[GitHub] spark pull request #17392: [SPARK-20008] [SQL] DISTINCT and EXCEPT Support o...

[gatorsmile]

Github user gatorsmile closed the pull request at:

https://github.com/apache/spark/pull/17392


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[GitHub] spark pull request #17392: [SPARK-20008] [SQL] DISTINCT and EXCEPT Support o...

[gatorsmile]

Github user gatorsmile commented on a diff in the pull request:

https://github.com/apache/spark/pull/17392#discussion_r107569402
  
--- Diff: 
sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/ObjectHashAggregateExec.scala
 ---
@@ -147,9 +147,13 @@ case class ObjectHashAggregateExec(
 
 object ObjectHashAggregateExec {
   def supportsAggregate(aggregateExpressions: Seq[AggregateExpression]): 
Boolean = {
-aggregateExpressions.map(_.aggregateFunction).exists {
-  case _: TypedImperativeAggregate[_] => true
-  case _ => false
+if (aggregateExpressions.isEmpty) {
+  false
--- End diff --

not needed.


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[GitHub] spark pull request #17392: [SPARK-20008] [SQL] DISTINCT and EXCEPT Support o...

[gatorsmile]

GitHub user gatorsmile opened a pull request:

https://github.com/apache/spark/pull/17392

[SPARK-20008] [SQL] DISTINCT and EXCEPT Support on DataFrame with Zero 
Columns

### What changes were proposed in this pull request?
So far, our aggregate does not consider the input with zero column. This PR 
is to fix the issue. 

After the fix, both `DISTINCT` and `EXCEPT` can correctly behave when the 
DataFrame has zero column.

### How was this patch tested?
Added test cases to check both in different scenarios.

You can merge this pull request into a Git repository by running:

$ git pull https://github.com/gatorsmile/spark emptyDF

Alternatively you can review and apply these changes as the patch at:

https://github.com/apache/spark/pull/17392.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

This closes #17392


commit c0c821f9056debf9385708d0cc0a0517261a5b7b
Author: Xiao Li 
Date:   2017-03-23T00:04:48Z

fix.




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