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• Practical Techniques for Developing with Pig and Hadoop

  

  By tomwhite : 28 October 2009 - 12:46 PM

  There are some practical techniques that are worth knowing about when you are developing and running Pig programs. This section covers some of them.ParallelismWhen running in Hadoop mode...

  Tags:

  • hadoop
  • mapreduce
  • cluster
  • parallel processing
  • big data
  • pig

  0Votes

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• How to Benchmark a Hadoop Cluster

  

  By tomwhite : 28 October 2009 - 12:24 PM

  Is the cluster set up correctly? The best way to answer this question is empirically: run some jobs and confirm that you get the expected results. Benchmarks make good tests, as you also...

  Tags:

  • hadoop
  • mapreduce
  • cluster
  • parallel processing
  • big data
  • benchmark

  2Votes

  0Comments

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• Anatomy of a MapReduce Job Run with Hadoop

  

  By tomwhite : 28 October 2009 - 12:16 PM

  You can run a MapReduce job with a single line of code: JobClient.runJob(conf). It’s very short, but it conceals a great deal of processing behind the scenes. This section uncov...

  Tags:

  • hadoop
  • mapreduce
  • parallel processing
  • big data
  • cluster

  1Vote

  0Comments

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• Get Started Analyzing Data with Hadoop

  

  By tomwhite : 28 October 2009 - 11:14 AM

  To take advantage of the parallel processing that Hadoop provides, we need to express our query as a MapReduce job. After some local, small-scale testing, we will be able to run it on a ...

  Tags:

  • hadoop
  • mapreduce
  • cluster
  • parallel processing
  • big data

  1Vote

  1Comment

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