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Michael Armbrust resolved SPARK-5472. ------------------------------------- Resolution: Fixed Fix Version/s: 1.3.0 Issue resolved by pull request 4261 [https://github.com/apache/spark/pull/4261] > 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org