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  Running mapreduce jobs that have hbase as source or sink, you'll need to 
specify source/sink table and column names in your configuration.
  
- Reading from hbase, the !TableInputFormat asks hbase for the list of regions 
and makes a map-per-region.  Writing, its better to have lots of reducers so 
load is spread across the hbase cluster.
+ Reading from hbase, the !TableInputFormat asks hbase for the list of regions 
and makes a map-per-region.  Writing, it may make sense to avoid the reduce 
step and write back into hbase from inside your map.  You'd do this when your 
job does not need the sort and collation that MR does inside in its reduce; on 
insert, hbase sorts so no point double-sorting (and shuffling data around your 
MR cluster) unless you need to.  If you do not need the reduce, you might just 
have your map emit counts of records processed just so the framework can emit 
that nice report of records processed when the job is done.  If running the 
reduce step makes sense in  your case, its better to have lots of reducers so 
load is spread across the hbase cluster.
  
  = Sample MR+HBase Jobs =
  A 
[http://www.nabble.com/Re%3A-Map-Reduce-over-HBase---sample-code-p18126819.html 
students/classes example] by Naama Kraus.

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