[jira] [Updated] (SPARK-26589) proper `median` method for spark dataframe

["Sean Owen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-26589?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen updated SPARK-26589:
------------------------------
    Priority: Minor  (was: Major)

Would you like to implement it? It's kind of DIY here. It's not crazy to add, but indeed, how would you do efficiently it at scale?

> proper `median` method for spark dataframe
> ------------------------------------------
>
>                 Key: SPARK-26589
>                 URL: https://issues.apache.org/jira/browse/SPARK-26589
>             Project: Spark
>          Issue Type: New Feature
>          Components: SQL
>    Affects Versions: 2.4.0
>            Reporter: Jan Gorecki
>            Priority: Minor
>
> I found multiple tickets asking for median function to be implemented in Spark. Most of those tickets links to "SPARK-6761 Approximate quantile" as duplicate of it. The thing is that approximate quantile is a workaround for lack of median function. Thus I am filling this Feature Request for proper, exact, not approximation of, median function. I am aware about difficulties that are caused by distributed environment when trying to compute median, nevertheless I don't think those difficulties is reason good enough to drop out `median` function from scope of Spark. I am not asking about efficient median but exact median.



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