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From "Arun C Murthy (JIRA)" <j...@apache.org>
Subject [jira] Resolved: (MAPREDUCE-1956) allow reducer to initialize lazily
Date Wed, 21 Jul 2010 22:24:50 GMT

     [ https://issues.apache.org/jira/browse/MAPREDUCE-1956?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Arun C Murthy resolved MAPREDUCE-1956.
--------------------------------------

    Resolution: Invalid

The part about 'loading data in reduce method controlled by an  
initialize flag variable which assures that it is loaded only once'  
makes no sense to me.

However, you can 'slowstart' reduces by ensuring sufficient maps are  
complete before _any_ reduces are launched... from mapred-default.xml:

<property>
  <name>mapred.reduce.slowstart.completed.maps</name>
  <value>0.05</value>
  <description>Fraction of the number of maps in the job which should  
be
  complete before reduces are scheduled for the job.
  </description>
</property>

> allow reducer to initialize lazily
> ----------------------------------
>
>                 Key: MAPREDUCE-1956
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1956
>             Project: Hadoop Map/Reduce
>          Issue Type: Improvement
>          Components: tasktracker
>    Affects Versions: 0.20.2
>            Reporter: Ted Yu
>
> From http://www.scribd.com/doc/23046928/Hadoop-Performance-Tuning:
> "In M/R job Reducers are initialized with Mappers at the job initialization, but the
reduce method is called in reduce phase when all the maps had been finished. So in large jobs
where Reducer loads data (>100 MB for business logic) in-memory on initialization, the
performance can be increased by lazily initializing Reducers i.e. loading data in reduce method
controlled by an initialize flag variable which assures that it is loaded only once. By lazily
initializing Reducers which require memory (for business logic) on initialization, number
of maps can be increased."
> Introducing a parameter for this purpose would allow more people to utilize the above
pattern.

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