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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2021/03/17 19:55:44 UTC
[GitHub] [spark] viirya commented on a change in pull request #29695: [SPARK-22390][SPARK-32833][SQL] [WIP]JDBC V2 Datasource aggregate push down
viirya commented on a change in pull request #29695:
URL: https://github.com/apache/spark/pull/29695#discussion_r596239451
##########
File path: sql/catalyst/src/main/java/org/apache/spark/sql/connector/read/SupportsPushDownAggregates.java
##########
@@ -0,0 +1,44 @@
+/*
+ * 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.connector.read;
+
+import org.apache.spark.annotation.Evolving;
+import org.apache.spark.sql.sources.Aggregation;
+
+/**
+ * A mix-in interface for {@link ScanBuilder}. Data sources can implement this interface to
+ * push down aggregates to the data source.
+ *
+ * @since 3.1.0
Review comment:
Maybe 3.2.0 now.
##########
File path: sql/catalyst/src/main/java/org/apache/spark/sql/connector/read/SupportsPushDownAggregates.java
##########
@@ -0,0 +1,44 @@
+/*
+ * 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.connector.read;
+
+import org.apache.spark.annotation.Evolving;
+import org.apache.spark.sql.sources.Aggregation;
+
+/**
+ * A mix-in interface for {@link ScanBuilder}. Data sources can implement this interface to
+ * push down aggregates to the data source.
+ *
+ * @since 3.1.0
+ */
+@Evolving
+public interface SupportsPushDownAggregates extends ScanBuilder {
+
+ /**
+ * Pushes down Aggregation to datasource.
+ * The Aggregation can be pushed down only if all the Aggregate Functions can
+ * be pushed down.
+ */
+ void pushAggregation(Aggregation aggregation);
+
+ /**
+ * Returns the aggregates that are pushed to the data source via
Review comment:
I think this returns `Aggregation`?
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/V2ScanRelationPushDown.scala
##########
@@ -17,38 +17,122 @@
package org.apache.spark.sql.execution.datasources.v2
-import org.apache.spark.sql.catalyst.expressions.{And, Expression, NamedExpression, ProjectionOverSchema, SubqueryExpression}
+import scala.collection.mutable.ArrayBuilder
+
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.expressions.aggregate.AggregateExpression
import org.apache.spark.sql.catalyst.planning.ScanOperation
-import org.apache.spark.sql.catalyst.plans.logical.{Filter, LogicalPlan, Project}
+import org.apache.spark.sql.catalyst.plans.logical.{Aggregate, Filter, LogicalPlan, Project}
import org.apache.spark.sql.catalyst.rules.Rule
-import org.apache.spark.sql.connector.read.{Scan, V1Scan}
+import org.apache.spark.sql.connector.read.{Scan, ScanBuilder, V1Scan}
import org.apache.spark.sql.execution.datasources.DataSourceStrategy
import org.apache.spark.sql.sources
+import org.apache.spark.sql.sources.{AggregateFunc, Aggregation}
import org.apache.spark.sql.types.StructType
-object V2ScanRelationPushDown extends Rule[LogicalPlan] {
+object V2ScanRelationPushDown extends Rule[LogicalPlan] with AliasHelper {
+
import DataSourceV2Implicits._
override def apply(plan: LogicalPlan): LogicalPlan = plan transformDown {
- case ScanOperation(project, filters, relation: DataSourceV2Relation) =>
- val scanBuilder = relation.table.asReadable.newScanBuilder(relation.options)
+ case Aggregate(groupingExpressions, resultExpressions, child) =>
+ child match {
+ case ScanOperation(project, filters, relation: DataSourceV2Relation) =>
+ val scanBuilder = relation.table.asReadable.newScanBuilder(relation.options)
+ val (pushedFilters, postScanFilters) = pushDownFilter(scanBuilder, filters, relation)
+ if (postScanFilters.nonEmpty) {
+ Aggregate(groupingExpressions, resultExpressions, child)
+ } else { // only push down aggregate of all the filers can be push down
+ val aliasMap = getAliasMap(project)
+ var aggregates = resultExpressions.flatMap { expr =>
+ expr.collect {
+ case agg: AggregateExpression =>
+ replaceAlias(agg, aliasMap).asInstanceOf[AggregateExpression]
+ }
+ }
+ aggregates = DataSourceStrategy.normalizeExprs(aggregates, relation.output)
+ .asInstanceOf[Seq[AggregateExpression]]
- val normalizedFilters = DataSourceStrategy.normalizeExprs(filters, relation.output)
- val (normalizedFiltersWithSubquery, normalizedFiltersWithoutSubquery) =
- normalizedFilters.partition(SubqueryExpression.hasSubquery)
+ val groupingExpressionsWithoutAlias = groupingExpressions.flatMap{ expr =>
+ expr.collect {
+ case a: AttributeReference => replaceAlias(a, aliasMap)
+ }
+ }
+ val normalizedgroupingExpressions =
Review comment:
normalizedGroupingExpressions
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceStrategy.scala
##########
@@ -700,6 +704,41 @@ object DataSourceStrategy
(nonconvertiblePredicates ++ unhandledPredicates, pushedFilters, handledFilters)
}
+ private def columnAsString(e: Expression): String = e match {
Review comment:
For predicate pushdown, seems we simplify the cases to handle by only looking at column name.
This covers a lot of cases but also makes it easy to break. We can begin with simplest case and add more supports later.
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/V2ScanRelationPushDown.scala
##########
@@ -17,38 +17,122 @@
package org.apache.spark.sql.execution.datasources.v2
-import org.apache.spark.sql.catalyst.expressions.{And, Expression, NamedExpression, ProjectionOverSchema, SubqueryExpression}
+import scala.collection.mutable.ArrayBuilder
+
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.expressions.aggregate.AggregateExpression
import org.apache.spark.sql.catalyst.planning.ScanOperation
-import org.apache.spark.sql.catalyst.plans.logical.{Filter, LogicalPlan, Project}
+import org.apache.spark.sql.catalyst.plans.logical.{Aggregate, Filter, LogicalPlan, Project}
import org.apache.spark.sql.catalyst.rules.Rule
-import org.apache.spark.sql.connector.read.{Scan, V1Scan}
+import org.apache.spark.sql.connector.read.{Scan, ScanBuilder, V1Scan}
import org.apache.spark.sql.execution.datasources.DataSourceStrategy
import org.apache.spark.sql.sources
+import org.apache.spark.sql.sources.{AggregateFunc, Aggregation}
import org.apache.spark.sql.types.StructType
-object V2ScanRelationPushDown extends Rule[LogicalPlan] {
+object V2ScanRelationPushDown extends Rule[LogicalPlan] with AliasHelper {
+
import DataSourceV2Implicits._
override def apply(plan: LogicalPlan): LogicalPlan = plan transformDown {
- case ScanOperation(project, filters, relation: DataSourceV2Relation) =>
- val scanBuilder = relation.table.asReadable.newScanBuilder(relation.options)
+ case Aggregate(groupingExpressions, resultExpressions, child) =>
+ child match {
+ case ScanOperation(project, filters, relation: DataSourceV2Relation) =>
+ val scanBuilder = relation.table.asReadable.newScanBuilder(relation.options)
+ val (pushedFilters, postScanFilters) = pushDownFilter(scanBuilder, filters, relation)
Review comment:
I can see there is a dependency between filter pushdown and aggregate pushdown. As we need to check if all filters are pushed down.
I think an alternative approach is to not touch filter pushdown, but to check if filter pushdown is happened and there is still `Filter` on top of the scan relation.
I feel that can simplify the code here. And we don't need to call `pushDownFilter` twice for aggregate and filter.
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRDD.scala
##########
@@ -181,21 +243,49 @@ private[jdbc] class JDBCRDD(
filters: Array[Filter],
partitions: Array[Partition],
url: String,
- options: JDBCOptions)
+ options: JDBCOptions,
+ aggregation: Aggregation = Aggregation.empty)
extends RDD[InternalRow](sc, Nil) {
/**
* Retrieve the list of partitions corresponding to this RDD.
*/
override def getPartitions: Array[Partition] = partitions
+ private var updatedSchema: StructType = new StructType()
+
/**
* `columns`, but as a String suitable for injection into a SQL query.
*/
private val columnList: String = {
+ val (compiledAgg, aggDataType) =
+ JDBCRDD.compileAggregates(aggregation.aggregateExpressions, JdbcDialects.get(url))
val sb = new StringBuilder()
- columns.foreach(x => sb.append(",").append(x))
- if (sb.isEmpty) "1" else sb.substring(1)
+ if (compiledAgg.length == 0) {
+ updatedSchema = schema
+ columns.foreach(x => sb.append(",").append(x))
+ } else {
+ getAggregateColumnsList(sb, compiledAgg, aggDataType)
+ }
+ if (sb.length == 0) "1" else sb.substring(1)
+ }
+
+ private def getAggregateColumnsList(
Review comment:
Shall we add a comment here to explain what `getAggregateColumnsList` does and why it is needed?
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceStrategy.scala
##########
@@ -700,6 +704,41 @@ object DataSourceStrategy
(nonconvertiblePredicates ++ unhandledPredicates, pushedFilters, handledFilters)
}
+ private def columnAsString(e: Expression): String = e match {
Review comment:
Let's wait for others. See if there is any other voices.
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRDD.scala
##########
@@ -296,13 +398,15 @@ private[jdbc] class JDBCRDD(
val myWhereClause = getWhereClause(part)
- val sqlText = s"SELECT $columnList FROM ${options.tableOrQuery} $myWhereClause"
+ val sqlText = s"SELECT $columnList FROM ${options.tableOrQuery} $myWhereClause" +
+ s" $getGroupByClause"
stmt = conn.prepareStatement(sqlText,
ResultSet.TYPE_FORWARD_ONLY, ResultSet.CONCUR_READ_ONLY)
stmt.setFetchSize(options.fetchSize)
stmt.setQueryTimeout(options.queryTimeout)
rs = stmt.executeQuery()
- val rowsIterator = JdbcUtils.resultSetToSparkInternalRows(rs, schema, inputMetrics)
+
Review comment:
unnecessary change?
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRDD.scala
##########
@@ -181,21 +243,49 @@ private[jdbc] class JDBCRDD(
filters: Array[Filter],
partitions: Array[Partition],
url: String,
- options: JDBCOptions)
+ options: JDBCOptions,
+ aggregation: Aggregation = Aggregation.empty)
extends RDD[InternalRow](sc, Nil) {
/**
* Retrieve the list of partitions corresponding to this RDD.
*/
override def getPartitions: Array[Partition] = partitions
+ private var updatedSchema: StructType = new StructType()
+
/**
* `columns`, but as a String suitable for injection into a SQL query.
*/
private val columnList: String = {
+ val (compiledAgg, aggDataType) =
+ JDBCRDD.compileAggregates(aggregation.aggregateExpressions, JdbcDialects.get(url))
val sb = new StringBuilder()
- columns.foreach(x => sb.append(",").append(x))
- if (sb.isEmpty) "1" else sb.substring(1)
+ if (compiledAgg.length == 0) {
+ updatedSchema = schema
+ columns.foreach(x => sb.append(",").append(x))
+ } else {
+ getAggregateColumnsList(sb, compiledAgg, aggDataType)
Review comment:
`columns` is empty for this case?
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/V2ScanRelationPushDown.scala
##########
@@ -17,38 +17,122 @@
package org.apache.spark.sql.execution.datasources.v2
-import org.apache.spark.sql.catalyst.expressions.{And, Expression, NamedExpression, ProjectionOverSchema, SubqueryExpression}
+import scala.collection.mutable.ArrayBuilder
+
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.expressions.aggregate.AggregateExpression
import org.apache.spark.sql.catalyst.planning.ScanOperation
-import org.apache.spark.sql.catalyst.plans.logical.{Filter, LogicalPlan, Project}
+import org.apache.spark.sql.catalyst.plans.logical.{Aggregate, Filter, LogicalPlan, Project}
import org.apache.spark.sql.catalyst.rules.Rule
-import org.apache.spark.sql.connector.read.{Scan, V1Scan}
+import org.apache.spark.sql.connector.read.{Scan, ScanBuilder, V1Scan}
import org.apache.spark.sql.execution.datasources.DataSourceStrategy
import org.apache.spark.sql.sources
+import org.apache.spark.sql.sources.{AggregateFunc, Aggregation}
import org.apache.spark.sql.types.StructType
-object V2ScanRelationPushDown extends Rule[LogicalPlan] {
+object V2ScanRelationPushDown extends Rule[LogicalPlan] with AliasHelper {
+
import DataSourceV2Implicits._
override def apply(plan: LogicalPlan): LogicalPlan = plan transformDown {
- case ScanOperation(project, filters, relation: DataSourceV2Relation) =>
- val scanBuilder = relation.table.asReadable.newScanBuilder(relation.options)
+ case Aggregate(groupingExpressions, resultExpressions, child) =>
+ child match {
+ case ScanOperation(project, filters, relation: DataSourceV2Relation) =>
+ val scanBuilder = relation.table.asReadable.newScanBuilder(relation.options)
+ val (pushedFilters, postScanFilters) = pushDownFilter(scanBuilder, filters, relation)
+ if (postScanFilters.nonEmpty) {
+ Aggregate(groupingExpressions, resultExpressions, child)
+ } else { // only push down aggregate of all the filers can be push down
Review comment:
of -> if
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/V2ScanRelationPushDown.scala
##########
@@ -17,38 +17,122 @@
package org.apache.spark.sql.execution.datasources.v2
-import org.apache.spark.sql.catalyst.expressions.{And, Expression, NamedExpression, ProjectionOverSchema, SubqueryExpression}
+import scala.collection.mutable.ArrayBuilder
+
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.expressions.aggregate.AggregateExpression
import org.apache.spark.sql.catalyst.planning.ScanOperation
-import org.apache.spark.sql.catalyst.plans.logical.{Filter, LogicalPlan, Project}
+import org.apache.spark.sql.catalyst.plans.logical.{Aggregate, Filter, LogicalPlan, Project}
import org.apache.spark.sql.catalyst.rules.Rule
-import org.apache.spark.sql.connector.read.{Scan, V1Scan}
+import org.apache.spark.sql.connector.read.{Scan, ScanBuilder, V1Scan}
import org.apache.spark.sql.execution.datasources.DataSourceStrategy
import org.apache.spark.sql.sources
+import org.apache.spark.sql.sources.{AggregateFunc, Aggregation}
import org.apache.spark.sql.types.StructType
-object V2ScanRelationPushDown extends Rule[LogicalPlan] {
+object V2ScanRelationPushDown extends Rule[LogicalPlan] with AliasHelper {
+
import DataSourceV2Implicits._
override def apply(plan: LogicalPlan): LogicalPlan = plan transformDown {
- case ScanOperation(project, filters, relation: DataSourceV2Relation) =>
- val scanBuilder = relation.table.asReadable.newScanBuilder(relation.options)
+ case Aggregate(groupingExpressions, resultExpressions, child) =>
+ child match {
+ case ScanOperation(project, filters, relation: DataSourceV2Relation) =>
+ val scanBuilder = relation.table.asReadable.newScanBuilder(relation.options)
+ val (pushedFilters, postScanFilters) = pushDownFilter(scanBuilder, filters, relation)
+ if (postScanFilters.nonEmpty) {
+ Aggregate(groupingExpressions, resultExpressions, child)
+ } else { // only push down aggregate of all the filers can be push down
+ val aliasMap = getAliasMap(project)
+ var aggregates = resultExpressions.flatMap { expr =>
+ expr.collect {
+ case agg: AggregateExpression =>
+ replaceAlias(agg, aliasMap).asInstanceOf[AggregateExpression]
+ }
+ }
+ aggregates = DataSourceStrategy.normalizeExprs(aggregates, relation.output)
+ .asInstanceOf[Seq[AggregateExpression]]
- val normalizedFilters = DataSourceStrategy.normalizeExprs(filters, relation.output)
- val (normalizedFiltersWithSubquery, normalizedFiltersWithoutSubquery) =
- normalizedFilters.partition(SubqueryExpression.hasSubquery)
+ val groupingExpressionsWithoutAlias = groupingExpressions.flatMap{ expr =>
+ expr.collect {
+ case a: AttributeReference => replaceAlias(a, aliasMap)
+ }
+ }
+ val normalizedgroupingExpressions =
+ DataSourceStrategy.normalizeExprs(groupingExpressionsWithoutAlias, relation.output)
- // `pushedFilters` will be pushed down and evaluated in the underlying data sources.
- // `postScanFilters` need to be evaluated after the scan.
- // `postScanFilters` and `pushedFilters` can overlap, e.g. the parquet row group filter.
- val (pushedFilters, postScanFiltersWithoutSubquery) = PushDownUtils.pushFilters(
- scanBuilder, normalizedFiltersWithoutSubquery)
- val postScanFilters = postScanFiltersWithoutSubquery ++ normalizedFiltersWithSubquery
+ val aggregation = PushDownUtils.pushAggregates(scanBuilder, aggregates,
+ normalizedgroupingExpressions)
+
+ val (scan, output, normalizedProjects) =
+ processFilerAndColumn(scanBuilder, project, postScanFilters, relation)
+
+ logInfo(
+ s"""
+ |Pushing operators to ${relation.name}
+ |Pushed Filters: ${pushedFilters.mkString(", ")}
+ |Post-Scan Filters: ${postScanFilters.mkString(",")}
+ |Pushed Aggregate Functions: ${aggregation.aggregateExpressions.mkString(", ")}
+ |Pushed Groupby: ${aggregation.groupByExpressions.mkString(", ")}
+ |Output: ${output.mkString(", ")}
+ """.stripMargin)
+
+ val wrappedScan = scan match {
+ case v1: V1Scan =>
+ val translated = filters.flatMap(DataSourceStrategy.translateFilter(_, true))
+ V1ScanWrapper(v1, translated, pushedFilters, aggregation)
+ case _ => scan
+ }
+ if (aggregation.aggregateExpressions.isEmpty) {
+ val plan = buildLogicalPlan(project, relation, wrappedScan, output,
+ normalizedProjects, postScanFilters)
+ Aggregate(groupingExpressions, resultExpressions, plan)
+ } else {
+ val aggOutputBuilder = ArrayBuilder.make[AttributeReference]
+ for (i <- 0 until aggregates.length) {
+ aggOutputBuilder += AttributeReference(
+ aggregation.aggregateExpressions(i).toString, aggregates(i).dataType)()
+ }
+ for (groupBy <- groupingExpressions) {
+ aggOutputBuilder += groupBy.asInstanceOf[AttributeReference]
+ }
Review comment:
`groupingExpressions` is `Seq[Expression]`, are we sure they all `AttributeReference`?
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