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 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 image
    Definition Classes
    ml
  • ImageSchema
o

org.apache.spark.ml.image

ImageSchema

object ImageSchema

Defines the image schema and methods to read and manipulate images.

Annotations
@Since( "2.3.0" )
Source
ImageSchema.scala
Linear Supertypes
AnyRef, Any
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  1. ImageSchema
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Value Members

  1. val columnSchema: StructType

    Schema for the image column: Row(String, Int, Int, Int, Int, Array[Byte])

  2. def getData(row: Row): Array[Byte]

    Gets the image data

    Gets the image data

    returns

    The image data

  3. def getHeight(row: Row): Int

    Gets the height of the image

    Gets the height of the image

    returns

    The height of the image

  4. def getMode(row: Row): Int

    Gets the OpenCV representation as an int

    Gets the OpenCV representation as an int

    returns

    The OpenCV representation as an int

  5. def getNChannels(row: Row): Int

    Gets the number of channels in the image

    Gets the number of channels in the image

    returns

    The number of channels in the image

  6. def getOrigin(row: Row): String

    Gets the origin of the image

    Gets the origin of the image

    returns

    The origin of the image

  7. def getWidth(row: Row): Int

    Gets the width of the image

    Gets the width of the image

    returns

    The width of the image

  8. val imageFields: Array[String]
  9. val imageSchema: StructType

    DataFrame with a single column of images named "image" (nullable)

  10. val javaOcvTypes: Map[String, Int]

    (Java-specific) OpenCV type mapping supported

  11. val ocvTypes: Map[String, Int]

    (Scala-specific) OpenCV type mapping supported

  12. val undefinedImageType: String