You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Denise Mauldin (Jira)" <ji...@apache.org> on 2020/10/26 17:27:00 UTC
[jira] [Commented] (SPARK-19335) Spark should support doing an
efficient DataFrame Upsert via JDBC
[ https://issues.apache.org/jira/browse/SPARK-19335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17220855#comment-17220855 ]
Denise Mauldin commented on SPARK-19335:
----------------------------------------
+1 This is a major deficiency for using Spark in ETL jobs.
> 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.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org