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3.  final def ==(arg0: Any): Boolean

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12.  def load(spark: SparkSession, dataPathWithScheme: String, columnDescription: Path = null, params: PoolLoadParams = new PoolLoadParams(), pairsDataPathWithScheme: String = null): Pool

    Load dataset in one of CatBoost's natively supported formats:

    Load dataset in one of CatBoost's natively supported formats:

    • dsv
    • libsvm

    spark

    SparkSession

    dataPathWithScheme

    Path with scheme to dataset in CatBoost format. For example, dsv:///home/user/datasets/my_dataset/train.dsv or libsvm:///home/user/datasets/my_dataset/train.libsvm

    columnDescription

    Path to column description file

    params

    Additional params specifying data format.

    pairsDataPathWithScheme

    (optional) Path with scheme to dataset pairs in CatBoost format. Only "dsv-grouped" format is supported for now. For example, dsv-grouped:///home/user/datasets/my_dataset/train_pairs.dsv

    returns

    Pool containing loaded data.

    Example:

    1. val spark = SparkSession.builder()
         .master("local[*]")
         .appName("testLoadDSVSimple")
         .getOrCreate()
       
       val pool = Pool.load(
         spark,
         "dsv:///home/user/datasets/my_dataset/train.dsv",
         columnDescription = "/home/user/datasets/my_dataset/cd"
       )
       
        val poolWithPairs = Pool.load(
         spark,
         "dsv:///home/user/datasets/my_dataset_with_pairs/train.dsv",
         columnDescription = "/home/user/datasets/my_dataset_with_pairs/cd",
         pairsDataPathWithScheme = "dsv-grouped:///home/user/datasets/my_dataset_with_pairs/train_pairs.dsv"
       )

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15.  final def notifyAll(): Unit

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16.  def read(spark: SparkSession): PoolReader

    Returns a PoolReader that can be used to read Pool (API similar to Spark's DataFrameReader).

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

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