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https://issues.apache.org/jira/browse/HIVE-549?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12773294#action_12773294
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Ning Zhang commented on HIVE-549:
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Just curious, how do we handle exceptions if tasks are executed in parallel. I
am asking this because we probably need to setup a global configuration at any
point of the query execution (e.g., change the replication factor of a table in
the map-side join), and change it back when the whole query is finished or an
exception is caught at the end.
It seems to me that the parallel execution paradigm can be applied only if
there is a child task waiting on all the parallel tasks at any point. The child
is responsible for rolling back if any exception is caught. An example I am
thinking that cannot use the parallel paradigm is the multi-insert case, where
each insert is a branch and they don't "meet" at the bottom of the plan.
> Parallel Execution Mechanism
> ----------------------------
>
> Key: HIVE-549
> URL: https://issues.apache.org/jira/browse/HIVE-549
> Project: Hadoop Hive
> Issue Type: Wish
> Components: Query Processor
> Reporter: Adam Kramer
> Assignee: Chaitanya Mishra
> Attachments: HIVE-549-v3.patch
>
>
> In a massively parallel database system, it would be awesome to also
> parallelize some of the mapreduce phases that our data needs to go through.
> One example that just occurred to me is UNION ALL: when you union two SELECT
> statements, effectively you could run those statements in parallel. There's
> no situation (that I can think of, but I don't have a formal proof) in which
> the left statement would rely on the right statement, or vice versa. So, they
> could be run at the same time...and perhaps they should be. Or, perhaps there
> should be a way to make this happen...PARALLEL UNION ALL? PUNION ALL?
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