Trait

com.ibm.sparktc.sparkbench.workload

Workload

Related Doc: package workload

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trait Workload extends AnyRef

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Known Subclasses
CacheTest, GraphDataGen, KMeansDataGen, KMeansWorkload, LinearRegressionDataGen, LogisticRegressionWorkload, PartitionAndSleepWorkload, SQLWorkload, Sleep, SparkPi
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Abstract Value Members

  1. abstract def doWorkload(df: Option[DataFrame], sparkSession: 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.

  2. abstract val input: Option[String]

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  3. abstract val output: Option[String]

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  4. abstract val saveMode: String

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Concrete Value Members

  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. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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

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  10. def hashCode(): Int

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  11. final def isInstanceOf[T0]: Boolean

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

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  13. final def notify(): Unit

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  14. final def notifyAll(): Unit

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  15. 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.

  16. def run(spark: SparkSession): DataFrame

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

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  18. def toMap: Map[String, Any]

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  19. def toString(): String

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  20. final def wait(): Unit

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

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

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