GitHub user lw-lin opened a pull request: https://github.com/apache/spark/pull/14298
[SPARK-16283][SQL] Implement `percentile_approx` SQL function ## What changes were proposed in this pull request? This patch Implements `percentile_approx` SQL function using Spark's implementation of G-K algorithm. - commit 1: moves the G-K algorithm implementation(`QuantileSummaries` and related tests) from `sql/core` to `sql/catalyst` - commit 2: implements `percentile_approx` using G-K algorithm ## How was this patch tested? - Jenkins - added new tests You can merge this pull request into a Git repository by running: $ git pull https://github.com/lw-lin/spark impl_percentile_approx Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/14298.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 #14298 ---- commit d3a6dc825577a4a5e44e8eb0f8e61ef2053e127d Author: Liwei Lin <lwl...@gmail.com> Date: 2016-07-21T08:29:00Z Move G-K all from `sql/core` to `sql/catalyst` commit 110158062cb1f6a571ad8e0bab9bc5962107b59a Author: Liwei Lin <lwl...@gmail.com> Date: 2016-07-21T08:38:06Z Implement percentile_approx ---- --- 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