Class/Object

com.ibm.sparktc.sparkbench.workload.exercise

Sleep

Related Docs: object Sleep | package exercise

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case class Sleep(input: Option[String] = None, output: Option[String] = None, saveMode: String = SaveModes.error, sleepMS: Long, distribution: Option[String] = None, distributionMean: Option[Double] = None, distributionStd: Option[Double] = None, distributionMin: Option[Long] = None, distributionMax: Option[Long] = None) extends Workload with Product with Serializable

Linear Supertypes
Serializable, Serializable, Product, Equals, Workload, AnyRef, Any
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Inherited
  1. Sleep
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. Workload
  7. AnyRef
  8. Any
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Visibility
  1. Public
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Instance Constructors

  1. new Sleep(input: Option[String] = None, output: Option[String] = None, saveMode: String = SaveModes.error, sleepMS: Long, distribution: Option[String] = None, distributionMean: Option[Double] = None, distributionStd: Option[Double] = None, distributionMin: Option[Long] = None, distributionMax: Option[Long] = None)

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Value Members

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

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    AnyRef → Any

  4. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  5. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  6. val distribution: Option[String]

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  7. val distributionMax: Option[Long]

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  8. val distributionMean: Option[Double]

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  9. val distributionMin: Option[Long]

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  10. val distributionStd: Option[Double]

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  11. def doWorkload(df: Option[DataFrame] = None, spark: SparkSession): DataFrame

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    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
    Sleep → Workload

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

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    Definition Classes
    AnyRef

  13. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

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    Definition Classes
    AnyRef → Any

  15. val input: Option[String]

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    Definition Classes
    Sleep → Workload

  16. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    AnyRef

  18. final def notify(): Unit

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    Definition Classes
    AnyRef

  19. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  20. val output: Option[String]

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    Definition Classes
    Sleep → Workload

  21. def reconcileSchema(dataFrame: DataFrame): DataFrame

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    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

  22. def run(spark: SparkSession): DataFrame

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    Definition Classes
    Workload

  23. val saveMode: String

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    Definition Classes
    Sleep → Workload

  24. val sleepMS: Long

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

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    Definition Classes
    AnyRef

  26. def toMap: Map[String, Any]

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    Definition Classes
    Workload

  27. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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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