public abstract class Partitioner
extends java.lang.Object
implements scala.Serializable
numPartitions - 1
.Constructor and Description |
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Partitioner() |
Modifier and Type | Method and Description |
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static Partitioner |
defaultPartitioner(RDD<?> rdd,
scala.collection.Seq<RDD<?>> others)
Choose a partitioner to use for a cogroup-like operation between a number of RDDs.
|
abstract int |
getPartition(java.lang.Object key) |
abstract int |
numPartitions() |
public static Partitioner defaultPartitioner(RDD<?> rdd, scala.collection.Seq<RDD<?>> others)
If any of the RDDs already has a partitioner, choose that one.
Otherwise, we use a default HashPartitioner. For the number of partitions, if spark.default.parallelism is set, then we'll use the value from SparkContext defaultParallelism, otherwise we'll use the max number of upstream partitions.
Unless spark.default.parallelism is set, the number of partitions will be the same as the number of partitions in the largest upstream RDD, as this should be least likely to cause out-of-memory errors.
We use two method parameters (rdd, others) to enforce callers passing at least 1 RDD.
rdd
- (undocumented)others
- (undocumented)public abstract int numPartitions()
public abstract int getPartition(java.lang.Object key)