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https://issues.apache.org/jira/browse/SPARK-5472?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14297105#comment-14297105
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Tor Myklebust commented on SPARK-5472:
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Not sure what you mean by "essentially" here.
JdbcRDD gives you an RDD of Array[Object]'s or, if you specify a function that
maps ResultSet rows to objects of your choosing, an RDD of some class of your
choosing. It doesn't natively produce Spark SQL DataFrames. In order to get a
DataFrame, you need an RDD of Row objects and their schema; a lot of the work
here comes from type mapping between types in the external database and Spark
SQL types.
JdbcRDD also doesn't expose itself as a data source in Spark SQL; you can't
"CREATE TABLE foo USING something" with some options in Spark SQL in order to
get a table named foo that really lives inside an external database.
> 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
> Priority: Minor
>
> 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.
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