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Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2020/06/30 01:25:00 UTC
[jira] [Assigned] (SPARK-32013) Support query execution
before/after reading/writing over JDBC
[ https://issues.apache.org/jira/browse/SPARK-32013?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-32013:
------------------------------------
Assignee: Apache Spark
> Support query execution before/after reading/writing over JDBC
> --------------------------------------------------------------
>
> Key: SPARK-32013
> URL: https://issues.apache.org/jira/browse/SPARK-32013
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Noritaka Sekiyama
> Assignee: Apache Spark
> Priority: Major
>
> For ETL workload, there is a common requirement to perform SQL statement before/after reading/writing over JDBC.
> Here's examples;
> - Create a view with specific conditions
> - Delete/Update some records
> - Truncate a table (it is already possible in `truncate` option)
> - Execute stored procedure (it is also requested in SPARK-32014)
> Currently `query` options is available to specify SQL statement against JDBC datasource when loading data as DataFrame.
> However, this query is only for reading data, and it does not support the common examples listed above.
> On the other hand, there is `sessionInitStatement` option available before writing data from DataFrame.
> This option is to run custom SQL in order to implement session initialization code. Since it runs per session, it cannot be used for non-idempotent operations.
>
> If Spark can support executing SQL statement against JDBC datasources before/after reading/writing over JDBC, it can cover a lot of common use-cases.
> Note: Databricks' old Redshift connector has similar option like `preactions` and `postactions`. [https://github.com/databricks/spark-redshift]
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