viirya commented on a change in pull request #28560:
URL: https://github.com/apache/spark/pull/28560#discussion_r426391779
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/NestedColumnAliasing.scala
##########
@@ -68,10 +76,23 @@ object NestedColumnAliasing {
*/
def replaceChildrenWithAliases(
plan: LogicalPlan,
+ nestedFieldToAlias: Map[ExtractValue, Alias],
attrToAliases: Map[ExprId, Seq[Alias]]): LogicalPlan = {
plan.withNewChildren(plan.children.map { plan =>
Project(plan.output.flatMap(a => attrToAliases.getOrElse(a.exprId,
Seq(a))), plan)
- })
+ }).transformExpressions {
+ case f: ExtractValue if nestedFieldToAlias.contains(f) =>
+ nestedFieldToAlias(f).toAttribute
+ }
+ }
+
+ /**
+ * Returns true for those operators that we can prune nested column on it.
+ */
+ private def canPruneOn(plan: LogicalPlan) = plan match {
+ case _: Aggregate => true
+ case _: Expand => true
+ case _ => false
Review comment:
I think I was wrong. Re-checking `FlatMapGroupsInPandas`'s Python API,
it looks like
```python
df.groupby("id").apply(normalize).show()
```
So basically the python udf takes no nested column selection but a full
columns of DataFrame. It doesn't do nested column pruning.
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