Github user andrewor14 commented on a diff in the pull request:
https://github.com/apache/spark/pull/7192#discussion_r34062205
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala ---
@@ -36,11 +36,15 @@ import org.apache.spark.{HashPartitioner, SparkEnv}
case class Project(projectList: Seq[NamedExpression], child: SparkPlan)
extends UnaryNode {
override def output: Seq[Attribute] = projectList.map(_.toAttribute)
- @transient lazy val buildProjection = newMutableProjection(projectList,
child.output)
+ private def buildProjection = newMutableProjection(projectList,
child.output)
- protected override def doExecute(): RDD[InternalRow] =
child.execute().mapPartitions { iter =>
- val reusableProjection = buildProjection()
- iter.map(reusableProjection)
+ protected override def doExecute(): RDD[InternalRow] = {
+ // Use local variable to avoid referencing to $out inside closure
--- End diff --
Though is this even a hot code path? The only reason why we do it in
`DataSourceStrategy` is because we call `mapPartitions` once for each data
partition there is (could be O(1000)). IIUC this is only called once or twice
per query. Is that correct @yhuai? If so I'm not sure if the optimization from
`DataSourceStrategy` is worth doing here.
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