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⇱ Bill Bejeck, Author at Java Code Geeks - Page 2 of 3


  • Enterprise Java👁 Image
    Bill BejeckNovember 30th, 2012
    0 348

    Calculating A Co-Occurrence Matrix with Hadoop

    This post continues with our series of implementing the MapReduce algorithms found in the Data-Intensive Text Processing with MapReduce book.…

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  • Core Java👁 Image
    Bill BejeckNovember 28th, 2012
    1 336

    Google Guava EventBus for Event Programming

     It’s a given in any software application there are objects that need to share information in order to get work…

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    Bill BejeckNovember 23rd, 2012
    0 183

    Guava Functions & Java 8 Lambdas

    I recently read Brian Goetz’s The State of the Lambda and after reading that article I wanted to try using…

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    Bill BejeckNovember 22nd, 2012
    0 207

    Google Guava Cache

    This Post is a continuation of my series on Google Guava, this time covering Guava Cache. Guava Cache offers more…

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    Bill BejeckNovember 21st, 2012
    0 156

    Google Guava – Futures

    This post is a continuation of my series on Google Guava, this time covering Futures. The Futures class is a…

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    Bill BejeckNovember 20th, 2012
    0 181

    Google Guava Concurrency – ListenableFuture

    In my last post I covered using the Monitor class from the com.google.common.util.concurrent package in the Guava Library. In this…

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    Bill BejeckNovember 19th, 2012
    1 176

    Google Guava – Synchronization with Monitor

    The Google Guava project is a collection of libraries that every Java developer should become familiar with. The Guava libraries…

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  • Enterprise Java👁 Image
    Bill BejeckNovember 1st, 2012
    0 304

    Testing Hadoop Programs with MRUnit

     This post will take a slight detour from implementing the patterns found in Data-Intensive Processing with MapReduce to discuss something…

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  • Enterprise Java👁 Image
    Bill BejeckOctober 17th, 2012
    0 171

    MapReduce: Working Through Data-Intensive Text Processing – Local Aggregation Part II

    This post continues with the series on implementing algorithms found in the Data Intensive Processing with MapReduce book. Part one…

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