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https://issues.apache.org/jira/browse/HIVE-3001?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Bhushan Mandhani updated HIVE-3001:
-----------------------------------

    Attachment: HIVE-3001.1.patch.txt

Reviewed in https://reviews.facebook.net/D3153
                
> Returning Meaningful Error Codes & Messages
> -------------------------------------------
>
>                 Key: HIVE-3001
>                 URL: https://issues.apache.org/jira/browse/HIVE-3001
>             Project: Hive
>          Issue Type: New Feature
>          Components: Diagnosability
>    Affects Versions: 0.9.1
>            Reporter: Bhushan Mandhani
>            Assignee: Bhushan Mandhani
>            Priority: Minor
>             Fix For: 0.9.1
>
>         Attachments: HIVE-3001.1.patch.txt
>
>   Original Estimate: 48h
>  Remaining Estimate: 48h
>
> Hive does not return meaningful error messages for runtime errors. Also, the 
> same error code is returned for a whole bunch of unrelated errors. A 
> programmatic caller cannot decide if it should retry or give up. This JIRA 
> will get the ball rolling for having Hive return useful error codes and 
> display useful messages when something goes wrong. I propose the following 
> partitioning of error codes:
> 10000 to 19999: Errors that occur during semantic analysis and compilation of 
> the query. Hive already does a pretty good job for these. Error codes will be 
> attached to the error messages currently being used.
> 20000 to 29999: Runtime errors where Hive believes that retries will not 
> succeed and the caller should not bother retrying.
> 30000 to 39999: Runtime errors which Hive thinks are probably transient and 
> retrying may succeed.
> 40000 to 49999: Runtime errors where Hive is unable to say anything about 
> whether retries will succeed or not. Ideally, we want to avoid using this 
> range as much as possible.
> Once we have this in place, over time we can migrate errors occurring in Hive 
> operators to use this scheme. This patch will deal with setting up the error 
> code space, setting up the mechanism for failed MapReduce tasks to relay the 
> error code back to Hive client, and using this new scheme for a couple of 
> common errors.

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