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org.apache.spark.h2o.converters

WriteConverterCtxUtils

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object WriteConverterCtxUtils

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Type Members

  1. type ConversionFunction[T] = (String, Array[Byte], Option[UploadPlan], Int, Short, Array[Boolean]) ⇒ SparkJob[T]

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  2. type SparkJob[T] = (TaskContext, Iterator[T]) ⇒ (Int, Long)

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  3. type UploadPlan = Map[Int, NodeDesc]

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

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  2. final def ##(): Int

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  5. def bufferedIteratorWithSize[T](uploadPlan: Option[UploadPlan], original: Iterator[T]): (Iterator[T], Option[Int])

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    This method is used for writing data from spark partitions to h2o chunks.

    This method is used for writing data from spark partitions to h2o chunks.

    In case of internal backend it returns the original iterator and empty length because we do not need it In case of external backend it returns new iterator with the same data and the length of the data

  6. def clone(): AnyRef

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  7. def convert[T](hc: H2OContext, rdd: RDD[T], keyName: String, colNames: Array[String], expectedTypes: Array[Byte], maxVecSizes: Array[Int], sparse: Array[Boolean], func: ConversionFunction[T]): water.fvec.H2OFrame

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    Converts the RDD to H2O Frame using specified conversion function

    Converts the RDD to H2O Frame using specified conversion function

    T

    type of RDD to convert

    hc

    H2O context

    rdd

    rdd to convert

    keyName

    key of the resulting frame

    colNames

    names of the columns in the H2O Frame

    expectedTypes

    expected types of the vectors in the H2O Frame

    sparse

    if at least one column in the dataset is sparse

    func

    conversion function - the function takes parameters needed extra by specific transformations and returns function which does the general transformation

    returns

    H2O Frame

  8. def create(uploadPlan: Option[UploadPlan], partitionId: Int, totalNumOfRows: Option[Int], writeTimeout: Int, driverTimeStamp: Short): WriteConverterCtx

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