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https://issues.apache.org/jira/browse/SPARK-19573?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15879387#comment-15879387
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Timothy Hunter commented on SPARK-19573:
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I do not have too strong an opinion, as long as:
1. we are consistent within Spark, or
2. we follow the standard for numerical stuff (IEEE-754)
I am not sure what the standard is for SQL, though.
> Make NaN/null handling consistent in approxQuantile
> ---------------------------------------------------
>
> Key: SPARK-19573
> URL: https://issues.apache.org/jira/browse/SPARK-19573
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.2.0
> Reporter: zhengruifeng
>
> As discussed in https://github.com/apache/spark/pull/16776, this jira is used
> to track the following issue:
> Multi-column version of approxQuantile drop the rows containing *any*
> NaN/null, the results are not consistent with outputs of the single-version.
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