pratham76 commented on code in PR #58656:
URL: https://github.com/apache/spark/pull/58656#discussion_r4066008156
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/subquery.scala:
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@@ -450,10 +471,171 @@ object RewritePredicateSubquery extends
Rule[LogicalPlan] with PredicateHelper {
ExistenceJoin(exists), newConditions, joinHint)
introducedAttrs += exists
exists
+ // A sub-query that `canRewrite` declined is left as it is, children
included.
+ case sq @ (_: Exists | Not(_: InSubquery) | _: InSubquery) => sq
+ case other => other.mapChildren(rewrite)
}
}
+ val newExprs = exprs.map(rewrite)
(newExprs.reduceOption(And), newPlan, introducedAttrs.toSeq)
}
+
+ /**
+ * Returns true if `e` references any of the attributes produced by `plan`.
+ */
+ private def referencesPlan(e: Expression, plan: LogicalPlan): Boolean = {
+ e.references.intersect(plan.outputSet).nonEmpty
+ }
+
+ /**
+ * Rewrites the existential sub-queries that are nested in the correlated
predicates which
+ * [[PullupCorrelatedPredicates]] hoisted out of a predicate sub-query, and
which therefore end
+ * up in the condition of the semi/anti join that replaces that sub-query.
+ *
+ * A hoisted predicate can carry a nested existential sub-query out of the
sub-query plan,
+ * because a correlated predicate is hoisted as a whole when it is a
disjunction. For example
+ *
+ * SELECT * FROM t1 WHERE EXISTS (
+ * SELECT 1 FROM t2 WHERE t1.a = t2.c1 OR t2.c1 IN (SELECT col1 FROM t3))
+ *
+ * hoists `a = c1 OR c1 IN (SELECT col1 FROM t3)` into the join condition.
Such a nested
+ * sub-query must be rewritten against the plan that produces the attributes
it references:
+ * the one above references `c1`, which is produced by the sub-query plan
and not by the outer
+ * plan, so its existence join has to be built on top of the sub-query plan.
Building it on top
+ * of the outer plan instead yields a join whose condition references an
attribute that neither
+ * of its children can produce (SPARK-59351).
+ *
+ * A nested sub-query that references both plans can be rewritten into an
existence join on
+ * neither side, so it is left in the join condition, where both plans are
in scope. Leaving it
+ * there is only correct while it is uncorrelated: the join condition of a
correlated one is
+ * dropped when it is planned as an in-subquery filter, which would silently
change the result,
+ * so a correlated one is reported as unsupported instead. Note that such a
sub-query can be
+ * correlated only to the sub-query plan, as being correlated to the outer
plan as well would
+ * require two levels of correlation, which the Analyzer rejects.
+ *
+ * A sub-query left here is further subject to the rewrite of predicate
sub-queries in join
+ * conditions, which rejects one referencing both plans under the default
configuration; it
+ * survives only with
`spark.sql.optimizer.decorrelatePredicateSubqueriesInJoinPredicate`
Review Comment:
Thanks for pointing it out, just noted that one commit was missed, just
pushed
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