InferenceTools

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. def convertInferenceConfigToDataFrame(config: InferenceMainConfig): DataFrame

   

   Seems a bit counter-intuitive to do this, but this allows for cloud-agnostic storage of the config.

   Seems a bit counter-intuitive to do this, but this allows for cloud-agnostic storage of the config. Otherwise, a configuration would need to be created to manage which cloud this is operating on and handle native SDK object writers. Instead of re-inventing the wheel here, a DataFrame can be serialized to any cloud-native storage medium with very little issue.

   config

   The inference configuration generated for a particular modeling run

   returns

   A DataFrame consisting of a single row and a single field. Cell 1:1 contains the json string.

7. def convertInferenceConfigToJson(config: InferenceMainConfig): InferenceJsonReturn

   

   Handler method for converting the InferenceMainConfig object to a serializable Json String with correct scala-compatible data structures.

   Handler method for converting the InferenceMainConfig object to a serializable Json String with correct scala-compatible data structures.

   config

   instance of InferenceMainConfig

   returns

   [InferenceJsonReturn] consisting of compact form (for logging) and prettyprint form (human readable)

8. def convertJsonConfigToClass(jsonConfig: String): InferenceMainConfig

   

   Handler method for converting a read-in json config String to an instance of InferenceMainConfig

   Handler method for converting a read-in json config String to an instance of InferenceMainConfig

   jsonConfig

   the config as a Json-formatted String

   returns

   config as InstanceOf[InferenceMainConfig]

9. def convertMainConfigToJson(config: MainConfig): MainJsonReturn

   

10. def createInferencePayload(dataFrame: DataFrame, modelingColumnsPayload: Array[String], allColumnsPayload: Array[String]): InferencePayload

    

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

    

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12. def equals(arg0: Any): Boolean

    

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13. def extractInferenceConfigFromDataFrame(configDataFrame: DataFrame): InferenceMainConfig

    

    Extract the InferenceMainConfig from a stored DataFrame containing the string-encoded json in row 1, column 1

    Extract the InferenceMainConfig from a stored DataFrame containing the string-encoded json in row 1, column 1

    configDataFrame

    A Dataframe that contains the configuration for the Inference run.

    returns

    an instance of InferenceMainConfig

14. def extractInferenceJsonFromDataFrame(configDataFrame: DataFrame): String

    

    From a supplied DataFrame that contains the configuration in cell 1:1, get the json string

    From a supplied DataFrame that contains the configuration in cell 1:1, get the json string

    configDataFrame

    A Dataframe that contains the configuration for the Inference run.

    returns

    The string-encoded json payload for InferenceMainConfig

15. def finalize(): Unit

    

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

    

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17. def hashCode(): Int

    

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18. final def isInstanceOf[T0]: Boolean

    

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

    

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20. final def notify(): Unit

    

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21. final def notifyAll(): Unit

    

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22. def removeArrayOfColumns(payload: InferencePayload, removalArray: Array[String]): InferencePayload

    

23. lazy val sc: SparkContext

    

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    SparkSessionWrapper

24. lazy val spark: SparkSession

    

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    SparkSessionWrapper

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

    

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26. def toString(): String

    

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27. final def wait(): Unit

    

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

    

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

    

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