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https://issues.apache.org/jira/browse/SPARK-22239?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Li Jin updated SPARK-22239:
---------------------------
Description:
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').rowsBetween(Window.unbounedPreceding,
Window.unbounedFollowing)
@pandas_udf(DoubleType())
def mean_udf(v):
return v.mean()
df.withColumn('v_mean', mean_udf(df.v1).over(window))
{code}
was:
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}
> 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').rowsBetween(Window.unbounedPreceding,
> Window.unbounedFollowing)
> @pandas_udf(DoubleType())
> def mean_udf(v):
> return v.mean()
> df.withColumn('v_mean', mean_udf(df.v1).over(window))
> {code}
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