sigmod commented on a change in pull request #32060:
URL: https://github.com/apache/spark/pull/32060#discussion_r608486639
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File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/QueryPlan.scala
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@@ -80,28 +105,57 @@ abstract class QueryPlan[PlanType <: QueryPlan[PlanType]]
* transformExpressionsDown or transformExpressionsUp should be used.
*
* @param rule the rule to be applied to every expression in this operator.
+ * @param cond a Lambda expression to prune tree traversals. If
`cond.apply` returns false
+ * on an expression T, skips processing T and its subtree;
otherwise, processes
+ * T and its subtree recursively.
+ * @param ruleId is a unique Id for `rule` to prune unnecessary tree
traversals. When it is
+ * RuleId.UnknownId, no pruning happens. Otherwise, if `rule`(with id
`ruleId`) has been
+ * marked as in effective on an expression T, skips processing T and
its subtree. Do not
+ * pass it if the rule is not purely functional and reads a varying
initial state for
+ * different invocations.
*/
- def transformExpressions(rule: PartialFunction[Expression, Expression]):
this.type = {
- transformExpressionsDown(rule)
+ def transformExpressions(rule: PartialFunction[Expression, Expression],
+ cond: TreePatternBits => Boolean = AlwaysProcess.fn,
+ ruleId: Int = RuleIdCollection.UnknownId): this.type = {
Review comment:
Yes, that's definitely a better approach -- if I implement it from
scratch, I'd do that way.
However, I don't have a good idea to get existing code like "plan transform
{...}" compile if change "rule: PartialFunction" to "rule: Rule". If we change
every call sites of transform, the PR might go too large.
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