Package org.apache.spark.ml

Class Pipeline

Object
org.apache.spark.ml.PipelineStage
org.apache.spark.ml.Estimator<PipelineModel>
org.apache.spark.ml.Pipeline
All Implemented Interfaces:
Serializable, org.apache.spark.internal.Logging, Params, Identifiable, MLWritable
public class Pipeline extends Estimator<PipelineModel> implements MLWritable
A simple pipeline, which acts as an estimator. A Pipeline consists of a sequence of stages, each of which is either an Estimator or a Transformer. When Pipeline.fit is called, the stages are executed in order. If a stage is an Estimator, its Estimator.fit method will be called on the input dataset to fit a model. Then the model, which is a transformer, will be used to transform the dataset as the input to the next stage. If a stage is a Transformer, its Transformer.transform method will be called to produce the dataset for the next stage. The fitted model from a Pipeline is a PipelineModel, which consists of fitted models and transformers, corresponding to the pipeline stages. If there are no stages, the pipeline acts as an identity transformer.
See Also:

  • Constructor Details

    • Pipeline

      public Pipeline(String uid)

    • Pipeline

      public Pipeline()

  • Method Details

    • read

      public static MLReader<Pipeline> read()

    • load

      public static Pipeline load(String path)

    • uid

      public String uid()
      Description copied from interface: Identifiable
      An immutable unique ID for the object and its derivatives.
      Specified by:
      uid in interface Identifiable
      Returns:
      (undocumented)

    • stages

      public Param<PipelineStage[]> stages()
      param for pipeline stages
      Returns:
      (undocumented)

    • setStages

      public Pipeline setStages(PipelineStage[] value)

    • getStages

      public PipelineStage[] getStages()

    • fit

      public PipelineModel fit(Dataset<?> dataset)
      Fits the pipeline to the input dataset with additional parameters. If a stage is an Estimator, its Estimator.fit method will be called on the input dataset to fit a model. Then the model, which is a transformer, will be used to transform the dataset as the input to the next stage. If a stage is a Transformer, its Transformer.transform method will be called to produce the dataset for the next stage. The fitted model from a Pipeline is an PipelineModel, which consists of fitted models and transformers, corresponding to the pipeline stages. If there are no stages, the output model acts as an identity transformer.

      Specified by:
      fit in class Estimator<PipelineModel>
      Parameters:
      dataset - input dataset
      Returns:
      fitted pipeline

    • copy

      public Pipeline copy(ParamMap extra)
      Description copied from interface: Params
      Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See defaultCopy().
      Specified by:
      copy in interface Params
      Specified by:
      copy in class Estimator<PipelineModel>
      Parameters:
      extra - (undocumented)
      Returns:
      (undocumented)

    • transformSchema

      public StructType transformSchema(StructType schema)
      Description copied from class: PipelineStage
      Check transform validity and derive the output schema from the input schema.

      We check validity for interactions between parameters during transformSchema and raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled by Param.validate().

      Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.

      Specified by:
      transformSchema in class PipelineStage
      Parameters:
      schema - (undocumented)
      Returns:
      (undocumented)

    • write

      public MLWriter write()
      Description copied from interface: MLWritable
      Returns an MLWriter instance for this ML instance.
      Specified by:
      write in interface MLWritable
      Returns:
      (undocumented)