holdenk commented on a change in pull request #32921:
URL: https://github.com/apache/spark/pull/32921#discussion_r658192361
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/BatchScanExec.scala
##########
@@ -17,38 +17,91 @@
package org.apache.spark.sql.execution.datasources.v2
+import com.google.common.base.Objects
+
+import org.apache.spark.SparkException
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.connector.read.{InputPartition,
PartitionReaderFactory, Scan}
+import org.apache.spark.sql.catalyst.plans.physical.UnknownPartitioning
+import org.apache.spark.sql.catalyst.util.truncatedString
+import org.apache.spark.sql.connector.read.{InputPartition,
PartitionReaderFactory, Scan, SupportsRuntimeFiltering}
+import org.apache.spark.sql.execution.datasources.DataSourceStrategy
/**
* Physical plan node for scanning a batch of data from a data source v2.
*/
case class BatchScanExec(
output: Seq[AttributeReference],
- @transient scan: Scan) extends DataSourceV2ScanExecBase {
+ @transient scan: Scan,
+ runtimeFilters: Seq[Expression]) extends DataSourceV2ScanExecBase {
@transient lazy val batch = scan.toBatch
// TODO: unify the equal/hashCode implementation for all data source v2
query plans.
override def equals(other: Any): Boolean = other match {
- case other: BatchScanExec => this.batch == other.batch
- case _ => false
+ case other: BatchScanExec =>
+ this.batch == other.batch && this.runtimeFilters == other.runtimeFilters
+ case _ =>
+ false
}
- override def hashCode(): Int = batch.hashCode()
+ override def hashCode(): Int = Objects.hashCode(batch, runtimeFilters)
@transient override lazy val partitions: Seq[InputPartition] =
batch.planInputPartitions()
+ @transient private lazy val filteredPartitions: Seq[InputPartition] = {
+ val dataSourceFilters = runtimeFilters.flatMap {
+ case DynamicPruningExpression(e) =>
DataSourceStrategy.translateRuntimeFilter(e)
+ case _ => None
+ }
+
+ if (dataSourceFilters.nonEmpty) {
+ // the cast is safe as runtime filters are only assigned if the scan can
be filtered
+ val filterableScan = scan.asInstanceOf[SupportsRuntimeFiltering]
+ val canChangeNumPartitions = outputPartitioning match {
+ case UnknownPartitioning(0) => true
+ case _ => false
+ }
+ filterableScan.filter(dataSourceFilters.toArray, canChangeNumPartitions)
+
+ // call toBatch again to get new partitions
+ val newPartitions = scan.toBatch.planInputPartitions()
Review comment:
We should update the comment in `Batch.java` since we are now calling
`planInputPartitions` more than once and people might put some logic there that
they assume is only run once.
##########
File path:
sql/catalyst/src/main/java/org/apache/spark/sql/connector/read/SupportsRuntimeFiltering.java
##########
@@ -0,0 +1,61 @@
+/*
+ * 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.Experimental;
+import org.apache.spark.sql.connector.expressions.NamedReference;
+import org.apache.spark.sql.sources.Filter;
+
+/**
+ * A mix-in interface for {@link Scan}. Data sources can implement this
interface if they can
+ * filter initially planned {@link InputPartition}s using predicates Spark
infers at runtime.
+ * <p>
+ * Note that Spark will push runtime filters only if they are beneficial.
Review comment:
How do we determine if it is beneficial?
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