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https://issues.apache.org/jira/browse/MAPREDUCE-1956?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Arun C Murthy resolved MAPREDUCE-1956.
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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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