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From "stack (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-5317) Implement insert, update, and delete in Hive with full ACID support
Date Thu, 19 Sep 2013 17:36:54 GMT

    [ https://issues.apache.org/jira/browse/HIVE-5317?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13772077#comment-13772077
] 

stack commented on HIVE-5317:
-----------------------------

bq. The HBase scan rate is much lower than HDFS, especially with short-circuit reads.

What kinda of numbers are you talking Owen?  Would be interested in knowing what they are.
 Implication would be also that it cannot be improved?  Or scanning the files written by hbase
offline from a snapshot wouldn't work from you (snapshots are cheap in hbase.  Going by your
use cases, you'd be doing these runs infrequently enough).

bq. HBase is tuned for a write-heavy workloads.

Funny.  Often we're accused of the other extreme.

bq. HBase doesn't have a columnar format and can't support column projection.

It doesn't. Too much work to add a storage engine that wrote columnar?

bq. HBase doesn't have the equivalent of partitions or buckets.

In hbase we call them 'Regions'.

                
> 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
>         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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