Github user jkbradley commented on a diff in the pull request: https://github.com/apache/spark/pull/20111#discussion_r159106208 --- Diff: mllib/src/test/scala/org/apache/spark/ml/feature/BucketedRandomProjectionLSHSuite.scala --- @@ -98,6 +97,21 @@ class BucketedRandomProjectionLSHSuite MLTestingUtils.checkCopyAndUids(brp, brpModel) } + test("BucketedRandomProjectionLSH: streaming transform") { + val brp = new BucketedRandomProjectionLSH() + .setNumHashTables(2) + .setInputCol("keys") + .setOutputCol("values") + .setBucketLength(1.0) + .setSeed(12345) + val brpModel = brp.fit(dataset) + + testTransformer[Tuple1[Vector]](dataset.toDF(), brpModel, "keys", "values") { + case Row(_: Vector, values: Seq[_]) => --- End diff -- I don't think we have to. The main thing here is to make sure that the transform really does happen. Other tests check validity of the values.
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