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 statistics

Common statistics utilities.

Definition Classes: processing

Buckets

BucketsAccumulator

CatalogStats

PayloadStats

PublisherStats

RetrieveStats

Statistics

UploadStats

com.here.platform.data.processing.statistics

Statistics

class Statistics extends ContextLogging

Container for all the statistics accumulators created. All methods can be called in driver only.

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ContextLogging, AnyRef, Any

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new Statistics(sc: SparkContext)

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final def !=(arg0: Any): Boolean

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final def ##(): Int

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final def ==(arg0: Any): Boolean

Definition Classes
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def accumulatorsToJson(): String
Returns accumulator names and current values as JSON, sorted by accumulator name.
def accumulatorsToStrings(valSep: String): Iterable[String]
def accumulatorsToTsv(): String
Returns accumulator names and current values as Tab Separated Values.
final def asInstanceOf[T0]: T0

Definition Classes
Any
val bucketAccumulators: Map[String, BucketsAccumulator[Int]]
def classForLogger: Class[_]
Override this to change the class that is displayed in logs.
Override this to change the class that is displayed in logs.

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protected
Definition Classes
ContextLogging
def clone(): AnyRef

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protected[lang]
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@throws( ... ) @native()
final def eq(arg0: AnyRef): Boolean

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def equals(arg0: Any): Boolean

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def finalize(): Unit

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protected[lang]
Definition Classes
AnyRef
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@throws( classOf[java.lang.Throwable] )
def getAccumulator(bucketsLimits: Array[Int], name: String): BucketsAccumulator[Int]
Retrieve existing Bucket accumulator with given name and initial value, or create new if it doesn't exist
def getAccumulator(name: String): LongAccumulator
Retrieve existing Long accumulator with given name, or create new if it doesn't exist
final def getClass(): Class[_]

Definition Classes
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@native()
def hashCode(): Int

Definition Classes
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Annotations
@native()
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
def logAccumulators(): Unit
Logs all accumulators.
final lazy val logger: ContextAwareLogger
The logger to use for normal and context-aware messages.
The logger to use for normal and context-aware messages.

Attributes
protected
Definition Classes
ContextLogging
val longAccumulators: Map[String, LongAccumulator]
final def ne(arg0: AnyRef): Boolean

Definition Classes
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final def notify(): Unit

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@native()
final def notifyAll(): Unit

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final def synchronized[T0](arg0: ⇒ T0): T0

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def toString(): String

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final def wait(): Unit

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@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

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@throws( ... )
final def wait(arg0: Long): Unit

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Statistics

class Statistics extends ContextLogging

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Statistics 

class Statistics extends ContextLogging

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Statistics