cloud-fan commented on a change in pull request #31083: URL: https://github.com/apache/spark/pull/31083#discussion_r555744641
########## File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/DistributionAndOrderingUtils.scala ########## @@ -0,0 +1,110 @@ +/* + * 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.sql.{catalyst, AnalysisException} +import org.apache.spark.sql.catalyst.analysis.Resolver +import org.apache.spark.sql.catalyst.expressions.{NamedExpression, 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, FieldReference, IdentityTransform, NullOrdering, SortDirection, SortValue} +import org.apache.spark.sql.connector.write.{RequiresDistributionAndOrdering, Write} +import org.apache.spark.sql.internal.SQLConf + +object DistributionAndOrderingUtils { + + def prepareQuery(write: Write, query: LogicalPlan, conf: SQLConf): LogicalPlan = write match { + case write: RequiresDistributionAndOrdering => + val resolver = conf.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 = conf.numShufflePartitions Review comment: I agree with @aokolnychyi that it should be Spark to decide these physical details (like numShufflePartitions), for better performance. It's an ill-pattern to let the data source to decide it. BTW why do we use `conf.numShufflePartitions` here? We can use `None` so that AQE can decide the number of partitions, which is even better. ---------------------------------------------------------------- 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]
