karenfeng commented on a change in pull request #29925:
URL: https://github.com/apache/spark/pull/29925#discussion_r498460591
##########
File path:
mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
##########
@@ -786,11 +786,15 @@ class RowMatrix @Since("1.0.0") (
* Based on the formulae: (numPartitions)^(1/depth) * objectSize <=
DriverMaxResultSize
* @param aggregatedObjectSizeInBytes the size, in megabytes, of the object
being tree aggregated
*/
- private[spark] def getTreeAggregateIdealDepth(aggregatedObjectSizeInBytes:
Long) = {
+ private[spark] def getTreeAggregateIdealDepth(aggregatedObjectSizeInBytes:
Long): Int = {
require(aggregatedObjectSizeInBytes > 0,
"Cannot compute aggregate depth heuristic based on a zero-size object to
aggregate")
val maxDriverResultSizeInBytes = rows.conf.get[Long](MAX_RESULT_SIZE)
+ if (maxDriverResultSizeInBytes == 0) {
+ // Unlimited result size, so 1 is OK
+ return 1
Review comment:
Out of curiosity, why is this 1 given that the default argument for
depth in `rdd.treeAggregate` is
[2](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/rdd/RDD.scala#L1131)?
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