Object

ai.h2o.sparkling.backend.converters

SparkDataFrameConverter

Related Doc: package converters

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object SparkDataFrameConverter extends Logging

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  1. SparkDataFrameConverter
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  11. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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  14. def log: Logger

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

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

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

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

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

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

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  21. def logName: String

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

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

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

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  27. final def notify(): Unit

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  28. final def notifyAll(): Unit

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

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  30. def toDataFrame(hc: H2OContext, fr: H2OFrame, copyMetadata: Boolean): DataFrame

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    Create a Spark DataFrame from a given REST-based H2O frame.

    Create a Spark DataFrame from a given REST-based H2O frame.

    hc

    an instance of H2O context

    fr

    an instance of H2O frame

    copyMetadata

    copy H2O metadata into Spark DataFrame

    returns

    a new DataFrame definition using given H2OFrame as data source

  31. def toH2OFrame(hc: H2OContext, dataFrame: DataFrame, frameKeyName: Option[String]): H2OFrame

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  32. def toString(): String

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  33. final def wait(): Unit

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

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