[
https://issues.apache.org/jira/browse/HIVE-15104?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16009026#comment-16009026
]
Rui Li commented on HIVE-15104:
-------------------------------
[~xuefuz], kryo was relocated in HIVE-5915. So it's not intended for Spark.
Actually, we're on the same version as Spark-2.0.0: kryo-shaded-3.0.3.
bq. I'm concerned that class conflicts might come back if we stop relocating
Kryo
You're right. I'm not sure whether it's a conflict or loading issue, but when I
tried to run some TPC-H benchmark, I got a ClassNotFoundException, although the
class is there in hive-exec.jar. I'll see how to workaround this.
BTW, the test in my last comment shuffles very little data. That's why
optimizing the overhead can have a significant improvement. I guess this won't
be the case in real world query. That's why I want to run some more serious
benchmark.
> Hive on Spark generate more shuffle data than hive on mr
> --------------------------------------------------------
>
> Key: HIVE-15104
> URL: https://issues.apache.org/jira/browse/HIVE-15104
> Project: Hive
> Issue Type: Bug
> Components: Spark
> Affects Versions: 1.2.1
> Reporter: wangwenli
> Assignee: Rui Li
> Attachments: HIVE-15104.1.patch
>
>
> the same sql, running on spark and mr engine, will generate different size
> of shuffle data.
> i think it is because of hive on mr just serialize part of HiveKey, but hive
> on spark which using kryo will serialize full of Hivekey object.
> what is your opionion?
--
This message was sent by Atlassian JIRA
(v6.3.15#6346)
