com/apache/spark/pull/29066#discussion_r539196366
########## File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/V2Writes.scala ########## @@ -0,0 +1,185 @@ +/* + * 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 java.util.UUID + +import org.apache.spark.SparkException +import org.apache.spark.sql.AnalysisException +import org.apache.spark.sql.catalyst +import org.apache.spark.sql.catalyst.analysis.Resolver +import org.apache.spark.sql.catalyst.expressions.{NamedExpression, PredicateHelper, SortOrder} +import org.apache.spark.sql.catalyst.plans.logical.{AppendData, LogicalPlan, OverwriteByExpression, OverwritePartitionsDynamic, RepartitionByExpression, Sort} +import org.apache.spark.sql.catalyst.rules.Rule +import org.apache.spark.sql.connector.catalog.Table +import org.apache.spark.sql.connector.distributions.{ClusteredDistribution, OrderedDistribution, UnspecifiedDistribution} +import org.apache.spark.sql.connector.expressions.{Expression, FieldReference, IdentityTransform, NullOrdering, SortDirection, SortValue} +import org.apache.spark.sql.connector.write.{LogicalWriteInfoImpl, RequiresDistributionAndOrdering, SupportsDynamicOverwrite, SupportsOverwrite, SupportsTruncate, Write, WriteBuilder} +import org.apache.spark.sql.execution.datasources.DataSourceStrategy +import org.apache.spark.sql.internal.SQLConf +import org.apache.spark.sql.sources.{AlwaysTrue, Filter} + +/** + * A rule that constructs [[Write]]s. + * + * This rule does resolution in the optimizer because some nodes like [[OverwriteByExpression]] + * must undergo the expression optimization before we can construct a logical write. + */ +object V2Writes extends Rule[LogicalPlan] with PredicateHelper { + + import DataSourceV2Implicits._ + + override def apply(plan: LogicalPlan): LogicalPlan = plan transformDown { + case a @ AppendData(r: DataSourceV2Relation, query, options, _, None) => + val writeBuilder = newWriteBuilder(r.table, query, options) + val write = writeBuilder.build() + a.copy(write = Some(write), query = addDistributionAndOrdering(write, query)) + + case o @ OverwriteByExpression(r: DataSourceV2Relation, deleteExpr, query, options, _, None) => + // fail if any filter cannot be converted. correctness depends on removing all matching data. + val filters = splitConjunctivePredicates(deleteExpr).flatMap { p => + val filter = DataSourceStrategy.translateFilter(p, supportNestedPredicatePushdown = true) + if (filter.isEmpty) { + throw new AnalysisException(s"Cannot translate expression to source filter: $p") + } + filter + }.toArray + + val table = r.table + val writeBuilder = newWriteBuilder(table, query, options) + val write = writeBuilder match { + case builder: SupportsTruncate if isTruncate(filters) => + builder.truncate().build() + case builder: SupportsOverwrite => + builder.overwrite(filters).build() + case _ => + throw new SparkException(s"Table does not support overwrite by expression: $table") + } + + o.copy(write = Some(write), query = addDistributionAndOrdering(write, query)) + + case o @ OverwritePartitionsDynamic(r: DataSourceV2Relation, query, options, _, None) => + val table = r.table + val writeBuilder = newWriteBuilder(table, query, options) + val write = writeBuilder match { + case builder: SupportsDynamicOverwrite => + builder.overwriteDynamicPartitions().build() + case _ => + throw new SparkException(s"Table does not support dynamic partition overwrite: $table") + } + o.copy(write = Some(write), query = addDistributionAndOrdering(write, query)) + } + + private def newWriteBuilder( + table: Table, + query: LogicalPlan, + writeOptions: Map[String, String]): WriteBuilder = { + + val info = LogicalWriteInfoImpl( + queryId = UUID.randomUUID().toString, + query.schema, + writeOptions.asOptions) + table.asWritable.newWriteBuilder(info) + } + + private def isTruncate(filters: Array[Filter]): Boolean = { + filters.length == 1 && filters(0).isInstanceOf[AlwaysTrue] + } + + private def addDistributionAndOrdering( + write: Write, + query: LogicalPlan): LogicalPlan = write match { + + case write: RequiresDistributionAndOrdering => + val sqlConf = SQLConf.get + val resolver = sqlConf.resolver + + val distribution = write.requiredDistribution match { + case d: OrderedDistribution => + d.ordering.map(e => toCatalyst(e, query, resolver)) + case d: ClusteredDistribution => + d.clustering.map(e => toCatalyst(e, query, resolver)) + case _: UnspecifiedDistribution => + Array.empty[catalyst.expressions.Expression] + } + + val queryWithDistribution = if (distribution.nonEmpty) { + val numShufflePartitions = sqlConf.numShufflePartitions + // the conversion to catalyst expressions above produces SortOrder expressions + // for OrderedDistribution and generic expressions for ClusteredDistribution + // this allows RepartitionByExpression to pick either range or hash partitioning + RepartitionByExpression(distribution, query, numShufflePartitions) Review comment: We are inserting repartition/sort nodes directly before writing so my assumption that Spark will only remove them if the incoming plan already satisfies these requirements. `WriteDistributionAndOrderingSuite` is kind of meant for testing that. Do you have ideas when this assumption will break, @viirya? ---------------------------------------------------------------- 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]
