Class

com.rbmhtechnology.eventuate.adapter.spark

SparkBatchAdapter

Related Doc: package spark

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class SparkBatchAdapter extends AnyRef

Eventuate Spark adapter for batch processing events from event logs with a Cassandra storage backend.

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Instance Constructors

  1. new SparkBatchAdapter(context: SparkContext, config: Config)

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    context

    Spark context configured for using the Spark Cassandra connector. Relevant configuration parameters are:

    • spark.cassandra.connection.host: hostname of a Cassandra contact point
    • spark.cassandra.connection.port: port of a Cassandra contact point
    • spark.cassandra.auth.username: connection username
    • spark.cassandra.auth.password: connection password
    config

    Configuration for a Cassandra storage backend and application-specific event serializers. Relevant storage backend configuration parameters are:

    • eventuate.log.cassandra.keyspace: keyspace of the event log table
    • eventuate.log.cassandra.table-prefix: prefix of the event log table

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

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  6. val config: Config

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    Configuration for a Cassandra storage backend and application-specific event serializers.

    Configuration for a Cassandra storage backend and application-specific event serializers. Relevant storage backend configuration parameters are:

    • eventuate.log.cassandra.keyspace: keyspace of the event log table
    • eventuate.log.cassandra.table-prefix: prefix of the event log table

  7. val context: SparkContext

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    Spark context configured for using the Spark Cassandra connector.

    Spark context configured for using the Spark Cassandra connector. Relevant configuration parameters are:

    • spark.cassandra.connection.host: hostname of a Cassandra contact point
    • spark.cassandra.connection.port: port of a Cassandra contact point
    • spark.cassandra.auth.username: connection username
    • spark.cassandra.auth.password: connection password

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  9. def equals(arg0: Any): Boolean

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  10. def eventBatch(logId: String, fromSequenceNr: Long = 1L): RDD[DurableEvent]

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    Exposes an event log with given logId as Spark RDD[DurableEvent].

    Exposes an event log with given logId as Spark RDD[DurableEvent]. Events are read concurrently from multiple Cassandra partitions so that events in the RDD are ordered per partition (by DurableEvent.localSequenceNr). Applications that want to have a total event ordering should sort the resulting RDD with .sortBy(_.localSequenceNr).

    logId

    Id of the event log.

    fromSequenceNr

    Sequence number from where to start reading.

  11. def finalize(): Unit

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