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https://issues.apache.org/jira/browse/HIVE-15104?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Rui Li updated HIVE-15104:
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Attachment: HIVE-15104.2.patch
The CNF is due to how kryo is loaded in {{KryoMessageCodec}}. W/ relocation,
kryo is in package {{org.apache.hive.com.esotericsoftware}}. So it's loaded
from hive-exec.jar. Spark adds hive-exec.jar at runtime with some URL class
loader. W/o relocation, we're using same kryo as Spark. Kryo's class loader is
by default the one that loads it - therefore the AppClassLoader. However,
AppClassLoader cannot load classes from hive-exec.jar and thus the CNF.
To solve it, we can make {{KryoMessageCodec}} use the current context loader.
> 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, HIVE-15104.2.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?
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