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za.co.absa.cobrix.spark.cobol.utils

SparkUtils

Related Doc: package utils

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object SparkUtils

This object contains common Spark tools used for easier processing of dataframes originated from mainframes.

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  1. final def !=(arg0: Any): Boolean

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  6. def convertDataFrameToPrettyJSON(df: DataFrame, takeN: Int = 0): String

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  7. def convertDataframeFieldsToStrings(df: DataFrame): DataFrame

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    Given an instance of DataFrame returns a dataframe where all primitive fields are converted to String

    Given an instance of DataFrame returns a dataframe where all primitive fields are converted to String

    df

    A dataframe

    returns

    A new dataframe with all primitive fields as Strings.

  8. def currentActiveExecutors(sc: SparkContext): Seq[String]

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    Retrieves all executors available for the current job.

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  12. def flattenSchema(df: DataFrame, useShortFieldNames: Boolean = false): DataFrame

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    Given an instance of DataFrame returns a dataframe with flattened schema.

    Given an instance of DataFrame returns a dataframe with flattened schema. All nested structures are flattened and arrays are projected as columns.

    Note. The method checks the maximum size for each array and that could perform slowly, especially on a vary big dataframes.

    df

    A dataframe

    useShortFieldNames

    When flattening a schema each field name will contain full path. You can override this behavior and use a short field names instead

    returns

    A new dataframe with flat schema.

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  19. def prettyJSON(jsonIn: String): String

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