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

Vinod KC updated SPARK-25301:
-----------------------------
    Description: 
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
 --------
```sql
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.

  was:
When a hive view uses an UDF from a non default database, Spark analyser throws 
AnalysisException

Steps to simulate this issue
 -----------------------------
 In Hive
 --------
 1) CREATE DATABASE d100;
 2) create function d100.udf100 as 
'org.apache.hadoop.hive.ql.udf.generic.GenericUDFUpper'; // Note: udf100 is 
created in d100
 3) create view d100.v100 as select *d100.udf100*(name)  from default.emp; // 
Note : table default.emp has two columns 'name', 'address', 
 5) select * from d100.v100; // query on view d100.v100 gives correct result

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.


> 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
>  --------
> ```sql
> 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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