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1.  final def !=(arg0: Any): Boolean

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2.  final def ##(): Int

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3.  final def ==(arg0: Any): Boolean

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4.  def apply(compression: Double = TDigest.compressionDefault, maxDiscrete: Int = TDigest.maxDiscreteDefault): TDigestMLLibVecAggregator

   Construct a TDigestMLLibVecAggregator

   Construct a TDigestMLLibVecAggregator

   compression

   the t-digest compression parameter.

   maxDiscrete

   maximum number of discrete values to track in PMF mode.

5.  final def asInstanceOf[T0]: T0

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6.  def clone(): AnyRef

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7.  final def eq(arg0: AnyRef): Boolean

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8.  def equals(arg0: Any): Boolean

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9.  def finalize(): Unit

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10.  final def getClass(): Class[_]

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11.  def hashCode(): Int

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12.  final def isInstanceOf[T0]: Boolean

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13.  final def ne(arg0: AnyRef): Boolean

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14.  final def notify(): Unit

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15.  final def notifyAll(): Unit

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

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17.  def toString(): String

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18.  def udf(compression: Double = TDigest.compressionDefault, maxDiscrete: Int = TDigest.maxDiscreteDefault): UserDefinedFunction

    Return a spark UDF, usable with DataFrames, that aggregates an MLLib Vector column using an array of t-digests.

    Return a spark UDF, usable with DataFrames, that aggregates an MLLib Vector column using an array of t-digests.

    compression

    the t-digest compression parameter.

    maxDiscrete

    maximum number of discrete values to track in PMF mode.

19.  final def wait(): Unit

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

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21.  final def wait(arg0: Long): Unit

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