org.apache.spark.rdd

Class NewHadoopRDD<K,V>

Object

org.apache.spark.rdd.RDD<scala.Tuple2<K,V>>

org.apache.spark.rdd.NewHadoopRDD<K,V>

All Implemented Interfaces:

java.io.Serializable, org.apache.spark.internal.Logging

public class NewHadoopRDD<K,V>
extends RDD<scala.Tuple2<K,V>>
implements org.apache.spark.internal.Logging

:: 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 new MapReduce API (org.apache.hadoop.mapreduce).

param: sc The SparkContext to associate the RDD with. 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.

See Also:

Serialized Form

Note:

Instantiating this class directly is not recommended, please use org.apache.spark.SparkContext.newAPIHadoopRDD()

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	NewHadoopRDD.NewHadoopMapPartitionsWithSplitRDD$

Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging

org.apache.spark.internal.Logging.SparkShellLoggingFilter

Constructor Summary

Constructors

Constructor and Description
NewHadoopRDD(SparkContext sc, Class<? extends org.apache.hadoop.mapreduce.InputFormat<K,V>> inputFormatClass, Class<K> keyClass, Class<V> valueClass, org.apache.hadoop.conf.Configuration _conf)

Method Summary

Modifier and Type	Method and Description
InterruptibleIterator<scala.Tuple2<K,V>>	compute(Partition theSplit, TaskContext context) :: DeveloperApi :: Implemented by subclasses to compute a given partition.
static Object	CONFIGURATION_INSTANTIATION_LOCK() Configuration's constructor is not threadsafe (see SPARK-1097 and HADOOP-10456).
org.apache.hadoop.conf.Configuration	getConf()
Partition[]	getPartitions() Implemented by subclasses to return the set of partitions in this RDD.
scala.collection.Seq<String>	getPreferredLocations(Partition hsplit) Optionally overridden by subclasses to specify placement preferences.
<U> RDD<U>	mapPartitionsWithInputSplit(scala.Function2<org.apache.hadoop.mapreduce.InputSplit,scala.collection.Iterator<scala.Tuple2<K,V>>,scala.collection.Iterator<U>> f, boolean preservesPartitioning, scala.reflect.ClassTag<U> evidence$1) Maps over a partition, providing the InputSplit that was used as the base of the partition.
NewHadoopRDD<K,V>	persist(StorageLevel storageLevel) Set this RDD's storage level to persist its values across operations after the first time it is computed.

Methods inherited from class org.apache.spark.rdd.RDD

aggregate, barrier, cache, cartesian, checkpoint, cleanShuffleDependencies, coalesce, collect, collect, context, count, countApprox, countApproxDistinct, countApproxDistinct, countByValue, countByValueApprox, dependencies, distinct, distinct, doubleRDDToDoubleRDDFunctions, filter, first, flatMap, fold, foreach, foreachPartition, getCheckpointFile, getNumPartitions, getResourceProfile, getStorageLevel, glom, groupBy, groupBy, groupBy, id, intersection, intersection, intersection, isCheckpointed, isEmpty, iterator, keyBy, localCheckpoint, map, mapPartitions, mapPartitionsWithEvaluator, mapPartitionsWithIndex, max, min, name, numericRDDToDoubleRDDFunctions, partitioner, partitions, persist, pipe, pipe, pipe, preferredLocations, randomSplit, rddToAsyncRDDActions, rddToOrderedRDDFunctions, rddToPairRDDFunctions, rddToSequenceFileRDDFunctions, reduce, repartition, sample, saveAsObjectFile, saveAsTextFile, saveAsTextFile, setName, sortBy, sparkContext, subtract, subtract, subtract, take, takeOrdered, takeSample, toDebugString, toJavaRDD, toLocalIterator, top, toString, treeAggregate, treeAggregate, treeReduce, union, unpersist, withResources, zip, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitions, zipPartitionsWithEvaluator, zipWithIndex, zipWithUniqueId

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.apache.spark.internal.Logging

$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitialize

Constructor Detail

NewHadoopRDD

public NewHadoopRDD(SparkContext sc,
                    Class<? extends org.apache.hadoop.mapreduce.InputFormat<K,V>> inputFormatClass,
                    Class<K> keyClass,
                    Class<V> valueClass,
                    org.apache.hadoop.conf.Configuration _conf)

Method Detail

CONFIGURATION_INSTANTIATION_LOCK

public static Object CONFIGURATION_INSTANTIATION_LOCK()

Configuration's constructor is not threadsafe (see SPARK-1097 and HADOOP-10456). Therefore, we synchronize on this lock before calling new Configuration().

Returns:

(undocumented)

getConf

public org.apache.hadoop.conf.Configuration getConf()

getPartitions

public Partition[] getPartitions()

Description copied from class: RDD

Implemented by subclasses to return the set of partitions in this RDD. This method will only be called once, so it is safe to implement a time-consuming computation in it.

The partitions in this array must satisfy the following property: rdd.partitions.zipWithIndex.forall { case (partition, index) => partition.index == index }

Returns:

(undocumented)

compute

public InterruptibleIterator<scala.Tuple2<K,V>> compute(Partition theSplit,
                                                        TaskContext context)

Description copied from class: RDD

:: DeveloperApi :: Implemented by subclasses to compute a given partition.

Specified by:

compute in class RDD<scala.Tuple2<K,V>>

Parameters:

theSplit - (undocumented)

context - (undocumented)

Returns:

(undocumented)

mapPartitionsWithInputSplit

public <U> RDD<U> mapPartitionsWithInputSplit(scala.Function2<org.apache.hadoop.mapreduce.InputSplit,scala.collection.Iterator<scala.Tuple2<K,V>>,scala.collection.Iterator<U>> f,
                                              boolean preservesPartitioning,
                                              scala.reflect.ClassTag<U> evidence$1)

Maps over a partition, providing the InputSplit that was used as the base of the partition.

getPreferredLocations

public scala.collection.Seq<String> getPreferredLocations(Partition hsplit)

Description copied from class: RDD

Optionally overridden by subclasses to specify placement preferences.

Parameters:

hsplit - (undocumented)

Returns:

(undocumented)

persist

public NewHadoopRDD<K,V> persist(StorageLevel storageLevel)

Description copied from class: RDD

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.

Overrides:

persist in class RDD<scala.Tuple2<K,V>>

Parameters:

storageLevel - (undocumented)

Returns:

(undocumented)