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From "Li Jin (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-22239) User-defined window functions with pandas udf (unbounded window)
Date Thu, 14 Jun 2018 13:55:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-22239?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Li Jin updated SPARK-22239:
---------------------------
    Summary: User-defined window functions with pandas udf (unbounded window)  (was: User-defined
window functions with pandas udf)

> User-defined window functions with pandas udf (unbounded window)
> ----------------------------------------------------------------
>
>                 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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