[GitHub] spark issue #19424: [SPARK-22197][SQL] push down operators to data source be...
Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/19424 thanks for review, merging to master! --- - 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 viirya commented on the issue: https://github.com/apache/spark/pull/19424 LGTM with minor comments. --- - 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 gatorsmile commented on the issue: https://github.com/apache/spark/pull/19424 I think the current PR is good enough to merge. Later, we still continue improving the Data source API v2. LGTM pending Jenkins. --- - 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/19424 @rdblue we assume the previous batches should push down operators as close to data source relations as possible. One special case is column pruning. The `ColumnPruning` rule tries to generate a new `Project` node under every node that has more input columns than it references, which means it will also generate a `Project` under `Filter`, and this conflicts with `PushDownPredicate` rule. Currently the conflict is resolved by a hacky way so there are cases `Project` under `Filter`. --- - 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 rdblue commented on the issue: https://github.com/apache/spark/pull/19424 What are the guarantees made by the previous batches in the optimizer? The work done by `FilterAndProject` seems redundant to me because the optimizer should already push filters below projection. Is that not guaranteed by the time this runs? --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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