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Cloud MapReduce

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Apparently claimed to be much faster than Hadoop, here is the cloud OS flavor for MapReduce.

http://code.google.com/p/cloudmapreduce/

Cloud MapReduce was initially developed at Accenture Technology Labs. It is a MapReduce implementation on top of the Amazon Cloud OS.

By exploiting a cloud OS’s scalability, Cloud MapReduce achieves three primary advantages over other MapReduce implementations built on a traditional OS:

  • It is faster than other implementations (e.g., 60 times faster than Hadoop in one case. Speedup depends on the application and data.).
  • It is more scalable and more failure resistant because it has no single point of bottleneck.
  • It is dramatically simpler with only 3,000 lines of code (e.g., two orders of magnitude simpler than Hadoop).


1 Comment

  1. Shankar Radhakrishnan says:

    My experience with cloud based MapReduce (flavor) is also dependent upon, how best the cloud architecture works. MPP databases and processes are very taxing on the nodes and cloud has several limitations as well – IO bottlenecks, network latency etc. And above all, the stability of the node as well.

    While it is easy to fire up a node in the cloud, its a pain in the cases, if you have a ‘shared’ instance, as after all most of them virtual-machines/space. Amazon for example, bets and recommends on reserved instances/EBS – that’s another option. Recent stories on Salesforce.com are scary.

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