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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 convertToHoconConfig(params: String): String
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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11.  def hashCode(): Int

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12.  final def isInstanceOf[T0]: Boolean

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13.  def loadSourceDataframe(args: Array[String], featureNamesInAnchorSet: Set[String]): Map[String, DataFrame]

    Load the DataFrames for sources that needs preprocessing by Pyspark.

    Load the DataFrames for sources that needs preprocessing by Pyspark.

    args

    Same arguments for the main job.

    featureNamesInAnchorSet

    A set of feature names of an anchor sorted and joined by comma. For example, anchor1 -> f1, f2, anchor2 -> f3, f4. Then the set is ("f1,f2", "f3,f4")

    returns

    A Java map whose key is Feature names of an anchor sorted and joined by comma and value is the DataFrame for this anchor source. For example, anchor1 -> f1, f2, anchor2 -> f3, f4. Then the result is Map("f1,f2" -> df1, "f3,f4" -> df2).

14.  val logger: Logger
15.  def main(args: Array[String]): Unit
16.  def mainWithPreprocessedDataFrame(args: Array[String], preprocessedDfMap: Map[String, DataFrame]): Unit
17.  final def ne(arg0: AnyRef): Boolean

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18.  final def notify(): Unit

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19.  final def notifyAll(): Unit

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20.  def prepareSparkSession(args: Array[String]): FeathrGenPreparationInfo
21.  def run(ss: SparkSession, featureGenConfigPath: String, featureDefInputs: FeatureDefinitionsInput, jobContext: FeatureGenJobContext): Map[TaggedFeatureName, SparkFeaturizedDataset]

    generate Feathr features according to config file paths and jobContext

    generate Feathr features according to config file paths and jobContext

    ss

    spark session

    featureGenConfigPath

    feature generation config file path

    featureDefInputs

    contains feature definition file paths and settings

    jobContext

    job context

    returns

    generated feature data

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

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23.  def toString(): String

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24.  final def wait(): Unit

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

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26.  final def wait(arg0: Long): Unit

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