mgaido91 commented on a change in pull request #24442: [SPARK-27547][SQL] fix
DataFrame self-join problems
URL: https://github.com/apache/spark/pull/24442#discussion_r278034421
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File path: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
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@@ -876,7 +885,30 @@ class Dataset[T] private[sql](
* @since 2.0.0
*/
def join(right: Dataset[_]): DataFrame = withPlan {
- Join(logicalPlan, right.logicalPlan, joinType = Inner, None, JoinHint.NONE)
+ val (joinLeft, joinRight) = prepareJoinPlan(this, right)
+ Join(joinLeft, joinRight, joinType = Inner, None, JoinHint.NONE)
+ }
+
+ // Called by `Dataset#join`, to attach the Dataset id to the logical plan,
so that we
+ // can resolve column reference correctly later. See
`ResolveDatasetColumnReference`.
+ private def createPlanWithDatasetId(): LogicalPlan = {
+ if
(!sparkSession.sessionState.conf.getConf(SQLConf.RESOLVE_DATASET_COLUMN_REFERENCE))
{
+ return logicalPlan
+ }
+
+ // The alias should start with `SubqueryAlias.HIDDEN_ALIAS_PREFIX`, so
that `SubqueryAlias` can
+ // recognize it and keep the output qualifiers unchanged.
+
SubqueryAlias(s"${SubqueryAlias.HIDDEN_ALIAS_PREFIX}${Dataset.ID_PREFIX}_$id",
logicalPlan)
Review comment:
I think that could be an option. And for the moment we could add it only to
the child/children of a join since we only need it there. But I see there is no
guarantee that the plan(s) are not replaces/removed during the
analysis/optimization phase, so it may not be doable indeed.
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