Spark 4.0.0-preview1 ScalaDoc < Back

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package root
Definition Classes
root
package org
Definition Classes
root
package apache
Definition Classes
org
package spark
Core Spark functionality.
Core Spark functionality. org.apache.spark.SparkContext serves as the main entry point to Spark, while org.apache.spark.rdd.RDD is the data type representing a distributed collection, and provides most parallel operations.
In addition, org.apache.spark.rdd.PairRDDFunctions contains operations available only on RDDs of key-value pairs, such as groupByKey and join; org.apache.spark.rdd.DoubleRDDFunctions contains operations available only on RDDs of Doubles; and org.apache.spark.rdd.SequenceFileRDDFunctions 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.
Java programmers should reference the org.apache.spark.api.java package for Spark programming APIs in Java.
Classes and methods marked with Experimental are user-facing features which have not been officially adopted by the Spark project. These are subject to change or removal in minor releases.
Classes and methods marked with Developer API are intended for advanced users want to extend Spark through lower level interfaces. These are subject to changes or removal in minor releases.
Definition Classes
apache
package api
Definition Classes
spark
package broadcast
Spark's broadcast variables, used to broadcast immutable datasets to all nodes.
Spark's broadcast variables, used to broadcast immutable datasets to all nodes.
Definition Classes
spark
package graphx
ALPHA COMPONENT GraphX is a graph processing framework built on top of Spark.
ALPHA COMPONENT GraphX is a graph processing framework built on top of Spark.
Definition Classes
spark
package input
Definition Classes
spark
package io
IO codecs used for compression.
IO codecs used for compression. See org.apache.spark.io.CompressionCodec.
Definition Classes
spark
package launcher
Definition Classes
spark
package mapred
Definition Classes
spark
package metrics
Definition Classes
spark
package ml
DataFrame-based machine learning APIs to let users quickly assemble and configure practical machine learning pipelines.
DataFrame-based machine learning APIs to let users quickly assemble and configure practical machine learning pipelines.
Definition Classes
spark
package mllib
RDD-based machine learning APIs (in maintenance mode).
RDD-based machine learning APIs (in maintenance mode).
The spark.mllib package is in maintenance mode as of the Spark 2.0.0 release to encourage migration to the DataFrame-based APIs under the org.apache.spark.ml package. While in maintenance mode,
- no new features in the RDD-based spark.mllib package will be accepted, unless they block implementing new features in the DataFrame-based spark.ml package;
- bug fixes in the RDD-based APIs will still be accepted.
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.
Definition Classes
spark
See also
SPARK-4591 to track the progress of feature parity
package partial
Support for approximate results.
Support for approximate results. This provides convenient api and also implementation for approximate calculation.
Definition Classes
spark
See also
org.apache.spark.rdd.RDD.countApprox
package paths
Definition Classes
spark
package rdd
Provides several RDD implementations.
Provides several RDD implementations. See org.apache.spark.rdd.RDD.
Definition Classes
spark
package resource
Definition Classes
spark
package scheduler
Spark's scheduling components.
Spark's scheduling components. This includes the org.apache.spark.scheduler.DAGScheduler and lower level org.apache.spark.scheduler.TaskScheduler.
Definition Classes
spark
package security
Definition Classes
spark
package serializer
Pluggable serializers for RDD and shuffle data.
Pluggable serializers for RDD and shuffle data.
Definition Classes
spark
See also
org.apache.spark.serializer.Serializer
package shuffle
Definition Classes
spark
package sql
Allows the execution of relational queries, including those expressed in SQL using Spark.
Allows the execution of relational queries, including those expressed in SQL using Spark.
Definition Classes
spark
package status
Definition Classes
spark
package storage
Definition Classes
spark
package streaming
Spark Streaming functionality.
Spark Streaming functionality. org.apache.spark.streaming.StreamingContext serves as the main entry point to Spark Streaming, while org.apache.spark.streaming.dstream.DStream is the data type representing a continuous sequence of RDDs, representing a continuous stream of data.
In addition, org.apache.spark.streaming.dstream.PairDStreamFunctions contains operations available only on DStreams of key-value pairs, such as groupByKey and reduceByKey. These operations are automatically available on any DStream of the right type (e.g. DStream[(Int, Int)] through implicit conversions.
For the Java API of Spark Streaming, take a look at the org.apache.spark.streaming.api.java.JavaStreamingContext which serves as the entry point, and the org.apache.spark.streaming.api.java.JavaDStream and the org.apache.spark.streaming.api.java.JavaPairDStream which have the DStream functionality.
Definition Classes
spark
package types
Definition Classes
spark
package ui
Definition Classes
spark
package unsafe
Definition Classes
spark
package util
Spark utilities.
Spark utilities.
Definition Classes
spark
Aggregator
BarrierTaskContext
BarrierTaskInfo
ComplexFutureAction
ContextAwareIterator
Dependency
ErrorClassesJsonReader
ExceptionFailure
ExecutorLostFailure
FetchFailed
FutureAction
HashPartitioner
InterruptibleIterator
JobExecutionStatus
JobSubmitter
NarrowDependency
OneToOneDependency
Partition
PartitionEvaluator
PartitionEvaluatorFactory
Partitioner
QueryContext
QueryContextType
RangeDependency
RangePartitioner
Resubmitted
SerializableWritable
ShuffleDependency
SimpleFutureAction
SparkConf
SparkContext
SparkEnv
SparkException
SparkExecutorInfo
SparkFiles
SparkFirehoseListener
SparkJobInfo
SparkStageInfo
SparkStatusTracker
SparkThrowable
Success
TaskCommitDenied
TaskContext
TaskEndReason
TaskFailedReason
TaskKilled
TaskKilledException
TaskResultLost
UnknownReason
WritableConverter
WritableFactory

org.apache.spark

SparkException

Companion class SparkException

object SparkException extends Serializable

Source: SparkException.scala

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@throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
def constructMessageParams(messageParameters: Map[String, String]): Map[String, String]
Utility method to construct message params from Java Map.
Utility method to construct message params from Java Map.
messageParameters
The Java Map.
returns
Scala collection that can be passed to SparkException constructor.
final def eq(arg0: AnyRef): Boolean
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def equals(arg0: AnyRef): Boolean
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final def getClass(): Class[_ <: AnyRef]
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def hashCode(): Int
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@IntrinsicCandidate() @native()
def internalError(msg: String, cause: Throwable): SparkException
def internalError(msg: String, category: String): SparkException
def internalError(msg: String): SparkException
def internalError(msg: String, context: Array[QueryContext], summary: String, category: Option[String]): SparkException
def internalError(msg: String, context: Array[QueryContext], summary: String): SparkException
final def isInstanceOf[T0]: Boolean
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final def ne(arg0: AnyRef): Boolean
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final def notify(): Unit
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final def notifyAll(): Unit
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@IntrinsicCandidate() @native()
def require(requirement: Boolean, errorClass: String, messageParameters: => Map[String, String]): Unit
This is like the Scala require precondition, except it uses SparkIllegalArgumentException.
This is like the Scala require precondition, except it uses SparkIllegalArgumentException.
requirement
The requirement you want to check
errorClass
The error class to type if the requirement isn't passed
messageParameters
Message parameters to append to the message
final def synchronized[T0](arg0: => T0): T0
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def toString(): String
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final def wait(arg0: Long, arg1: Int): Unit
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final def wait(arg0: Long): Unit
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@throws(classOf[java.lang.InterruptedException]) @native()
final def wait(): Unit
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final def ==(arg0: Any): Boolean
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@throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
def constructMessageParams(messageParameters: Map[String, String]): Map[String, String]
Utility method to construct message params from Java Map.
Utility method to construct message params from Java Map.
messageParameters
The Java Map.
returns
Scala collection that can be passed to SparkException constructor.
final def eq(arg0: AnyRef): Boolean
Definition Classes
AnyRef
def equals(arg0: AnyRef): Boolean
Definition Classes
AnyRef → Any
final def getClass(): Class[_ <: AnyRef]
Definition Classes
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@IntrinsicCandidate() @native()
def hashCode(): Int
Definition Classes
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@IntrinsicCandidate() @native()
def internalError(msg: String, cause: Throwable): SparkException
def internalError(msg: String, category: String): SparkException
def internalError(msg: String): SparkException
def internalError(msg: String, context: Array[QueryContext], summary: String, category: Option[String]): SparkException
def internalError(msg: String, context: Array[QueryContext], summary: String): SparkException
final def isInstanceOf[T0]: Boolean
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final def ne(arg0: AnyRef): Boolean
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final def notify(): Unit
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@IntrinsicCandidate() @native()
final def notifyAll(): Unit
Definition Classes
AnyRef
Annotations
@IntrinsicCandidate() @native()
def require(requirement: Boolean, errorClass: String, messageParameters: => Map[String, String]): Unit
This is like the Scala require precondition, except it uses SparkIllegalArgumentException.
This is like the Scala require precondition, except it uses SparkIllegalArgumentException.
requirement
The requirement you want to check
errorClass
The error class to type if the requirement isn't passed
messageParameters
Message parameters to append to the message
final def synchronized[T0](arg0: => T0): T0
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AnyRef
def toString(): String
Definition Classes
AnyRef → Any
final def wait(arg0: Long, arg1: Int): Unit
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@throws(classOf[java.lang.InterruptedException])
final def wait(arg0: Long): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException]) @native()
final def wait(): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException])
def finalize(): Unit
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protected[lang]
Definition Classes
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@throws(classOf[java.lang.Throwable]) @Deprecated
Deprecated
(Since version 9)

Packages

SparkException

Companion class SparkException

object SparkException extends Serializable

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SparkException

Companion class SparkException

object SparkException extends Serializable

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SparkException