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https://issues.apache.org/jira/browse/SPARK-5472?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Reynold Xin updated SPARK-5472:
-------------------------------
Comment: was deleted
(was: What if we expand the JDBC data source to support arbitrary queries?
)
> 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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