Github user MrBago commented on a diff in the pull request:
https://github.com/apache/spark/pull/18888#discussion_r132575143
--- Diff: python/pyspark/ml/pipeline.py ---
@@ -242,3 +327,65 @@ def _to_java(self):
JavaParams._new_java_obj("org.apache.spark.ml.PipelineModel",
self.uid, java_stages)
return _java_obj
+
+
+@inherit_doc
+class SharedReadWrite():
+ """
+ Functions for :py:class:`MLReader` and :py:class:`MLWriter` shared
between
+ :py:class:'Pipeline' and :py:class'PipelineModel'
+
+ .. versionadded:: 2.3.0
+ """
+
+ @staticmethod
+ def validateStages(stages):
+ """
+ Check that all stages are Writable
+ """
+ for stage in stages:
+ if not isinstance(stage, MLWritable):
+ raise ValueError("Pipeline write will fail on this pipline
" +
+ "because stage %s of type %s is not
MLWritable",
+ stage.uid, type(stage))
+
+ @staticmethod
+ def saveImpl(instance, stages, sc, path):
+ """
+ Save metadata and stages for a :py:class:`Pipeline` or
:py:class:`PipelineModel`
+ - save metadata to path/metadata
+ - save stages to stages/IDX_UID
+ """
+ stageUids = [stage.uid for stage in stages]
+ jsonParams = {'stageUids': stageUids, 'savedAsPython': True}
+ DefaultParamsWriter.saveMetadata(instance, path, sc,
paramMap=jsonParams)
+ stagesDir = os.path.join(path, "stages")
--- End diff --
@jkbradley, what's the right way to handle Paths in pyspark? Scala has
`org.apache.hadoop.fs.Path`, is there something similar in pyspark?
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