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Parallel K-means using Map Reduce on Big Data Cluster Analysis

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Summary of Parallel k-means using MapReduce​

  • Map: classification step
    • data parallel over data points
  • Recuce: recompute means
    • data parallel over centers

Some practical considerations​

  • k-means needs an iterative version of MapReduce
    • Not standard formulation
  • Mapper needs to get data point and all centers
    • A lot of data
    • Better implmentation
      • mapper gets many data points