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From "Paul Fosse (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-5317) Implement insert, update, and delete in Hive with full ACID support
Date Mon, 06 Jul 2015 16:37:04 GMT

    [ https://issues.apache.org/jira/browse/HIVE-5317?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14615279#comment-14615279
] 

Paul Fosse commented on HIVE-5317:
----------------------------------

Merge command seems to be needed to do the first use case of the ACID feature.

"Once an hour, a set of inserts and updates (up to 500k rows) for various dimension tables
(eg. customer, inventory, stores) needs to be processed. The dimension tables have primary
keys and are typically bucketed and sorted on those keys."

Typically we will load the updates to a hive table and just want to merge that table to the
existing dimension. We are either using the old way of doing this (ingest, reconcile, compact
& purge) or we are writing a Python script to process the updates. But we can't do 500K
update statements an hour, so it doesn't seem the ACID does us any good for this use case
until we have merge

> Implement insert, update, and delete in Hive with full ACID support
> -------------------------------------------------------------------
>
>                 Key: HIVE-5317
>                 URL: https://issues.apache.org/jira/browse/HIVE-5317
>             Project: Hive
>          Issue Type: New Feature
>            Reporter: Owen O'Malley
>            Assignee: Owen O'Malley
>             Fix For: 0.14.0
>
>         Attachments: InsertUpdatesinHive.pdf
>
>
> Many customers want to be able to insert, update and delete rows from Hive tables with
full ACID support. The use cases are varied, but the form of the queries that should be supported
are:
> * INSERT INTO tbl SELECT …
> * INSERT INTO tbl VALUES ...
> * UPDATE tbl SET … WHERE …
> * DELETE FROM tbl WHERE …
> * MERGE INTO tbl USING src ON … WHEN MATCHED THEN ... WHEN NOT MATCHED THEN ...
> * SET TRANSACTION LEVEL …
> * BEGIN/END TRANSACTION
> Use Cases
> * Once an hour, a set of inserts and updates (up to 500k rows) for various dimension
tables (eg. customer, inventory, stores) needs to be processed. The dimension tables have
primary keys and are typically bucketed and sorted on those keys.
> * Once a day a small set (up to 100k rows) of records need to be deleted for regulatory
compliance.
> * Once an hour a log of transactions is exported from a RDBS and the fact tables need
to be updated (up to 1m rows)  to reflect the new data. The transactions are a combination
of inserts, updates, and deletes. The table is partitioned and bucketed.



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