cloud-fan commented on code in PR #58656:
URL: https://github.com/apache/spark/pull/58656#discussion_r4057052748
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/subquery.scala:
##########
@@ -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:
**Nit (P3):** The code-formatted configuration name is missing its
`.enabled` suffix. The registered key is
`spark.sql.optimizer.decorrelatePredicateSubqueriesInJoinPredicate.enabled`;
please use that exact name here.
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/subquery.scala:
##########
@@ -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`
+ * disabled.
+ *
+ * An existence join yields only whether a row matched, so its `exists`
attribute cannot tell
+ * FALSE from unknown, while `IN` is three-valued. The two are
indistinguishable while the value
+ * only feeds a predicate, which is what a hoisted condition normally does,
but not when it
+ * reaches something else, e.g. `(c1 IN (SELECT col1 FROM t3)) <=> false`,
which is FALSE for a
+ * NULL that matches nothing and TRUE for the `exists` attribute. An IN
sub-query whose row
+ * comparison can evaluate to unknown is therefore rejected in that position
rather than
+ * rewritten. NOT IN is rewritten with a null-aware join condition of its
own, which is equally
+ * two-valued, so it is rejected there too.
+ *
+ * Returns the rewritten condition along with the updated outer and
sub-query plans.
+ */
+ private def rewriteExistentialExprInJoinCondition(
+ conditions: Seq[Expression],
+ outerPlan: LogicalPlan,
+ subPlan: LogicalPlan): (Option[Expression], LogicalPlan, LogicalPlan) = {
+ val (subCond, newSubPlan) =
+ rewriteExistentialExprInSubqueryPlan(conditions, outerPlan, subPlan)
+ // The sub-queries that do not reference the sub-query plan are rewritten
against the outer
+ // plan, as they only reference attributes of the outer plan, if any.
+ val (newCond, newOuterPlan, _) = rewriteExistentialExprWithAttrs(
+ subCond.toSeq, outerPlan, e => !referencesPlan(e, subPlan))
+ (newCond, newOuterPlan, newSubPlan)
+ }
+
+ /**
+ * Rewrites the existential sub-queries in `conditions` that can only be
evaluated by the
+ * sub-query plan, that is those referencing the sub-query plan but not the
outer plan, into
+ * existence joins on top of the sub-query plan. See
+ * [[rewriteExistentialExprInJoinCondition]] for details.
+ *
+ * Returns the rewritten condition along with the updated sub-query plan.
+ */
+ private def rewriteExistentialExprInSubqueryPlan(
+ conditions: Seq[Expression],
+ outerPlan: LogicalPlan,
+ subPlan: LogicalPlan): (Option[Expression], LogicalPlan) = {
+ // A sub-query left in the join condition loses its own join condition
when it is planned
+ // there, so a correlated one would silently return a wrong result: reject
it instead. Note
+ // that this walks the whole expression, including the join condition of a
sub-query that the
+ // rewrite below declines to descend into. That is deliberate: a
correlated sub-query hidden
+ // under a declined one would equally be planned without its join
condition, or reach
+ // execution unevaluable, so it must be rejected even though nothing would
have rewritten it.
+ val referencingBothPlans = conditions.flatMap(_.collect {
+ case sq @ (_: Exists | _: InSubquery)
+ if isCorrelatedSubquery(sq) && referencesPlan(sq, subPlan) &&
Review Comment:
**Non-blocking (P2):** `listQuery.isCorrelated` is based on retained
`outerAttrs`, not the surviving pulled-up condition.
`PullupCorrelatedPredicates` deliberately keeps wrapper state for idempotency,
so a query such as `a = c1 OR a IN (SELECT col1 FROM t3 WHERE false AND col1 =
c1)` reaches this guard with no effective nested correlation but still has
`outerAttrs = c1`; this branch then rejects the valid, effectively uncorrelated
IN as referencing both plans. Please classify correlation from the surviving
condition and add this simplification case to the regression tests, while
preserving rejection of the genuinely correlated shape.
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