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package root
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package com
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package here
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com
package platform
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here
package data
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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 impl
Definition Classes
driver
package deltasets
Definition Classes
impl
package executors
Definition Classes
impl
package state
Definition Classes
impl
CatalogIdVersionEncoding
CommitProducer
CompleteConfigLoader
DepResolution
DriverContextImpl
DriverImpl
FailOnEmptyUploader
FixedVersionIdEncoding
Implicits
PreviousRunIdEncoding

com.here.platform.data.processing.driver.impl

CatalogIdVersionEncoding

Companion class CatalogIdVersionEncoding

object CatalogIdVersionEncoding

Provides generic functionality for encoding and decoding version information in catalog IDs.

Attributes: protected[driver]

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def encode(catalogId: String, encodingSchemeID: String, argument: Long): Id
Given a catalog ID, an encoding scheme ID, and an generic integer argument, returns a catalog ID encoding the integer argument and the encoding scheme ID.
Given a catalog ID, an encoding scheme ID, and an generic integer argument, returns a catalog ID encoding the integer argument and the encoding scheme ID.
catalogId
The original catalog ID, with no version information encoded.
encodingSchemeID
A unique identifier for the encoding scheme.
argument
A generic argument to be encoded.
returns
The new catalog ID, with version information encoded.
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def hasAnyVersion(catalogID: String): Boolean
Checks if the given catalog ID was encoded using encode.
Checks if the given catalog ID was encoded using encode.
catalogID
The catalog ID to be checked.
returns
true if the given catalog ID is encoded, false if not.
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protected[driver]
def hashCode(): Int
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final def isInstanceOf[T0]: Boolean
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val nameEncoding: Regex
Defines a regular expression to decode catalog IDs encoded using encode.
Defines a regular expression to decode catalog IDs encoded using encode.
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final def ne(arg0: AnyRef): Boolean
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def unapply(catalogId: Id): Option[(Id, String, Long)]
Given a catalog ID encoded using encode, returns the decoded catalog ID and the encoding argument.
Given a catalog ID encoded using encode, returns the decoded catalog ID and the encoding argument. Returns None if the given catalog ID is not encoded in this encoding scheme.
catalogId
The catalog ID to be decoded.
returns
The original catalog ID and the encoding argument.
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final def wait(arg0: Long, arg1: Int): Unit
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Deprecated
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Packages

CatalogIdVersionEncoding

Companion class CatalogIdVersionEncoding

object CatalogIdVersionEncoding

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CatalogIdVersionEncoding

Companion class CatalogIdVersionEncoding

object CatalogIdVersionEncoding

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CatalogIdVersionEncoding