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copied!<p>You should become familiar with the <a href="http://java.sun.com/j2se/6/docs/api/index.html?java/util/concurrent/package-summary.html" rel="nofollow noreferrer">java.util.concurrent</a> package. It has simple and robust primitives for parallel programming upon which to base higher-level libraries. One example of such a library is <a href="http://functionaljava.org" rel="nofollow noreferrer">Functional Java</a>, which has <a href="http://functionaljava.googlecode.com/svn/artifacts/2.20/javadoc/fj/control/parallel/ParModule.html" rel="nofollow noreferrer">an easy-to-use module for parallel programming</a>.</p> <p>For example, here is the canonical MapReduce example written using Functional Java. It counts the number of words in a set of documents, assuming documents are Streams of characters:</p> <pre><code>public static long countWords(final List<Stream<Character>> documents, final ParModule m) { return m.parFoldMap(documents, new F<Stream<Character>, Long>() { public Long f(final Stream<Character> document) { return (long)fromStream(document).words().length(); }}, longAdditionMonoid) .claim(); } </code></pre> <p>To instantiate ParModule, you give it a parallel Strategy. You can implement your own Strategies, or use one that's supplied. Here's one that uses a fixed pool of 16 threads:</p> <pre><code>ExecutorService pool = newFixedThreadPool(16); ParModule m = parModule(executorStrategy(pool)); </code></pre> <p>You need the following imports for the example above:</p> <pre><code>import fj.F; import fj.data.Stream; import fj.control.parallel.ParModule; import static fj.control.parallel.ParModule.parModule; import static fj.pre.Monoid.longAdditionMonoid; import static fj.data.LazyString.fromStream; import static fj.control.parallel.Strategy.executorStrategy; import static java.util.concurrent.Executors.newFixedThreadPool; import java.util.concurrent.ExecutorService; </code></pre>

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