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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2017/02/25 23:56:44 UTC
[jira] [Assigned] (SPARK-19602) Unable to query using the fully
qualified column name of the form ( ..)
[ https://issues.apache.org/jira/browse/SPARK-19602?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-19602:
------------------------------------
Assignee: Apache Spark
> Unable to query using the fully qualified column name of the form ( <DBNAME>.<TABLENAME>.<COLUMNNAME>)
> ------------------------------------------------------------------------------------------------------
>
> Key: SPARK-19602
> URL: https://issues.apache.org/jira/browse/SPARK-19602
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 2.1.0
> Reporter: Sunitha Kambhampati
> Assignee: Apache Spark
> Attachments: Design_ColResolution_JIRA19602.pdf
>
>
> 1) Spark SQL fails to analyze this query: select db1.t1.i1 from db1.t1, db2.t1
> Most of the other database systems support this ( e.g DB2, Oracle, MySQL).
> Note: In DB2, Oracle, the notion is of <schema>.<tablename>.<columnname>
> 2) Another scenario where this fully qualified name is useful is as follows:
> // current database is db1.
> select t1.i1 from t1, db2.t1
> If the i1 column exists in both tables: db1.t1 and db2.t1, this will throw an error during column resolution in the analyzer, as it is ambiguous.
> Lets say the user intended to retrieve i1 from db1.t1 but in the example db2.t1 only has i1 column. The query would still succeed instead of throwing an error.
> One way to avoid confusion would be to explicitly specify using the fully qualified name db1.t1.i1
> For e.g: select db1.t1.i1 from t1, db2.t1
> Workarounds:
> There is a workaround for these issues, which is to use an alias.
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