[GitHub] spark pull request #14452: [SPARK-16849][SQL][WIP] Improve subquery executio...
Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/14452#discussion_r78499987
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/EnsureRequirements.scala
---
@@ -268,3 +269,35 @@ case class EnsureRequirements(conf: SQLConf) extends
Rule[SparkPlan] {
case operator: SparkPlan => ensureDistributionAndOrdering(operator)
}
}
+
+
+/**
+ * Pushs down [[ShuffleExchange]] on the top of [[CommonSubqueryExec]] to
make them reusable.
+ */
+case object PushDownShuffleExchange extends Rule[SparkPlan] {
--- End diff --
I revert this change because don't see improvement with it.
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[GitHub] spark pull request #14452: [SPARK-16849][SQL][WIP] Improve subquery executio...
Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/14452#discussion_r78499975
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/subquery/CommonSubquery.scala
---
@@ -0,0 +1,68 @@
+/*
+ * 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.subquery
+
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.plans.QueryPlan
+import org.apache.spark.sql.catalyst.plans.logical
+import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan,
Statistics}
+import org.apache.spark.sql.execution.SparkPlan
+import org.apache.spark.util.Utils
+
+private[sql] case class SubqueryExecHelper(executedPlan: SparkPlan) {
+ private var _computedOutput: RDD[InternalRow] = null
+
+ def computeOrGetResult(): RDD[InternalRow] = this.synchronized {
+if (_computedOutput == null) {
+ _computedOutput = executedPlan.execute().mapPartitionsInternal {
rowIterator =>
+rowIterator.map(_.copy())
+ }.cache()
--- End diff --
I revert this change because don't see improvement with it.
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[GitHub] spark pull request #14452: [SPARK-16849][SQL][WIP] Improve subquery executio...
Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/14452#discussion_r78494742
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/EnsureRequirements.scala
---
@@ -268,3 +269,35 @@ case class EnsureRequirements(conf: SQLConf) extends
Rule[SparkPlan] {
case operator: SparkPlan => ensureDistributionAndOrdering(operator)
}
}
+
+
+/**
+ * Pushs down [[ShuffleExchange]] on the top of [[CommonSubqueryExec]] to
make them reusable.
+ */
+case object PushDownShuffleExchange extends Rule[SparkPlan] {
--- End diff --
The common pattern of common subquery in TPC-DS, is joining two or more the
same subquery. The joining is `SortMergeJoin` and `ShuffleExchange` is executed
for all the subqueries after some operators (e.g., `Project`, `Filter`).
E.g.,
: :- *SortMergeJoin [customer_id#898], [customer_id#912], Inner
: : :- *Sort [customer_id#898 ASC], false, 0
: : : +- Exchange hashpartitioning(customer_id#898, 200)
: : : +- *Project [customer_id#898, year_total#902]
: : :+- *Filter (isnotnull(year#901) &&
isnotnull(year_total#902)) && (sale_type#903 = s)) && (year#901 = 2001)) &&
(year_total#902 > 0.0)) && isnotnull(customer_id#898))
: : : +- CommonSubquery [customer_id#898,
customer_first_name#899, customer_last_name#900, year#901, year_total#902,
sale_type#903]
This rule is to pushdown `ShuffleExchange` on the top of
`CommonSubqueryExec`. So other `ShuffleExchange`s can be transformed to
`ReusedExchange` later. Then we can reuse the exchange.
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[GitHub] spark pull request #14452: [SPARK-16849][SQL][WIP] Improve subquery executio...
Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/14452#discussion_r78494245
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/subquery/CommonSubquery.scala
---
@@ -0,0 +1,68 @@
+/*
+ * 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.subquery
+
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.plans.QueryPlan
+import org.apache.spark.sql.catalyst.plans.logical
+import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan,
Statistics}
+import org.apache.spark.sql.execution.SparkPlan
+import org.apache.spark.util.Utils
+
+private[sql] case class SubqueryExecHelper(executedPlan: SparkPlan) {
+ private var _computedOutput: RDD[InternalRow] = null
+
+ def computeOrGetResult(): RDD[InternalRow] = this.synchronized {
+if (_computedOutput == null) {
+ _computedOutput = executedPlan.execute().mapPartitionsInternal {
rowIterator =>
+rowIterator.map(_.copy())
+ }.cache()
--- End diff --
We need to cache explicitly the result of common subquery. Becasue in RDD
materialization implementation, if a RDD is not marked to cache, even it is
materialization before, the later call to its iterator will invoke computation
again.
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