Github user GraceH commented on a diff in the pull request:
https://github.com/apache/spark/pull/8128#discussion_r37046803
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/basicOperators.scala ---
@@ -224,6 +225,56 @@ case class Limit(limit: Int, child: SparkPlan)
/**
* :: DeveloperApi ::
+ * Take the first limit elements. and the limit can be any number less
than Integer.MAX_VALUE.
+ * If it is terminal and is invoked using executeCollect, it probably
cause OOM if the
+ * records number is large enough. Not like the Limit clause, this
operator will not change
+ * any partitions of its child operator.
+ */
+@DeveloperApi
+case class LargeLimit(limit: Int, child: SparkPlan)
+ extends UnaryNode {
+ /** We must copy rows when sort based shuffle is on */
+ private def sortBasedShuffleOn =
SparkEnv.get.shuffleManager.isInstanceOf[SortShuffleManager]
+
+ override def output: Seq[Attribute] = child.output
+
+ override def executeCollect(): Array[Row] = child.executeTake(limit)
+
+ protected override def doExecute(): RDD[InternalRow] = {
+ val rdd = if (sortBasedShuffleOn) {
+ child.execute().map(_.copy()).persist(StorageLevel.MEMORY_AND_DISK)
+ } else {
+ child.execute().persist(StorageLevel.MEMORY_AND_DISK)
+ }
+
+ // We assume the maximize record number in a partition is less than
Integer.MAX_VALUE
+ val partitionRecordCounts = rdd.mapPartitions({ iterator =>
+ Iterator(iterator.count(_ => true))
+ }, true).collect()
+
+ var totalSize = 0
+ // how many records we have to take from each partition
+ val requiredRecordCounts = partitionRecordCounts.map { count =>
--- End diff --
just minor suggestion.
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