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https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17001220#comment-17001220
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Cory Lassila commented on SPARK-19335:
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+1 I believe this would be useful, my scenario is using a 5-min aggregate Spark
Structured Streaming job which Reads from Kafka & uses forEachBatch to do
multi-out to several different postgres tables. If we fail half-way thru
multi-out writing to postgres, we get duplicate records in the postgres tables.
Let me know if this makes sense or if I'm missing something.
Thanks!
> Spark should support doing an efficient DataFrame Upsert via JDBC
> -----------------------------------------------------------------
>
> Key: SPARK-19335
> URL: https://issues.apache.org/jira/browse/SPARK-19335
> Project: Spark
> Issue Type: Improvement
> Reporter: Ilya Ganelin
> Priority: Minor
>
> Doing a database update, as opposed to an insert is useful, particularly when
> working with streaming applications which may require revisions to previously
> stored data.
> Spark DataFrames/DataSets do not currently support an Update feature via the
> JDBC Writer allowing only Overwrite or Append.
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