[jira] [Resolved] (SPARK-22980) Using pandas_udf when inputs are not Pandas's Series or DataFrame

2018-01-17 Thread Hyukjin Kwon (JIRA) 

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

Hyukjin Kwon resolved SPARK-22980.
--
Resolution: Fixed

> 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
>Priority: Major
> Fix For: 2.3.0
>
>
> {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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[jira] [Resolved] (SPARK-22980) Using pandas_udf when inputs are not Pandas's Series or DataFrame

2018-01-12 Thread Hyukjin Kwon (JIRA) 

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

Hyukjin Kwon resolved SPARK-22980.
--
   Resolution: Fixed
Fix Version/s: 2.3.0

Issue resolved by pull request 20237
[https://github.com/apache/spark/pull/20237]

> 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
>Assignee: Hyukjin Kwon
> Fix For: 2.3.0
>
>
> {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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