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com.datastax.spark.connector.rdd.partitioner

TokenRangeClusterer

Related Docs: object TokenRangeClusterer | package partitioner

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class TokenRangeClusterer[V, T <: Token[V]] extends AnyRef

Groups a set of token ranges into groupCount groups containing not more than maxGroupSize token ranges. Each group will form a single CassandraRDDPartition.

The algorithm is as follows: 1. Sort token ranges by endpoints lexicographically. 2. Take the highest possible number of token ranges from the beginning of the list, such that their sum of ringFraction does not exceed ringFractionPerGroup and they all contain at least one common endpoint. If it is not possible, take at least one item. Those token ranges will make a group. 3. Repeat the previous step until no more token ranges left.

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  1. new TokenRangeClusterer(groupCount: Int, maxGroupSize: Int = Int.MaxValue)

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Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  9. final def getClass(): Class[_]

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  10. def group(tokenRanges: Seq[TokenRange[V, T]]): Iterable[Seq[TokenRange[V, T]]]

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    Groups small token ranges on the same server(s) in order to reduce task scheduling overhead.

    Groups small token ranges on the same server(s) in order to reduce task scheduling overhead. Useful mostly with virtual nodes, which may create lots of small token range splits. Each group will make a single Spark task.

  11. def hashCode(): Int

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  18. final def wait(): Unit

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