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https://issues.apache.org/jira/browse/HADOOP-908?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#action_12465912
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Doug Cutting commented on HADOOP-908:
-------------------------------------

This looks great!

It would be good to add a package.html in the sources, with a description of 
abacus.  Also the top-level build.xml should be modified so that abacus's 
javadoc is included as a "contrib: Abacus" group.

> Hadoop Abacus, a package for performing simple counting/aggregation
> -------------------------------------------------------------------
>
>                 Key: HADOOP-908
>                 URL: https://issues.apache.org/jira/browse/HADOOP-908
>             Project: Hadoop
>          Issue Type: New Feature
>          Components: contrib/streaming
>            Reporter: Runping Qi
>         Assigned To: Runping Qi
>         Attachments: abacus.patch
>
>
> Hadoop Abacus package is a specialization of map/reduce framework, 
> specilizing for performing various counting and aggregations. 
> It offers similar functionalities to Google's SawZall. 
> Generally speaking, in order to implement an application using Map/Reduce 
> model, 
> the developer needs to implement Map and Reduce functions (and possibly 
> Combine function). 
> However, for a lot of applications related to counting and statistics 
> computing, 
> these functions have very similar characteristics. 
> Abacus abstracts out the general patterns and provides a package implementing 
> those patterns. 
> In particular, the package provides a generic mapper class, a reducer class 
> and a combiner class, 
> and a set of built-in value aggregators. It also provides a generic utility 
> class, ValueAggregatorJob
> for creating Abacus jobs.
> To create an Abacus job, the user just needs to implement one plugin class 
> that 
> is responsible for specifying what aggregators to use and what values are for 
> which aggregators. 
> The mapper will call this class in the runtime to generate aggregation ids 
> and values.
> The generic  combiner and reducer will aggregate the values associated with 
> the same 
> aggregation ids accordingly. Thus, it is much easier to create and run an 
> Abacus job than 
> a normal map/reduce job. Since a  built-in generic combiner is always used, 
> the execution is very efficient.

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