gagafunctor commented on a change in pull request #23983: [SPARK-26881][mllib]
Heuristic for tree aggregate depth
URL: https://github.com/apache/spark/pull/23983#discussion_r267349002
##########
File path:
mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
##########
@@ -775,6 +778,27 @@ class RowMatrix @Since("1.0.0") (
s"The number of rows $m is different from what specified or previously
computed: ${nRows}.")
}
}
+
+ /**
+ * Computing desired tree aggregate depth necessary to avoid exceeding
+ * driver.MaxResultSize during aggregation.
+ * Based on the formulae: (numPartitions)^(1/depth) * objectSize <=
DriverMaxResultSize
+ * @param aggregatedObjectSizeInMb the size, in megabytes, of the object
being tree aggregated
+ */
+ private[spark] def getTreeAggregateIdealDepth(aggregatedObjectSizeInMb: Int)
= {
+ val maxDriverResultSizeInMb = rows.conf.get[Long](MAX_RESULT_SIZE) / (1024
* 1024)
Review comment:
I added max depth capping, and changed unit for memory sizes (Mb -> Bytes).
Thing is it made me change the API (Int -> Long), as size in Bytes might be
too big for Int (cf gramian size = nt * 8, with nt potentially already being a
big Int).
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