GitHub user gatorsmile opened a pull request: https://github.com/apache/spark/pull/16762
[SPARK-19419] [SPARK-19420] Fix the cross join detection ### What changes were proposed in this pull request? There are two issues in the existing detection of cartesian products. 1) When users use the outer joins where both sides of the tables are unable to be broadcasted, Spark will still select `BroadcastNestedLoopJoin`. CROSS JOIN syntax is unable to cover the scenario of outer join, but we still issue the following error message: ``` Use the CROSS JOIN syntax to allow cartesian products between these relations ``` 2) The existing detection is unable to cover all the cartesian product cases. For example, - Case 1) having non-equal predicates in join conditiions of an inner join. - Case 2) equi-join's key columns are not sortable and both sides are not small enough for broadcasting. This PR is to move the cross-join detection back to `BroadcastNestedLoopJoinExec` and `CartesianProductExec`. ### How was this patch tested? Added the extra test cases. You can merge this pull request into a Git repository by running: $ git pull https://github.com/gatorsmile/spark crossJoin Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/16762.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #16762 ---- commit e4e3c9b84993ca415a1d07bcb07f20393c6fd5b4 Author: gatorsmile <gatorsm...@gmail.com> Date: 2017-02-01T05:47:04Z fix. ---- --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org