case class CassandraPartition[V, T <: Token[V]](index: Int, endpoints: Array[String], tokenRanges: Iterable[CqlTokenRange[V, T]], dataSize: Long) extends EndpointPartition with InputPartition with Product with Serializable
Metadata describing Cassandra table partition processed by a single Spark task.
Beware the term "partition" is overloaded. Here, in the context of Spark,
it means an arbitrary collection of rows that can be processed locally on a single Cassandra cluster node.
A CassandraPartition typically contains multiple CQL partitions, i.e. rows identified by different values of
the CQL partitioning key.
- index
identifier of the partition, used internally by Spark
- endpoints
which nodes the data partition is located on
- tokenRanges
token ranges determining the row set to be fetched
- dataSize
estimated amount of data in the partition
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Instance Constructors
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new
CassandraPartition(index: Int, endpoints: Array[String], tokenRanges: Iterable[CqlTokenRange[V, T]], dataSize: Long)
- index
identifier of the partition, used internally by Spark
- endpoints
which nodes the data partition is located on
- tokenRanges
token ranges determining the row set to be fetched
- dataSize
estimated amount of data in the partition
Value Members
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final
def
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- val dataSize: Long
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val
endpoints: Array[String]
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- CassandraPartition → EndpointPartition
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final
def
eq(arg0: AnyRef): Boolean
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equals(other: Any): Boolean
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hashCode(): Int
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val
index: Int
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- CassandraPartition → Partition
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def
preferredLocations(): Array[String]
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- CassandraPartition → InputPartition
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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- val tokenRanges: Iterable[CqlTokenRange[V, T]]
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final
def
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(Since version ) see corresponding Javadoc for more information.