org.apache.spark.rdd

SequenceFileRDDFunctions

class SequenceFileRDDFunctions[K, V] extends Logging with Serializable

Extra functions available on RDDs of (key, value) pairs to create a Hadoop SequenceFile, through an implicit conversion. Note that this can't be part of PairRDDFunctions because we need more implicit parameters to convert our keys and values to Writable.

Import org.apache.spark.SparkContext._ at the top of their program to use these functions.

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Instance Constructors

  1. new SequenceFileRDDFunctions(self: RDD[(K, V)])(implicit arg0: (K) ⇒ Writable, arg1: ClassTag[K], arg2: (V) ⇒ Writable, arg3: ClassTag[V])

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

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

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

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  14. def isTraceEnabled(): Boolean

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  15. def log: Logger

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  16. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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  17. def logDebug(msg: ⇒ String): Unit

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  18. def logError(msg: ⇒ String, throwable: Throwable): Unit

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  19. def logError(msg: ⇒ String): Unit

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  20. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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  21. def logInfo(msg: ⇒ String): Unit

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  22. def logName: String

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  23. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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  24. def logTrace(msg: ⇒ String): Unit

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  25. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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  27. final def ne(arg0: AnyRef): Boolean

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  28. final def notify(): Unit

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  29. final def notifyAll(): Unit

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  30. def saveAsSequenceFile(path: String, codec: Option[Class[_ <: CompressionCodec]] = None): Unit

    Output the RDD as a Hadoop SequenceFile using the Writable types we infer from the RDD's key and value types.

    Output the RDD as a Hadoop SequenceFile using the Writable types we infer from the RDD's key and value types. If the key or value are Writable, then we use their classes directly; otherwise we map primitive types such as Int and Double to IntWritable, DoubleWritable, etc, byte arrays to BytesWritable, and Strings to Text. The path can be on any Hadoop-supported file system.

  31. final def synchronized[T0](arg0: ⇒ T0): T0

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  32. def toString(): String

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  33. final def wait(): Unit

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