[
https://issues.apache.org/jira/browse/SPARK-21918?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16155047#comment-16155047
]
Marco Gaido commented on SPARK-21918:
-------------------------------------
What I meant is that if we want to support doAs, we shouldn't just support it
for DDL operations, but also for all DML & DQL. Your fix I am pretty sure won't
affect the DML & DQL behavior, ie. we would support the doAs only for DDL
operations with your change. This means that there would be a hybrid situation:
for DDL we'd have doAs working, for DML & DQL no. This is not a desirable
condition.
PS For my sake of curiosity, may I ask you how you tested that your DDL
commands were run using the session user?
Thanks.
> HiveClient shouldn't share Hive object between different thread
> ---------------------------------------------------------------
>
> Key: SPARK-21918
> URL: https://issues.apache.org/jira/browse/SPARK-21918
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.2.0
> Reporter: Hu Liu,
>
> I'm testing the spark thrift server and found that all the DDL statements are
> run by user hive even if hive.server2.enable.doAs=true
> The root cause is that Hive object is shared between different thread in
> HiveClientImpl
> {code:java}
> private def client: Hive = {
> if (clientLoader.cachedHive != null) {
> clientLoader.cachedHive.asInstanceOf[Hive]
> } else {
> val c = Hive.get(conf)
> clientLoader.cachedHive = c
> c
> }
> }
> {code}
> But in impersonation mode, we should just share the Hive object inside the
> thread so that the metastore client in Hive could be associated with right
> user.
> we can pass the Hive object of parent thread to child thread when running
> the sql to fix it
> I have already had a initial patch for review and I'm glad to work on it if
> anyone could assign it to me.
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
