gagafunctor commented on a change in pull request #23983: [SPARK-26881][core]
Heuristic for tree aggregate depth
URL: https://github.com/apache/spark/pull/23983#discussion_r263817158
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File path: core/src/main/scala/org/apache/spark/rdd/RDD.scala
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@@ -1178,6 +1178,37 @@ abstract class RDD[T: ClassTag](
}
}
+ /**
+ * 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
+ * @param numPartitions the number of partitions for which to aggregate
partial results
+ * @param maxDriverResultSizeInMb the value of the parameter
spark.driver.maxResultSize in MB
+ */
+ def getTreeAggregateIdealDepth(
+ aggregatedObjectSizeInMb: Int,
+ numPartitions: Int = getNumPartitions,
+ maxDriverResultSizeInMb: Int = Utils.memoryStringToMb(
+ context.getConf.get("spark.driver.maxResultSize"))): Int = {
Review comment:
So,playing in UTests with different ways to play with this config field made
me realize something...
I tried the following:
*conf.set(""spark.driver.maxResultSize", "10g")* Then I get:
- *conf.get(MAX_RESULT_SIZE)* returns 10737418240 -> it's in Bytes
- *Utils.memoryStringToMb(conf.get("spark.driver.maxResultSize"))* returns
10240 -> It's in megabytes
So the units are as expected, but the results are a bit different from each
other...
-> I'm not sure what's the best way to get the maxResultSize in Mb from code
here:
- Utils.memoryStringToMb(conf.get("spark.driver.maxResultSize"))
OR
- conf.get(MAX_RESULT_SIZE) / (1000L * 1000L * 1000L)
??
(Knowing that these might yield slightly different results, but I don't know
if it's a big deal)
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