Spark 4.0.0-preview2 ScalaDoc < Back

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package root
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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 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 clustering
Definition Classes
ml
BisectingKMeans
BisectingKMeansModel
BisectingKMeansSummary
ClusteringSummary
DistributedLDAModel
GaussianMixture
GaussianMixtureModel
GaussianMixtureSummary
KMeans
KMeansModel
KMeansSummary
LDA
LDAModel
LocalLDAModel
PowerIterationClustering

org.apache.spark.ml.clustering

ClusteringSummary

class ClusteringSummary extends Serializable

Summary of clustering algorithms.

Source: ClusteringSummary.scala

Linear Supertypes

Serializable, AnyRef, Any

Known Subclasses

BisectingKMeansSummary, GaussianMixtureSummary, KMeansSummary

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@throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
lazy val cluster: DataFrame
Cluster centers of the transformed data.
Cluster centers of the transformed data.
Annotations
@transient()
lazy val clusterSizes: Array[Long]
Size of (number of data points in) each cluster.
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val featuresCol: String
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val numIter: Int
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val predictionCol: String
val predictions: DataFrame
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Deprecated
(Since version 9)

Packages

ClusteringSummary

class ClusteringSummary extends Serializable

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Packages

ClusteringSummary

class ClusteringSummary extends Serializable

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ClusteringSummary