public class Pipeline extends Estimator<PipelineModel>
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 an 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.| Constructor and Description |
|---|
Pipeline() |
| Modifier and Type | Method and Description |
|---|---|
PipelineModel |
fit(SchemaRDD dataset,
ParamMap paramMap)
Fits the pipeline to the input dataset with additional parameters.
|
PipelineStage[] |
getStages() |
Pipeline |
setStages(PipelineStage[] value) |
Param<PipelineStage[]> |
stages()
param for pipeline stages
|
org.apache.spark.sql.catalyst.types.StructType |
transformSchema(org.apache.spark.sql.catalyst.types.StructType schema,
ParamMap paramMap)
Derives the output schema from the input schema and parameters.
|
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitexplainParams, get, getParam, isSet, paramMap, params, set, validate, validateuidinitializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarningpublic Param<PipelineStage[]> stages()
public Pipeline setStages(PipelineStage[] value)
public PipelineStage[] getStages()
public PipelineModel fit(SchemaRDD dataset, ParamMap paramMap)
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.
fit in class Estimator<PipelineModel>dataset - input datasetparamMap - parameter mappublic org.apache.spark.sql.catalyst.types.StructType transformSchema(org.apache.spark.sql.catalyst.types.StructType schema,
ParamMap paramMap)
PipelineStagetransformSchema in class PipelineStage