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    <title>Apache Ignite - In-Memory Compute Grid</title>
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        <section id="computegrid" class="page-section">
            <div class="col-sm-12 col-md-12 col-xs-12" style="padding:0 0 20px 0;">
                <div class="col-sm-6 col-md-7 col-xs-12" style="padding-left:0; padding-right:0">
                    <h2 class="first">In-Memory Compute Grid</h2>
                    <p>
                        Distributed computations are performed in parallel fashion to gain high performance,
                        low latency, and linear scalability. Ignite compute grid provides a set of simple APIs
                        that allow users distribute computations and data processing across multiple computers
                        in the cluster.
                    </p>
                    <p>
                        Distributed parallel processing is based on the ability to take any computation and
                        execute it on any set of cluster nodes and return the results back.
                    </p>
                    <div class="videos">
                        <div class="page-heading">Videos:</div>
                        <ul>
                            <li>
                                <i class="fa fa-lg fa-play-circle-o"></i>
                                    <span class="video-title">
                                        <a target="youtube" href="https://www.youtube.com/watch?v=J775J77_-B8">Getting Started with Compute Grid</a>
                                    </span>
                                <span class="video-duration">03:50</span>
                            </li>
                        </ul>
                    </div>
                </div>
                <br/>
                <div class="col-sm-6 col-md-5 col-xs-12" style="padding-right:0">
                    <img class="first img-responsive" src="/images/in_memory_compute.png" width="400px" style="float:right;"/>
                </div>
            </div>
            <div class="code-examples">
                <div class="page-heading">Code Examples:</div>
                <!-- Nav tabs -->
                <ul id="compute-examples" class="nav nav-tabs">
                    <li class="active"><a href="#compute-example-broadcast" aria-controls="home" data-toggle="tab">Broadcast</a></li>
                    <li><a href="#compute-example-countchars" aria-controls="profile" data-toggle="tab">Count Characters with Callable</a></li>
                    <li><a href="#compute-example-closure" aria-controls="profile" data-toggle="tab">Count Characters with Closure</a></li>
                </ul>

                <!-- Tab panes -->
                <div class="tab-content">
                    <div class="tab-pane active" id="compute-example-broadcast">
                            <pre class="brush:java">
                                Ignite ignite = Ignition.ignite();

                                // Print out hello message on all cluster nodes.
                                ignite.compute().broadcast(() -> System.out.println("Hello Node!"));
                            </pre>
                    </div>
                    <div class="tab-pane" id="compute-example-countchars">
                            <pre class="brush:java">
                                Collection&lt;IgniteCallable&lt;Integer&gt;&gt; calls = new ArrayList&lt;&gt;();

                                // Iterate through all words in the sentence and create callable jobs.
                                for (String word : "How Many Characters".split(" "))
                                    calls.add(word::length);

                                // Execute collection of callables on the Ignite cluster.
                                Collection&lt;Integer&gt; res = ignite.compute().call(calls);

                                // Add all the word lengths received from cluster nodes.
                                int total = res.stream().mapToInt(Integer::intValue).sum();
                            </pre>
                    </div>
                    <div class="tab-pane" id="compute-example-closure">
                            <pre class="brush:java">
                                IgniteCompute compute  = ignite.compute();

                                // Execute closure on all cluster nodes.
                                Collection&lt;Integer&gt; res = ignite.compute().apply(
                                    String::length,
                                    Arrays.asList("How Many Characters".split(" "))
                                );

                                // Add all the word lengths received from cluster nodes.
                                int total = res.stream().mapToInt(Integer::intValue).sum();
                            </pre>
                    </div>
                </div>
            </div>

            <div class="page-heading">GitHub Examples:</div>
            <p>
                Also see <a href="https://github.com/apache/incubator-ignite/tree/master/examples/src/main/java/org/apache/ignite/examples/computegrid" target="github">Java 7 examples</a>
                and <a href="https://github.com/apache/incubator-ignite/tree/master/examples/src/main/java8/org/apache/ignite/examples/java8/computegrid" target="github">Java 8 examples</a> available on GitHub.
            </p>
        </section>
        <section id="key-features" class="page-section">
            <h2>Compute Grid Features</h2>
            <table class="formatted" name="Compute Grid Features">
                <thead>
                    <tr>
                        <th width="35%" class="left">Feature</th>
                        <th>Description</th>
                    </tr>
                </thead>
                <tbody>
                    <tr>
                        <td class="left">Distributed Closure Execution</td>
                        <td>
                            <p>
                                Ignite compute grid allows to broadcast and load-balance any closure within the cluster
                                or a cluster group, including Java 8 lambdas, as well as plain Java runnables and callables.
                            </p>
                            <div class="page-links">
                                <a href=http://apacheignite.readme.io/docs/distributed-closures" target="docs">Docs for this Feature <i class="fa fa-angle-double-right"></i></a>
                            </div>
                        </td>
                    </tr>
                    <tr>
                        <td class="left">ForkJoin Processing</td>
                        <td>
                            <p>
                                <code>ComputeTask</code> is Ignite abstraction for the in-memory <code>ForkJoin</code>,
                                paradigm, which is a light-weight form of MapReduce. Pure
                                MapReduce was never built for performance and only works well when dealing with
                                off-line batch oriented processing (e.g. Hadoop MapReduce).
                            </p>
                            <p>
                                However, when computing on data that resides in-memory, real-time low latencies
                                and high throughput usually take the highest priority. Also, simplicity of the API
                                becomes very important as well. With that in mind, Ignite introduced the
                                <code>ComputeTask</code> API, which is Ignite <code>ForkJoin</code> (or a
                                light-weight MapReduce) implementation.
                            </p>
                            <div class="page-links">
                                <a href="http://apacheignite.readme.io/docs/compute-tasks" target="docs">Docs for this Feature <i class="fa fa-angle-double-right"></i></a>
                            </div>
                        </td>
                    </tr>
                    <tr>
                        <td class="left">Clustered ExecutorService</td>
                        <td>
                            <p>
                                Ignite provides a cluster-enabled implementation of standard JDK
                                <code>ExecutorService</code> and automatically executes all the computations in
                                load-balanced fashion within the cluster. Your computations also become fault-tolerant
                                and are guaranteed to execute as long as there is at least one node left. You can
                                think of it as a distributed cluster-enabled thread pool.
                            </p>
                            <div class="page-links">
                                <a href="http://apacheignite.readme.io/docs/executor-service" target="docs">Docs for this Feature <i class="fa fa-angle-double-right"></i></a>
                            </div>
                        </td>
                    </tr>
                    <tr>
                        <td class="left">Collocation of Compute & Data</td>
                        <td>
                            <p>
                                Collocation of computations with data allow for minimizing data serialization within the
                                network and can significantly improve performance and scalability of your application.
                                Whenever possible, you should always make best effort to collocate your computations
                                with the cluster nodes caching the data that needs to be processed.
                            </p>
                            <p>
                                Ignite provides various ways to collocate compute with data either automatically
                                or manually as needed.
                            </p>
                            <div class="page-links">
                                <a href="http://apacheignite.readme.io/docs/collocate-compute-and-data" target="docs">Docs for this Feature <i class="fa fa-angle-double-right"></i></a>
                            </div>
                        </td>
                    </tr>
                    <tr>
                        <td class="left">Fault Tolerance</td>
                        <td>
                            <p>
                                Ignite supports automatic job failover. In case of a node crash or any other error,
                                jobs are automatically transferred to other available nodes for re-execution.
                                The pluggable <code>FailoverSpi</code> is responsible for handling the selection of a
                                new node for the execution of a failed job.
                            </p>
                            <p>
                                <b>At Least Once Guarantee</b> - Ignite guarantees that as long as there is at
                                least one node standing, no job will ever be lost.
                            </p>
                            <div class="page-links">
                                <a href="http://apacheignite.readme.io/docs/fault-tolerance" target="docs">Docs for this Feature <i class="fa fa-angle-double-right"></i></a>
                            </div>
                        </td>
                    </tr>
                    <tr>
                        <td class="left">Load Balancing</td>
                        <td>
                            <p>
                                Load balancing component balances job distribution among cluster nodes. In Ignite
                                load balancing is achieved via a pluggable <code>LoadBalancingSpi</code> which controls
                                load on all nodes and makes sure that every node in the cluster is equally loaded.
                            </p>
                            <p>
                                In homogeneous environments with homogeneous tasks load balancing is achieved by random or
                                round-robin policies. However, in many other use cases, especially under uneven load,
                                more complex adaptive load-balancing policies are provided.
                            </p>
                            <div class="page-links">
                                <a href="http://apacheignite.readme.io/docs/load-balancing" target="docs">Docs for this Feature <i class="fa fa-angle-double-right"></i></a>
                            </div>
                        </td>
                    </tr>
                    <tr>
                        <td class="left">Job Checkpointing</td>
                        <td>
                            <p>
                                Checkpointing is supported via a pluggable <code>CheckpointSpi</code>. It
                                provides ability to save an intermediate job state. Checkpointing can be useful
                                when long running jobs need to store some intermediate state to protect from node
                                failures. Then on restart of a failed node, a job would load the saved checkpoint
                                and continue from where it left off.
                            </p>
                            <div class="page-links">
                                <a href="http://apacheignite.readme.io/docs/checkpointing" target="docs">Docs for this Feature <i class="fa fa-angle-double-right"></i></a>
                            </div>
                        </td>
                    </tr>
                    <tr>
                        <td class="left">Job Scheduling</td>
                        <td>
                            <p>
                                Pluggable <code>CollisionSpi</code> provides a fine-grained control over how the jobs
                                are scheduled once they arrive to a specific cluster node for execution. Various
                                policies are supported, including FIFO, Priority, or even job stealing.
                            </p>
                            <div class="page-links">
                                <a href="http://apacheignite.readme.io/docs/job-scheduling" target="docs">Docs for this Feature <i class="fa fa-angle-double-right"></i></a>
                            </div>
                        </td>
                    </tr>
                </tbody>
            </table>
        </section>
    </main>

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