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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2022/11/29 06:35:22 UTC
[GitHub] [spark] zhengruifeng commented on a diff in pull request #38799: [SPARK-37099][SQL] Introduce the group limit of Window for rank-based filter to optimize top-k computation
zhengruifeng commented on code in PR #38799:
URL: https://github.com/apache/spark/pull/38799#discussion_r1034340755
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/window/WindowGroupLimitExec.scala:
##########
@@ -0,0 +1,236 @@
+/*
+ * 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.window
+
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions.{Ascending, Attribute, DenseRank, Expression, Rank, RowNumber, SortOrder, UnsafeProjection, UnsafeRow}
+import org.apache.spark.sql.catalyst.expressions.codegen.GenerateOrdering
+import org.apache.spark.sql.catalyst.plans.physical.{AllTuples, ClusteredDistribution, Distribution, Partitioning}
+import org.apache.spark.sql.execution.{ExternalAppendOnlyUnsafeRowArray, SparkPlan, UnaryExecNode}
+
+sealed trait WindowGroupLimitMode
+
+case object Partial extends WindowGroupLimitMode
+
+case object Final extends WindowGroupLimitMode
+
+/**
+ * This operator is designed to filter out unnecessary rows before WindowExec
+ * for top-k computation.
+ * @param partitionSpec Should be the same as [[WindowExec#partitionSpec]]
+ * @param orderSpec Should be the same as [[WindowExec#orderSpec]]
+ * @param rankLikeFunction The function to compute row rank, should be RowNumber/Rank/DenseRank.
+ */
+case class WindowGroupLimitExec(
+ partitionSpec: Seq[Expression],
+ orderSpec: Seq[SortOrder],
+ rankLikeFunction: Expression,
+ limit: Int,
+ mode: WindowGroupLimitMode,
+ child: SparkPlan) extends UnaryExecNode {
+
+ override def output: Seq[Attribute] = child.output
+
+ override def requiredChildDistribution: Seq[Distribution] = mode match {
+ case Partial => super.requiredChildDistribution
+ case Final =>
+ if (partitionSpec.isEmpty) {
+ // Only show warning when the number of bytes is larger than 100 MiB?
+ logWarning("No Partition Defined for Window operation! Moving all data to a single "
Review Comment:
I think we don't need this warning, since `WindowExec` log this warning anyway
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/window/WindowGroupLimitExec.scala:
##########
@@ -0,0 +1,236 @@
+/*
+ * 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.window
+
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions.{Ascending, Attribute, DenseRank, Expression, Rank, RowNumber, SortOrder, UnsafeProjection, UnsafeRow}
+import org.apache.spark.sql.catalyst.expressions.codegen.GenerateOrdering
+import org.apache.spark.sql.catalyst.plans.physical.{AllTuples, ClusteredDistribution, Distribution, Partitioning}
+import org.apache.spark.sql.execution.{ExternalAppendOnlyUnsafeRowArray, SparkPlan, UnaryExecNode}
+
+sealed trait WindowGroupLimitMode
+
+case object Partial extends WindowGroupLimitMode
+
+case object Final extends WindowGroupLimitMode
+
+/**
+ * This operator is designed to filter out unnecessary rows before WindowExec
+ * for top-k computation.
+ * @param partitionSpec Should be the same as [[WindowExec#partitionSpec]]
+ * @param orderSpec Should be the same as [[WindowExec#orderSpec]]
+ * @param rankLikeFunction The function to compute row rank, should be RowNumber/Rank/DenseRank.
+ */
+case class WindowGroupLimitExec(
+ partitionSpec: Seq[Expression],
+ orderSpec: Seq[SortOrder],
+ rankLikeFunction: Expression,
+ limit: Int,
+ mode: WindowGroupLimitMode,
+ child: SparkPlan) extends UnaryExecNode {
+
+ override def output: Seq[Attribute] = child.output
+
+ override def requiredChildDistribution: Seq[Distribution] = mode match {
+ case Partial => super.requiredChildDistribution
+ case Final =>
+ if (partitionSpec.isEmpty) {
+ // Only show warning when the number of bytes is larger than 100 MiB?
+ logWarning("No Partition Defined for Window operation! Moving all data to a single "
+ + "partition, this can cause serious performance degradation.")
+ AllTuples :: Nil
+ } else {
+ ClusteredDistribution(partitionSpec) :: Nil
+ }
+ }
+
+ override def requiredChildOrdering: Seq[Seq[SortOrder]] =
+ Seq(partitionSpec.map(SortOrder(_, Ascending)) ++ orderSpec)
+
+ override def outputOrdering: Seq[SortOrder] = child.outputOrdering
+
+ override def outputPartitioning: Partitioning = child.outputPartitioning
+
+ protected override def doExecute(): RDD[InternalRow] = {
+ val inMemoryThreshold = conf.windowExecBufferInMemoryThreshold
+ val spillThreshold = conf.windowExecBufferSpillThreshold
Review Comment:
are the two config dedicated to WindowExec?
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/window/WindowGroupLimitExec.scala:
##########
@@ -0,0 +1,236 @@
+/*
+ * 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.window
+
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions.{Ascending, Attribute, DenseRank, Expression, Rank, RowNumber, SortOrder, UnsafeProjection, UnsafeRow}
+import org.apache.spark.sql.catalyst.expressions.codegen.GenerateOrdering
+import org.apache.spark.sql.catalyst.plans.physical.{AllTuples, ClusteredDistribution, Distribution, Partitioning}
+import org.apache.spark.sql.execution.{ExternalAppendOnlyUnsafeRowArray, SparkPlan, UnaryExecNode}
+
+sealed trait WindowGroupLimitMode
+
+case object Partial extends WindowGroupLimitMode
+
+case object Final extends WindowGroupLimitMode
+
+/**
+ * This operator is designed to filter out unnecessary rows before WindowExec
+ * for top-k computation.
+ * @param partitionSpec Should be the same as [[WindowExec#partitionSpec]]
+ * @param orderSpec Should be the same as [[WindowExec#orderSpec]]
+ * @param rankLikeFunction The function to compute row rank, should be RowNumber/Rank/DenseRank.
+ */
+case class WindowGroupLimitExec(
+ partitionSpec: Seq[Expression],
+ orderSpec: Seq[SortOrder],
+ rankLikeFunction: Expression,
+ limit: Int,
+ mode: WindowGroupLimitMode,
+ child: SparkPlan) extends UnaryExecNode {
+
+ override def output: Seq[Attribute] = child.output
+
+ override def requiredChildDistribution: Seq[Distribution] = mode match {
+ case Partial => super.requiredChildDistribution
+ case Final =>
+ if (partitionSpec.isEmpty) {
+ // Only show warning when the number of bytes is larger than 100 MiB?
+ logWarning("No Partition Defined for Window operation! Moving all data to a single "
+ + "partition, this can cause serious performance degradation.")
+ AllTuples :: Nil
+ } else {
+ ClusteredDistribution(partitionSpec) :: Nil
+ }
+ }
+
+ override def requiredChildOrdering: Seq[Seq[SortOrder]] =
Review Comment:
for `row_number` and small `k`, can use `Utils.takeOrdered` to relax the requirement of ordering.
For a special case, row_number < k without partitionSpec, it can avoid the extra SortExec.
just a suggestion, do not need to be in this PR.
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