Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/18747#discussion_r144618498
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/InMemoryTableScanExec.scala
---
@@ -23,21 +23,37 @@ import org.apache.spark.sql.catalyst.dsl.expressions._
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.plans.QueryPlan
import org.apache.spark.sql.catalyst.plans.physical.{HashPartitioning,
Partitioning}
-import org.apache.spark.sql.execution.LeafExecNode
-import org.apache.spark.sql.execution.metric.SQLMetrics
+import org.apache.spark.sql.execution.{ColumnarBatchScan, LeafExecNode}
+import org.apache.spark.sql.execution.vectorized.OnHeapColumnVector
import org.apache.spark.sql.types.UserDefinedType
case class InMemoryTableScanExec(
attributes: Seq[Attribute],
predicates: Seq[Expression],
@transient relation: InMemoryRelation)
- extends LeafExecNode {
+ extends LeafExecNode with ColumnarBatchScan {
override protected def innerChildren: Seq[QueryPlan[_]] = Seq(relation)
++ super.innerChildren
- override lazy val metrics = Map(
- "numOutputRows" -> SQLMetrics.createMetric(sparkContext, "number of
output rows"))
+ override def vectorTypes: Option[Seq[String]] =
+
Option(Seq.fill(attributes.length)(classOf[OnHeapColumnVector].getName))
+
+ override val columnIndexes =
+ attributes.map(a => relation.output.map(o =>
o.exprId).indexOf(a.exprId)).toArray
+
+ override val supportCodegen: Boolean = relation.useColumnarBatches
+
+ override def inputRDDs(): Seq[RDD[InternalRow]] = {
+ if (supportCodegen) {
+ val buffers = relation.cachedColumnBuffers
+ // HACK ALERT: This is actually an RDD[CachedBatch].
+ // We're taking advantage of Scala's type erasure here to pass these
batches along.
+ Seq(buffers.asInstanceOf[RDD[InternalRow]])
--- End diff --
yes please
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