Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/20686#discussion_r173594072
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala ---
@@ -299,18 +310,17 @@ class StringIndexerSuite
.setInputCol("label")
.setOutputCol("labelIndex")
- val expected = Seq(Set((0, 0.0), (1, 0.0), (2, 2.0), (3, 1.0), (4,
1.0), (5, 0.0)),
- Set((0, 2.0), (1, 2.0), (2, 0.0), (3, 1.0), (4, 1.0), (5, 2.0)),
- Set((0, 1.0), (1, 1.0), (2, 0.0), (3, 2.0), (4, 2.0), (5, 1.0)),
- Set((0, 1.0), (1, 1.0), (2, 2.0), (3, 0.0), (4, 0.0), (5, 1.0)))
+ val expected = Seq(Seq((0, 0.0), (1, 0.0), (2, 2.0), (3, 1.0), (4,
1.0), (5, 0.0)),
--- End diff --
I'd keep using Set. The point is to be row-order-agnostic since DataFrames
do not guarantee stable row ordering in general.
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