trait DepCompilerBase[T] extends OutputLayers with OutputPartitioner
Base class for all the compilers based on RDDs and the concept of dependencies.
This class models the final step, the actual compilation of output partitions,
that is requested by the library after collecting all the T from
the dependencies that affect the output partitions candidate to recompilation.
T is a custom type that is produced when generating dependencies but
has nothing to do with them. Objects of this custom type are
the only one passed to the compile functions.
- T
The type of the values collected from dependencies for each output partition
- See also
traits mixed in for more details
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Type Members
- type IntermediateResult = RDD[(OutKey, T)]
The values calculated as part of the dependencies that are provided for each com.here.platform.data.processing.compiler.OutKey.
The values calculated as part of the dependencies that are provided for each com.here.platform.data.processing.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.compiler.OutKey as key.
- type ToCompile = RDD[(OutKey, Iterable[T])]
The aggregated
Ts for each com.here.platform.data.processing.compiler.OutKey provided as input of compilation.
Abstract Value Members
- 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
Tcontains the dependency values for that key. The input is provided partitioned according to com.here.platform.data.processing.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.compiler.InputOptPartitioner and/or from com.here.platform.data.processing.compiler.OutputOptPartitioner traits
- returns
com.here.platform.data.processing.compiler.OutKey is the key of compiled partition. com.here.platform.data.processing.blobstore.Payload is the output data, if any. The returned keys shall be partitioned as specified in com.here.platform.data.processing.compiler.OutputPartitioner, 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 outLayers: Set[Id]
Layers to be produced by the compiler.
Layers to be produced by the compiler.
- Definition Classes
- OutputLayers
- abstract def outPartitioner(parallelism: Int): Partitioner[OutKey]
Specifies the partitioner to use when querying the output catalog and producing output data.
Specifies the partitioner to use when querying the output catalog and producing output data.
- parallelism
The number of partitions the partitioner should partition the catalog into, this should match the parallelism of the Spark RDD containing the output partitions.
- returns
The output partitioner with the parallelism specified.
- Definition Classes
- OutputPartitioner
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- final val outCatalogId: Id
Identifier for the output catalog.
Identifier for the output catalog.
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- Deprecated
(Since version 9)