[jira] [Commented] (IGNITE-10314) Spark dataframe will get wrong schema if user executes add/drop column DDL

["Nikolay Izhikov (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/IGNITE-10314?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16747446#comment-16747446 ] 

Nikolay Izhikov commented on IGNITE-10314:
------------------------------------------

Hello, [~ldz]

Sorry for the pause in the review.

Looks good to me! I think this PR is ready to be merged.

I left some very minor comments regarding the code formatting.
Please, fix them before the merge.

Also, please, make sure you use spaces instead of tabs for indenting.

package.scala#sqlCacheName
package.scala#isValidSchema.

> 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: 40m
>  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



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)