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From "Phabricator (JIRA)" <>
Subject [jira] [Commented] (HIVE-2206) add a new optimizer for query correlation discovery and optimization
Date Tue, 16 Jul 2013 20:56:51 GMT


Phabricator commented on HIVE-2206:

ashutoshc has requested changes to the revision "HIVE-2206 [jira] add a new optimizer for
query correlation discovery and optimization".

  Minor comments, mostly around improving documentation in code.

  ql/src/java/org/apache/hadoop/hive/ql/exec/ Does this patch makes
this necessary? Or, you added it just for completeness?
  ql/src/java/org/apache/hadoop/hive/ql/exec/ Better to do it as List<Object>
thisRow = (List<Object>) row;
  ql/src/java/org/apache/hadoop/hive/ql/exec/ Will be good to add comments
for all these maps. What mappings they are tracking?
  ql/src/java/org/apache/hadoop/hive/ql/exec/ Will be good to add some
ascii art showing an example of such a plan.
  ql/src/java/org/apache/hadoop/hive/ql/exec/ Is this necessary?
  ql/src/java/org/apache/hadoop/hive/ql/exec/ I understand this but it
will be confusing for someone reading this comment for first time because before this patch
RS operator is always in map side. We need to reword this so its easier to read.
  ql/src/java/org/apache/hadoop/hive/ql/exec/ Can you add a comment when
this boolean will be true and when it will be false.
  ql/src/java/org/apache/hadoop/hive/ql/exec/ Lets throw an exception
here. if (childOperatorsArray.length != 1) throw new HiveException ("Expected number of children
is 1. Found : " + childOperatorsArray.length)
  ql/src/java/org/apache/hadoop/hive/ql/exec/ This should not be required.
You can always get all the values of enum by using valueOf() method on enum.
  ql/src/java/org/apache/hadoop/hive/ql/optimizer/ It will be good to
add javadoc for this explaining why we should leave it as it is?
It will be good to add javadoc for this class.




To: JIRA, ashutoshc, yhuai
Cc: brock

> add a new optimizer for query correlation discovery and optimization
> --------------------------------------------------------------------
>                 Key: HIVE-2206
>                 URL:
>             Project: Hive
>          Issue Type: New Feature
>          Components: Query Processor
>    Affects Versions: 0.12.0
>            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-2206.20-r1434012.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, HIVE-2206.D11097.10.patch, HIVE-2206.D11097.11.patch, HIVE-2206.D11097.12.patch,
HIVE-2206.D11097.13.patch, HIVE-2206.D11097.14.patch, HIVE-2206.D11097.15.patch, HIVE-2206.D11097.16.patch,
HIVE-2206.D11097.17.patch, HIVE-2206.D11097.18.patch, HIVE-2206.D11097.1.patch, HIVE-2206.D11097.2.patch,
HIVE-2206.D11097.3.patch, HIVE-2206.D11097.4.patch, HIVE-2206.D11097.5.patch, HIVE-2206.D11097.6.patch,
HIVE-2206.D11097.7.patch, HIVE-2206.D11097.8.patch, HIVE-2206.D11097.9.patch, testQueries.2.q,
> 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
( 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;
> # Optimize queries involving self join. 
> References:
> Paper and presentation of YSmart.
> Paper:
> Slides:

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