Packages

•  package root

  Definition Classes

  root

•  package com

  Definition Classes

  root

•  package here

  Definition Classes

  com

•  package platform

  Definition Classes

  here

•  package data

  Definition Classes

  platform

•  package processing

  This package provides the Data Processing Library for building distributed data processing applications.

  This package provides the Data Processing Library for building distributed data processing applications.

  A Runner both implements the interface with the environment for an application to run, and starts the application. The application, in turn, is driven by a Driver, that controls and performs the distributed processing.

  Choose a Runner best suited for the environment where the application runs.

  The Driver performs one of more tasks which read layers from input catalogs and write to one or more layers of an output catalog.

  The main entry point in the processing library is the com.here.platform.data.processing.driver.DriverBuilder class where you can add different kinds of tasks to the driver. The driver runs the tasks, and commits the final results to the output catalog.

  Tasks are implemented using one or more compilers.

  The simplest compiler is the direct compiler which maps each input tile to N output tiles. The application needs to define com.here.platform.data.processing.compiler.Direct1ToNCompiler.

  Other more complex compilation patterns are based on some kind of dependency tracking between input partitions and output partitions.

  The processing Library supports the following patterns:

  - com.here.platform.data.processing.compiler.NonIncrementalCompiler: non-incremental compilation only - com.here.platform.data.processing.compiler.DepCompiler: non-incremental dependency calculation and incremental compilation - com.here.platform.data.processing.compiler.IncrementalDepCompiler: incremental dependency calculation and compilation - com.here.platform.data.processing.compiler.Direct1ToNCompiler: incremental compilation where every output tile depends only on one input tile, and this mapping is independent from tile content - com.here.platform.data.processing.compiler.DirectMToNCompiler: incremental compilation where every output tile depends on multiple input tiles, and this mapping is independent from tile content - com.here.platform.data.processing.compiler.MapGroupCompiler: incremental compilation where every output tile can depend on multiple input tiles, and this mapping depend on the tile content - com.here.platform.data.processing.compiler.RefTreeCompiler: fully-managed two phases incremental compilation that can resolve references between input partitions. Input/Output dependency management is implemented and the developer doesn't need to provide this logic

  The application's main object normally mixes in the a runner trait (like PipelineRunner) to setup the Driver, and interfaces with the environment where the application is run. See the Main classes in the example compilers for more details.

  com.here.platform.data.processing.catalog, com.here.platform.data.processing.blobstore, and com.here.platform.data.processing.publisher contain utilities for accessing catalogs and payloads in a Spark-friendly way, providing an RDD-based abstraction over data and metadata. These classes are used by the processing library, but can also be used independently.

  Definition Classes

  data

•  package blobstore

  Contains an abstract interface used to access BlobStore.

  Contains an abstract interface used to access BlobStore.

  Obtain the retriever and uploader for a catalog directly from the com.here.platform.data.processing.catalog.Catalog instance.

  Definition Classes

  processing

•  package broadcast

  This package should be considered as the preferred way of working with broadcast variables in a Data Processing Library compiler.

  This package should be considered as the preferred way of working with broadcast variables in a Data Processing Library compiler. It provides the basic functionality to create an instance of org.apache.spark.broadcast.Broadcast.

  This functionality is based on org.apache.spark.broadcast.Broadcast which offers a self-contained mechanism to create a single broadcast variable of a generic type.

  The toBroadcast() method is provided to create a broadcast variable and add the hash to the fingerprint of the com.here.platform.data.processing.driver.DriverContext, which is required in order for incremental compilations to work correctly.

  The package also enables developers to query the catalogs without the need to manage versions manually.

  Definition Classes

  processing

•  package catalog

  Contains an abstract Scala interface for accessing catalogs from Spark.

  Contains an abstract Scala interface for accessing catalogs from Spark.

  Use the com.here.platform.data.processing.catalog.Catalog factory methods to obtain instances.

  Definition Classes

  processing

•  package clientfactory

  Definition Classes

  processing

•  package compiler

  Definition Classes

  processing

•  package driver

  Definition Classes

  processing

•  package exception

  Definition Classes

  processing

•  package java

  This package provides Java bindings for the Data Processing Library, to build distributed data processing applications in Java.

  This package provides Java bindings for the Data Processing Library, to build distributed data processing applications in Java.

  A Runner both implements the interface with the environment for an application to run, and starts the application. The application, in turn, is driven by a Driver, that controls and performs the distributed processing.

  Choose a Runner best suited for the environment where the application runs.

  The Driver performs one of more tasks which read layers from input catalogs and write to one or more layers of an output catalog.

  The main entry point in the processing library is the com.here.platform.data.processing.java.driver.DriverBuilder class where you can add different kinds of tasks to the driver. The driver runs the tasks, and commits the final results to the output catalog.

  Tasks are implemented using one or more compilers.

  The simplest compiler is the direct compiler which maps each input tile to N output tiles. The application needs to implement a com.here.platform.data.processing.java.compiler.Direct1ToNCompiler.

  Other more complex compilation patterns are based on different types of dependency tracking between input partitions and output partitions.

  The processing Library supports the following patterns:

  - com.here.platform.data.processing.java.compiler.NonIncrementalCompiler: non-incremental compilation only - com.here.platform.data.processing.java.compiler.DepCompiler: non-incremental dependency calculation and incremental compilation - com.here.platform.data.processing.java.compiler.IncrementalDepCompiler: incremental dependency calculation and compilation - com.here.platform.data.processing.java.compiler.Direct1ToNCompiler: incremental compilation where every output tile depends only on one input tile, and this mapping is independent from tile content - com.here.platform.data.processing.java.compiler.DirectMToNCompiler: incremental compilation where every output tile can depend on multiple input tiles, and this mapping is independent from tile content - com.here.platform.data.processing.java.compiler.MapGroupCompiler: incremental compilation where every output tile can depend on multiple input tiles, and this mapping depend on the tile content - com.here.platform.data.processing.java.compiler.RefTreeCompiler: fully-managed two phases incremental compilation that can resolve references between input partitions. Input/Output dependency management is implemented and the developer doesn't need to provide this logic

  The application's main object normally extends a runner class (like PipelineRunner) to setup the Driver, and interfaces with the environment where the application runs. For more details, see the Main classes in the example compilers.

  com.here.platform.data.processing.java.catalog, com.here.platform.data.processing.java.blobstore, and com.here.platform.data.processing.java.publisher contain utilities for accessing catalogs and payloads in a Spark-friendly way, providing an RDD-based abstraction over data and metadata. These classes are used by the processing library, but can also be used independently.

  Definition Classes

  processing

•  package blobstore

  Java bindings for the blobstore package.

•  package broadcast

  Provides the basic functionality to perform org.apache.spark.broadcast.Broadcast creation.

  Provides the basic functionality to perform org.apache.spark.broadcast.Broadcast creation.

  To use a broadcast variable in the processing library, developers are required to add the variable's hash to the fingerprints. This ensures that incremental compilations are not compromised. This package object provides the method toBroadcast() to use for that purpose. The package also offers a functionality to query catalogs by properly managing versions. The functionality is based on the org.apache.spark.broadcast.Broadcast which offers a self-contained mechanism to create a single broadcast variable of a generic type.

  This compiler class is the preferred way of working with broadcast variables in the Data Processing Library.

•  package catalog

  Java bindings for the catalog package.

•  package compiler
•  package driver
•  package impl
•  package leveling
•  package publisher
•  package spark
•  package utils
• Java
• Pair
•  package leveling

  Definition Classes

  processing

•  package logging

  Definition Classes

  processing

•  package publisher

  Definition Classes

  processing

•  package spark

  Definition Classes

  processing

•  package statistics

  Common statistics utilities.

  Common statistics utilities.

  Definition Classes

  processing

•  package utils

  Definition Classes

  processing

•  package validation

  Definition Classes

  processing

com.here.platform.data.processing

java 