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<div class="subTitle">org.apache.spark.rdd</div>
<h2 title="Class HadoopRDD" class="title">Class HadoopRDD<K,V></h2>
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<ul class="inheritance">
<li>java.lang.Object</li>
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<li><a href="../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">org.apache.spark.rdd.RDD</a><scala.Tuple2<K,V>></li>
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<li>org.apache.spark.rdd.HadoopRDD<K,V></li>
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<pre>public class <span class="strong">HadoopRDD<K,V></span>
extends <a href="../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a><scala.Tuple2<K,V>>
implements <a href="../../../../org/apache/spark/Logging.html" title="interface in org.apache.spark">Logging</a></pre>
<div class="block">:: DeveloperApi ::
An RDD that provides core functionality for reading data stored in Hadoop (e.g., files in HDFS,
sources in HBase, or S3), using the older MapReduce API (<code>org.apache.hadoop.mapred</code>).
<p>
Note: Instantiating this class directly is not recommended, please use
<code>org.apache.spark.SparkContext.hadoopRDD()</code>
<p>
param: sc The SparkContext to associate the RDD with.
param: broadcastedConf A general Hadoop Configuration, or a subclass of it. If the enclosed
variabe references an instance of JobConf, then that JobConf will be used for the Hadoop job.
Otherwise, a new JobConf will be created on each slave using the enclosed Configuration.
param: initLocalJobConfFuncOpt Optional closure used to initialize any JobConf that HadoopRDD
creates.
param: inputFormatClass Storage format of the data to be read.
param: keyClass Class of the key associated with the inputFormatClass.
param: valueClass Class of the value associated with the inputFormatClass.
param: minPartitions Minimum number of HadoopRDD partitions (Hadoop Splits) to generate.</div>
<dl><dt><span class="strong">See Also:</span></dt><dd><a href="../../../../serialized-form.html#org.apache.spark.rdd.HadoopRDD">Serialized Form</a></dd></dl>
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<caption><span>Constructors</span><span class="tabEnd"> </span></caption>
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<th class="colOne" scope="col">Constructor and Description</th>
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<td class="colOne"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#HadoopRDD(org.apache.spark.SparkContext, org.apache.spark.broadcast.Broadcast, scala.Option, java.lang.Class, java.lang.Class, java.lang.Class, int)">HadoopRDD</a></strong>(<a href="../../../../org/apache/spark/SparkContext.html" title="class in org.apache.spark">SparkContext</a> sc,
<a href="../../../../org/apache/spark/broadcast/Broadcast.html" title="class in org.apache.spark.broadcast">Broadcast</a><org.apache.spark.util.SerializableConfiguration> broadcastedConf,
scala.Option<scala.Function1<org.apache.hadoop.mapred.JobConf,scala.runtime.BoxedUnit>> initLocalJobConfFuncOpt,
java.lang.Class<? extends org.apache.hadoop.mapred.InputFormat<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>>> inputFormatClass,
java.lang.Class<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>> keyClass,
java.lang.Class<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>> valueClass,
int minPartitions)</code> </td>
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<tr class="rowColor">
<td class="colOne"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#HadoopRDD(org.apache.spark.SparkContext, org.apache.hadoop.mapred.JobConf, java.lang.Class, java.lang.Class, java.lang.Class, int)">HadoopRDD</a></strong>(<a href="../../../../org/apache/spark/SparkContext.html" title="class in org.apache.spark">SparkContext</a> sc,
org.apache.hadoop.mapred.JobConf conf,
java.lang.Class<? extends org.apache.hadoop.mapred.InputFormat<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>>> inputFormatClass,
java.lang.Class<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>> keyClass,
java.lang.Class<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>> valueClass,
int minPartitions)</code> </td>
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<caption><span>Methods</span><span class="tabEnd"> </span></caption>
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<th class="colFirst" scope="col">Modifier and Type</th>
<th class="colLast" scope="col">Method and Description</th>
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<td class="colFirst"><code>static void</code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#addLocalConfiguration(java.lang.String, int, int, int, org.apache.hadoop.mapred.JobConf)">addLocalConfiguration</a></strong>(java.lang.String jobTrackerId,
int jobId,
int splitId,
int attemptId,
org.apache.hadoop.mapred.JobConf conf)</code>
<div class="block">Add Hadoop configuration specific to a single partition and attempt.</div>
</td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code>void</code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#checkpoint()">checkpoint</a></strong>()</code>
<div class="block">Mark this RDD for checkpointing.</div>
</td>
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<tr class="altColor">
<td class="colFirst"><code><a href="../../../../org/apache/spark/InterruptibleIterator.html" title="class in org.apache.spark">InterruptibleIterator</a><scala.Tuple2<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>>></code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#compute(org.apache.spark.Partition, org.apache.spark.TaskContext)">compute</a></strong>(<a href="../../../../org/apache/spark/Partition.html" title="interface in org.apache.spark">Partition</a> theSplit,
<a href="../../../../org/apache/spark/TaskContext.html" title="class in org.apache.spark">TaskContext</a> context)</code>
<div class="block">:: DeveloperApi ::
Implemented by subclasses to compute a given partition.</div>
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<td class="colFirst"><code>static java.lang.Object</code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#CONFIGURATION_INSTANTIATION_LOCK()">CONFIGURATION_INSTANTIATION_LOCK</a></strong>()</code>
<div class="block">Configuration's constructor is not threadsafe (see SPARK-1097 and HADOOP-10456).</div>
</td>
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<td class="colFirst"><code>static boolean</code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#containsCachedMetadata(java.lang.String)">containsCachedMetadata</a></strong>(java.lang.String key)</code> </td>
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<td class="colFirst"><code>static java.lang.Object</code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#getCachedMetadata(java.lang.String)">getCachedMetadata</a></strong>(java.lang.String key)</code>
<div class="block">The three methods below are helpers for accessing the local map, a property of the SparkEnv of
the local process.</div>
</td>
</tr>
<tr class="altColor">
<td class="colFirst"><code>org.apache.hadoop.conf.Configuration</code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#getConf()">getConf</a></strong>()</code> </td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code>protected org.apache.hadoop.mapred.InputFormat<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>></code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#getInputFormat(org.apache.hadoop.mapred.JobConf)">getInputFormat</a></strong>(org.apache.hadoop.mapred.JobConf conf)</code> </td>
</tr>
<tr class="altColor">
<td class="colFirst"><code>protected org.apache.hadoop.mapred.JobConf</code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#getJobConf()">getJobConf</a></strong>()</code> </td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code><a href="../../../../org/apache/spark/Partition.html" title="interface in org.apache.spark">Partition</a>[]</code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#getPartitions()">getPartitions</a></strong>()</code>
<div class="block">Implemented by subclasses to return the set of partitions in this RDD.</div>
</td>
</tr>
<tr class="altColor">
<td class="colFirst"><code>scala.collection.Seq<java.lang.String></code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#getPreferredLocations(org.apache.spark.Partition)">getPreferredLocations</a></strong>(<a href="../../../../org/apache/spark/Partition.html" title="interface in org.apache.spark">Partition</a> split)</code>
<div class="block">Optionally overridden by subclasses to specify placement preferences.</div>
</td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code>protected java.lang.String</code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#inputFormatCacheKey()">inputFormatCacheKey</a></strong>()</code> </td>
</tr>
<tr class="altColor">
<td class="colFirst"><code>protected java.lang.String</code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#jobConfCacheKey()">jobConfCacheKey</a></strong>()</code> </td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code><U> <a href="../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a><U></code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#mapPartitionsWithInputSplit(scala.Function2, boolean, scala.reflect.ClassTag)">mapPartitionsWithInputSplit</a></strong>(scala.Function2<org.apache.hadoop.mapred.InputSplit,scala.collection.Iterator<scala.Tuple2<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>>>,scala.collection.Iterator<U>> f,
boolean preservesPartitioning,
scala.reflect.ClassTag<U> evidence$1)</code>
<div class="block">Maps over a partition, providing the InputSplit that was used as the base of the partition.</div>
</td>
</tr>
<tr class="altColor">
<td class="colFirst"><code><a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="class in org.apache.spark.rdd">HadoopRDD</a><<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>></code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#persist(org.apache.spark.storage.StorageLevel)">persist</a></strong>(<a href="../../../../org/apache/spark/storage/StorageLevel.html" title="class in org.apache.spark.storage">StorageLevel</a> storageLevel)</code>
<div class="block">Set this RDD's storage level to persist its values across operations after the first time
it is computed.</div>
</td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code>static int</code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#RECORDS_BETWEEN_BYTES_READ_METRIC_UPDATES()">RECORDS_BETWEEN_BYTES_READ_METRIC_UPDATES</a></strong>()</code>
<div class="block">Update the input bytes read metric each time this number of records has been read</div>
</td>
</tr>
<tr class="altColor">
<td class="colFirst"><code>static scala.Option<org.apache.spark.rdd.HadoopRDD.SplitInfoReflections></code></td>
<td class="colLast"><code><strong><a href="../../../../org/apache/spark/rdd/HadoopRDD.html#SPLIT_INFO_REFLECTIONS()">SPLIT_INFO_REFLECTIONS</a></strong>()</code> </td>
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<h3>Methods inherited from class org.apache.spark.rdd.<a href="../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a></h3>
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<pre>public HadoopRDD(<a href="../../../../org/apache/spark/SparkContext.html" title="class in org.apache.spark">SparkContext</a> sc,
<a href="../../../../org/apache/spark/broadcast/Broadcast.html" title="class in org.apache.spark.broadcast">Broadcast</a><org.apache.spark.util.SerializableConfiguration> broadcastedConf,
scala.Option<scala.Function1<org.apache.hadoop.mapred.JobConf,scala.runtime.BoxedUnit>> initLocalJobConfFuncOpt,
java.lang.Class<? extends org.apache.hadoop.mapred.InputFormat<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>>> inputFormatClass,
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java.lang.Class<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>> valueClass,
int minPartitions)</pre>
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<pre>public HadoopRDD(<a href="../../../../org/apache/spark/SparkContext.html" title="class in org.apache.spark">SparkContext</a> sc,
org.apache.hadoop.mapred.JobConf conf,
java.lang.Class<? extends org.apache.hadoop.mapred.InputFormat<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>>> inputFormatClass,
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java.lang.Class<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>> valueClass,
int minPartitions)</pre>
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<pre>public static java.lang.Object CONFIGURATION_INSTANTIATION_LOCK()</pre>
<div class="block">Configuration's constructor is not threadsafe (see SPARK-1097 and HADOOP-10456).
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<dl><dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public static int RECORDS_BETWEEN_BYTES_READ_METRIC_UPDATES()</pre>
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<pre>public static void addLocalConfiguration(java.lang.String jobTrackerId,
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int splitId,
int attemptId,
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<div class="block">Add Hadoop configuration specific to a single partition and attempt.</div>
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<pre>protected org.apache.hadoop.mapred.JobConf getJobConf()</pre>
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<pre>protected org.apache.hadoop.mapred.InputFormat<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>> getInputFormat(org.apache.hadoop.mapred.JobConf conf)</pre>
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<pre>public <a href="../../../../org/apache/spark/Partition.html" title="interface in org.apache.spark">Partition</a>[] getPartitions()</pre>
<div class="block"><strong>Description copied from class: <code><a href="../../../../org/apache/spark/rdd/RDD.html#getPartitions()">RDD</a></code></strong></div>
<div class="block">Implemented by subclasses to return the set of partitions in this RDD. This method will only
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<dl>
<dt><strong>Specified by:</strong></dt>
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<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public <a href="../../../../org/apache/spark/InterruptibleIterator.html" title="class in org.apache.spark">InterruptibleIterator</a><scala.Tuple2<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>>> compute(<a href="../../../../org/apache/spark/Partition.html" title="interface in org.apache.spark">Partition</a> theSplit,
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<div class="block"><strong>Description copied from class: <code><a href="../../../../org/apache/spark/rdd/RDD.html#compute(org.apache.spark.Partition, org.apache.spark.TaskContext)">RDD</a></code></strong></div>
<div class="block">:: DeveloperApi ::
Implemented by subclasses to compute a given partition.</div>
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<dt><strong>Specified by:</strong></dt>
<dd><code><a href="../../../../org/apache/spark/rdd/RDD.html#compute(org.apache.spark.Partition, org.apache.spark.TaskContext)">compute</a></code> in class <code><a href="../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a><scala.Tuple2<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>>></code></dd>
<dt><span class="strong">Parameters:</span></dt><dd><code>theSplit</code> - (undocumented)</dd><dd><code>context</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<h4>mapPartitionsWithInputSplit</h4>
<pre>public <U> <a href="../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a><U> mapPartitionsWithInputSplit(scala.Function2<org.apache.hadoop.mapred.InputSplit,scala.collection.Iterator<scala.Tuple2<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>>>,scala.collection.Iterator<U>> f,
boolean preservesPartitioning,
scala.reflect.ClassTag<U> evidence$1)</pre>
<div class="block">Maps over a partition, providing the InputSplit that was used as the base of the partition.</div>
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<a name="getPreferredLocations(org.apache.spark.Partition)">
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<h4>getPreferredLocations</h4>
<pre>public scala.collection.Seq<java.lang.String> getPreferredLocations(<a href="../../../../org/apache/spark/Partition.html" title="interface in org.apache.spark">Partition</a> split)</pre>
<div class="block"><strong>Description copied from class: <code><a href="../../../../org/apache/spark/rdd/RDD.html#getPreferredLocations(org.apache.spark.Partition)">RDD</a></code></strong></div>
<div class="block">Optionally overridden by subclasses to specify placement preferences.</div>
<dl>
<dt><strong>Overrides:</strong></dt>
<dd><code><a href="../../../../org/apache/spark/rdd/RDD.html#getPreferredLocations(org.apache.spark.Partition)">getPreferredLocations</a></code> in class <code><a href="../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a><scala.Tuple2<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>>></code></dd>
<dt><span class="strong">Parameters:</span></dt><dd><code>split</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<h4>checkpoint</h4>
<pre>public void checkpoint()</pre>
<div class="block"><strong>Description copied from class: <code><a href="../../../../org/apache/spark/rdd/RDD.html#checkpoint()">RDD</a></code></strong></div>
<div class="block">Mark this RDD for checkpointing. It will be saved to a file inside the checkpoint
directory set with <code>SparkContext#setCheckpointDir</code> and all references to its parent
RDDs will be removed. This function must be called before any job has been
executed on this RDD. It is strongly recommended that this RDD is persisted in
memory, otherwise saving it on a file will require recomputation.</div>
<dl>
<dt><strong>Overrides:</strong></dt>
<dd><code><a href="../../../../org/apache/spark/rdd/RDD.html#checkpoint()">checkpoint</a></code> in class <code><a href="../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a><scala.Tuple2<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>>></code></dd>
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<h4>persist</h4>
<pre>public <a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="class in org.apache.spark.rdd">HadoopRDD</a><<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>> persist(<a href="../../../../org/apache/spark/storage/StorageLevel.html" title="class in org.apache.spark.storage">StorageLevel</a> storageLevel)</pre>
<div class="block"><strong>Description copied from class: <code><a href="../../../../org/apache/spark/rdd/RDD.html#persist(org.apache.spark.storage.StorageLevel)">RDD</a></code></strong></div>
<div class="block">Set this RDD's storage level to persist its values across operations after the first time
it is computed. This can only be used to assign a new storage level if the RDD does not
have a storage level set yet. Local checkpointing is an exception.</div>
<dl>
<dt><strong>Overrides:</strong></dt>
<dd><code><a href="../../../../org/apache/spark/rdd/RDD.html#persist(org.apache.spark.storage.StorageLevel)">persist</a></code> in class <code><a href="../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a><scala.Tuple2<<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">K</a>,<a href="../../../../org/apache/spark/rdd/HadoopRDD.html" title="type parameter in HadoopRDD">V</a>>></code></dd>
<dt><span class="strong">Parameters:</span></dt><dd><code>storageLevel</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<h4>getConf</h4>
<pre>public org.apache.hadoop.conf.Configuration getConf()</pre>
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