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https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16826378#comment-16826378
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Danny Guinther commented on SPARK-19335:
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Any update on this?
Also, please forgive this dumb question, but I'm shocked that there's not more
demand for this feature which makes me wonder if I have major misconceptions
about Spark and its intended use. How do users survive without this
functionality? I take it that the destination SQL database should have flexible
up-time requirements allowing for drastic changes? The overwrite save mode is
the only thing that offers anything like an UPDATE, but totally
dropping/truncating the destination table seems inconceivable for many
production environments. What am I missing?
> 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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