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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 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 compiler

Definition Classes
java
package direct

Definition Classes
compiler
package mapgroup

Definition Classes
compiler
package reftree

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

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

DepCompiler

trait DepCompiler[T] extends InputLayers with InputPartitioner with OutputLayers with OutputPartitioner

Interface for a basic incremental dependency-based compiler.

Calculated dependencies shall be exhaustive especially for the incremental case, as the compiler will schedule compilation of the output partition returned as part of dependency calculation without any intermediate further processing.

Returning non-exhaustive dependencies has the effect of producing a corrupted output catalog when doing incremental compilation, or an output catalog with missing/invalid data when doing full compilation.

The compiler is efficient only in case the cost of calculating dependencies is negligible compared to the cost of actually producing the output map, as dependency calculation is always triggered with the full input map.

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

Note: This is a Java friendly version of com.here.platform.data.processing.compiler.DepCompiler.
See also: traits mixed in for more details

Linear Supertypes

OutputPartitioner, OutputLayers, InputPartitioner, InputLayers, AnyRef, Any

Known Subclasses

IncrementalDepCompiler

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Type Members

type DepGraph = JavaPairRDD[InKey, OutKey]
The input/output dependencies in the following form: as first key com.here.platform.data.processing.java.compiler.InKey, the input partition key, as value com.here.platform.data.processing.java.compiler.OutKey, the output partition key that depends on the input.
The input/output dependencies in the following form: as first key com.here.platform.data.processing.java.compiler.InKey, the input partition key, as value com.here.platform.data.processing.java.compiler.OutKey, the output partition key that depends on the input. In case one input partition originates dependencies to multiple outputs, each must be represented as single entry in this RDD with the same com.here.platform.data.processing.java.compiler.InKey as key.
type IntermediateResult = JavaPairRDD[OutKey, T]
The values calculated as part of the dependencies that are provided for each com.here.platform.data.processing.java.compiler.OutKey.
The values calculated as part of the dependencies that are provided for each com.here.platform.data.processing.java.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.java.compiler.OutKey as key.
type ToCompile = JavaPairRDD[OutKey, Iterable[T]]
The aggregated Ts for each com.here.platform.data.processing.java.compiler.OutKey provided as input of compilation.

Abstract Value Members

abstract def compileIn(inData: InData, parallelism: Int): Java.Pair[DepGraph, IntermediateResult]
Calculates the dependencies of the output partitions in terms of input partitions.
Calculates the dependencies of the output partitions in terms of input partitions. These dependencies are aggregated and provided later to the compileOut call. This method is invoked in both full and incremental re-compile cases with the whole input catalog as input.
inData
the metadata of the whole input catalog. 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.InputPartitioner and/or from com.here.platform.data.processing.java.compiler.OutputOptPartitioner traits
returns
the input/output dependencies and the values for each of them. Returned graph must be partitioned by inPartitioner and the intermediate result by outPartitioner for optimal performances.

Note
please note and follow the RDD persistence policy described in com.here.platform.data.processing.driver.Executor
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.java.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.java.compiler.InputOptPartitioner and/or from com.here.platform.data.processing.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 outPartitioner, 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 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

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def equals(arg0: Any): Boolean

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def finalize(): Unit

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protected[lang]
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final def getClass(): Class[_]

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final def isInstanceOf[T0]: Boolean

Definition Classes
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final def ne(arg0: AnyRef): Boolean

Definition Classes
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final def notify(): Unit

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Packages

DepCompiler

trait DepCompiler[T] extends InputLayers with InputPartitioner with OutputLayers with OutputPartitioner

Type Members

Abstract Value Members

Concrete Value Members

Inherited from OutputPartitioner

Inherited from OutputLayers

Inherited from InputPartitioner

Inherited from InputLayers

Inherited from AnyRef

Inherited from Any

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Packages

DepCompiler 

trait DepCompiler[T] extends InputLayers with InputPartitioner with OutputLayers with OutputPartitioner

Type Members

Abstract Value Members

Concrete Value Members

Inherited from OutputPartitioner

Inherited from OutputLayers

Inherited from InputPartitioner

Inherited from InputLayers

Inherited from AnyRef

Inherited from Any

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DepCompiler