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com.linkedin.feathr.sparkcommon

FeatureDerivationFunctionSpark

abstract class FeatureDerivationFunctionSpark extends FeatureDerivationFunctionBase

Spark DataFrame based derived feature base class, Feathr user can extend this class to implement their customized derivation function to produce derived features

see TestDataFrameDerivationFunctionExtractor in feathr repo for example

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FeatureDerivationFunctionBase, Serializable, Serializable, AnyRef, Any
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  1. FeatureDerivationFunctionSpark
  2. FeatureDerivationFunctionBase
  3. Serializable
  4. Serializable
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Instance Constructors

  1. new FeatureDerivationFunctionSpark()

Abstract Value Members

  1. abstract def transform(dataframe: DataFrame): DataFrame

    Append the derived feature column, the column name should be the same as declared in the Feathr featureDef file E.g, in the following TestDataFrameDerivationFunctionExtractor (extends FeatureDerivationFunctionSpark), the input dataframe will contain dependent feature columns "f1" and "f2", output DataFrame should contain the output column 'E' derivations: { E: { key: [x, y] inputs: { f1: { key: x, feature: C }, f2: { key: y, feature: D } } class: "com.linkedin.feathr.offline.TestDataFrameDerivationFunctionExtractor" }

    Append the derived feature column, the column name should be the same as declared in the Feathr featureDef file E.g, in the following TestDataFrameDerivationFunctionExtractor (extends FeatureDerivationFunctionSpark), the input dataframe will contain dependent feature columns "f1" and "f2", output DataFrame should contain the output column 'E' derivations: { E: { key: [x, y] inputs: { f1: { key: x, feature: C }, f2: { key: y, feature: D } } class: "com.linkedin.feathr.offline.TestDataFrameDerivationFunctionExtractor" }

    dataframe

    context DataFrame with all dependency feature columns ready to use, the input columns could be of any valid org.apache.spark.sql.types.DataType

    returns

    the transformed DataFrame

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. var _params: Option[Config]
  5. final def asInstanceOf[T0]: T0
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  6. def clone(): AnyRef
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    protected[lang]
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    @throws( ... ) @native()
  7. final def eq(arg0: AnyRef): Boolean
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  8. def equals(arg0: Any): Boolean
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  9. def finalize(): Unit
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  10. final def getClass(): Class[_]
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    @native()
  11. def getInputFeatureList(): Seq[JoiningFeatureParams]

    return dependency/input feature list This function is only used in derivation function that produces multiple derived features, i.e., derived features defined within 'advancedDerivations' section.

    return dependency/input feature list This function is only used in derivation function that produces multiple derived features, i.e., derived features defined within 'advancedDerivations' section. Derived features defined in 'derivations' section do not need to override this.

    Definition Classes
    FeatureDerivationFunctionBase
  12. def getOutputFeatureList(): Seq[String]

    return output feature list Used together with getInputFeatureList()

    return output feature list Used together with getInputFeatureList()

    Definition Classes
    FeatureDerivationFunctionBase
  13. def hashCode(): Int
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    Annotations
    @native()
  14. def init(params: Config): Unit

    init with parameter map

    init with parameter map

    Definition Classes
    FeatureDerivationFunctionBase
  15. final def isInstanceOf[T0]: Boolean
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    Any
  16. final def ne(arg0: AnyRef): Boolean
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    AnyRef
  17. final def notify(): Unit
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    @native()
  18. final def notifyAll(): Unit
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  19. final def synchronized[T0](arg0: ⇒ T0): T0
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  20. def toString(): String
    Definition Classes
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  21. def validateInputSchema(schema: StructType): Unit

    Check the validity of the input DataFrame, raise an exception if the schema is invalid, e.g, does not contain required input columns or has incorrect column types It is the developer's responsibility to validate the input schema's validity

  22. final def wait(): Unit
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    @throws( ... )
  23. final def wait(arg0: Long, arg1: Int): Unit
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  24. final def wait(arg0: Long): Unit
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