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From "Nikolay Izhikov (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (IGNITE-10314) Spark dataframe will get wrong schema if user executes add/drop column DDL
Date Mon, 21 Jan 2019 08:37:00 GMT

    [ https://issues.apache.org/jira/browse/IGNITE-10314?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16747749#comment-16747749
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Nikolay Izhikov commented on IGNITE-10314:
------------------------------------------

https://github.com/apache/ignite/commit/015166804eb2d7fd596e8458a0eaf0a3c3f49edd - merged
to master

[~ldz] Thanks you, for the contribution!

> Spark dataframe will get wrong schema if user executes add/drop column DDL
> --------------------------------------------------------------------------
>
>                 Key: IGNITE-10314
>                 URL: https://issues.apache.org/jira/browse/IGNITE-10314
>             Project: Ignite
>          Issue Type: Bug
>          Components: spark
>    Affects Versions: 2.3, 2.4, 2.5, 2.6, 2.7
>            Reporter: Ray Liu
>            Assignee: Ray Liu
>            Priority: Critical
>             Fix For: 2.8
>
>          Time Spent: 673.5h
>  Remaining Estimate: 0h
>
> When user performs add/remove column in DDL,  Spark will get the old/wrong schema.
>  
> Analyse 
> Currently Spark data frame API relies on QueryEntity to construct schema, but QueryEntity
in QuerySchema is a local copy of the original QueryEntity, so the original QueryEntity is
not updated when modification happens.
>  
> Solution
> Use GridQueryTypeDescriptor to replace QueryEntity



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