class ShuffleDependency[K, V, C] extends Dependency[Product2[K, V]]
:: DeveloperApi :: Represents a dependency on the output of a shuffle stage. Note that in the case of shuffle, the RDD is transient since we don't need it on the executor side.
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new
ShuffleDependency(_rdd: RDD[_ <: Product2[K, V]], partitioner: Partitioner, serializer: Serializer = SparkEnv.get.serializer, keyOrdering: Option[Ordering[K]] = None, aggregator: Option[Aggregator[K, V, C]] = None, mapSideCombine: Boolean = false)(implicit arg0: ClassTag[K], arg1: ClassTag[V], arg2: ClassTag[C])
- _rdd
the parent RDD
- partitioner
partitioner used to partition the shuffle output
- serializer
Serializer to use. If not set explicitly then the default serializer, as specified by
spark.serializer
config option, will be used.- keyOrdering
key ordering for RDD's shuffles
- aggregator
map/reduce-side aggregator for RDD's shuffle
- mapSideCombine
whether to perform partial aggregation (also known as map-side combine)
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- val aggregator: Option[Aggregator[K, V, C]]
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- val keyOrdering: Option[Ordering[K]]
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- val partitioner: Partitioner
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def
rdd: RDD[Product2[K, V]]
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- ShuffleDependency → Dependency
- val serializer: Serializer
- val shuffleHandle: ShuffleHandle
- val shuffleId: Int
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