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.

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 java

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

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 compiler

Definition Classes: java

package direct

Definition Classes: compiler

package mapgroup

Definition Classes: compiler

package reftree

Definition Classes: compiler

IncrementalDepCompiler

NonIncrementalCompiler

com.here.platform.data.processing.java.compiler

NonIncrementalCompiler

trait NonIncrementalCompiler extends InputLayers with InputPartitioner with OutputLayers with OutputPartitioner

The simplest interface that an actual compiler can implement. This leaves the maximum flexibility to the compiler implementors, but has no support for incremental compilation.

Note: This is a Java friendly version of com.here.platform.data.processing.compiler.NonIncrementalCompiler.
See also: extended interfaces for more details

Linear Supertypes

OutputPartitioner, OutputLayers, InputPartitioner, InputLayers, AnyRef, Any

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Inherited

NonIncrementalCompiler
OutputPartitioner
OutputLayers
InputPartitioner
InputLayers
AnyRef
Any

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Abstract Value Members

abstract def compile(toCompile: InData, parallelism: Int): ToPublish
Compiles partitions and returns actual compiled data, if any.
Compiles partitions and returns actual compiled data, if any.
toCompile
the complete input metadata for the layer requested. Keys are partitioned as specified in com.here.platform.data.processing.java.compiler.InputPartitioner
parallelism
the parallelism of both the input and the output RDDs. This parameter is normally needed to get partitioners from com.here.platform.data.processing.java.compiler.InputOptPartitioner and/or from com.here.platform.data.processing.java.compiler.OutputOptPartitioner traits
returns
com.here.platform.data.processing.java.compiler.OutKey is the key of compiled partition. com.here.platform.data.processing.java.blobstore.Payload is the output data, if any The returned keys shall be partitioned as specified in com.here.platform.data.processing.java.compiler.OutputPartitioner
Note
please note and follow the RDD persistence policy described in com.here.platform.data.processing.driver.Executor
abstract def inLayers: Map[String, Set[String]]
Layers of the input catalogs that should be queried and provided to the compiler, grouped by input catalog and identified by catalog id and layer ID.
Layers of the input catalogs that should be queried and provided to the compiler, grouped by input catalog and identified by catalog id and layer ID.
Definition Classes
InputLayers
abstract def inPartitioner(parallelism: Int): PartitionerOfKey
The partitioner to be applied when querying the input catalog.
The partitioner to be applied when querying the input catalog.
parallelism
the parallelism of the partitioner
returns
the input partitioner with the given parallelism
Definition Classes
InputPartitioner
abstract def outLayers: Set[String]
Layers that are expected to be produced by the compiler.
Layers that are expected to be produced by the compiler.
Definition Classes
OutputLayers
abstract def outPartitioner(parallelism: Int): PartitionerOfKey
The partitioner to be applied when querying the output catalog and producing output data.
The partitioner to be applied when querying the output catalog and producing output data.
parallelism
the parallelism of the partitioner
returns
the output partitioner with the given parallelism
Definition Classes
OutputPartitioner

Concrete Value Members

final def !=(arg0: Any): Boolean
Definition Classes
AnyRef → Any
final def ##: Int
Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean
Definition Classes
AnyRef → Any
final def asInstanceOf[T0]: T0
Definition Classes
Any
def clone(): AnyRef
Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
final def eq(arg0: AnyRef): Boolean
Definition Classes
AnyRef
def equals(arg0: AnyRef): Boolean
Definition Classes
AnyRef → Any
final def getClass(): Class[_ <: AnyRef]
Definition Classes
AnyRef → Any
Annotations
@IntrinsicCandidate() @native()
def hashCode(): Int
Definition Classes
AnyRef → Any
Annotations
@IntrinsicCandidate() @native()
final def isInstanceOf[T0]: Boolean
Definition Classes
Any
final def ne(arg0: AnyRef): Boolean
Definition Classes
AnyRef
final def notify(): Unit
Definition Classes
AnyRef
Annotations
@IntrinsicCandidate() @native()
final def notifyAll(): Unit
Definition Classes
AnyRef
Annotations
@IntrinsicCandidate() @native()
final def synchronized[T0](arg0: => T0): T0
Definition Classes
AnyRef
def toString(): String
Definition Classes
AnyRef → Any
final def wait(arg0: Long, arg1: Int): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException])
final def wait(arg0: Long): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException]) @native()
final def wait(): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException])

Deprecated Value Members

def finalize(): Unit
Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.Throwable]) @Deprecated
Deprecated
(Since version 9)

Packages

NonIncrementalCompiler

trait NonIncrementalCompiler extends InputLayers with InputPartitioner with OutputLayers with OutputPartitioner

Abstract Value Members

Concrete Value Members

Deprecated Value Members

Inherited from OutputPartitioner

Inherited from OutputLayers

Inherited from InputPartitioner

Inherited from InputLayers

Inherited from AnyRef

Inherited from Any

Ungrouped

Packages

NonIncrementalCompiler

trait NonIncrementalCompiler extends InputLayers with InputPartitioner with OutputLayers with OutputPartitioner

Abstract Value Members

Concrete Value Members

Deprecated Value Members

Inherited from OutputPartitioner

Inherited from OutputLayers

Inherited from InputPartitioner

Inherited from InputLayers

Inherited from AnyRef

Inherited from Any

Ungrouped

NonIncrementalCompiler