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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.

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

BucketsAccumulator

Companion class BucketsAccumulator

object BucketsAccumulator extends Serializable

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def apply[T](sc: SparkContext, description: String, bucketDelimiters: Array[T])(implicit arg0: Ordering[T], arg1: Numeric[T]): BucketsAccumulator[T]
Creates [org.apache.spark.util.AccumulatorV2 AccumulatorV2] of [Buckets].
Creates [org.apache.spark.util.AccumulatorV2 AccumulatorV2] of [Buckets].
T
the type of elements in the bucket. With this type you define the type of delimiters of your buckets and the type of value that this accumulable will accumulate.
sc
Spark Context is required to register accumulators
description
the description that will be visible in Spark Web UI near your accumulable
bucketDelimiters
the delimiters of buckets as Array of Numeric. For example, given (1, 10, 100), four buckets will be created (-inf:1), [1:10), [10:100), [100:+inf)
returns
an instance of [org.apache.spark.util.AccumulatorV2 AccumulatorV2] registered in Spark
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BucketsAccumulator

Companion class BucketsAccumulator

object BucketsAccumulator extends Serializable

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BucketsAccumulator 

Companion class BucketsAccumulator

object BucketsAccumulator extends Serializable

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BucketsAccumulator