Github user yhuai commented on a diff in the pull request:
https://github.com/apache/spark/pull/8038#discussion_r36562104
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/TungstenAggregate.scala
---
@@ -61,32 +62,54 @@ case class TungstenAggregate(
}
protected override def doExecute(): RDD[InternalRow] = attachTree(this,
"execute") {
- child.execute().mapPartitions { iter =>
- val hasInput = iter.hasNext
- if (!hasInput && groupingExpressions.nonEmpty) {
- // This is a grouped aggregate and the input iterator is empty,
- // so return an empty iterator.
- Iterator.empty.asInstanceOf[Iterator[UnsafeRow]]
- } else {
- val aggregationIterator =
- new TungstenAggregationIterator(
- groupingExpressions,
- nonCompleteAggregateExpressions,
- completeAggregateExpressions,
- initialInputBufferOffset,
- resultExpressions,
- newMutableProjection,
- child.output,
- iter.asInstanceOf[Iterator[UnsafeRow]],
- testFallbackStartsAt)
- if (!hasInput && groupingExpressions.isEmpty) {
+ /**
+ * Set up the underlying unsafe data structures used before computing
the parent partition.
+ * This makes sure our iterator is not starved by other operators in
the same task.
+ */
+ def preparePartition(): TungstenAggregationIterator = {
+ new TungstenAggregationIterator(
+ groupingExpressions,
+ nonCompleteAggregateExpressions,
+ completeAggregateExpressions,
+ initialInputBufferOffset,
+ resultExpressions,
+ newMutableProjection,
+ child.output,
+ testFallbackStartsAt)
--- End diff --
What will happen if there is no memory space left to reserve?
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