andygrove commented on code in PR #6459: URL: https://github.com/apache/datafusion-comet/pull/6459#discussion_r4186236774
########## spark/src/main/scala/org/apache/comet/rules/CometCoalesceShufflePartitions.scala: ########## @@ -0,0 +1,128 @@ +/* + * 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.comet.rules + +import org.apache.spark.sql.SparkSession +import org.apache.spark.sql.catalyst.trees.TreeNodeTag +import org.apache.spark.sql.comet.CometExec +import org.apache.spark.sql.execution.{SparkPlan, UnionExec} +import org.apache.spark.sql.execution.adaptive.{AQEShuffleReadExec, AQEShuffleReadRule, CoalesceShufflePartitions, ShuffleQueryStageExec} +import org.apache.spark.sql.execution.exchange.ShuffleOrigin +import org.apache.spark.sql.execution.joins.{BroadcastHashJoinExec, BroadcastNestedLoopJoinExec, CartesianProductExec} + +/** + * Coalesces the shuffle partitions below a Comet operator that Spark's CoalesceShufflePartitions + * coalesces child by child but does not recognize. + * + * Spark coalesces each child of a `UnionExec` as a group of its own, and from Spark 4.0 each + * child of a `CartesianProductExec`, `BroadcastHashJoinExec` or `BroadcastNestedLoopJoinExec` + * too. It matches those classes, and the Comet operators that replace them are other classes, so + * it falls through to the case that coalesces only when every leaf below the operator is an + * exchange stage. A union with a scan or a table-cache stage in one branch then keeps every + * partition of the shuffles in the others: `spark.sql.shuffle.partitions` tasks for a query that + * needs a few. + * + * Comet replaces these operators while AQE prepares a stage, before its optimizer rules run, and + * plans the operators above them against the Comet versions. So this runs after Spark's rule + * instead, on each such operator whose shuffle stages that rule left untouched. It rebuilds the + * Spark operator each Comet one replaced over the Comet children, has Spark's own rule coalesce + * that, and swaps the Comet operators back in. The partitions come out as Spark would have + * coalesced them, down to which operators count, since it is Spark's code deciding. The one + * difference is that Spark divides its minimum partition count among the coalesce groups of the + * whole plan, and this among those below the Comet operator, which are usually all of them. + * + * When every leaf below such an operator is an exchange stage, Spark's rule already coalesces its + * shuffles, together rather than child by child, and this leaves them as they are. + * + * Extending `AQEShuffleReadRule` gets this the same treatment from AQE as Spark's rule: it is + * skipped for the final stage when that stage's shuffle optimizations are off, and its result is + * discarded if it breaks a distribution required above it. + */ +case object CometCoalesceShufflePartitions extends AQEShuffleReadRule { + + // The Comet operator that a stand-in Spark operator was rebuilt from. + private val COMET_OPERATOR = TreeNodeTag[SparkPlan]("cometCoalesceShufflePartitions") + + // Required by the trait. Which shuffles are coalesced is decided by Spark's rule, which applies + // its own list. + override protected def supportedShuffleOrigins: Seq[ShuffleOrigin] = + CoalesceShufflePartitions(SparkSession.active).supportedShuffleOrigins + + override def apply(plan: SparkPlan): SparkPlan = { + if (!conf.coalesceShufflePartitionsEnabled || !plan.exists(replaced(_).isDefined)) { + return plan + } + plan.transformDown { + case p if replaced(p).isDefined && untouched(p) => coalesceBelow(p) + } + } + + // The Spark operator a Comet operator replaced, if Spark's rule coalesces its children one by + // one. The class match mirrors Spark's, and Spark's rule decides, for its version, which of + // these it actually treats that way. + private def replaced(plan: SparkPlan): Option[SparkPlan] = plan match { + case comet: CometExec => + comet.originalPlan match { + case original @ (_: UnionExec | _: CartesianProductExec | _: BroadcastHashJoinExec | + _: BroadcastNestedLoopJoinExec) + if original.children.length == comet.children.length => + Some(original) + case _ => None + } + case _ => None + } + + // No AQE rule has put a read over any shuffle stage below `plan`: Spark's rule coalesced none + // of them, and none is a skew-split or local read that coalescing now could disturb. + private def untouched(plan: SparkPlan): Boolean = + plan.exists(_.isInstanceOf[ShuffleQueryStageExec]) && + !plan.exists(_.isInstanceOf[AQEShuffleReadExec]) + + private def coalesceBelow(plan: SparkPlan): SparkPlan = { + val asSpark = plan.transformUp { case p => + replaced(p) match { + case Some(original) => + val standIn = original.withNewChildren(p.children) + // `withNewChildren` hands back the original itself when the children are the same ones, + // and the tag must not land on the operator that the Comet one keeps. + if (standIn eq original) { + p + } else { + standIn.setTagValue(COMET_OPERATOR, p) + standIn + } + case None => p + } + } + val coalesced = CoalesceShufflePartitions(SparkSession.active).apply(asSpark) + if (coalesced eq asSpark) plan else restore(coalesced) Review Comment: Reproduced. `keys.repartition($"k").union(keys.repartition(20, $"k")).groupBy("k").count()` plans the aggregate directly over the union on 4.1, the rule coalesced only the first branch, and each key came back twice. The rule now stands in only for operators whose output partitioning is `UnknownPartitioning`, since nothing in the stage can rely on that. `AQE leaves the shuffles of a union alone when an aggregate relies on its partitioning` runs that query. ########## spark/src/main/scala/org/apache/comet/rules/CometCoalesceShufflePartitions.scala: ########## @@ -0,0 +1,128 @@ +/* + * 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.comet.rules + +import org.apache.spark.sql.SparkSession +import org.apache.spark.sql.catalyst.trees.TreeNodeTag +import org.apache.spark.sql.comet.CometExec +import org.apache.spark.sql.execution.{SparkPlan, UnionExec} +import org.apache.spark.sql.execution.adaptive.{AQEShuffleReadExec, AQEShuffleReadRule, CoalesceShufflePartitions, ShuffleQueryStageExec} +import org.apache.spark.sql.execution.exchange.ShuffleOrigin +import org.apache.spark.sql.execution.joins.{BroadcastHashJoinExec, BroadcastNestedLoopJoinExec, CartesianProductExec} + +/** + * Coalesces the shuffle partitions below a Comet operator that Spark's CoalesceShufflePartitions + * coalesces child by child but does not recognize. + * + * Spark coalesces each child of a `UnionExec` as a group of its own, and from Spark 4.0 each + * child of a `CartesianProductExec`, `BroadcastHashJoinExec` or `BroadcastNestedLoopJoinExec` + * too. It matches those classes, and the Comet operators that replace them are other classes, so + * it falls through to the case that coalesces only when every leaf below the operator is an + * exchange stage. A union with a scan or a table-cache stage in one branch then keeps every + * partition of the shuffles in the others: `spark.sql.shuffle.partitions` tasks for a query that + * needs a few. + * + * Comet replaces these operators while AQE prepares a stage, before its optimizer rules run, and + * plans the operators above them against the Comet versions. So this runs after Spark's rule + * instead, on each such operator whose shuffle stages that rule left untouched. It rebuilds the + * Spark operator each Comet one replaced over the Comet children, has Spark's own rule coalesce + * that, and swaps the Comet operators back in. The partitions come out as Spark would have + * coalesced them, down to which operators count, since it is Spark's code deciding. The one + * difference is that Spark divides its minimum partition count among the coalesce groups of the + * whole plan, and this among those below the Comet operator, which are usually all of them. + * + * When every leaf below such an operator is an exchange stage, Spark's rule already coalesces its + * shuffles, together rather than child by child, and this leaves them as they are. + * + * Extending `AQEShuffleReadRule` gets this the same treatment from AQE as Spark's rule: it is + * skipped for the final stage when that stage's shuffle optimizations are off, and its result is + * discarded if it breaks a distribution required above it. + */ +case object CometCoalesceShufflePartitions extends AQEShuffleReadRule { + + // The Comet operator that a stand-in Spark operator was rebuilt from. + private val COMET_OPERATOR = TreeNodeTag[SparkPlan]("cometCoalesceShufflePartitions") + + // Required by the trait. Which shuffles are coalesced is decided by Spark's rule, which applies + // its own list. + override protected def supportedShuffleOrigins: Seq[ShuffleOrigin] = + CoalesceShufflePartitions(SparkSession.active).supportedShuffleOrigins + + override def apply(plan: SparkPlan): SparkPlan = { + if (!conf.coalesceShufflePartitionsEnabled || !plan.exists(replaced(_).isDefined)) { + return plan + } + plan.transformDown { + case p if replaced(p).isDefined && untouched(p) => coalesceBelow(p) + } + } + + // The Spark operator a Comet operator replaced, if Spark's rule coalesces its children one by + // one. The class match mirrors Spark's, and Spark's rule decides, for its version, which of + // these it actually treats that way. + private def replaced(plan: SparkPlan): Option[SparkPlan] = plan match { + case comet: CometExec => + comet.originalPlan match { + case original @ (_: UnionExec | _: CartesianProductExec | _: BroadcastHashJoinExec | + _: BroadcastNestedLoopJoinExec) + if original.children.length == comet.children.length => + Some(original) + case _ => None + } + case _ => None + } + + // No AQE rule has put a read over any shuffle stage below `plan`: Spark's rule coalesced none + // of them, and none is a skew-split or local read that coalescing now could disturb. + private def untouched(plan: SparkPlan): Boolean = + plan.exists(_.isInstanceOf[ShuffleQueryStageExec]) && + !plan.exists(_.isInstanceOf[AQEShuffleReadExec]) + + private def coalesceBelow(plan: SparkPlan): SparkPlan = { + val asSpark = plan.transformUp { case p => + replaced(p) match { + case Some(original) => + val standIn = original.withNewChildren(p.children) + // `withNewChildren` hands back the original itself when the children are the same ones, + // and the tag must not land on the operator that the Comet one keeps. + if (standIn eq original) { Review Comment: Done. When `withNewChildren` hands back the original, the rule copies it with `makeCopy` and tags the copy. `AQE coalesces the shuffle partitions of a union planned again over its stages` builds such a union from a finished query's stages, and fails without the copy. ########## spark/src/test/scala/org/apache/comet/exec/CometExecSuite.scala: ########## @@ -3573,6 +3573,44 @@ class CometExecSuite extends CometTestBase { } } + // https://github.com/apache/datafusion-comet/issues/6454 + test("AQE coalesces the shuffle partitions of a union whose other branch is a scan") { Review Comment: Added `AQE coalesces each branch of a union whose shuffles have different partition counts`, a port of that Spark test. Spark's rule gives up on the Comet union because of the aggregate's single-partition shuffle, and the rule coalesces the join's two shuffles. ########## spark/src/main/scala/org/apache/comet/rules/CometCoalesceShufflePartitions.scala: ########## @@ -0,0 +1,128 @@ +/* + * 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.comet.rules + +import org.apache.spark.sql.SparkSession +import org.apache.spark.sql.catalyst.trees.TreeNodeTag +import org.apache.spark.sql.comet.CometExec +import org.apache.spark.sql.execution.{SparkPlan, UnionExec} +import org.apache.spark.sql.execution.adaptive.{AQEShuffleReadExec, AQEShuffleReadRule, CoalesceShufflePartitions, ShuffleQueryStageExec} +import org.apache.spark.sql.execution.exchange.ShuffleOrigin +import org.apache.spark.sql.execution.joins.{BroadcastHashJoinExec, BroadcastNestedLoopJoinExec, CartesianProductExec} + +/** + * Coalesces the shuffle partitions below a Comet operator that Spark's CoalesceShufflePartitions + * coalesces child by child but does not recognize. + * + * Spark coalesces each child of a `UnionExec` as a group of its own, and from Spark 4.0 each + * child of a `CartesianProductExec`, `BroadcastHashJoinExec` or `BroadcastNestedLoopJoinExec` + * too. It matches those classes, and the Comet operators that replace them are other classes, so + * it falls through to the case that coalesces only when every leaf below the operator is an + * exchange stage. A union with a scan or a table-cache stage in one branch then keeps every + * partition of the shuffles in the others: `spark.sql.shuffle.partitions` tasks for a query that + * needs a few. + * + * Comet replaces these operators while AQE prepares a stage, before its optimizer rules run, and + * plans the operators above them against the Comet versions. So this runs after Spark's rule + * instead, on each such operator whose shuffle stages that rule left untouched. It rebuilds the + * Spark operator each Comet one replaced over the Comet children, has Spark's own rule coalesce + * that, and swaps the Comet operators back in. The partitions come out as Spark would have + * coalesced them, down to which operators count, since it is Spark's code deciding. The one + * difference is that Spark divides its minimum partition count among the coalesce groups of the + * whole plan, and this among those below the Comet operator, which are usually all of them. + * + * When every leaf below such an operator is an exchange stage, Spark's rule already coalesces its + * shuffles, together rather than child by child, and this leaves them as they are. + * + * Extending `AQEShuffleReadRule` gets this the same treatment from AQE as Spark's rule: it is + * skipped for the final stage when that stage's shuffle optimizations are off, and its result is + * discarded if it breaks a distribution required above it. + */ +case object CometCoalesceShufflePartitions extends AQEShuffleReadRule { + + // The Comet operator that a stand-in Spark operator was rebuilt from. + private val COMET_OPERATOR = TreeNodeTag[SparkPlan]("cometCoalesceShufflePartitions") + + // Required by the trait. Which shuffles are coalesced is decided by Spark's rule, which applies + // its own list. + override protected def supportedShuffleOrigins: Seq[ShuffleOrigin] = + CoalesceShufflePartitions(SparkSession.active).supportedShuffleOrigins + + override def apply(plan: SparkPlan): SparkPlan = { + if (!conf.coalesceShufflePartitionsEnabled || !plan.exists(replaced(_).isDefined)) { + return plan + } + plan.transformDown { + case p if replaced(p).isDefined && untouched(p) => coalesceBelow(p) + } + } + + // The Spark operator a Comet operator replaced, if Spark's rule coalesces its children one by + // one. The class match mirrors Spark's, and Spark's rule decides, for its version, which of + // these it actually treats that way. + private def replaced(plan: SparkPlan): Option[SparkPlan] = plan match { + case comet: CometExec => + comet.originalPlan match { + case original @ (_: UnionExec | _: CartesianProductExec | _: BroadcastHashJoinExec | Review Comment: Dropped `CartesianProductExec`. The two broadcast join arms matter more now: the rule hands Spark's rule the whole stage (see [the thread on ancestor joins](https://github.com/apache/datafusion-comet/pull/6459#discussion_r4154984789)), so a union below a Comet broadcast join is reached only through the join's stand-in, and a nested loop join's stand-in also brings Spark's smaller target size. `AQE coalesces the shuffle partitions of a union below a join as Spark does` covers both, and a Cartesian product above the union. ########## spark/src/main/scala/org/apache/comet/rules/CometCoalesceShufflePartitions.scala: ########## @@ -0,0 +1,128 @@ +/* + * 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.comet.rules + +import org.apache.spark.sql.SparkSession +import org.apache.spark.sql.catalyst.trees.TreeNodeTag +import org.apache.spark.sql.comet.CometExec +import org.apache.spark.sql.execution.{SparkPlan, UnionExec} +import org.apache.spark.sql.execution.adaptive.{AQEShuffleReadExec, AQEShuffleReadRule, CoalesceShufflePartitions, ShuffleQueryStageExec} +import org.apache.spark.sql.execution.exchange.ShuffleOrigin +import org.apache.spark.sql.execution.joins.{BroadcastHashJoinExec, BroadcastNestedLoopJoinExec, CartesianProductExec} + +/** + * Coalesces the shuffle partitions below a Comet operator that Spark's CoalesceShufflePartitions + * coalesces child by child but does not recognize. + * + * Spark coalesces each child of a `UnionExec` as a group of its own, and from Spark 4.0 each Review Comment: Fixed in the scaladoc: 3.5 has all four cases and 3.4 only the union. ########## spark/src/main/scala/org/apache/comet/CometSparkSessionExtensions.scala: ########## @@ -107,6 +107,7 @@ class CometSparkSessionExtensions } injectQueryStageOptimizerRuleShim(extensions, CometPlanAdaptiveDynamicPruningFilters) injectQueryStageOptimizerRuleShim(extensions, CometReuseSubquery) + injectQueryStageOptimizerRuleShim(extensions, CometCoalesceShufflePartitions) Review Comment: Added it to the per-stage list, after Spark's three shuffle-read rules, and to the Spark 3.4 note. ########## spark/src/main/scala/org/apache/comet/rules/CometCoalesceShufflePartitions.scala: ########## @@ -0,0 +1,128 @@ +/* + * 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.comet.rules + +import org.apache.spark.sql.SparkSession +import org.apache.spark.sql.catalyst.trees.TreeNodeTag +import org.apache.spark.sql.comet.CometExec +import org.apache.spark.sql.execution.{SparkPlan, UnionExec} +import org.apache.spark.sql.execution.adaptive.{AQEShuffleReadExec, AQEShuffleReadRule, CoalesceShufflePartitions, ShuffleQueryStageExec} +import org.apache.spark.sql.execution.exchange.ShuffleOrigin +import org.apache.spark.sql.execution.joins.{BroadcastHashJoinExec, BroadcastNestedLoopJoinExec, CartesianProductExec} + +/** + * Coalesces the shuffle partitions below a Comet operator that Spark's CoalesceShufflePartitions + * coalesces child by child but does not recognize. + * + * Spark coalesces each child of a `UnionExec` as a group of its own, and from Spark 4.0 each + * child of a `CartesianProductExec`, `BroadcastHashJoinExec` or `BroadcastNestedLoopJoinExec` + * too. It matches those classes, and the Comet operators that replace them are other classes, so + * it falls through to the case that coalesces only when every leaf below the operator is an + * exchange stage. A union with a scan or a table-cache stage in one branch then keeps every + * partition of the shuffles in the others: `spark.sql.shuffle.partitions` tasks for a query that + * needs a few. + * + * Comet replaces these operators while AQE prepares a stage, before its optimizer rules run, and + * plans the operators above them against the Comet versions. So this runs after Spark's rule + * instead, on each such operator whose shuffle stages that rule left untouched. It rebuilds the + * Spark operator each Comet one replaced over the Comet children, has Spark's own rule coalesce + * that, and swaps the Comet operators back in. The partitions come out as Spark would have + * coalesced them, down to which operators count, since it is Spark's code deciding. The one + * difference is that Spark divides its minimum partition count among the coalesce groups of the + * whole plan, and this among those below the Comet operator, which are usually all of them. + * + * When every leaf below such an operator is an exchange stage, Spark's rule already coalesces its + * shuffles, together rather than child by child, and this leaves them as they are. + * + * Extending `AQEShuffleReadRule` gets this the same treatment from AQE as Spark's rule: it is + * skipped for the final stage when that stage's shuffle optimizations are off, and its result is + * discarded if it breaks a distribution required above it. + */ +case object CometCoalesceShufflePartitions extends AQEShuffleReadRule { + + // The Comet operator that a stand-in Spark operator was rebuilt from. + private val COMET_OPERATOR = TreeNodeTag[SparkPlan]("cometCoalesceShufflePartitions") + + // Required by the trait. Which shuffles are coalesced is decided by Spark's rule, which applies + // its own list. + override protected def supportedShuffleOrigins: Seq[ShuffleOrigin] = + CoalesceShufflePartitions(SparkSession.active).supportedShuffleOrigins + + override def apply(plan: SparkPlan): SparkPlan = { + if (!conf.coalesceShufflePartitionsEnabled || !plan.exists(replaced(_).isDefined)) { + return plan + } + plan.transformDown { + case p if replaced(p).isDefined && untouched(p) => coalesceBelow(p) + } + } + + // The Spark operator a Comet operator replaced, if Spark's rule coalesces its children one by + // one. The class match mirrors Spark's, and Spark's rule decides, for its version, which of + // these it actually treats that way. + private def replaced(plan: SparkPlan): Option[SparkPlan] = plan match { + case comet: CometExec => + comet.originalPlan match { + case original @ (_: UnionExec | _: CartesianProductExec | _: BroadcastHashJoinExec | + _: BroadcastNestedLoopJoinExec) + if original.children.length == comet.children.length => + Some(original) + case _ => None + } + case _ => None + } + + // No AQE rule has put a read over any shuffle stage below `plan`: Spark's rule coalesced none + // of them, and none is a skew-split or local read that coalescing now could disturb. + private def untouched(plan: SparkPlan): Boolean = + plan.exists(_.isInstanceOf[ShuffleQueryStageExec]) && + !plan.exists(_.isInstanceOf[AQEShuffleReadExec]) + + private def coalesceBelow(plan: SparkPlan): SparkPlan = { + val asSpark = plan.transformUp { case p => + replaced(p) match { + case Some(original) => + val standIn = original.withNewChildren(p.children) + // `withNewChildren` hands back the original itself when the children are the same ones, + // and the tag must not land on the operator that the Comet one keeps. + if (standIn eq original) { + p + } else { + standIn.setTagValue(COMET_OPERATOR, p) + standIn + } + case None => p + } + } + val coalesced = CoalesceShufflePartitions(SparkSession.active).apply(asSpark) Review Comment: The rule now gives Spark's rule the whole stage rather than the subtree below each Comet operator, so Spark's walk sees a Cartesian product or nested loop join above the union and uses the minimum partition size, and it divides the minimum partition count over every group in the stage, as it would for Spark's operators. It runs only when no AQE rule has put a read over any shuffle in the stage, since Spark's rule would coalesce those reads a second time. In the new `AQE coalesces the shuffle partitions of a union below a join as Spark does`, with a `crossJoin` above the union, the shuffled branch keeps its 10 partitions on Spark 4.1, as it does without Comet, where the previous revision coalesced them to 1. -- 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. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
