Github user MLnick commented on a diff in the pull request: https://github.com/apache/spark/pull/18281#discussion_r128456402 --- Diff: python/pyspark/ml/tests.py --- @@ -1389,11 +1389,25 @@ def test_output_columns(self): (2.0, Vectors.dense(0.5, 0.5))], ["label", "features"]) lr = LogisticRegression(maxIter=5, regParam=0.01) - ovr = OneVsRest(classifier=lr) + ovr = OneVsRest(classifier=lr, parallelism=1) model = ovr.fit(df) output = model.transform(df) self.assertEqual(output.columns, ["label", "features", "prediction"]) + def test_parallelism_doesnt_change_output(self): + df = self.spark.createDataFrame([(0.0, Vectors.dense(1.0, 0.8)), + (1.0, Vectors.sparse(2, [], [])), + (2.0, Vectors.dense(0.5, 0.5))], + ["label", "features"]) + ovrPar1 = OneVsRest(classifier=LogisticRegression(maxIter=5, regParam=.01), parallelism=1) + modelPar1 = ovrPar1.fit(df) + ovrPar2 = OneVsRest(classifier=LogisticRegression(maxIter=5, regParam=.01), parallelism=2) + modelPar2 = ovrPar2.fit(df) + self.assertEqual(modelPar1.getPredictionCol(), modelPar2.getPredictionCol()) --- End diff -- Not really sure what the point of this assert is? Did you intend to check equality of actual predictions?
--- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org