[jira] [Commented] (SPARK-5472) Add support for reading from and writing to a JDBC database

["Jia Li (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-5472?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14960052#comment-14960052 ] 

Jia Li commented on SPARK-5472:
-------------------------------

[~tmyklebu] Does your PR handle BINARY type? 

Thanks,

> Add support for reading from and writing to a JDBC database
> -----------------------------------------------------------
>
>                 Key: SPARK-5472
>                 URL: https://issues.apache.org/jira/browse/SPARK-5472
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>            Reporter: Tor Myklebust
>            Assignee: Tor Myklebust
>            Priority: Blocker
>             Fix For: 1.3.0
>
>
> It would be nice to be able to make a table in a JDBC database appear as a table in Spark SQL.  This would let users, for instance, perform a JOIN between a DataFrame in Spark SQL with a table in a Postgres database.
> It might also be nice to be able to go the other direction -- save a DataFrame to a database -- for instance in an ETL job.
> Edited to clarify:  Both of these tasks are certainly possible to accomplish at the moment with a little bit of ad-hoc glue code.  However, there is no fundamental reason why the user should need to supply the table schema and some code for pulling data out of a ResultSet row into a Catalyst Row structure when this information can be derived from the schema of the database table itself.



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