trait Stateful[K, V] extends AnyRef
Groups transformations for a DeltaSet[K, V] that require storing metadata in the output
catalog, to enable incremental processing.
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abstract
val
autoIdAssigner: BaseSetIdAssigner
The ID assigner used to automatically assign DeltaSet IDs if not provided.
The ID assigner used to automatically assign DeltaSet IDs if not provided.
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- protected
-
abstract
def
detectChanges(checkSum: (V) ⇒ IndexedSeq[Byte], id: Id = autoIdAssigner("detectChanges"), configOverride: Override = DeltaSetConfig.noOverride): DeltaSet[K, V]
Returns the same DeltaSet but with more precise information about what has changed in the data since the last run.
Returns the same DeltaSet but with more precise information about what has changed in the data since the last run. For this, values in this DeltaSet are compared to those in the previous run using a user-provided
checkSumfunction. ThecheckSumfunction should be (with high probability) collision-free for the same key, and the return value should be relatively small, as the checksum of every value is stored in the output catalog.If the previous state is available, this DeltaSet returns changes even when the upstream DeltaSet runs non-incrementally.
This function does not shuffle any data any data.
- checkSum
The function to compute the checksum.
- id
Deprecated.
- configOverride
Deprecated.
- returns
A DeltaSet that represents the same data as this DeltaSet, but with more precise information about changes.
- Note
All arguments must be serializable, since this transformation is serialized and sent to workers nodes.
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abstract
def
flatMapGroup[K2, V2](flatMapFn: (K, V) ⇒ Iterable[(K2, V2)], partitioning: PartitioningStrategy[K2], id: Id = autoIdAssigner("flatMapGroup"), configOverride: Override = DeltaSetConfig.noOverride)(implicit arg0: ClassTag[K2], arg1: ClassTag[V2]): DeltaSet[K2, Iterable[V2]]
Applies a function to all key-value pairs in this DeltaSet, partitions the result, and then groups all output key-value pairs by key.
Applies a function to all key-value pairs in this DeltaSet, partitions the result, and then groups all output key-value pairs by key.
If the
partitioningis not PreservesPartitioning, this transformation will shuffle data. In particular, all key-value pairs that belong to a different partition after the key transformation may have to be transferred between executors.- K2
The type of output key.
- V2
The type of output value.
- flatMapFn
The function applied to the key-value pairs in the DeltaSet.
- partitioning
Either a partitioner to use, or PreservesPartitioning to indicate that the mapped keys are always in the same Spark partition as the original keys. This will be checked at run-time.
- id
Deprecated.
- configOverride
Deprecated.
- returns
A DeltaSet that represents the result of the transformation.
- Note
All arguments must be serializable, since this transformation is serialized and sent to workers nodes.
-
abstract
def
flatMapReduce[K2, V2](flatMapFn: (K, V) ⇒ Iterable[(K2, V2)], reduceFn: (V2, V2) ⇒ V2, partitioning: PartitioningStrategy[K2], id: Id = autoIdAssigner("flatMapReduce"), configOverride: Override = DeltaSetConfig.noOverride)(implicit arg0: ClassTag[K2], arg1: ClassTag[V2]): DeltaSet[K2, V2]
Applies a function to all key-value pairs in this DeltaSet, partitions the result, and then reduces all values with the same key to a single value.
Applies a function to all key-value pairs in this DeltaSet, partitions the result, and then reduces all values with the same key to a single value.
If the
partitioningis not PreservesPartitioning, this transformation will shuffle data. In particular, all key-value pairs that belong to a different partition after the key transformation may have to be transferred between executors.- K2
The type of output key.
- V2
The type of output value.
- flatMapFn
The function applied to the key-value pairs in the DeltaSet.
- reduceFn
The associative and commutative reduce function.
- partitioning
Either a partitioner to use, or PreservesPartitioning to indicate that the mapped keys are always in the same Spark partition as the original keys. This will be checked at run-time.
- id
Deprecated.
- configOverride
Deprecated.
- returns
A DeltaSet that represents the result of the transformation.
- Note
All arguments must be serializable, since this transformation is serialized and sent to workers nodes.
-
abstract
def
flatMapUnique[K2, V2](flatMapFn: (K, V) ⇒ Iterable[(K2, V2)], partitioning: PartitioningStrategy[K2], id: Id = autoIdAssigner("flatMapUnique"), configOverride: Override = DeltaSetConfig.noOverride)(implicit arg0: ClassTag[K2], arg1: ClassTag[V2]): DeltaSet[K2, V2]
Applies a function to all key-value pairs in this DeltaSet and partitions the result.
Applies a function to all key-value pairs in this DeltaSet and partitions the result. This function fails if applying
flatMapFnto all key-values in the DeltaSet produces duplicate keys.If the
partitioningis not PreservesPartitioning, this transformation will shuffle data. In particular, all key-value pairs that belong to a different partition after the key transformation may have to be transferred between executors.- K2
The type of output key.
- V2
The type of output value.
- flatMapFn
The function applied to the key-value pairs in the DeltaSet.
- partitioning
Either a partitioner to use, or PreservesPartitioning to indicate that the mapped keys are always in the same Spark partition as the original keys. This will be checked at run-time.
- id
Deprecated.
- configOverride
Deprecated.
- returns
A DeltaSet that represents the result of the transformation.
- Note
All arguments must be serializable, since this transformation is serialized and sent to workers nodes.
-
abstract
def
join[W](other: DeltaSet[K, W], id: Id = autoIdAssigner("join"), configOverride: Override = DeltaSetConfig.noOverride)(implicit arg0: ClassTag[W]): DeltaSet[K, (V, W)]
Computes the inner join of this DeltaSet with another DeltaSet.
Computes the inner join of this DeltaSet with another DeltaSet. For each key contained in both DeltaSets, the result contains the pair of values associated with the key in each of the DeltaSets.
This function does not shuffle any data any data.
Both DeltaSets must be partitioned by the same partitioner. If they are not, you must explicitly repartition one or both DeltaSets.
- W
The value type of the other DeltaSet.
- other
The other DeltaSet.
- id
Deprecated.
- configOverride
Deprecated.
- returns
A DeltaSet that represents the result of the join.
- Note
All arguments must be serializable, since this transformation is serialized and sent to workers nodes.
-
abstract
def
mapGroup[K2, V2](mapFn: (K, V) ⇒ (K2, V2), partitioning: PartitioningStrategy[K2], id: Id = autoIdAssigner("mapGroup"), configOverride: Override = DeltaSetConfig.noOverride)(implicit arg0: ClassTag[K2], arg1: ClassTag[V2]): DeltaSet[K2, Iterable[V2]]
Applies a function to all key-value pairs in this DeltaSet, partitions the result, and then groups all output key-value pairs by key.
Applies a function to all key-value pairs in this DeltaSet, partitions the result, and then groups all output key-value pairs by key.
If the
partitioningis not PreservesPartitioning, this transformation will shuffle data. In particular, all key-value pairs that belong to a different partition after the key transformation may have to be transferred between executors.- K2
The type of output key.
- V2
The type of output value.
- mapFn
The function applied to the key-value pairs in the DeltaSet.
- partitioning
Either a partitioner to use, or PreservesPartitioning to indicate that the mapped keys are always in the same Spark partition as the original keys. This will be checked at run-time.
- id
Deprecated.
- configOverride
Deprecated.
- returns
A DeltaSet that represents the result of the transformation.
- Note
All arguments must be serializable, since this transformation is serialized and sent to workers nodes.
-
abstract
def
mapReduce[K2, V2](mapFn: (K, V) ⇒ (K2, V2), reduceFn: (V2, V2) ⇒ V2, partitioning: PartitioningStrategy[K2], id: Id = autoIdAssigner("mapReduce"), configOverride: Override = DeltaSetConfig.noOverride)(implicit arg0: ClassTag[K2], arg1: ClassTag[V2]): DeltaSet[K2, V2]
Applies a function to all key-value pairs in this DeltaSet, partitions the result, and then reduces all values with the same key to a single value.
Applies a function to all key-value pairs in this DeltaSet, partitions the result, and then reduces all values with the same key to a single value.
If the
partitioningis not PreservesPartitioning, this transformation will shuffle data. In particular, all key-value pairs that belong to a different partition after the key transformation may have to be transferred between executors.- K2
The type of output key.
- V2
The type of output value.
- mapFn
The function applied to the key-value pairs in the DeltaSet.
- reduceFn
The associative and commutative reduce function.
- partitioning
Either a partitioner to use, or PreservesPartitioning to indicate that the mapped keys are always in the same Spark partition as the original keys. This will be checked at run-time.
- id
Deprecated.
- configOverride
Deprecated.
- returns
A DeltaSet that represents the result of the transformation.
- Note
All arguments must be serializable, since this transformation is serialized and sent to workers nodes.
-
abstract
def
mapUnique[K2, V2](mapFn: (K, V) ⇒ (K2, V2), partitioning: PartitioningStrategy[K2], id: Id = autoIdAssigner("mapUnique"), configOverride: Override = DeltaSetConfig.noOverride)(implicit arg0: ClassTag[K2], arg1: ClassTag[V2]): DeltaSet[K2, V2]
Applies a function to all key-value pairs in this DeltaSet and partitions the result.
Applies a function to all key-value pairs in this DeltaSet and partitions the result. This function fails if applying
mapFnto all key-values in the DeltaSet produces duplicate keys.If the
partitioningis not PreservesPartitioning, this transformation will shuffle data. In particular, all key-value pairs that belong to a different partition after the key transformation may have to be transferred between executors.- K2
The type of output key.
- V2
The type of output value.
- mapFn
The function applied to the key-value pairs of the DeltaSet.
- partitioning
Either a partitioner to use, or PreservesPartitioning to indicate that the mapped keys are always in the same Spark partition as the original keys. This will be checked at run-time.
- id
Deprecated.
- configOverride
Deprecated.
- returns
A DeltaSet that represents the result of the transformation.
- Note
All arguments must be serializable, since this transformation is serialized and sent to workers nodes.
-
abstract
def
mapValuesWithResolver[V2](mapFn: (Resolver, K, V) ⇒ V2, strategies: Seq[ResolutionStrategy[K, V]], referencePartitioner: Partitioner[Key], id: Id = ..., configOverride: Override = DeltaSetConfig.noOverride)(implicit arg0: ClassTag[V2]): DeltaSet[K, V2]
Transforms the DeltaSet, the _subjects_, while having access to a Resolver that allows finding the metadata for related partitions, the _references_.
Transforms the DeltaSet, the _subjects_, while having access to a Resolver that allows finding the metadata for related partitions, the _references_.
- mapFn
The function to transform the values of the subject DeltaSet. Takes the Resolver, the key, and the original value of the subject as input; returns the new value of the subject.
- strategies
Defines a list of strategies to find the metadata corresponding to a reference key. See ResolutionStrategy.
- referencePartitioner
The partitioner used for references.
- id
Deprecated.
- configOverride
Deprecated.
- Note
The
mapFnmust be scala.Serializable as it is copied to workers and run inside Spark map functions.
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