xuanyuanking commented on a change in pull request #35673:
URL: https://github.com/apache/spark/pull/35673#discussion_r825682652
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/AggUtils.scala
##########
@@ -153,7 +179,8 @@ object AggUtils {
// If we have session window expression in aggregation, we add
UpdatingSessionsExec to
// calculate sessions for input rows and update rows' session column, so
that further
// aggregations can aggregate input rows for the same session.
- val maySessionChild = mayAppendUpdatingSessionExec(groupingExpressions,
child)
+ val maySessionChild = mayAppendUpdatingSessionExec(groupingExpressions,
child,
Review comment:
ditto
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/AggUtils.scala
##########
@@ -447,8 +475,10 @@ object AggUtils {
val aggregateExpressions = functionsWithoutDistinct.map(_.copy(mode =
PartialMerge))
val aggregateAttributes = aggregateExpressions.map(_.resultAttribute)
MergingSessionsExec(
- requiredChildDistributionExpressions = None,
- requiredChildDistributionOption =
Some(restored.requiredChildDistribution),
+ requiredChildDistributionExpressions =
Some(groupingWithoutSessionAttributes),
+ isStreaming = true,
+ // This will be replaced with actual value in state rule.
Review comment:
let's link the state rule class name here?
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/AggUtils.scala
##########
@@ -491,10 +521,15 @@ object AggUtils {
private def mayAppendUpdatingSessionExec(
groupingExpressions: Seq[NamedExpression],
- maybeChildPlan: SparkPlan): SparkPlan = {
+ maybeChildPlan: SparkPlan,
+ isStreaming: Boolean): SparkPlan = {
groupingExpressions.find(_.metadata.contains(SessionWindow.marker)) match {
case Some(sessionExpression) =>
UpdatingSessionsExec(
+ isStreaming = isStreaming,
+ // numShufflePartitions will be set to None, and replaced to the
actual value in the
+ // state rule if the query is streaming.
Review comment:
ditto
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StatefulOperatorPartitioning.scala
##########
@@ -0,0 +1,53 @@
+/*
+ * 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.streaming
+
+import org.apache.spark.sql.catalyst.expressions.Expression
+import org.apache.spark.sql.catalyst.plans.physical.{ClusteredDistribution,
Distribution, StatefulOpClusteredDistribution}
+import org.apache.spark.sql.internal.SQLConf
+import
org.apache.spark.sql.internal.SQLConf.STATEFUL_OPERATOR_USE_STRICT_DISTRIBUTION
+
+/**
+ * This object is to provide clustered distribution for stateful operator with
ensuring backward
+ * compatibility. Please read through the NOTE on the classdoc of
+ * [[StatefulOpClusteredDistribution]] before making any changes. Please refer
SPARK-38204
+ * for details.
+ *
+ * Do not use methods in this object for stateful operators which already uses
+ * StatefulOpClusteredDistribution as its required child distribution.
Review comment:
nit: [[StatefulOpClusteredDistribution]]
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
##########
@@ -1773,6 +1773,23 @@ object SQLConf {
.booleanConf
.createWithDefault(true)
+ val STATEFUL_OPERATOR_USE_STRICT_DISTRIBUTION =
+ buildConf("spark.sql.streaming.statefulOperator.useStrictDistribution")
+ .internal()
+ .doc("When true, the stateful operator for streaming query will use " +
+ "StatefulOpClusteredDistribution which guarantees stable state
partitioning as long as " +
+ "the operator provides consistent grouping keys across the lifetime of
query. " +
+ "When false, the stateful operator for streaming query will use
ClusteredDistribution " +
+ "which is not sufficient to guarantee stable state partitioning
despite the operator " +
+ "provides consistent grouping keys across the lifetime of query. " +
+ "This config will be set to true for new streaming queries to
guarantee stable state " +
+ "partitioning, and set to false for existing streaming queries to not
break queries " +
+ "which are restored from existing checkpoints. Please refer
SPARK-38204 for details. " +
+ "The purpose of this config is only compatibility; DO NOT MANUALLY
CHANGE THIS!!!")
Review comment:
let's move the description of `This config is for compatility only; DO
NOT MANUALLY CHANGE THIS!!!` as the first sentence in the doc.
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/AggUtils.scala
##########
@@ -121,7 +147,7 @@ object AggUtils {
// If we have session window expression in aggregation, we add
MergingSessionExec to
// merge sessions with calculating aggregation values.
val interExec: SparkPlan = mayAppendMergingSessionExec(groupingExpressions,
- aggregateExpressions, partialAggregate)
+ aggregateExpressions, partialAggregate, isStreaming = false)
Review comment:
nit: how about using default value in `mayAppendMergingSessionExec` and
let here unchange?
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