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Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/22326 late LGTM --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user xuanyuanking commented on the issue: https://github.com/apache/spark/pull/22326 Thanks everyone for your review and advise. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/22326 LGTM except some unnecessary end-to-end tests. +1 for @mgaido91 's idea about unit test, something like the test suites under `org.apache.spark.sql.catalyst.optimizer`. I'm ok to do it in a followup, since it will be the first UT for python rules. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user dilipbiswal commented on the issue: https://github.com/apache/spark/pull/22326 Does it make sense to have a test case where the PythonUDF referencing attributes from both legs of join in disjunction with a regular predicate ? i.e joinCond = pythonUDF(leftattr, rightattr) || leftattr > 5 .. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user xuanyuanking commented on the issue: https://github.com/apache/spark/pull/22326 ``` move this rule to optimizer, as the last batch (but before the UpdateAttributeReferences batch). Since we apply this rule after filter pushdown, we can simply pull out any python udf in join condition. Also add this rule to Optimizer.nonExcludableRules, since this is a special optimizer rule that can't be turned off. ``` Make sense, implement like this can also avoid breaking the assumption in Dataset.join of Join plan only return Join after analysis. I'll reimplement as this proposal soon. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/22326 Some thoughts: 1. This rule is a little tricky as it only handles python udf accessing attributes from both side. If it only accesses one side, we assume it can be pushed down later. Generally we should not depend on optimizer rules in an analyzer rule. My proposal is: move this rule to optimizer, as the last batch (but before the `UpdateAttributeReferences` batch). Since we apply this rule after filter pushdown, we can simply pull out any python udf in join condition. Also add this rule to `Optimizer.nonExcludableRules`, since this is a special optimizer rule that can't be turned off. 2. About cross join. I think we don't need to take care of it. My only concern is we have to keep the behavior same as before. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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