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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 compiler

Definition Classes
processing
package direct

Definition Classes
compiler
package mapgroup

Definition Classes
compiler
package reftree

Definition Classes
compiler
CompileOut1To1Fn
CompileOut1ToNFn
CompileOutFn
CompileOutLayerStackFn
DepCompiler
DepCompilerBase
Direct1ToNCompiler
DirectMToNCompiler
IncrementalDepCompiler
InputLayers
InputOptPartitioner
InputPartitioner
MapGroupCompiler
NonIncrementalCompiler
OutputLayers
OutputOptPartitioner
OutputPartitioner
RefTreeCompiler

com.here.platform.data.processing.compiler

DepCompilerBase

trait DepCompilerBase[T] extends OutputLayers with OutputPartitioner

Base class for all the compilers based on RDDs and the concept of dependencies.

This class models the final step, the actual compilation of output partitions, that is requested by the library after collecting all the T from the dependencies that affect the output partitions candidate to recompilation.

T is a custom type that is produced when generating dependencies but has nothing to do with them. Objects of this custom type are the only one passed to the compile functions.

T: The type of the values collected from dependencies for each output partition

See also: traits mixed in for more details

Linear Supertypes

OutputPartitioner, OutputLayers, AnyRef, Any

Known Subclasses

DepCompiler, IncrementalDepCompiler, ConcreteDepCompiler, ConcreteIncrementalDepCompiler, DepCompilerWrapper, IncrementalDepCompilerWrapper

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DepCompilerBase
OutputPartitioner
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Type Members

type IntermediateResult = RDD[(OutKey, T)]
The values calculated as part of the dependencies that are provided for each com.here.platform.data.processing.compiler.OutKey.
The values calculated as part of the dependencies that are provided for each com.here.platform.data.processing.compiler.OutKey. In case one output partition receives multiple values, these must be represented as multiple entries in this RDD with the same com.here.platform.data.processing.compiler.OutKey as key.
type ToCompile = RDD[(OutKey, Iterable[T])]
The aggregated Ts for each com.here.platform.data.processing.compiler.OutKey provided as input of compilation.

Abstract Value Members

abstract def compileOut(toCompile: ToCompile, parallelism: Int): ToPublish
Compiles partitions and returns actual compiled data, if any.
Compiles partitions and returns actual compiled data, if any. This method is invoked in both full and incremental re-compile cases.
The required behaviour for this method is to return exactly the same number of elements, with the same values for the out keys, as were passed in toCompile.
toCompile
the first com.here.platform.data.processing.compiler.OutKey is the output partition key. The second iterable collection of T contains the dependency values for that key. The input is provided partitioned according to com.here.platform.data.processing.compiler.OutputPartitioner. The RDD is not persisted and, if used multiple times, it should be persisted.
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.compiler.InputOptPartitioner and/or from com.here.platform.data.processing.compiler.OutputOptPartitioner traits
returns
com.here.platform.data.processing.compiler.OutKey is the key of compiled partition. com.here.platform.data.processing.blobstore.Payload is the output data, if any. The returned keys shall be partitioned as specified in com.here.platform.data.processing.compiler.OutputPartitioner, so it is expected that this function keeps using this partitioner passed in the input otherwise the produced data is shuffled and this must be avoided (and enforced)
abstract def outLayers: Set[Id]
Layers to be produced by the compiler.
Layers to be produced by the compiler.

Definition Classes
OutputLayers
abstract def outPartitioner(parallelism: Int): Partitioner[OutKey]
Specifies the partitioner to use when querying the output catalog and producing output data.
Specifies the partitioner to use when querying the output catalog and producing output data.
parallelism
The number of partitions the partitioner should partition the catalog into, this should match the parallelism of the Spark RDD containing the output partitions.
returns
The output partitioner with the parallelism specified.

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

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
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()
def hashCode(): Int

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()
final val outCatalogId: Id
Identifier for the output catalog.
Identifier for the output catalog.

Definition Classes
OutputLayers
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
AnyRef → Any
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

DepCompilerBase

trait DepCompilerBase[T] extends OutputLayers with OutputPartitioner

Type Members

Abstract Value Members

Concrete Value Members

Inherited from OutputPartitioner

Inherited from OutputLayers

Inherited from AnyRef

Inherited from Any

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Packages

DepCompilerBase 

trait DepCompilerBase[T] extends OutputLayers with OutputPartitioner

Type Members

Abstract Value Members

Concrete Value Members

Inherited from OutputPartitioner

Inherited from OutputLayers

Inherited from AnyRef

Inherited from Any

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DepCompilerBase