Packages

  • 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 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 linalg
    Definition Classes
    mllib
  • package distributed
    Definition Classes
    linalg
  • DenseMatrix
  • DenseVector
  • Matrices
  • Matrix
  • QRDecomposition
  • SingularValueDecomposition
  • SparseMatrix
  • SparseVector
  • Vector
  • VectorUDT
  • Vectors

class VectorUDT extends UserDefinedType[Vector]

:: AlphaComponent ::

User-defined type for Vector which allows easy interaction with SQL via org.apache.spark.sql.Dataset.

Annotations
@AlphaComponent()
Source
Vectors.scala
Linear Supertypes
UserDefinedType[Vector], Serializable, DataType, AbstractDataType, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. VectorUDT
  2. UserDefinedType
  3. Serializable
  4. DataType
  5. AbstractDataType
  6. AnyRef
  7. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new VectorUDT()

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##: Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def catalogString: String

    String representation for the type saved in external catalogs.

    String representation for the type saved in external catalogs.

    Definition Classes
    UserDefinedType → DataType
  6. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
  7. def defaultSize: Int

    The default size of a value of this data type, used internally for size estimation.

    The default size of a value of this data type, used internally for size estimation.

    Definition Classes
    UserDefinedType → DataType
  8. def deserialize(datum: Any): Vector

    Convert a SQL datum to the user type

    Convert a SQL datum to the user type

    Definition Classes
    VectorUDT → UserDefinedType
  9. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  10. def equals(o: Any): Boolean
    Definition Classes
    VectorUDT → UserDefinedType → AnyRef → Any
  11. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @IntrinsicCandidate() @native()
  12. def hashCode(): Int
    Definition Classes
    VectorUDT → UserDefinedType → AnyRef → Any
  13. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  14. def json: String

    The compact JSON representation of this data type.

    The compact JSON representation of this data type.

    Definition Classes
    DataType
  15. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  16. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @IntrinsicCandidate() @native()
  17. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @IntrinsicCandidate() @native()
  18. def prettyJson: String

    The pretty (i.e.

    The pretty (i.e. indented) JSON representation of this data type.

    Definition Classes
    DataType
  19. def pyUDT: String

    Paired Python UDT class, if exists.

    Paired Python UDT class, if exists.

    Definition Classes
    VectorUDT → UserDefinedType
  20. def serialize(obj: Vector): InternalRow

    Convert the user type to a SQL datum

    Convert the user type to a SQL datum

    Definition Classes
    VectorUDT → UserDefinedType
  21. def serializedPyClass: String

    Serialized Python UDT class, if exists.

    Serialized Python UDT class, if exists.

    Definition Classes
    UserDefinedType
  22. def simpleString: String

    Readable string representation for the type.

    Readable string representation for the type.

    Definition Classes
    DataType → AbstractDataType
  23. def sql: String
    Definition Classes
    UserDefinedType → DataType
  24. def sqlType: StructType

    Underlying storage type for this UDT

    Underlying storage type for this UDT

    Definition Classes
    VectorUDT → UserDefinedType
  25. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  26. def toString(): String
    Definition Classes
    AnyRef → Any
  27. def typeName: String

    Name of the type used in JSON serialization.

    Name of the type used in JSON serialization.

    Definition Classes
    VectorUDT → DataType
  28. def userClass: Class[Vector]

    Class object for the UserType

    Class object for the UserType

    Definition Classes
    VectorUDT → UserDefinedType
  29. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  30. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  31. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable]) @Deprecated
    Deprecated

    (Since version 9)

Inherited from UserDefinedType[Vector]

Inherited from Serializable

Inherited from DataType

Inherited from AbstractDataType

Inherited from AnyRef

Inherited from Any

Ungrouped