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The source code for MapRejuice, the distributed client-side computing implementation of Map Reduce built on top of Node.js for the Node Knockout competition in 2010. Built over 48 hours, code is not perfect and hasn't been touched since. Feel free to peruse though!

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README driven development! Here we go!

Anansi (why is it called like that?) is a distributed MapReduce implementation for JavaScript that runs on the worlds largest computational network. Consumer PCs.

Trade-offs

Technically there is no reason not to run MapReduce jobs on idling web clients. But of course this was a competition and we had to spend some time to implement cool realtime scrolling graphs, so some things were left out.

  • There is no input reader step. Data has to be uploaded in chunks.
  • There's always exactly one map phase and one reduce phase. No partitions and you can't supply a partitioning function.
  • The grouping step after the map step is lame and slow.
  • Results aren't validated by more than one client.
  • We're using a relational database goes and hides in the basement

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The source code for MapRejuice, the distributed client-side computing implementation of Map Reduce built on top of Node.js for the Node Knockout competition in 2010. Built over 48 hours, code is not perfect and hasn't been touched since. Feel free to peruse though!

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