spark DistributionAndOrderingUtils 源码
spark DistributionAndOrderingUtils 代码
文件路径:/sql/core/src/main/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,
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package org.apache.spark.sql.execution.datasources.v2
import org.apache.spark.sql.catalyst.analysis.{AnsiTypeCoercion, TypeCoercion}
import org.apache.spark.sql.catalyst.expressions.{Expression, Literal, SortOrder, TransformExpression, V2ExpressionUtils}
import org.apache.spark.sql.catalyst.expressions.V2ExpressionUtils._
import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, RebalancePartitions, RepartitionByExpression, Sort}
import org.apache.spark.sql.catalyst.rules.Rule
import org.apache.spark.sql.connector.catalog.FunctionCatalog
import org.apache.spark.sql.connector.catalog.functions.ScalarFunction
import org.apache.spark.sql.connector.distributions._
import org.apache.spark.sql.connector.write.{RequiresDistributionAndOrdering, Write}
import org.apache.spark.sql.errors.QueryCompilationErrors
object DistributionAndOrderingUtils {
def prepareQuery(
write: Write,
query: LogicalPlan,
funCatalogOpt: Option[FunctionCatalog]): LogicalPlan = write match {
case write: RequiresDistributionAndOrdering =>
val numPartitions = write.requiredNumPartitions()
val distribution = write.requiredDistribution match {
case d: OrderedDistribution =>
toCatalystOrdering(d.ordering(), query, funCatalogOpt)
.map(e => resolveTransformExpression(e).asInstanceOf[SortOrder])
case d: ClusteredDistribution =>
d.clustering.map(e => toCatalyst(e, query, funCatalogOpt))
.map(e => resolveTransformExpression(e)).toSeq
case _: UnspecifiedDistribution => Seq.empty[Expression]
}
val queryWithDistribution = if (distribution.nonEmpty) {
val optNumPartitions = if (numPartitions > 0) Some(numPartitions) else None
// the conversion to catalyst expressions above produces SortOrder expressions
// for OrderedDistribution and generic expressions for ClusteredDistribution
// this allows RebalancePartitions/RepartitionByExpression to pick either
// range or hash partitioning
if (write.distributionStrictlyRequired()) {
RepartitionByExpression(distribution, query, optNumPartitions)
} else {
RebalancePartitions(distribution, query, optNumPartitions)
}
} else if (numPartitions > 0) {
throw QueryCompilationErrors.numberOfPartitionsNotAllowedWithUnspecifiedDistributionError()
} else {
query
}
val ordering = toCatalystOrdering(write.requiredOrdering, query, funCatalogOpt)
val queryWithDistributionAndOrdering = if (ordering.nonEmpty) {
Sort(
ordering.map(e => resolveTransformExpression(e).asInstanceOf[SortOrder]),
global = false,
queryWithDistribution)
} else {
queryWithDistribution
}
// Apply typeCoercionRules since the converted expression from TransformExpression
// implemented ImplicitCastInputTypes
typeCoercionRules.foldLeft(queryWithDistributionAndOrdering)((plan, rule) => rule(plan))
case _ =>
query
}
private def resolveTransformExpression(expr: Expression): Expression = expr.transform {
case TransformExpression(scalarFunc: ScalarFunction[_], arguments, Some(numBuckets)) =>
V2ExpressionUtils.resolveScalarFunction(scalarFunc, Seq(Literal(numBuckets)) ++ arguments)
case TransformExpression(scalarFunc: ScalarFunction[_], arguments, None) =>
V2ExpressionUtils.resolveScalarFunction(scalarFunc, arguments)
}
private def typeCoercionRules: List[Rule[LogicalPlan]] = if (conf.ansiEnabled) {
AnsiTypeCoercion.typeCoercionRules
} else {
TypeCoercion.typeCoercionRules
}
}
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