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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-22980) Using pandas_udf when inputs are not Pandas's Series or DataFrame
Date Thu, 11 Jan 2018 15:51:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-22980?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-22980:
------------------------------------

    Assignee:     (was: Apache Spark)

> Using pandas_udf when inputs are not Pandas's Series or DataFrame
> -----------------------------------------------------------------
>
>                 Key: SPARK-22980
>                 URL: https://issues.apache.org/jira/browse/SPARK-22980
>             Project: Spark
>          Issue Type: Sub-task
>          Components: PySpark
>    Affects Versions: 2.3.0
>            Reporter: Xiao Li
>
> {noformat}
> from pyspark.sql.functions import pandas_udf
> from pyspark.sql.functions import col, lit
> from pyspark.sql.types import LongType
> df = spark.range(3)
> f = pandas_udf(lambda x, y: len(x) + y, LongType())
> df.select(f(lit('text'), col('id'))).show()
> {noformat}
> {noformat}
> from pyspark.sql.functions import udf
> from pyspark.sql.functions import col, lit
> from pyspark.sql.types import LongType
> df = spark.range(3)
> f = udf(lambda x, y: len(x) + y, LongType())
> df.select(f(lit('text'), col('id'))).show()
> {noformat}
> The results of pandas_udf are different from udf. 



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