trait DirectMToNCompiler[T] extends InputLayers with InputOptPartitioner with CompileInFn[T] with OutputLayers with OutputOptPartitioner with CompileOutFn[T]
This compiler allows a stateless incremental compilation, in the case the keys of output partitions are a function of the input keys only, so where the input/output mapping does not depend on the input content but only on the input keys.
This compiler allows multiple input partitions to map to the same output partition. In the more limited case where each output partition is affected by one single input partition, Direct1ToNCompiler should be used instead, that enforce this property and can perform incremental compilation in an even for efficient way.
- T
the type of the values passed between front-end and back-end
- Note
the implementation must be scala.Serializable as this is copied to workers and run inside Spark map functions.
- See also
traits mixed in for more details
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- DirectMToNCompiler
- CompileOutFn
- OutputOptPartitioner
- OutputLayers
- CompileInFn
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- Serializable
- InputOptPartitioner
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abstract
def
compileInFn(in: (InKey, InMeta)): T
Calculates the intermediate result from a single input partition.
Calculates the intermediate result from a single input partition. The result will be provided together with the input key in the com.here.platform.data.processing.compiler.direct.CompileOutFn.
- in
the input partition to process
- returns
the value of intermediate data of type
Tfor this partition. This value will be passed in com.here.platform.data.processing.compiler.direct.CompileOutFn to all output keys impacted by the in partition.
- Definition Classes
- CompileInFn
-
abstract
def
compileOutFnDefined(): Unit
Must be overridden as final by all subclasses, to block the mixin of different interfaces in the same compiler class and to assure that at least one child interface is mixed in.
Must be overridden as final by all subclasses, to block the mixin of different interfaces in the same compiler class and to assure that at least one child interface is mixed in.
- Attributes
- protected
- Definition Classes
- CompileOutFn
-
abstract
def
inLayers: Map[Id, Set[Id]]
Represents layers of the input catalogs that you should query and provide to the compiler.
Represents layers of the input catalogs that you should query and provide to the compiler. These layers are grouped by input catalog and identified by catalog ID and layer ID.
- Definition Classes
- InputLayers
-
abstract
def
inPartitioner(parallelism: Int): Option[Partitioner[InKey]]
Specifies the partitioner to use when querying the input catalogs.
Specifies the partitioner to use when querying the input catalogs. If no partitioner is provided, by returning None from this function, then the Executor uses the default partitioner.
- parallelism
The number of partitions the partitioner should partition the catalog into, this should match the parallelism of the Spark RDD containing the input partitions.
- returns
The optional input partitioner with the parallelism specified.
- Definition Classes
- InputOptPartitioner
-
abstract
def
mappingFn(inKey: InKey): Iterable[OutKey]
Calculates which output partitions, if any, are affected by the given single input partition.
Calculates which output partitions, if any, are affected by the given single input partition. The mapping must be function of only the input com.here.platform.data.processing.compiler.InKey.
The metadata is intentionally not provided, because the result of this call cannot be function of the metadata and therefore the data. This is because the direct.CompileInFn implementation does not perform a stateful dependency-tracking for incremental compilation. If the function would use additional information from the tile content, it would break incremental compilation use case.
- inKey
the input partition being mapped
- returns
the output partitions that the given input partition maps to
- Definition Classes
- CompileInFn
-
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): Option[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. If no partitioner is provided, by returning None from this function, then the Executor uses the default partitioner.
- 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 optional output partitioner with the parallelism specified.
- Definition Classes
- OutputOptPartitioner
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val
outCatalogId: Id
Identifier for the output catalog.
Identifier for the output catalog.
- Definition Classes
- OutputLayers
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