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 source
    Definition Classes
    ml
  • package image
    Definition Classes
    source
  • ImageDataSource
  • package libsvm
    Definition Classes
    source

package image

Type Members

  1. class ImageDataSource extends AnyRef

    image package implements Spark SQL data source API for loading image data as DataFrame.

    image package implements Spark SQL data source API for loading image data as DataFrame. It can load compressed image (jpeg, png, etc.) into raw image representation via ImageIO in Java library. The loaded DataFrame has one StructType column: image, containing image data stored as image schema. The schema of the image column is:

    • origin: StringType (represents the file path of the image)
    • height: IntegerType (height of the image)
    • width: IntegerType (width of the image)
    • nChannels: IntegerType (number of image channels)
    • mode: IntegerType (OpenCV-compatible type)
    • data: BinaryType (Image bytes in OpenCV-compatible order: row-wise BGR in most cases)

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

    // Scala
val df = spark.read.format("image")
  .option("dropInvalid", true)
  .load("data/mllib/images/partitioned")

// Java
Dataset<Row> df = spark.read().format("image")
  .option("dropInvalid", true)
  .load("data/mllib/images/partitioned");

    Image data source supports the following options:

    • "dropInvalid": Whether to drop the files that are not valid images from the result.
    Note

    This IMAGE data source does not support saving images to files.

    ,

    This class is public for documentation purpose. Please don't use this class directly. Rather, use the data source API as illustrated above.

Members