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https://issues.apache.org/jira/browse/HIVE-2206?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13555155#comment-13555155
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Yin Huai commented on HIVE-2206:
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So, if a Map join is involved in a plan and the output of this join will be
consumed by another subsequent operator, we should leave the Map join in the
Map phase of the subsequent operator instead of cutting Map join to a separate
MR job. Is my understanding correct? If so, I think that we should change the
process on generating Map join Operators. After generating a Map join operator,
we do not insert a FileSinkOperator after the Map Join. Seems that Rule 11 in
org.apache.hadoop.hive.ql.parse.SemanticAnalyzer.genMapRedTasks is the rule for
generating a separate MR job for a Map Join.
> add a new optimizer for query correlation discovery and optimization
> --------------------------------------------------------------------
>
> Key: HIVE-2206
> URL: https://issues.apache.org/jira/browse/HIVE-2206
> Project: Hive
> Issue Type: New Feature
> Components: Query Processor
> Affects Versions: 0.10.0
> Reporter: He Yongqiang
> Assignee: Yin Huai
> Attachments: HIVE-2206.10-r1384442.patch.txt,
> HIVE-2206.11-r1385084.patch.txt, HIVE-2206.12-r1386996.patch.txt,
> HIVE-2206.13-r1389072.patch.txt, HIVE-2206.14-r1389704.patch.txt,
> HIVE-2206.15-r1392491.patch.txt, HIVE-2206.16-r1399936.patch.txt,
> HIVE-2206.17-r1404933.patch.txt, HIVE-2206.18-r1407720.patch.txt,
> HIVE-2206.19-r1410581.patch.txt, HIVE-2206.1.patch.txt,
> HIVE-2206.2.patch.txt, HIVE-2206.3.patch.txt, HIVE-2206.4.patch.txt,
> HIVE-2206.5-1.patch.txt, HIVE-2206.5.patch.txt, HIVE-2206.6.patch.txt,
> HIVE-2206.7.patch.txt, HIVE-2206.8.r1224646.patch.txt,
> HIVE-2206.8-r1237253.patch.txt, testQueries.2.q, YSmartPatchForHive.patch
>
>
> This issue proposes a new logical optimizer called Correlation Optimizer,
> which is used to merge correlated MapReduce jobs (MR jobs) into a single MR
> job. The idea is based on YSmart (http://ysmart.cse.ohio-state.edu/).The
> paper and slides of YSmart are linked at the bottom.
> Since Hive translates queries in a sentence by sentence fashion, for every
> operation which may need to shuffle the data (e.g. join and aggregation
> operations), Hive will generate a MapReduce job for that operation. However,
> for those operations which may need to shuffle the data, they may involve
> correlations explained below and thus can be executed in a single MR job.
> # Input Correlation: Multiple MR jobs have input correlation (IC) if their
> input relation sets are not disjoint;
> # Transit Correlation: Multiple MR jobs have transit correlation (TC) if they
> have not only input correlation, but also the same partition key;
> # Job Flow Correlation: An MR has job flow correlation (JFC) with one of its
> child nodes if it has the same partition key as that child node.
> The current implementation of correlation optimizer only detect correlations
> among MR jobs for reduce-side join operators and reduce-side aggregation
> operators (not map only aggregation). A query will be optimized if it
> satisfies following conditions.
> # There exists a MR job for reduce-side join operator or reduce side
> aggregation operator which have JFC with all of its parents MR jobs (TCs will
> be also exploited if JFC exists);
> # All input tables of those correlated MR job are original input tables (not
> intermediate tables generated by sub-queries); and
> # No self join is involved in those correlated MR jobs.
> Correlation optimizer is implemented as a logical optimizer. The main reasons
> are that it only needs to manipulate the query plan tree and it can leverage
> the existing component on generating MR jobs.
> Current implementation can serve as a framework for correlation related
> optimizations. I think that it is better than adding individual optimizers.
> There are several work that can be done in future to improve this optimizer.
> Here are three examples.
> # Support queries only involve TC;
> # Support queries in which input tables of correlated MR jobs involves
> intermediate tables; and
> # Optimize queries involving self join.
> References:
> Paper and presentation of YSmart.
> Paper:
> http://www.cse.ohio-state.edu/hpcs/WWW/HTML/publications/papers/TR-11-7.pdf
> Slides: http://sdrv.ms/UpwJJc
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