[jira] [Resolved] (SPARK-22978) Register Vectorized UDFs for SQL Statement

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-22978?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-22978.
----------------------------------
       Resolution: Fixed
    Fix Version/s: 2.3.0

Issue resolved by pull request 20171
[https://github.com/apache/spark/pull/20171]

> Register Vectorized UDFs for SQL Statement
> ------------------------------------------
>
>                 Key: SPARK-22978
>                 URL: https://issues.apache.org/jira/browse/SPARK-22978
>             Project: Spark
>          Issue Type: Sub-task
>          Components: PySpark
>    Affects Versions: 2.3.0
>            Reporter: Xiao Li
>            Assignee: Xiao Li
>            Priority: Major
>             Fix For: 2.3.0
>
>
> Capable of registering vectorized UDFs and then use it in SQL statement.
> For example,
> {noformat}
> >>> import random
> >>> from pyspark.sql.types import IntegerType
> >>> from pyspark.sql.functions import pandas_udf
> >>> random_pandas_udf = pandas_udf(
> ...     lambda x: random.randint(0, 100) + x, IntegerType())
> ...     .asNondeterministic()  # doctest: +SKIP
> >>> _ = spark.catalog.registerFunction(
> ...     "random_pandas_udf", random_pandas_udf, IntegerType())  # doctest: +SKIP
> >>> spark.sql("SELECT random_pandas_udf(2)").collect()  # doctest: +SKIP
> [Row(random_pandas_udf(2)=84)]
> {noformat}



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