edu.berkeley.cs.amplab.mlmatrix

RowPartitionedMatrix

object RowPartitionedMatrix extends Serializable

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

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

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  3. final def ##(): Int

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  4. final def ==(arg0: AnyRef): Boolean

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  5. final def ==(arg0: Any): Boolean

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  6. def arrayToMatrix(matrixRDD: RDD[Array[Double]]): RDD[DenseMatrix[Double]]

  7. def arrayToMatrix(matrixRDD: RDD[Array[Double]], rowsPerPartition: Seq[Int], cols: Int): RDD[DenseMatrix[Double]]

  8. final def asInstanceOf[T0]: T0

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  9. def clone(): AnyRef

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    @throws( ... )

  10. def createRandom(sc: SparkContext, numRows: Int, numCols: Int, numParts: Int, cache: Boolean = true): RowPartitionedMatrix

  11. def dataFrameToMatrix(df: DataFrame): RDD[DenseMatrix[Double]]

  12. def dataFrameToMatrix(df: DataFrame, rowsPerPartition: Seq[Int], cols: Int): RDD[DenseMatrix[Double]]

  13. final def eq(arg0: AnyRef): Boolean

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  14. def equals(arg0: Any): Boolean

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  15. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )

  16. def fromArray(matrixRDD: RDD[Array[Double]], rowsPerPartition: Seq[Int], cols: Int): RowPartitionedMatrix

  17. def fromArray(matrixRDD: RDD[Array[Double]]): RowPartitionedMatrix

  18. def fromDataFrame(df: DataFrame, rowsPerPartition: Seq[Int], cols: Int): RowPartitionedMatrix

  19. def fromDataFrame(df: DataFrame): RowPartitionedMatrix

  20. def fromMatrix(matrixRDD: RDD[DenseMatrix[Double]]): RowPartitionedMatrix

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

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  22. def hashCode(): Int

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  23. final def isInstanceOf[T0]: Boolean

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

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  25. final def notify(): Unit

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  26. final def notifyAll(): Unit

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

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  28. def toString(): String

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  29. final def wait(): Unit

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

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

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