tanelk opened a new pull request #31772:
URL: https://github.com/apache/spark/pull/31772
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### What changes were proposed in this pull request?
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Added physical optimization rule `PushDownAggregates`.
### Why are the changes needed?
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A common pattern I have encountered
```
dataset
.groupBy(col("a"), col("b")).count()
.groupBy(col("a")).agg(max("count"))
.explain();
```
Produces a plan:
```
*(3) HashAggregate(keys=[a#53], functions=[max(count#119L)])
+- Exchange hashpartitioning(a#53, 1), ENSURE_REQUIREMENTS, [id=#98]
+- *(2) HashAggregate(keys=[a#53], functions=[partial_max(count#119L)])
+- *(2) HashAggregate(keys=[a#53, b#52], functions=[count(1)])
+- Exchange hashpartitioning(a#53, b#52, 1), ENSURE_REQUIREMENTS,
[id=#93]
+- *(1) HashAggregate(keys=[a#53, b#52],
functions=[partial_count(1)])
+- FileScan parquet
```
In most cases the second exchange could be avoided if the first exchange
partitioned only by column `a` - reducing the total amount of data exchanged.
Spark can not do this optimization on its own, because `a` could have low
cardinality (less than the number of executors) or high skew. But if the user
knows, that this is not the case, they could manually repartition it:
```
dataset
.repartition(col("a"))
.groupBy(col("a"), col("b")).count()
.groupBy(col("a")).agg(max("count"))
.explain();
```
This produces this plan:
```
*(2) HashAggregate(keys=[a#53], functions=[max(count#119L)])
+- *(2) HashAggregate(keys=[a#53], functions=[partial_max(count#119L)])
+- *(2) HashAggregate(keys=[a#53, b#52], functions=[count(1)])
+- *(2) HashAggregate(keys=[a#53, b#52], functions=[partial_count(1)])
+- Exchange hashpartitioning(a#53, 1), REPARTITION, [id=#90]
+- FileScan parquet
```
We have avoided one exchange and this has had positive performance impact on
my queries. But this could be improved further, if the first partial aggregate
would be before the manually inserted repartition - reducing the exchanged data
even more. The proposed rule would push that partial aggregate bellow the
exchange.
### Does this PR introduce _any_ user-facing change?
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A configuration parameter to disable this optimization.
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