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| <p class="shortcomment cmt">Core Spark functionality.</p><div class="fullcomment"><div class="comment cmt"><p>Core Spark functionality. <a href="SparkContext.html" class="extype" name="org.apache.spark.SparkContext">org.apache.spark.SparkContext</a> serves as the main entry point to |
| Spark, while <a href="rdd/RDD.html" class="extype" name="org.apache.spark.rdd.RDD">org.apache.spark.rdd.RDD</a> is the data type representing a distributed collection, |
| and provides most parallel operations.</p><p>In addition, <a href="rdd/PairRDDFunctions.html" class="extype" name="org.apache.spark.rdd.PairRDDFunctions">org.apache.spark.rdd.PairRDDFunctions</a> contains operations available only on RDDs |
| of key-value pairs, such as <code>groupByKey</code> and <code>join</code>; <a href="rdd/DoubleRDDFunctions.html" class="extype" name="org.apache.spark.rdd.DoubleRDDFunctions">org.apache.spark.rdd.DoubleRDDFunctions</a> |
| contains operations available only on RDDs of Doubles; and |
| <a href="rdd/SequenceFileRDDFunctions.html" class="extype" name="org.apache.spark.rdd.SequenceFileRDDFunctions">org.apache.spark.rdd.SequenceFileRDDFunctions</a> contains operations available on RDDs that can |
| be saved as SequenceFiles. These operations are automatically available on any RDD of the right |
| type (e.g. RDD[(Int, Int)] through implicit conversions.</p><p>Java programmers should reference the <a href="api/java/index.html" class="extype" name="org.apache.spark.api.java">org.apache.spark.api.java</a> package |
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| <p class="shortcomment cmt">Spark's broadcast variables, used to broadcast immutable datasets to all nodes.</p><div class="fullcomment"><div class="comment cmt"><p>Spark's broadcast variables, used to broadcast immutable datasets to all nodes. |
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| </span> |
| |
| <p class="shortcomment cmt"><span class="badge" style="float: right;">ALPHA COMPONENT</span> |
| GraphX is a graph processing framework built on top of Spark.</p><div class="fullcomment"><div class="comment cmt"><p><span class="badge" style="float: right;">ALPHA COMPONENT</span> |
| GraphX is a graph processing framework built on top of Spark. |
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| <p class="shortcomment cmt">IO codecs used for compression.</p><div class="fullcomment"><div class="comment cmt"><p>IO codecs used for compression. See <a href="io/CompressionCodec.html" class="extype" name="org.apache.spark.io.CompressionCodec">org.apache.spark.io.CompressionCodec</a>. |
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| <p class="shortcomment cmt">DataFrame-based machine learning APIs to let users quickly assemble and configure practical |
| machine learning pipelines.</p><div class="fullcomment"><div class="comment cmt"><p>DataFrame-based machine learning APIs to let users quickly assemble and configure practical |
| machine learning pipelines. |
| </p></div><dl class="attributes block"> <dt>Definition Classes</dt><dd><a href="index.html" class="extype" name="org.apache.spark">spark</a></dd></dl></div> |
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| |
| <p class="shortcomment cmt">RDD-based machine learning APIs (in maintenance mode).</p><div class="fullcomment"><div class="comment cmt"><p>RDD-based machine learning APIs (in maintenance mode).</p><p>The <code>spark.mllib</code> package is in maintenance mode as of the Spark 2.0.0 release to encourage |
| migration to the DataFrame-based APIs under the <a href="ml/index.html" class="extype" name="org.apache.spark.ml">org.apache.spark.ml</a> package. |
| While in maintenance mode,</p><ul><li>no new features in the RDD-based <code>spark.mllib</code> package will be accepted, unless they block |
| implementing new features in the DataFrame-based <code>spark.ml</code> package;</li><li>bug fixes in the RDD-based APIs will still be accepted.</li></ul><p>The developers will continue adding more features to the DataFrame-based APIs in the 2.x series |
| to reach feature parity with the RDD-based APIs. |
| And once we reach feature parity, this package will be deprecated. |
| </p></div><dl class="attributes block"> <dt>Definition Classes</dt><dd><a href="index.html" class="extype" name="org.apache.spark">spark</a></dd><dt>See also</dt><dd><span class="cmt"><p><a href="https://issues.apache.org/jira/browse/SPARK-4591">SPARK-4591</a> to track |
| the progress of feature parity</p></span></dd></dl></div> |
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| |
| <p class="shortcomment cmt">Support for approximate results.</p><div class="fullcomment"><div class="comment cmt"><p>Support for approximate results. This provides convenient api and also implementation for |
| approximate calculation. |
| </p></div><dl class="attributes block"> <dt>Definition Classes</dt><dd><a href="index.html" class="extype" name="org.apache.spark">spark</a></dd><dt>See also</dt><dd><span class="cmt"><p><a href="rdd/RDD.html#countApprox(timeout:Long,confidence:Double):org.apache.spark.partial.PartialResult[org.apache.spark.partial.BoundedDouble]" class="extmbr" name="org.apache.spark.rdd.RDD#countApprox">org.apache.spark.rdd.RDD.countApprox</a></p></span></dd></dl></div> |
| </li><li name="org.apache.spark.rdd" visbl="pub" class="indented4 " data-isabs="false" fullComment="yes" group="Ungrouped"> |
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| <a title="Provides several RDD implementations." href="rdd/index.html"><span class="name">rdd</span></a> |
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| |
| <p class="shortcomment cmt">Provides several RDD implementations.</p><div class="fullcomment"><div class="comment cmt"><p>Provides several RDD implementations. See <a href="rdd/RDD.html" class="extype" name="org.apache.spark.rdd.RDD">org.apache.spark.rdd.RDD</a>. |
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| <p class="shortcomment cmt">Spark's scheduling components.</p><div class="fullcomment"><div class="comment cmt"><p>Spark's scheduling components. This includes the <code>org.apache.spark.scheduler.DAGScheduler</code> and |
| lower level <code>org.apache.spark.scheduler.TaskScheduler</code>. |
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| <div id="comment" class="fullcommenttop"><div class="comment cmt"><p>:: DeveloperApi :: |
| A <code>org.apache.spark.scheduler.ShuffleMapTask</code> that completed successfully earlier, but we |
| lost the executor before the stage completed. This means Spark needs to reschedule the task |
| to be re-executed on a different executor. |
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