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https://issues.apache.org/jira/browse/HIVE-3764?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13509300#comment-13509300
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Shreepadma Venugopalan commented on HIVE-3764:
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I think adding the consistency check is a good idea too. I've not looked into 
all the details of the code, but I noticed that the metastore version number is 
the hive release version. While this makes the version numbers easily readable, 
we would need to provide scripts and perform a metastore upgrade on every Hive 
release even if there are no other patches in the release that require a 
metastore schema upgrade. The other option would be to use version numbers from 
a monotonically increasing sequence instead and bump up the version number only 
if there are changes in a release that require a metastore upgrade. Wondering 
if you have considered the later option. Thanks.
                
> Support metastore version consistency check
> -------------------------------------------
>
>                 Key: HIVE-3764
>                 URL: https://issues.apache.org/jira/browse/HIVE-3764
>             Project: Hive
>          Issue Type: Improvement
>          Components: Metastore
>            Reporter: Prasad Mujumdar
>            Assignee: Prasad Mujumdar
>             Fix For: 0.10.0
>
>         Attachments: HIVE-3764-1.patch
>
>
> Today there's no version/compatibility information stored in hive metastore. 
> Also the datanucleus configuration property to automatically create missing 
> tables is enabled by default. If you happen to start an older or newer hive 
> or don't run the correct upgrade scripts during migration, the metastore 
> would end up corrupted. The autoCreate schema is not always sufficient to 
> upgrade metastore when migrating to newer release. It's not supported with 
> all databases. Besides the migration often involves altering existing table, 
> changing or moving data etc.
> Hence it's very useful to have some consistency check to make sure that hive 
> is using correct metastore and for production systems the schema is not 
> automatically by running hive.

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