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spark mllib的pipeline，是指将多个机器学习的算法串联到一个工作链中，依次执行各种算法。/**
* :: Experimental ::
* 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 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.
*/
@Experimental
class Pipeline(override val uid: String) extends Estimator[PipelineModel] {
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原文地址：http://www.cnblogs.com/zwCHAN/p/4633753.html
