Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/15851#discussion_r87579139
--- Diff: R/pkg/inst/tests/testthat/test_mllib.R ---
@@ -971,10 +971,15 @@ test_that("spark.randomForest Classification", {
predictions <- collect(predict(model, data))$prediction
expect_equal(length(grep("1.0", predictions)), 50)
expect_equal(length(grep("2.0", predictions)), 50)
+
+ # spark.randomForest classification can work on libsvm data
+ data <-
read.df(absoluteSparkPath("data/mllib/sample_multiclass_classification_data.txt"),
+ source = "libsvm")
+ model <- spark.randomForest(data, label ~ features, "classification")
+ expect_equal(summary(model)$numFeatures, 4)
--- End diff --
BTW, I only add tests of libsvm data for ```spark.gbt``` and
```spark.randomForest```. This PR fix the exception for ```spark.naiveBayes```
and ```spark.glm``` also, I did not add tests for those algorithms because we
fix the issue at ```RWrapperUtils.checkDataColumns``` which was called by all
algorithms. It means that if one algorithm works well, others should also work
well.
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