Github user sarutak commented on a diff in the pull request:
https://github.com/apache/spark/pull/14719#discussion_r78190424
--- Diff: sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
---
@@ -1580,6 +1583,28 @@ class DataFrameSuite extends QueryTest with
SharedSQLContext {
assert(df.persist.take(1).apply(0).toSeq(100).asInstanceOf[Long] ==
100)
}
+ test("""SPARK-17154: df("column_name") should return correct result when
we do self-join""") {
--- End diff --
Yeah, direct-self-join (means both child Datasets are same) is still
ambiguous.
In this case, `df("colmn-name")` will refers to a Dataset of the right
side in the proposed implementation.
I'm wondering a direct-self-join like df.join(df, <condition-exprs>,
<join-type>) is similar to a query like as follows.
SELECT ... FROM my_table df join my_table df on <condition>;
Those queries should not be valid so I also think we shouldn't allow users
to join two same Datasets and warn to duplicate the Dataset if they intend to
do direct-self-join.
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