maropu commented on a change in pull request #32494:
URL: https://github.com/apache/spark/pull/32494#discussion_r633516953
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/statsEstimation/UnionEstimation.scala
##########
@@ -70,8 +70,20 @@ object UnionEstimation {
None
}
- val unionOutput = union.output
+ val (attrToComputeMinMaxStats, attrToComputeNullCount) =
getAttributeToComputeStats(union)
+ val attrStatsWithMinMax = computeMinMaxAttributeStatsMap(union,
attrToComputeMinMaxStats)
+ val newAttrStats = updateAttributeStatsMapWithNullCount(union,
attrStatsWithMinMax,
+ attrToComputeNullCount)
+
+ Some(
+ Statistics(
+ sizeInBytes = sizeInBytes,
+ rowCount = outputRows,
+ attributeStats = newAttrStats))
+ }
+ private def getAttributeToComputeStats(union: Union) = {
Review comment:
We need this method? I think its okay to check if we need to update
stats or not in the `computeMinMaxAttributeStatsMap` and
`updateAttributeStatsMapWithNullCount` sides. How about organizing the
`estimate` method like this?
```
def estimate(union: Union).... = {
...
val newMinMaxStats = computeNewMinMaxStats(union)
val newNullCountStats = computeNewNullCountStats(union)
val newAttrStats = (builds a new stats from `newMinMaxStats` and
`newNullCountStats`)
Some(
Statistics(...
```
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