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The following page has been changed by udanax:
http://wiki.apache.org/hadoop/DataProcessingBenchmarks

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  ||<bgcolor="#E5E5E5">Time  ||4.43 sec ||172.30 sec||108.01 sec||77.41 
sec||66.30 sec||60.78 sec||
  
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- == Hbase Matrix computations Benchmarks ==
-  * You can download the Hbase [http://incubator.apache.org/hama Matrix 
Package] for Map/Reduce-based Parallel Matrix Computations (still under 
development)
  
- ==== MapReduce Flow ====
+ I also investigate a lot of traditional methods of parallel processing and 
experiment some high level processing (e.g. matrix algebra, graph algorithm) 
using Hadoop/Hbase/MapReduce. The only way to increase speed linearly was 
locality (Do write all data even if there are duplicated efforts). Increased 
node numbers, there is a linear increase of IO channel.
  
-  * The Multiplication requires (n + 1) table full scan irrespective of the 
number of mapper. 
-  * Each map processor requires O(n2) for the communication and O(n3/mappers) 
the computation. 
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