maropu commented on a change in pull request #28804:
URL: https://github.com/apache/spark/pull/28804#discussion_r447512443
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File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
##########
@@ -2196,6 +2196,13 @@ object SQLConf {
.checkValue(bit => bit >= 10 && bit <= 30, "The bit value must be in
[10, 30].")
.createWithDefault(16)
+ val SKIP_PARTIAL_AGGREGATE_ENABLED =
+ buildConf("spark.sql.aggregate.partialaggregate.skip.enabled")
+ .internal()
+ .doc("Avoid sort/spill to disk during partial aggregation")
+ .booleanConf
+ .createWithDefault(true)
Review comment:
> They turn off map side aggregate (i.e., partial aggregate will be
pass through) in Physical operator (i.e., Group-By operator) if map-side
aggregation reduce the entries by at least half and they look at 100000 rows to
do that
Looks whether that approach improves performance depends on IO performance,
but looks interesting to me. WDYT? @cloud-fan
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