Package 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:

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. param: ignoreCorruptFiles Whether to ignore corrupt files. param: ignoreMissingFiles Whether to ignore missing files.

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	Description
static class	NewHadoopRDD.NewHadoopMapPartitionsWithSplitRDD$

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

org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter

Constructor Summary

Constructors

Constructor	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)
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, boolean ignoreCorruptFiles, boolean ignoreMissingFiles)

Method Summary

Modifier and Type	Method	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()
scala.collection.immutable.Seq<String>	getPreferredLocations(Partition hsplit)
<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 java.lang.Object

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

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

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

Constructor Details

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,
 boolean ignoreCorruptFiles,
 boolean ignoreMissingFiles)

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 Details

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()

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.immutable.Seq<String> getPreferredLocations(Partition hsplit)

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)