Github user maropu commented on the issue:
https://github.com/apache/spark/pull/14876
I found that we need to push-down partial aggregation below exchange
operators instead of merging them? For example, in the spark v2.0 branch,
```
(0 to 1000).map(x => (x % 2, x.toString)).toDF("a",
"b").repartition($"a").createOrReplaceTempView("t")
spark.sql("select max(b) from t group by a").explain
```
This prints like:
```
== Physical Plan ==
SortAggregate(key=[a#5], functions=[max(b#6)], output=[max(b)#20])
+- SortAggregate(key=[a#5], functions=[partial_max(b#6)],
output=[a#5,max#22])
+- *Sort [a#5 ASC], false, 0
+- Exchange hashpartitioning(a#5, 4)
+- LocalTableScan [a#5, b#6]
```
In this case, I think it is more natural to push-down the partial
aggregation below the exchange.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
