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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2018/09/06 07:02:00 UTC

[jira] [Resolved] (SPARK-25301) When a view uses an UDF from a non default database, Spark analyser throws AnalysisException

     [ https://issues.apache.org/jira/browse/SPARK-25301?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-25301.
----------------------------------
    Resolution: Not A Problem

I am resolving this since for the current status it works as designed. See the discussion in the PR.

> When a view uses an UDF from a non default database, Spark analyser throws AnalysisException
> --------------------------------------------------------------------------------------------
>
>                 Key: SPARK-25301
>                 URL: https://issues.apache.org/jira/browse/SPARK-25301
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.4.0
>            Reporter: Vinod KC
>            Priority: Minor
>
> When a hive view uses an UDF from a non default database, Spark analyser throws AnalysisException
> Steps to simulate this issue
>  -----------------------------
>  Step 1 : Run following statements in Hive
>  --------
>  ```
>  CREATE TABLE emp AS SELECT 'user' AS name, 'address' as address;
>  CREATE DATABASE d100;
>  CREATE FUNCTION d100.udf100 as 'org.apache.hadoop.hive.ql.udf.generic.GenericUDFUpper'; // Note: udf100 is created in d100
>  CREATE VIEW d100.v100 AS SELECT d100.udf100(name) FROM default.emp; 
>  SELECT * FROM d100.v100; // query on view d100.v100 gives correct result
>  ```
>  Step2 : Run following statements in Spark
>  -------------
>  1) spark.sql("select * from d100.v100").show
>  throws 
>  ```
>  org.apache.spark.sql.AnalysisException: Undefined function: '*d100.udf100*'. This function is neither a registered temporary function nor a permanent function registered in the database '*default*'
>  ```
> This is because, while parsing the SQL statement of the View 'select `d100.udf100`(`emp`.`name`) from `default`.`emp`' , spark parser fails to split database name and udf name and hence Spark function registry tries to load the UDF 'd100.udf100' from 'default' database.



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