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https://issues.apache.org/jira/browse/SPARK-26589?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17451936#comment-17451936
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Nicholas Chammas commented on SPARK-26589:
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Just for reference, Stack Overflow provides evidence that a proper median
function has been in high demand for some time:
* [How can I calculate exact median with Apache
Spark?|https://stackoverflow.com/q/28158729/877069] (14K views)
* [How to find median and quantiles using
Spark|https://stackoverflow.com/q/31432843/877069] (117K views)
* [Median / quantiles within PySpark
groupBy|https://stackoverflow.com/q/46845672/877069] (67K views)
> 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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