| org.apache.spark |
Core Spark classes in Scala.
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| org.apache.spark.annotation |
Spark annotations to mark an API experimental or intended only for advanced usages by developers.
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| org.apache.spark.api.java |
Spark Java programming APIs.
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| org.apache.spark.api.java.function |
Set of interfaces to represent functions in Spark's Java API.
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| org.apache.spark.api.r |
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| org.apache.spark.broadcast |
Spark's broadcast variables, used to broadcast immutable datasets to all nodes.
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| org.apache.spark.examples.streaming |
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| org.apache.spark.graphx |
ALPHA COMPONENT
GraphX is a graph processing framework built on top of Spark.
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| org.apache.spark.graphx.impl |
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| org.apache.spark.graphx.lib |
Various analytics functions for graphs.
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| org.apache.spark.graphx.util |
Collections of utilities used by graphx.
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| org.apache.spark.input |
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| org.apache.spark.io |
IO codecs used for compression.
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| org.apache.spark.launcher |
Library for launching Spark applications.
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| org.apache.spark.ml |
Spark ML is a BETA component that adds a new set of machine learning APIs to let users quickly
assemble and configure practical machine learning pipelines.
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| org.apache.spark.ml.attribute |
ML attributes
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| org.apache.spark.ml.classification |
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| org.apache.spark.ml.clustering |
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| org.apache.spark.ml.evaluation |
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| org.apache.spark.ml.feature |
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| org.apache.spark.ml.param |
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| org.apache.spark.ml.recommendation |
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| org.apache.spark.ml.regression |
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| org.apache.spark.ml.tree |
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| org.apache.spark.ml.tuning |
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| org.apache.spark.ml.util |
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| org.apache.spark.mllib.classification |
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| org.apache.spark.mllib.clustering |
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| org.apache.spark.mllib.evaluation |
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| org.apache.spark.mllib.feature |
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| org.apache.spark.mllib.fpm |
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| org.apache.spark.mllib.linalg |
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| org.apache.spark.mllib.linalg.distributed |
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| org.apache.spark.mllib.optimization |
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| org.apache.spark.mllib.pmml |
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| org.apache.spark.mllib.random |
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| org.apache.spark.mllib.rdd |
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| org.apache.spark.mllib.recommendation |
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| org.apache.spark.mllib.regression |
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| org.apache.spark.mllib.stat |
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| org.apache.spark.mllib.stat.distribution |
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| org.apache.spark.mllib.stat.test |
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| org.apache.spark.mllib.tree |
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| org.apache.spark.mllib.tree.configuration |
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| org.apache.spark.mllib.tree.impurity |
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| org.apache.spark.mllib.tree.loss |
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| org.apache.spark.mllib.tree.model |
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| org.apache.spark.mllib.util |
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| org.apache.spark.partial |
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| org.apache.spark.rdd |
Provides implementation's of various RDDs.
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| org.apache.spark.scheduler |
Spark's DAG scheduler.
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| org.apache.spark.scheduler.cluster |
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| org.apache.spark.scheduler.local |
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| org.apache.spark.serializer |
Pluggable serializers for RDD and shuffle data.
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| org.apache.spark.sql |
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| org.apache.spark.sql.api.java |
Allows the execution of relational queries, including those expressed in SQL using Spark.
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| org.apache.spark.sql.expressions |
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| org.apache.spark.sql.hive |
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| org.apache.spark.sql.hive.execution |
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| org.apache.spark.sql.jdbc |
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| org.apache.spark.sql.sources |
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| org.apache.spark.sql.types |
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| org.apache.spark.status.api.v1 |
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| org.apache.spark.storage |
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| org.apache.spark.streaming |
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| org.apache.spark.streaming.api.java |
Java APIs for spark streaming.
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| org.apache.spark.streaming.dstream |
Various implementations of DStreams.
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| org.apache.spark.streaming.flume |
Spark streaming receiver for Flume.
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| org.apache.spark.streaming.kafka |
Kafka receiver for spark streaming.
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| org.apache.spark.streaming.kinesis |
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| org.apache.spark.streaming.mqtt |
MQTT receiver for Spark Streaming.
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| org.apache.spark.streaming.receiver |
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| org.apache.spark.streaming.scheduler |
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| org.apache.spark.streaming.twitter |
Twitter feed receiver for spark streaming.
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| org.apache.spark.streaming.util |
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| org.apache.spark.streaming.zeromq |
Zeromq receiver for spark streaming.
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| org.apache.spark.ui.env |
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| org.apache.spark.ui.exec |
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| org.apache.spark.ui.jobs |
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| org.apache.spark.ui.storage |
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| org.apache.spark.util |
Spark utilities.
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| org.apache.spark.util.random |
Utilities for random number generation.
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