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 driver

Definition Classes: processing

package deltasets

Definition Classes: driver

package transformations

Definition Classes: deltasets

BaseSet

BaseSetIdAssigner

CanDetermine

CannotDetermine

Changes

DeltaContext

DeltaSet

DeltaSetConfig

Determine

KeyValues

Keys

ManyToMany

ManyToOne

NoChanges

OneToMany

OneToOne

PartMapperByLevel

PartitioningStrategy

PreservesPartitioning

PublishedPart

PublishedPartMapper

PublishedSet

PublishedSetLike

RequiresRepartitioning

ResolutionStrategy

Resolver

SomeChanges

StateManager

Transformations

com.here.platform.data.processing.driver.deltasets

KeyValues

final case class KeyValues[K, V](rdd: RDD[(K, V)], partitioner: Partitioner[K]) extends Product with Serializable

Uses a Spark RDD to store key-value pairs. Compared to a normal RDD, the use of this class asserts and, where possible, ensures that two conditions are met:

1. There are no duplicate keys. 2. The RDD is partitioned with the given partitioner.

K: The type of the keys.
V: The type of the values.
rdd: The Spark RDD storing a set of key-value pairs. Must be partitioned using partitioner.
partitioner: The partitioner.

Linear Supertypes

Serializable, Serializable, Product, Equals, AnyRef, Any

Ordering

Alphabetic
By Inheritance

Inherited

KeyValues
Serializable
Serializable
Product
Equals
AnyRef
Any

Hide All
Show All

Visibility

Public
All

Instance Constructors

new KeyValues(rdd: RDD[(K, V)], partitioner: Partitioner[K])
rdd
The Spark RDD storing a set of key-value pairs. Must be partitioned using partitioner.
partitioner
The partitioner.

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( ... ) @native()
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def finalize(): Unit

Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
Annotations
@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
@native()
final def notifyAll(): Unit

Definition Classes
AnyRef
Annotations
@native()
val partitioner: Partitioner[K]
val rdd: RDD[(K, V)]
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... ) @native()

Packages

KeyValues

final case class KeyValues[K, V](rdd: RDD[(K, V)], partitioner: Partitioner[K]) extends Product with Serializable

Instance Constructors

Value Members

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from AnyRef

Inherited from Any

Ungrouped

Packages

KeyValues 

final case class KeyValues[K, V](rdd: RDD[(K, V)], partitioner: Partitioner[K]) extends Product with Serializable

Instance Constructors

Value Members

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from AnyRef

Inherited from Any

Ungrouped

KeyValues