Details
Major Description
Currently, when using VectorSizeHint().setSize(3) in an ML pipeline, transforming a stream will return a nondescript exception about the stream not started. At core are the following bugs that setSize and getSize do not return values but None:
https://github.com/apache/spark/blob/master/python/pyspark/ml/feature.py#L3846
How to reproduce, using the example in the doc:
from pyspark.ml.linalg import Vectors from pyspark.ml import Pipeline, PipelineModel from pyspark.ml.feature import VectorAssembler, VectorSizeHint data = [(Vectors.dense([1., 2., 3.]), 4.)] df = spark.createDataFrame(data, ["vector", "float"]) sizeHint = VectorSizeHint(inputCol="vector", handleInvalid="skip").setSize(3) # Will fail vecAssembler = VectorAssembler(inputCols=["vector", "float"], outputCol="assembled") pipeline = Pipeline(stages=[sizeHint, vecAssembler]) pipelineModel = pipeline.fit(df) pipelineModel.transform(df).head().assembled
