ignite-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Ray (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (IGNITE-10314) Spark dataframe will get wrong schema if user executes add/drop column DDL
Date Wed, 21 Nov 2018 08:26:00 GMT

    [ https://issues.apache.org/jira/browse/IGNITE-10314?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16694377#comment-16694377
] 

Ray commented on IGNITE-10314:
------------------------------

This bug is blocked by another bug I just found.

https://issues.apache.org/jira/browse/IGNITE-10356

JDBC thin driver will return wrong metadata if one table contains fields with Date or Decimal
or data type.

I provided a fix for that issue.

> 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
>            Assignee: Ray
>            Priority: Critical
>             Fix For: 2.8
>
>
> 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
> Get the schema using sql, get rid of QueryEntity.



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

Mime
View raw message