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From "RaviShankar KS (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-10967) Incorrect UNION ALL behavior
Date Wed, 07 Oct 2015 06:22:27 GMT

     [ https://issues.apache.org/jira/browse/SPARK-10967?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

RaviShankar KS updated SPARK-10967:
-----------------------------------
    Description: IGNORE  (was: We notice that the join conditions are not working as expected
in the case of nested columns being compared.
As long as leaf columns have the same name under a nested column, should order matter ??

Consider below example for two data frames d5 and d5_opp : 
d5 and d5_opp have a nested field 'value', but their inner leaf columns do not have the same
ordering. 

--       d5.printSchema
root
 |-- key: integer (nullable = false)
 |-- value: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- col1: string (nullable = true)
 |    |    |-- col2: string (nullable = true)
 |-- value1: struct (nullable = false)
 |    |-- col1: string (nullable = false)
 |    |-- col2: string (nullable = false)

--        d5_opp.printSchema
root
 |-- key: integer (nullable = false)
 |-- value: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- col2: string (nullable = true)
 |    |    |-- col1: string (nullable = true)
 |-- value1: struct (nullable = false)
 |    |-- col2: string (nullable = false)
 |    |-- col1: string (nullable = false)

The below join statement do not work in spark 1.5, and raises exception. In spark 1.4, no
exception is raised, but join result is incorrect :

--    d5.as("d5").join( d5_opp.as("d5_opp"),  $"d5.value"  === $"d5_opp.value",  "inner").show
Exception raised is :  
org.apache.spark.sql.AnalysisException: cannot resolve '(value = value)' due to data type
mismatch: differing types in '(value = value)' (array<struct<col1:string,col2:string>>
and array<struct<col2:string,col1:string>>).;

--    d5.as("d5").join( d5_opp.as("d5_opp"),  $"d5.value1"  === $"d5_opp.value1",  "inner").show
Exception raised is :
org.apache.spark.sql.AnalysisException: cannot resolve '(value1 = value1)' due to data type
mismatch: differing types in '(value1 = value1)' (struct<col1:string,col2:string> and
struct<col2:string,col1:string>).;

// Code to be used in spark shell to create the data frames is attached.
-------------------------
The only work-around is to explode the conditions for every leaf field. 
In our case, we are generating the conditions and dataframes programmatically, and exploding
the conditions for every leaf field is additional overhead, and may not be always possible.)

> Incorrect UNION ALL behavior
> ----------------------------
>
>                 Key: SPARK-10967
>                 URL: https://issues.apache.org/jira/browse/SPARK-10967
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core, SQL
>    Affects Versions: 1.4.1
>         Environment: RHEL
>            Reporter: RaviShankar KS
>            Assignee: Josh Rosen
>              Labels: sql, union
>             Fix For: 1.5.0
>
>
> IGNORE



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