org.apache.spark.ml.source.libsvm

DefaultSource

class DefaultSource extends RelationProvider with DataSourceRegister

libsvm package implements Spark SQL data source API for loading LIBSVM data as DataFrame. The loaded DataFrame has two columns: label containing labels stored as doubles and features containing feature vectors stored as Vectors.

To use LIBSVM data source, you need to set "libsvm" as the format in DataFrameReader and optionally specify options, for example:

// Scala
val df = sqlContext.read.format("libsvm")
  .option("numFeatures", "780")
  .load("data/mllib/sample_libsvm_data.txt")

// Java
DataFrame df = sqlContext.read().format("libsvm")
  .option("numFeatures, "780")
  .load("data/mllib/sample_libsvm_data.txt");

LIBSVM data source supports the following options:

Annotations
@Since( "1.6.0" )
Source
LibSVMRelation.scala
See also

LIBSVM datasets

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  1. DefaultSource
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Instance Constructors

  1. new DefaultSource()

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    @throws( ... )
  8. def createRelation(sqlContext: SQLContext, parameters: Map[String, String]): BaseRelation

    Returns a new base relation with the given parameters.

    Returns a new base relation with the given parameters. Note: the parameters' keywords are case insensitive and this insensitivity is enforced by the Map that is passed to the function.

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    DefaultSourceRelationProvider
    Annotations
    @Since( "1.6.0" )
  9. final def eq(arg0: AnyRef): Boolean

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  16. final def notify(): Unit

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  17. final def notifyAll(): Unit

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  18. def shortName(): String

    The string that represents the format that this data source provider uses.

    The string that represents the format that this data source provider uses. This is overridden by children to provide a nice alias for the data source. For example:

    override def shortName(): String = "parquet"
    Definition Classes
    DefaultSourceDataSourceRegister
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    @Since( "1.6.0" )
    Since

    1.5.0

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Inherited from DataSourceRegister

Inherited from RelationProvider

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