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c

com.linkedin.feathr.sparkcommon

OutputProcessor

abstract class OutputProcessor extends Serializable

base class for a post processor in feature data generation User can apply customized operation on the feature data, e.g, write to disk/console see example in feathr repo, e.g, WriteToConsolePostProcessor, WriteToHDFSPostProcessor

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Instance Constructors

  1. new OutputProcessor(outputProcessorConfig: OutputProcessorConfig, endTimeOpt: Option[String] = None)

    outputProcessorConfig

    output processor config object

    endTimeOpt

    end time of feature generation date, in form of yyyy/MM/dd

Abstract Value Members

  1. abstract def processAll(ss: SparkSession, featureData: Map[TaggedFeatureName, (DataFrame, Header)]): Map[TaggedFeatureName, (DataFrame, Header)]

    process all feature data(dataframes)

    process all feature data(dataframes)

    ss

    Spark session

    featureData

    map of string tagged feature name to pair of (feature column name in the dataframe, the dataframe contains the feature) each feature is represented as a column in the dataframe

    returns

    processed dataframe and header

  2. abstract def processSingle(ss: SparkSession, df: DataFrame, header: Header, parentPath: String): (DataFrame, Header)

    process a single dataframe, typically called by processAll.

    process a single dataframe, typically called by processAll.

    ss

    Spark session

    df

    dataframe contains a set of features

    header

    contains meta of the datefeathr

    parentPath

    path to save the dataframe

    returns

    processed dataframe and header

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  15. val outputProcessorConfig: OutputProcessorConfig
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