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Date: Thu, 19 Oct 2017 17:40:01 +0000 (UTC)
From: "Matyas Orhidi (JIRA)" <jira@apache.org>
To: issues@spark.apache.org
Message-ID: <JIRA.13110732.1508434730000.9909.1508434801098@Atlassian.JIRA>
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Subject: [jira] [Updated] (SPARK-22314) Accessing Hive UDFs defined without
 'USING JAR' from Spark
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archived-at: Thu, 19 Oct 2017 17:40:07 -0000


     [ https://issues.apache.org/jira/browse/SPARK-22314?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Matyas Orhidi updated SPARK-22314:
----------------------------------
    Summary: Accessing Hive UDFs defined without 'USING JAR' from Spark   (was: Accessing Hive UDFs from Spark originally defined without 'USING JAR')

> Accessing Hive UDFs defined without 'USING JAR' from Spark 
> -----------------------------------------------------------
>
>                 Key: SPARK-22314
>                 URL: https://issues.apache.org/jira/browse/SPARK-22314
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 2.2.0
>            Reporter: Matyas Orhidi
>
> When defining UDF functions in Hive it is possible to load the UDF jar(s) from a shared location e.g. from hive.reloadable.aux.jars.path, and then use the CREATE FUNCTION statement:
> {{CREATE FUNCTION <your_function_name> AS '<fully_qualified_class_name>';}}
> These UDFs are not working from Spark unless you use the 
> {{CREATE FUNCTION <your_function_name> AS '<fully_qualified_class_name>' USING JAR
>                   'hdfs:///<path/to/jar/in/hdfs>';}}
> command to create the Hive UDF function.


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