srowen commented on a change in pull request #33449:
URL: https://github.com/apache/spark/pull/33449#discussion_r673607385
##########
File path:
mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala
##########
@@ -531,7 +534,8 @@ class WeightedLeastSquaresSuite extends SparkFunSuite with
MLlibTestSparkContext
standardization <- Seq(false, true)) {
for (solver <- WeightedLeastSquares.supportedSolvers) {
val wls = new WeightedLeastSquares(fitIntercept, regParam,
elasticNetParam = 0.0,
- standardizeFeatures = standardization, standardizeLabel = true,
solverType = solver)
+ standardizeFeatures = standardization, standardizeLabel = true,
solverType = solver,
Review comment:
The updated tol is needed to allow it to pass - and matches the tol in
the R code that was used to generate 'correct' answers, so seems OK. Same with
maxIter. I made a similar change throughout this test suite for consistency.
##########
File path: mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala
##########
@@ -295,7 +295,9 @@ class VectorsSuite extends SparkFunSuite with Logging {
val denseVector1 = Vectors.dense(sparseVector1.toArray)
val denseVector2 = Vectors.dense(sparseVector2.toArray)
- val squaredDist = breezeSquaredDistance(sparseVector1.asBreeze,
sparseVector2.asBreeze)
+ val squaredDist = sparseVector1.toArray.zip(sparseVector2.toArray).map {
Review comment:
There was a weird compile error on breeze's squaredDistance, so I just
wrote it out here instead
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