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https://issues.apache.org/jira/browse/SPARK-26589?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17451283#comment-17451283
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Nicholas Chammas edited comment on SPARK-26589 at 11/30/21, 6:17 PM:
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I think there is a potential solution using the algorithm [described here by
Michael
Harris|https://www.quora.com/Distributed-Algorithms/What-is-the-distributed-algorithm-to-determine-the-median-of-arrays-of-integers-located-on-different-computers].
was (Author: nchammas):
I'm going to try to implement this using the algorithm [described here by
Michael
Harris|https://www.quora.com/Distributed-Algorithms/What-is-the-distributed-algorithm-to-determine-the-median-of-arrays-of-integers-located-on-different-computers].
> 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: 3.1.0
> 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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