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HYBRID LOCAL/REMOTE INFRASTRUCTURE FOR DATA PROCESSING WITH LIGHTWEIGHT SETUP, POWERFUL DEBUGGABILITY, CONTROLLABILITY, INTEGRATION, AND PRODUCTIVITY FEATURES

  • US 20140123115A1
  • Filed: 10/16/2013
  • Published: 05/01/2014
  • Est. Priority Date: 10/26/2012
  • Status: Active Grant
First Claim
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1. A method for providing an entirely hosted MapReduce data analytic infrastructure for executing a distributed large-scale compute job, the method comprising:

  • providing complete portability with respect to a programmer'"'"'s local machine, operating system, and browser;

    continuous metering of consumed compute, storage, and network resources on a hosting system;

    continuously reporting cost metering to a user;

    for each compute instance of the distributed large-scale compute job, monitoring of input and output data for the compute instance, and logging of the input and output data for the compute instance;

    generating input data from a kernel program, wherein the kernel program is smaller than the generated input data; and

    data-sorting at least a portion of the output data of the distributed large-scale compute job during a Map phase, wherein the data-sorting comprises,indexed writing of data sorting keys to shared storage by independently-executed Map jobs,wherein the hosted infrastructure does not require an installed client software or software development kit and wherein the hosted infrastructure does not require the compilation of computer code.

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