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[SPARK-34026][SQL] Inject repartition and sort nodes to satisfy requi…
…red distribution and ordering (apache#905) ### What changes were proposed in this pull request? This PR adds repartition and sort nodes to satisfy the required distribution and ordering introduced in SPARK-33779. Note: This PR contains the final part of changes discussed in PR apache#29066. ### Why are the changes needed? These changes are the next step as discussed in the [design doc](https://docs.google.com/document/d/1X0NsQSryvNmXBY9kcvfINeYyKC-AahZarUqg3nS1GQs/edit#) for SPARK-23889. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? This PR comes with a new test suite. Closes apache#31083 from aokolnychyi/spark-34026. Authored-by: Anton Okolnychyi <[email protected]> Signed-off-by: Wenchen Fan <[email protected]>
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...in/scala/org/apache/spark/sql/execution/datasources/v2/DistributionAndOrderingUtils.scala
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| /* | ||
| * 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. | ||
| */ | ||
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| package org.apache.spark.sql.execution.datasources.v2 | ||
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| import org.apache.spark.sql.AnalysisException | ||
| import org.apache.spark.sql.catalyst.analysis.Resolver | ||
| import org.apache.spark.sql.catalyst.expressions.{Ascending, Descending, Expression, NamedExpression, NullOrdering, NullsFirst, NullsLast, SortDirection, SortOrder} | ||
| import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, RepartitionByExpression, Sort} | ||
| import org.apache.spark.sql.connector.distributions.{ClusteredDistribution, OrderedDistribution, UnspecifiedDistribution} | ||
| import org.apache.spark.sql.connector.expressions.{Expression => V2Expression, FieldReference, IdentityTransform, NullOrdering => V2NullOrdering, SortDirection => V2SortDirection, SortValue} | ||
| import org.apache.spark.sql.connector.write.{RequiresDistributionAndOrdering, Write} | ||
| import org.apache.spark.sql.internal.SQLConf | ||
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| object DistributionAndOrderingUtils { | ||
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| def prepareQuery(write: Write, query: LogicalPlan, conf: SQLConf): LogicalPlan = write match { | ||
| case write: RequiresDistributionAndOrdering => | ||
| val resolver = conf.resolver | ||
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| 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[Expression] | ||
| } | ||
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| val queryWithDistribution = if (distribution.nonEmpty) { | ||
| val numShufflePartitions = conf.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) | ||
| } else { | ||
| query | ||
| } | ||
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| val ordering = write.requiredOrdering.toSeq | ||
| .map(e => toCatalyst(e, query, resolver)) | ||
| .asInstanceOf[Seq[SortOrder]] | ||
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| val queryWithDistributionAndOrdering = if (ordering.nonEmpty) { | ||
| Sort(ordering, global = false, queryWithDistribution) | ||
| } else { | ||
| queryWithDistribution | ||
| } | ||
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| queryWithDistributionAndOrdering | ||
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| case _ => | ||
| query | ||
| } | ||
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| private def toCatalyst( | ||
| expr: V2Expression, | ||
| query: LogicalPlan, | ||
| resolver: Resolver): Expression = { | ||
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| // we cannot perform the resolution in the analyzer since we need to optimize expressions | ||
| // in nodes like OverwriteByExpression before constructing a logical write | ||
| def resolve(ref: FieldReference): NamedExpression = { | ||
| query.resolve(ref.parts, resolver) match { | ||
| case Some(attr) => attr | ||
| case None => throw new AnalysisException(s"Cannot resolve '$ref' using ${query.output}") | ||
| } | ||
| } | ||
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| expr match { | ||
| case SortValue(child, direction, nullOrdering) => | ||
| val catalystChild = toCatalyst(child, query, resolver) | ||
| SortOrder(catalystChild, toCatalyst(direction), toCatalyst(nullOrdering), Seq.empty) | ||
| case IdentityTransform(ref) => | ||
| resolve(ref) | ||
| case ref: FieldReference => | ||
| resolve(ref) | ||
| case _ => | ||
| throw new AnalysisException(s"$expr is not currently supported") | ||
| } | ||
| } | ||
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| private def toCatalyst(direction: V2SortDirection): SortDirection = direction match { | ||
| case V2SortDirection.ASCENDING => Ascending | ||
| case V2SortDirection.DESCENDING => Descending | ||
| } | ||
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| private def toCatalyst(nullOrdering: V2NullOrdering): NullOrdering = nullOrdering match { | ||
| case V2NullOrdering.NULLS_FIRST => NullsFirst | ||
| case V2NullOrdering.NULLS_LAST => NullsLast | ||
| } | ||
| } |
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