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| <li> |
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| <a href="/docs/latest/distributed-computing/executor-service" |
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| class='' |
| >Executor Service</a> |
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| <li> |
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| <a href="/docs/latest/distributed-computing/map-reduce" |
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| class='' |
| >MapReduce API</a> |
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| </li> |
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| <li> |
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| <a href="/docs/latest/distributed-computing/load-balancing" |
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| class='' |
| >Load Balancing</a> |
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| </li> |
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| <li> |
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| <a href="/docs/latest/distributed-computing/fault-tolerance" |
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| class='' |
| >Fault Tolerance</a> |
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| <li> |
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| <a href="/docs/latest/distributed-computing/job-scheduling" |
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| class='' |
| >Job Scheduling</a> |
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| <li> |
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| <a href="/docs/latest/collocated-computations" class='' >Colocating Computations with Data</a> |
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| <a href="/docs/latest/events/listening-to-events" |
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| class='' |
| >Enabling and Listenting to Events</a> |
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| <li> |
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| <a href="/docs/latest/events/events" |
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| <a href="/docs/latest/near-cache" class='' >Near Caches</a> |
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| <a href="/docs/latest/platform-cache" class='' >.NET Platform Cache</a> |
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| class='' |
| >Queue and Set</a> |
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| <li> |
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| <a href="/docs/latest/data-structures/atomic-types" |
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| >Atomic Types</a> |
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| <li> |
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| <a href="/docs/latest/data-structures/countdownlatch" |
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| class='' |
| >CountDownLatch</a> |
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| <li> |
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| <a href="/docs/latest/data-structures/atomic-sequence" |
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| <a href="/docs/latest/data-structures/semaphore" |
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| class='' |
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| <li><a href="/docs/latest//machine-learning/regression/knn-regression" class=''>k-NN Regression</a></li> |
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| <li><a href="/docs/latest//machine-learning/clustering/introduction" class=''>Introduction</a></li> |
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| <li><a href="/docs/latest//machine-learning/clustering/k-means-clustering" class=''>K-Means Clustering</a></li> |
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| <li><a href="/docs/latest//machine-learning/clustering/gaussian-mixture" class=''>Gaussian mixture (GMM)</a></li> |
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| <li> |
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| <a href="/docs/latest/machine-learning/preprocessing" |
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| >Preprocessing</a> |
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| <li> |
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| class='collapsed '>Model Selection<img class="state-indicator" src="/assets/images/left-nav-arrow.svg"></button> |
| <nav class="sub_pages collapsed"> |
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| <li><a href="/docs/latest//machine-learning/model-selection/introduction" class=''>Introduction</a></li> |
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| <li><a href="/docs/latest//machine-learning/model-selection/evaluator" class=''>Evaluator</a></li> |
| |
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| <li><a href="/docs/latest//machine-learning/model-selection/split-the-dataset-on-test-and-train-datasets" class=''>Split the dataset on test and train datasets</a></li> |
| |
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| <li><a href="/docs/latest//machine-learning/model-selection/hyper-parameter-tuning" class=''>Hyper-parameter tuning</a></li> |
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| <li><a href="/docs/latest//machine-learning/model-selection/pipeline-api" class=''>Pipeline API</a></li> |
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| </nav> |
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| <li> |
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| <a href="/docs/latest/machine-learning/multiclass-classification" |
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| class='' |
| >Multiclass Classification</a> |
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| |
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| <li> |
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| <button |
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| <li><a href="/docs/latest//machine-learning/ensemble-methods/introduction" class=''></a></li> |
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| <li><a href="/docs/latest//machine-learning/ensemble-methods/stacking" class=''>Stacking</a></li> |
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| <li><a href="/docs/latest//machine-learning/ensemble-methods/baggin" class=''>Bagging</a></li> |
| |
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| <li><a href="/docs/latest//machine-learning/ensemble-methods/random-forest" class=''>Random Forest</a></li> |
| |
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| <li><a href="/docs/latest//machine-learning/ensemble-methods/gradient-boosting" class=''>Gradient Boosting</a></li> |
| |
| </nav> |
| |
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| <li> |
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| <a href="/docs/latest/machine-learning/recommendation-systems" |
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| class='' |
| >Recommendation Systems</a> |
| |
| </li> |
| |
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| <li> |
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| <button |
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| <li><a href="/docs/latest//machine-learning/importing-model/introduction" class=''>Introduction</a></li> |
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| <li><a href="/docs/latest//machine-learning/importing-model/model-import-from-gxboost" class=''>Import Model from XGBoost</a></li> |
| |
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| <li><a href="/docs/latest//machine-learning/importing-model/model-import-from-apache-spark" class=''>Import Model from Apache Spark</a></li> |
| |
| </nav> |
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| </li> |
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| </nav> |
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| <a href="/docs/latest/monitoring-metrics/intro" |
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| >Introduction</a> |
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| <li> |
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| <a href="/docs/latest/monitoring-metrics/cluster-id" |
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| class='' |
| >Cluster ID and Tag</a> |
| |
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| <li><a href="/docs/latest//monitoring-metrics/configuring-metrics" class=''>Configuring Metrics</a></li> |
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| <li><a href="/docs/latest//monitoring-metrics/metrics" class=''>JMX Metrics</a></li> |
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| <li><a href="/docs/latest//security/tde" class=''>Introduction</a></li> |
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| >Thin Clients Overview</a> |
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| <a href="/docs/latest/thin-clients/java-thin-client" |
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| >Java Thin Client</a> |
| |
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| <a href="/docs/latest/thin-clients/dotnet-thin-client" |
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| >.NET Thin Client</a> |
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| <li> |
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| <a href="/docs/latest/thin-clients/cpp-thin-client" |
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| >C++ Thin Client</a> |
| |
| </li> |
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| <li> |
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| <a href="/docs/latest/thin-clients/python-thin-client" |
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| class='' |
| >Python Thin Client</a> |
| |
| </li> |
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| <li> |
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| <a href="/docs/latest/thin-clients/php-thin-client" |
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| class='' |
| >PHP Thin Client</a> |
| |
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| <li> |
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| <a href="/docs/latest/thin-clients/nodejs-thin-client" |
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| class='' |
| >Node.js Thin Client</a> |
| |
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| |
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| <button |
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| <li><a href="/docs/latest//binary-client-protocol/binary-client-protocol" class=''>Binary Client Protocol</a></li> |
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| <li><a href="/docs/latest//binary-client-protocol/data-format" class=''>Data Format</a></li> |
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| <li><a href="/docs/latest//binary-client-protocol/key-value-queries" class=''>Key-Value Queries</a></li> |
| |
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| <li><a href="/docs/latest//binary-client-protocol/sql-and-scan-queries" class=''>SQL and Scan Queries</a></li> |
| |
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| <li><a href="/docs/latest//binary-client-protocol/binary-type-metadata" class=''>Binary Types Metadata</a></li> |
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| <li><a href="/docs/latest//binary-client-protocol/cache-configuration" class=''>Cache Configuration</a></li> |
| |
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| <li> |
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| <a href="/docs/latest/SQL/ODBC/odbc-driver" |
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| class='' |
| >ODBC Driver</a> |
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| </li> |
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| |
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| <li> |
| |
| <a href="/docs/latest/SQL/ODBC/connection-string-dsn" |
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| class='' |
| >Connection String and DSN</a> |
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| </li> |
| |
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| |
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| <li> |
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| <a href="/docs/latest/SQL/ODBC/querying-modifying-data" |
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| class='' |
| >Querying and Modifying Data</a> |
| |
| </li> |
| |
| |
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| |
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| <li> |
| |
| <a href="/docs/latest/SQL/ODBC/specification" |
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| class='' |
| >Specification</a> |
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| </li> |
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| |
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| <li> |
| |
| <a href="/docs/latest/SQL/ODBC/data-types" |
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| class='' |
| >Data Types</a> |
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| </li> |
| |
| |
| |
| |
| |
| <li> |
| |
| <a href="/docs/latest/SQL/ODBC/error-codes" |
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| class='' |
| >Error Codes</a> |
| |
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| |
| |
| </nav> |
| |
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| <li> |
| |
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| <a href="/docs/latest/restapi" class='' >REST API</a> |
| |
| </li> |
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| <li> |
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| |
| <a href="/docs/latest/control-script" class='' >Control Script</a> |
| |
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| <a href="/docs/latest/plugins" class='' >Plugins</a> |
| |
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| <li> |
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| |
| <a href="/docs/latest/sqlline" class='' >SQLLine</a> |
| |
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| |
| <li> |
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| <button type='button' data-guide-url="" class='group-toggle collapsed '>Ignite for Spark<img class="state-indicator" src="/assets/images/left-nav-arrow.svg"></button> |
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| <li> |
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| <a href="/docs/latest/ignite-for-spark/overview" |
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| class='' |
| >Overview</a> |
| |
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| |
| |
| |
| <li> |
| |
| <a href="/docs/latest/ignite-for-spark/ignitecontext-and-rdd" |
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| class='' |
| >IgniteContext and IgniteRDD</a> |
| |
| </li> |
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| <article data-swiftype-index='true'> |
| <a class='edit-link' href="https://github.com/apache/ignite/tree/IGNITE-7595/docs/_docs/ignite-for-spark/ignitecontext-and-rdd.adoc" target="_blank">Edit</a> |
| |
| <h1>IgniteContext and IgniteRDD</h1> |
| |
| <div class="sect1"> |
| <h2 id="ignitecontext">IgniteContext</h2> |
| <div class="sectionbody"> |
| <div class="paragraph"> |
| <p>IgniteContext is the main entry point to Spark-Ignite integration. To create an instance of Ignite context, user must provide an instance of SparkContext and a closure creating <code>IgniteConfiguration</code> (configuration factory). Ignite context will make sure that server or client Ignite nodes exist in all involved job instances. Alternatively, a path to an XML configuration file can be passed to <code>IgniteContext</code> constructor which will be used to configure nodes being started.</p> |
| </div> |
| <div class="paragraph"> |
| <p>When creating an <code>IgniteContext</code> instance, an optional boolean <code>client</code> argument (defaulting to <code>true</code>) can be passed to context constructor. This is typically used in a Shared Deployment installation. When <code>client</code> is set to <code>false</code>, context will operate in embedded mode and will start server nodes on all workers during the context construction. This is required in an Embedded Deployment installation. See <a href="/docs/latest/ignite-for-spark/installation">Installation</a> for information on deployment configurations.</p> |
| </div> |
| <div class="admonitionblock caution"> |
| <table> |
| <tr> |
| <td class="icon"> |
| <div class="title">Caution</div> |
| </td> |
| <td class="content"> |
| <h3 id="embedded-mode-deprecation" class="discrete">Embedded Mode Deprecation</h3> |
| <div class="paragraph"> |
| <p>Embedded mode implies starting Ignite server nodes within Spark executors which can cause unexpected rebalancing or even data loss. Therefore this mode is currently deprecated and will be eventually discontinued. Consider starting a separate Ignite cluster and using standalone mode to avoid data consistency and performance issues.</p> |
| </div> |
| </td> |
| </tr> |
| </table> |
| </div> |
| <div class="paragraph"> |
| <p>Once <code>IgniteContext</code> is created, instances of <code>IgniteRDD</code> may be obtained using <code>fromCache</code> methods. It is not required that requested cache exist in Ignite cluster when RDD is created. If the cache with the given name does not exist, it will be created using provided configuration or template configuration.</p> |
| </div> |
| <div class="paragraph"> |
| <p>For example, the following code will create an Ignite context with default Ignite configuration</p> |
| </div> |
| <div class="listingblock"> |
| <div class="content"> |
| <pre class="rouge highlight"><code data-lang="scala"><span class="k">val</span> <span class="nv">igniteContext</span> <span class="k">=</span> <span class="k">new</span> <span class="nc">IgniteContext</span><span class="o">(</span><span class="n">sparkContext</span><span class="o">,</span> |
| <span class="o">()</span> <span class="k">=></span> <span class="k">new</span> <span class="nc">IgniteConfiguration</span><span class="o">())</span></code></pre> |
| </div> |
| </div> |
| <div class="paragraph"> |
| <p>The following code will create an Ignite context configured from a file <code>example-shared-rdd.xml</code>:</p> |
| </div> |
| <div class="listingblock"> |
| <div class="content"> |
| <pre class="rouge highlight"><code data-lang="scala"><span class="k">val</span> <span class="nv">igniteContext</span> <span class="k">=</span> <span class="k">new</span> <span class="nc">IgniteContext</span><span class="o">(</span><span class="n">sparkContext</span><span class="o">,</span> |
| <span class="s">"examples/config/spark/example-shared-rdd.xml"</span><span class="o">)</span></code></pre> |
| </div> |
| </div> |
| </div> |
| </div> |
| <div class="sect1"> |
| <h2 id="igniterdd">IgniteRDD</h2> |
| <div class="sectionbody"> |
| <div class="paragraph"> |
| <p><code>IgniteRDD</code> is an implementation of Spark RDD abstraction representing a live view of Ignite cache. <code>IgniteRDD</code> is not immutable, all changes in Ignite cache (regardless whether they were caused by another RDD or external changes in cache) will be visible to RDD users immediately.</p> |
| </div> |
| <div class="paragraph"> |
| <p><code>IgniteRDD</code> utilizes partitioned nature of Ignite caches and provides partitioning information to Spark executor. Number of partitions in <code>IgniteRDD</code> equals to the number of partitions in underlying Ignite cache. <code>IgniteRDD</code> also provides affinity information to Spark via <code>getPrefferredLocations</code> method so that RDD computations use data locality.</p> |
| </div> |
| </div> |
| </div> |
| <div class="sect1"> |
| <h2 id="reading-values-from-ignite">Reading values from Ignite</h2> |
| <div class="sectionbody"> |
| <div class="paragraph"> |
| <p>Since <code>IgniteRDD</code> is a live view of Ignite cache, there is no need to explicitly load data to Spark application from Ignite. All RDD methods are available to use right away after an instance of <code>IgniteRDD</code> is created.</p> |
| </div> |
| <div class="paragraph"> |
| <p>For example, assuming an Ignite cache with name "partitioned" contains string values, the following code will find all values that contain the word "Ignite":</p> |
| </div> |
| <div class="listingblock"> |
| <div class="content"> |
| <pre class="rouge highlight"><code data-lang="scala"><span class="k">val</span> <span class="nv">cache</span> <span class="k">=</span> <span class="nv">igniteContext</span><span class="o">.</span><span class="py">fromCache</span><span class="o">(</span><span class="s">"partitioned"</span><span class="o">)</span> |
| <span class="k">val</span> <span class="nv">result</span> <span class="k">=</span> <span class="nv">cache</span><span class="o">.</span><span class="py">filter</span><span class="o">(</span><span class="nv">_</span><span class="o">.</span><span class="py">_2</span><span class="o">.</span><span class="py">contains</span><span class="o">(</span><span class="s">"Ignite"</span><span class="o">)).</span><span class="py">collect</span><span class="o">()</span></code></pre> |
| </div> |
| </div> |
| </div> |
| </div> |
| <div class="sect1"> |
| <h2 id="saving-values-to-ignite">Saving values to Ignite</h2> |
| <div class="sectionbody"> |
| <div class="paragraph"> |
| <p>Since Ignite caches operate on key-value pairs, the most straightforward way to save values to Ignite cache is to use a Spark tuple RDD and <code>savePairs</code> method. This method will take advantage of the RDD partitioning and store value to cache in a parallel manner, if possible.</p> |
| </div> |
| <div class="paragraph"> |
| <p>It is also possible to save value-only RDD into Ignite cache using <code>saveValues</code> method. In this case <code>IgniteRDD</code> will generate a unique affinity-local key for each value being stored into the cache.</p> |
| </div> |
| <div class="paragraph"> |
| <p>For example, the following code will store pairs of integers from 1 to 10000 into cache named "partitioned" using 10 parallel store operations:</p> |
| </div> |
| <div class="listingblock"> |
| <div class="content"> |
| <pre class="rouge highlight"><code data-lang="scala"><span class="k">val</span> <span class="nv">cacheRdd</span> <span class="k">=</span> <span class="nv">igniteContext</span><span class="o">.</span><span class="py">fromCache</span><span class="o">(</span><span class="s">"partitioned"</span><span class="o">)</span> |
| |
| <span class="nv">cacheRdd</span><span class="o">.</span><span class="py">savePairs</span><span class="o">(</span><span class="nv">sparkContext</span><span class="o">.</span><span class="py">parallelize</span><span class="o">(</span><span class="mi">1</span> <span class="n">to</span> <span class="mi">10000</span><span class="o">,</span> <span class="mi">10</span><span class="o">).</span><span class="py">map</span><span class="o">(</span><span class="n">i</span> <span class="k">=></span> <span class="o">(</span><span class="n">i</span><span class="o">,</span> <span class="n">i</span><span class="o">)))</span></code></pre> |
| </div> |
| </div> |
| </div> |
| </div> |
| <div class="sect1"> |
| <h2 id="running-sql-queries-against-ignite-cache">Running SQL queries against Ignite cache</h2> |
| <div class="sectionbody"> |
| <div class="paragraph"> |
| <p>When Ignite cache is configured with the indexing subsystem enabled, it is possible to run SQL queries against the cache using <code>objectSql</code> and <code>sql</code> methods. See <a href="/docs/latest/SQL/sql-introduction">Working with SQL</a> for more information about Ignite SQL queries.</p> |
| </div> |
| <div class="paragraph"> |
| <p>For example, assuming the "partitioned" cache is configured to index pairs of integers, the following code will get all integers in the range (10, 100):</p> |
| </div> |
| <div class="listingblock"> |
| <div class="content"> |
| <pre class="rouge highlight"><code data-lang="scala"><span class="k">val</span> <span class="nv">cacheRdd</span> <span class="k">=</span> <span class="nv">igniteContext</span><span class="o">.</span><span class="py">fromCache</span><span class="o">(</span><span class="s">"partitioned"</span><span class="o">)</span> |
| |
| <span class="k">val</span> <span class="nv">result</span> <span class="k">=</span> <span class="nv">cacheRdd</span><span class="o">.</span><span class="py">sql</span><span class="o">(</span><span class="s">"select _val from Integer where val > ? and val < ?"</span><span class="o">,</span> <span class="mi">10</span><span class="o">,</span> <span class="mi">100</span><span class="o">)</span></code></pre> |
| </div> |
| </div> |
| </div> |
| </div> |
| <div class="sect1"> |
| <h2 id="example">Example</h2> |
| <div class="sectionbody"> |
| <div class="paragraph"> |
| <p>There are a couple of examples available on GitHub that demonstrate the usage of <code>IgniteRDD</code>:</p> |
| </div> |
| <div class="ulist"> |
| <ul> |
| <li> |
| <p><a href="https://github.com/apache/ignite/tree/master/examples/src/main/scala/org/apache/ignite/scalar/examples/spark/ScalarSharedRDDExample.scala" target="_blank" rel="noopener">Scala Example</a></p> |
| </li> |
| <li> |
| <p><a href="https://github.com/apache/ignite/tree/master/examples/src/main/spark/org/apache/ignite/examples/spark/SharedRDDExample.java" target="_blank" rel="noopener">Java Example</a></p> |
| </li> |
| </ul> |
| </div> |
| </div> |
| </div> |
| <div class="copyright"> |
| © 2020 The Apache Software Foundation.<br/> |
| Apache, Apache Ignite, the Apache feather and the Apache Ignite logo are either registered trademarks or trademarks of The Apache Software Foundation. |
| |
| </div> |
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| </article> |
| <nav class="right-nav" data-swiftype-index='false'> |
| <ul class="sectlevel1"> |
| <li><a href="#ignitecontext">IgniteContext</a></li> |
| <li><a href="#igniterdd">IgniteRDD</a></li> |
| <li><a href="#reading-values-from-ignite">Reading values from Ignite</a></li> |
| <li><a href="#saving-values-to-ignite">Saving values to Ignite</a></li> |
| <li><a href="#running-sql-queries-against-ignite-cache">Running SQL queries against Ignite cache</a></li> |
| <li><a href="#example">Example</a></li> |
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