szehon-ho commented on code in PR #54459:
URL: https://github.com/apache/spark/pull/54459#discussion_r2909284758
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/PushDownUtils.scala:
##########
@@ -96,18 +159,55 @@ object PushDownUtils {
}
}
- // Data source filters that need to be evaluated again after scanning.
which means
- // the data source cannot guarantee the rows returned can pass these
filters.
- // As a result we must return it so Spark can plan an extra filter
operator.
- val postScanFilters = r.pushPredicates(translatedFilters.toArray).map
{ predicate =>
- DataSourceV2Strategy.rebuildExpressionFromFilter(predicate,
translatedFilterToExpr)
+ // Post-scan filters candidates: those the data source rejected in the
first pass
+ // and need to be evaluated by Spark after the scan.
+ val returnedFirstPassFilters =
r.pushPredicates(translatedFilters.toArray).map {
+ predicate =>
+ DataSourceV2Strategy.rebuildExpressionFromFilter(predicate,
translatedFilterToExpr)
+ }
+
+ val finalPostScanFilters = (partitionSchema,
r.supportsEnhancedPartitionFiltering()) match {
+ // If the scan supports enhanced partition filtering, convert to
PartitionPredicates
+ // (see SPARK-55596). PartitionPredicates are pushed to the scan in
a second pass.
+ case (Some(structType), true) =>
+ val (postScanPartitionFilters, postScanDataFilters) =
+ DataSourceUtils.getPartitionFiltersAndDataFilters(
+ structType, returnedFirstPassFilters.toIndexedSeq)
+ val (untranslatablePartitionFilters, untranslatableDataFilters) =
+ DataSourceUtils.getPartitionFiltersAndDataFilters(
+ structType, untranslatableExprs.toSeq)
+
+ // Push second-pass partition filters as PartitionPredicates
+ val allPartitionFilters = postScanPartitionFilters ++
untranslatablePartitionFilters
+ val (partitionFiltersForPush, partitionFiltersNotPushed) =
+ allPartitionFilters.partition(isPartitionPushableFilter)
+ val partitionPredicatesForPush = partitionFiltersForPush
+ .map(expr => PartitionPredicateImpl(expr,
toAttributes(structType)))
+ val returnedSecondPassPartitionFilters =
+ r.pushPredicates(partitionPredicatesForPush.toArray).map {
predicate =>
+ V2ExpressionUtils.toCatalyst(predicate).getOrElse(
+ // should not happen
+ DataSourceV2Strategy.rebuildExpressionFromFilter(
+ predicate, translatedFilterToExpr))
+ }
+
+ // Normally translated filters (postScanFilters) are simple
filters that can be
+ // evaluated faster, while the untranslated filters are
complicated filters that take
+ // more time to evaluate, so we want to evaluate the
postScanFilters filters first.
Review Comment:
this is a good catch. I had this in mind but end up reversing it, fixed it.
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/PushDownUtils.scala:
##########
@@ -96,18 +159,55 @@ object PushDownUtils {
}
}
- // Data source filters that need to be evaluated again after scanning.
which means
- // the data source cannot guarantee the rows returned can pass these
filters.
- // As a result we must return it so Spark can plan an extra filter
operator.
- val postScanFilters = r.pushPredicates(translatedFilters.toArray).map
{ predicate =>
- DataSourceV2Strategy.rebuildExpressionFromFilter(predicate,
translatedFilterToExpr)
+ // Post-scan filters candidates: those the data source rejected in the
first pass
+ // and need to be evaluated by Spark after the scan.
+ val returnedFirstPassFilters =
r.pushPredicates(translatedFilters.toArray).map {
+ predicate =>
+ DataSourceV2Strategy.rebuildExpressionFromFilter(predicate,
translatedFilterToExpr)
+ }
+
+ val finalPostScanFilters = (partitionSchema,
r.supportsEnhancedPartitionFiltering()) match {
+ // If the scan supports enhanced partition filtering, convert to
PartitionPredicates
+ // (see SPARK-55596). PartitionPredicates are pushed to the scan in
a second pass.
+ case (Some(structType), true) =>
+ val (postScanPartitionFilters, postScanDataFilters) =
+ DataSourceUtils.getPartitionFiltersAndDataFilters(
+ structType, returnedFirstPassFilters.toIndexedSeq)
+ val (untranslatablePartitionFilters, untranslatableDataFilters) =
+ DataSourceUtils.getPartitionFiltersAndDataFilters(
+ structType, untranslatableExprs.toSeq)
+
+ // Push second-pass partition filters as PartitionPredicates
+ val allPartitionFilters = postScanPartitionFilters ++
untranslatablePartitionFilters
+ val (partitionFiltersForPush, partitionFiltersNotPushed) =
+ allPartitionFilters.partition(isPartitionPushableFilter)
+ val partitionPredicatesForPush = partitionFiltersForPush
+ .map(expr => PartitionPredicateImpl(expr,
toAttributes(structType)))
+ val returnedSecondPassPartitionFilters =
+ r.pushPredicates(partitionPredicatesForPush.toArray).map {
predicate =>
+ V2ExpressionUtils.toCatalyst(predicate).getOrElse(
+ // should not happen
Review Comment:
ok done
##########
sql/catalyst/src/test/scala/org/apache/spark/sql/connector/catalog/InMemoryEnhancedPartitionFilterTable.scala:
##########
@@ -0,0 +1,161 @@
+/*
+ * 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.catalog
+
+import java.util
+
+import scala.collection.mutable.{ArrayBuffer, Buffer}
+
+import
org.apache.spark.sql.connector.catalog.CatalogV2Implicits.MultipartIdentifierHelper
+import org.apache.spark.sql.connector.expressions.Transform
+import org.apache.spark.sql.connector.expressions.filter.{PartitionPredicate,
Predicate}
+import org.apache.spark.sql.connector.read.{InputPartition, Scan, ScanBuilder,
SupportsPushDownRequiredColumns, SupportsPushDownV2Filters}
+import org.apache.spark.sql.connector.write.{LogicalWriteInfo, WriteBuilder}
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.util.CaseInsensitiveStringMap
+import org.apache.spark.util.ArrayImplicits._
+
+/**
+ * In-memory table whose scan builder implements enhanced partition filtering
using
+ * PartitionPredicates pushed in a second pass.
+ */
+class InMemoryEnhancedPartitionFilterTable(
+ name: String,
+ columns: Array[Column],
+ partitioning: Array[Transform],
+ properties: util.Map[String, String])
+ extends InMemoryTable(name, columns, partitioning, properties) {
+
+ override def newScanBuilder(options: CaseInsensitiveStringMap): ScanBuilder
= {
+ new InMemoryEnhancedPartitionFilterScanBuilder(schema())
+ }
+
+ override def newWriteBuilder(info: LogicalWriteInfo): WriteBuilder = {
+ InMemoryBaseTable.maybeSimulateFailedTableWrite(new
CaseInsensitiveStringMap(properties))
+ InMemoryBaseTable.maybeSimulateFailedTableWrite(info.options)
+ new InMemoryWriterBuilderWithOverWrite(info)
+ }
+
+ class InMemoryEnhancedPartitionFilterScanBuilder(
+ tableSchema: StructType)
+ extends ScanBuilder
+ with SupportsPushDownV2Filters
+ with SupportsPushDownRequiredColumns {
+
+ private var readSchema: StructType = tableSchema
+ private val partitionPredicates: Buffer[PartitionPredicate] =
ArrayBuffer.empty
+ private val firstPassPushedPredicates: Buffer[Predicate] =
ArrayBuffer.empty
+
+ private val rejectPartitionPredicates =
+ InMemoryEnhancedPartitionFilterTable.this.properties.getOrDefault(
+ InMemoryEnhancedPartitionFilterTable.RejectPartitionPredicatesKey,
"false")
+ .toBoolean
+
+ private val rejectDataPredicates =
+ InMemoryEnhancedPartitionFilterTable.this.properties.getOrDefault(
+ InMemoryEnhancedPartitionFilterTable.RejectDataPredicatesKey, "false")
+ .toBoolean
+
+ override def supportsEnhancedPartitionFiltering(): Boolean = true
+
+ override def pushPredicates(predicates: Array[Predicate]):
Array[Predicate] = {
+ val partNames =
InMemoryEnhancedPartitionFilterTable.this.partCols.flatMap(_.toSeq).toSet
+ def referencesOnlyPartitionCols(p: Predicate): Boolean =
+ p.references().forall(ref =>
partNames.contains(ref.fieldNames().mkString(".")))
+ def referencesOnlyDataCols(p: Predicate): Boolean =
+ p.references().forall(ref =>
!partNames.contains(ref.fieldNames().mkString(".")))
+
+ val returned = ArrayBuffer.empty[Predicate]
+
+ predicates.foreach {
+ case p: PartitionPredicate =>
+ if (rejectPartitionPredicates) {
+ returned += p
+ } else {
+ partitionPredicates += p
+ }
+ case p if referencesOnlyPartitionCols(p) &&
+ InMemoryTableWithV2Filter.supportsPredicates(Array(p)) =>
+ if (rejectPartitionPredicates) {
+ returned += p
+ } else {
+ firstPassPushedPredicates += p
+ }
+ case p if rejectDataPredicates && referencesOnlyDataCols(p) =>
+ // Reject: we are mocking a data source that can evaluate this data
predicate
+ case p =>
+ returned += p
+ }
+
+ if (partitionPredicates.nonEmpty) Array.empty[Predicate]
Review Comment:
done
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