SnappyStreamingContext

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

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6. final def asInstanceOf[T0]: T0

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10. def finalize(): Unit

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11. def getActive(): Option[SnappyStreamingContext]

    :: Experimental ::

    :: Experimental ::

    Get the currently active context, if there is one. Active means started but not stopped.

    Annotations

    @Experimental()

12. def getActiveOrCreate(checkpointPath: String, creatingFunc: () ⇒ SnappyStreamingContext, hadoopConf: Configuration = SparkHadoopUtil.get.conf, createOnError: Boolean = false): SnappyStreamingContext

    :: Experimental ::

    :: Experimental ::

    Either get the currently active StreamingContext (that is, started but not stopped), OR recreate a StreamingContext from checkpoint data in the given path. If checkpoint data does not exist in the provided, then create a new StreamingContext by calling the provided creatingFunc.

    checkpointPath

    Checkpoint directory used in an earlier StreamingContext program

    creatingFunc

    Function to create a new StreamingContext

    hadoopConf

    Optional Hadoop configuration if necessary for reading from the file system

    createOnError

    Optional, whether to create a new StreamingContext if there is an error in reading checkpoint data. By default, an exception will be thrown on error.

    Annotations

    @Experimental()

13. def getActiveOrCreate(creatingFunc: () ⇒ SnappyStreamingContext): SnappyStreamingContext

    :: Experimental :: Either return the "active" StreamingContext (that is, started but not stopped), or create a new StreamingContext that is started by the creating function

    :: Experimental :: Either return the "active" StreamingContext (that is, started but not stopped), or create a new StreamingContext that is started by the creating function

    creatingFunc

    Function to create a new StreamingContext

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    @Experimental()

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

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15. def getInstance(): Option[SnappyStreamingContext]

    :: Experimental ::

    :: Experimental ::

    Get the currently created context, it may be started or not, but never stopped.

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    @Experimental()

16. def getOrCreate(checkpointPath: String, creatingFunc: () ⇒ SnappyStreamingContext, hadoopConf: Configuration = SparkHadoopUtil.get.conf, createOnError: Boolean = false): SnappyStreamingContext

    Either recreate a SnappyStreamingContext from checkpoint data or create a new SnappyStreamingContext.

    Either recreate a SnappyStreamingContext from checkpoint data or create a new SnappyStreamingContext. If checkpoint data exists in the provided checkpointPath, then SnappyStreamingContext will be recreated from the checkpoint data. If the data does not exist, then the StreamingContext will be created by called the provided creatingFunc.

    checkpointPath

    Checkpoint directory used in an earlier StreamingContext program

    creatingFunc

    Function to create a new SnappyStreamingContext

    hadoopConf

    Optional Hadoop configuration if necessary for reading from the file system

    createOnError

    Optional, whether to create a new SnappyStreamingContext if there is an error in reading checkpoint data. By default, an exception will be thrown on error.

17. def hashCode(): Int

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18. final def isInstanceOf[T0]: Boolean

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

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22. def logDebug(msg: ⇒ String): Unit

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

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24. def logError(msg: ⇒ String): Unit

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

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26. def logInfo(msg: ⇒ String): Unit

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27. def logName: String

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

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29. def logTrace(msg: ⇒ String): Unit

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

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31. def logWarning(msg: ⇒ String): Unit

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33. final def notify(): Unit

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

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36. def toString(): String

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37. final def wait(): Unit

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38. final def wait(arg0: Long, arg1: Int): Unit

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39. final def wait(arg0: Long): Unit

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