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package root

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root
package com

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root
package here

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com
package platform

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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 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

ResolutionStrategy

Companion trait ResolutionStrategy

object ResolutionStrategy

Default ResolutionStrategies to use in mapValuesWithResolver.

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case class BackwardResolution[K, V](references: DeltaSet[Key, Meta], referencesToSubjects: (Key, Meta) ⇒ Set[K])(implicit evidence$4: Ordering[K], evidence$5: ClassTag[K], evidence$6: ClassTag[V]) extends ResolutionStrategy[K, V] with Product with Serializable
Given a DeltaSet containing references and a function that maps each reference to a set of subject partitions, BackwardResolution makes the mapped references available to the resolver when processing the subject partition, without any further network query.
Given a DeltaSet containing references and a function that maps each reference to a set of subject partitions, BackwardResolution makes the mapped references available to the resolver when processing the subject partition, without any further network query.
references
The DeltaSet containing the referenced partition key-meta pairs.
referencesToSubjects
The function that maps each reference to a set of referenced partition keys.
case class Broadcast(references: DeltaSet[Key, Meta]) extends ResolutionStrategy[Any, Any] with Product with Serializable
Sends a full copy of the metadata contained in a given DeltaSet to all Spark executors in the cluster.
Sends a full copy of the metadata contained in a given DeltaSet to all Spark executors in the cluster. The metadata will be completely available to mapValuesWithResolver; no further network requests are required for resolving an existing key.
references
The DeltaSet containing the metadata.

Note
The references DeltaSet is evaluated non-incrementally by this strategy.
case class DirectQuery(referenceCatalog: Id, referenceLayers: Set[Id], cacheSize: Long = 10000) extends ResolutionStrategy[Any, Any] with Product with Serializable
Resolves a reference by directly querying the Data API.
Resolves a reference by directly querying the Data API.
referenceCatalog
The catalog to query.
referenceLayers
The layers to query.
cacheSize
The number of key-meta pairs to keep in a local cache to avoid querying the service several times for the same key. Defaults to 10000.
case class ForwardResolution[K, V](references: DeltaSet[Key, Meta], subjectToReferences: (K, V) ⇒ Set[Key])(implicit evidence$1: Ordering[K], evidence$2: ClassTag[K], evidence$3: ClassTag[V]) extends ResolutionStrategy[K, V] with Product with Serializable
Given a DeltaSet containing references and a function that maps each subject to a set of reference partitions makes the mapped references available to the resolver when processing the subject partition, without any further network query.
Given a DeltaSet containing references and a function that maps each subject to a set of reference partitions makes the mapped references available to the resolver when processing the subject partition, without any further network query.
references
The DeltaSet containing the referenced partition key-meta pairs.
subjectToReferences
The function that maps each subject to a set of referenced partition keys.

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object BackwardResolution extends Serializable
Defines default instances for the BackwardResolution strategy.

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ResolutionStrategy

Companion trait ResolutionStrategy

object ResolutionStrategy

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ResolutionStrategy 

Companion trait ResolutionStrategy

object ResolutionStrategy

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ResolutionStrategy