Packages

case class KMeansDataGen(numRows: Int, numCols: Int, input: Option[String] = None, output: Option[String], saveMode: String, k: Int, scaling: Double, numPartitions: Int) extends Workload with Product with Serializable

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Serializable, Serializable, Product, Equals, Workload, AnyRef, Any
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  1. KMeansDataGen
  2. Serializable
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  6. Workload
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Instance Constructors

  1. new KMeansDataGen(numRows: Int, numCols: Int, input: Option[String] = None, output: Option[String], saveMode: String, k: Int, scaling: Double, numPartitions: Int)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  6. def doWorkload(df: Option[DataFrame] = None, spark: SparkSession): DataFrame

    Actually run the workload.

    Actually run the workload. Takes an optional DataFrame as input if the user supplies an inputDir, and returns the generated results DataFrame.

    Definition Classes
    KMeansDataGen → Workload
  7. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  8. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  9. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  10. val input: Option[String]
    Definition Classes
    KMeansDataGen → Workload
  11. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  12. val k: Int
  13. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  14. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  15. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  16. val numCols: Int
  17. val numPartitions: Int
  18. val numRows: Int
  19. val output: Option[String]
    Definition Classes
    KMeansDataGen → Workload
  20. def reconcileSchema(dataFrame: DataFrame): DataFrame

    Validate that the data set has a correct schema and fix if necessary.

    Validate that the data set has a correct schema and fix if necessary. This is to solve issues such as the KMeans load-from-disk pathway returning a DataFrame with all the rows as StringType instead of DoubleType.

    Definition Classes
    Workload
  21. def run(spark: SparkSession): DataFrame
    Definition Classes
    Workload
  22. val saveMode: String
    Definition Classes
    KMeansDataGen → Workload
  23. val scaling: Double
  24. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  25. def toMap: Map[String, Any]
    Definition Classes
    Workload
  26. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  27. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  28. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from Workload

Inherited from AnyRef

Inherited from Any

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