spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Andrew Or (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-14684) Verification of partition specs in SessionCatalog
Date Thu, 12 May 2016 18:09:13 GMT

     [ https://issues.apache.org/jira/browse/SPARK-14684?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Andrew Or updated SPARK-14684:
------------------------------
    Description: 
When attempting to drop partitions of a table, if the user provides an unknown column, Hive
will drop all the partitions of the table, which is likely not intended. E.g.
{code}
ALTER TABLE my_tab DROP PARTITION (ds='2008-04-09', unknownCol='12')
{code}
We should verify that the columns provided in the specs are actually partitioned columns.

  was:When users inputting invalid partition spec, we might not be able to catch and issue
the error messages. Sometimes, it could cause a disaster result. For example, previously,
when we alter a table and drop a partition with invalid spec, it could drop all the partitions
due to a bug/defect in Hive Metastore API. 


> Verification of partition specs in SessionCatalog
> -------------------------------------------------
>
>                 Key: SPARK-14684
>                 URL: https://issues.apache.org/jira/browse/SPARK-14684
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.0.0
>            Reporter: Xiao Li
>            Assignee: Xiao Li
>
> When attempting to drop partitions of a table, if the user provides an unknown column,
Hive will drop all the partitions of the table, which is likely not intended. E.g.
> {code}
> ALTER TABLE my_tab DROP PARTITION (ds='2008-04-09', unknownCol='12')
> {code}
> We should verify that the columns provided in the specs are actually partitioned columns.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org


Mime
View raw message