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https://issues.apache.org/jira/browse/HIVE-1641?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12914332#action_12914332
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Liyin Tang commented on HIVE-1641:
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Right now, the local work is only for processing small tables for map join
operation. Also one MapredTask can at most have one map join operation. Because
if one map join followed by anther map join, they will be split into 2 tasks.
So one MapredTask can at most one local work to do.
One feasible solution is to create a new type of task, named MapredLocalTask,
which is to do some MapredLocalWork (local work). If one MapredTask has a local
work to do, then create a new MapredLocal Task for this local work, let the
current MapredTask depends on this new generated Task, and let this new
generated task depends on the parent tasks of the current task.
In this new MapredLocalTask, it does the local work only once and generate the
mapped file(JDBM file). Next step is to put the new generated mapped file into
distributed cache. All the mappers will
read this file from the distributed cache and construct the in memory hash
table based on this file.
Any comments are so welcome:)
> add map joined table to distributed cache
> -----------------------------------------
>
> Key: HIVE-1641
> URL: https://issues.apache.org/jira/browse/HIVE-1641
> Project: Hadoop Hive
> Issue Type: Improvement
> Components: Query Processor
> Reporter: Namit Jain
> Assignee: Liyin Tang
> Fix For: 0.7.0
>
>
> Currently, the mappers directly read the map-joined table from HDFS, which
> makes it difficult to scale.
> We end up getting lots of timeouts once the number of mappers are beyond a
> few thousand, due to
> concurrent mappers.
> It would be good idea to put the mapped file into distributed cache and read
> from there instead.
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