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Posted to issues@spark.apache.org by "Li Jin (JIRA)" <ji...@apache.org> on 2018/06/13 18:14:00 UTC
[jira] [Commented] (SPARK-22239) User-defined window functions with
pandas udf
[ https://issues.apache.org/jira/browse/SPARK-22239?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16511495#comment-16511495 ]
Li Jin commented on SPARK-22239:
--------------------------------
[~hyukjin.kwon] I actually don't think this Jira is done. The PR only resolves the unbounded window case, do you mind if I edit the Jira to reflect what's done and create a new Jira for rolling window case?
> User-defined window functions with pandas udf
> ---------------------------------------------
>
> Key: SPARK-22239
> URL: https://issues.apache.org/jira/browse/SPARK-22239
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark
> Affects Versions: 2.2.0
> Environment:
> Reporter: Li Jin
> Assignee: Li Jin
> Priority: Major
> Fix For: 2.4.0
>
>
> Window function is another place we can benefit from vectored udf and add another useful function to the pandas_udf suite.
> Example usage (preliminary):
> {code:java}
> w = Window.partitionBy('id').orderBy('time').rangeBetween(-200, 0)
> @pandas_udf(DoubleType())
> def ema(v1):
> return v1.ewm(alpha=0.5).mean().iloc[-1]
> df.withColumn('v1_ema', ema(df.v1).over(window))
> {code}
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