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• How to Work With MongoDB's Shell Interface

  

  By chco : 02 May 2011 - 10:20 AM

  This excerpt covers some operational aspects of running a cluster. Once you have a cluster up and running, how do you know what’s going on? Below we have some information from the O'Reilly publi...

  Tags:

  • mongodb
  • database
  • shell
  • cluster

  1Vote

  0Comments

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• How to Create a VMware Cluster

  

  By adfm : 24 May 2010 - 10:14 AM

  Managing multiple ESX Servers is easy with the VMware. This excerpt from Troy & Helmke's VMware Cookbook will guide you through the process of creating a cluster with the vCenter client. If you ...

  Tags:

  • VMware
  • cluster
  • ESX
  • vCenter
  • DRS
  • HA

  0Votes

  0Comments

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• Big Data -- A link roundup

  

  By adfm : 08 December 2009 - 12:07 AM

  Big Data is when your data is so large you seriously have to consider how you're going to organize, store, and manage it in order to gain some benefit from it. Here are a few links to get you star...

  Tags:

  • Big Data
  • MapReduce
  • NoSQL
  • databases
  • cluster

  4Votes

  0Comments

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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

  0Comments

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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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