[SPARK-14314][SPARK-14315][ML][SPARKR] Model persistence in SparkR (glm & kmeans)

SparkR ```glm``` and ```kmeans``` model persistence.

Unit tests.

Author: Yanbo Liang <ybliang8@gmail.com>
Author: Gayathri Murali <gayathri.m.softie@gmail.com>

Closes #12778 from yanboliang/spark-14311.
Closes #12680
Closes #12683

1 files changed, 41 insertions, 0 deletions

diff --git a/R/pkg/inst/tests/testthat/test_mllib.R b/R/pkg/inst/tests/testthat/test_mllib.R
index 954abb00d4..6a822be121 100644
--- a/R/pkg/inst/tests/testthat/test_mllib.R
+++ b/R/pkg/inst/tests/testthat/test_mllib.R
@@ -126,6 +126,33 @@ test_that("glm summary", {
   expect_true(abs(baseSummary$deviance - 12.19313) < 1e-4)
 })
 
+test_that("glm save/load", {
+  training <- suppressWarnings(createDataFrame(sqlContext, iris))
+  m <- glm(Sepal_Width ~ Sepal_Length + Species, data = training)
+  s <- summary(m)
+
+  modelPath <- tempfile(pattern = "glm", fileext = ".tmp")
+  ml.save(m, modelPath)
+  expect_error(ml.save(m, modelPath))
+  ml.save(m, modelPath, overwrite = TRUE)
+  m2 <- ml.load(modelPath)
+  s2 <- summary(m2)
+
+  expect_equal(s$coefficients, s2$coefficients)
+  expect_equal(rownames(s$coefficients), rownames(s2$coefficients))
+  expect_equal(s$dispersion, s2$dispersion)
+  expect_equal(s$null.deviance, s2$null.deviance)
+  expect_equal(s$deviance, s2$deviance)
+  expect_equal(s$df.null, s2$df.null)
+  expect_equal(s$df.residual, s2$df.residual)
+  expect_equal(s$aic, s2$aic)
+  expect_equal(s$iter, s2$iter)
+  expect_true(!s$is.loaded)
+  expect_true(s2$is.loaded)
+
+  unlink(modelPath)
+})
+
 test_that("kmeans", {
   newIris <- iris
   newIris$Species <- NULL
@@ -150,6 +177,20 @@ test_that("kmeans", {
   summary.model <- summary(model)
   cluster <- summary.model$cluster
   expect_equal(sort(collect(distinct(select(cluster, "prediction")))$prediction), c(0, 1))
+
+  # Test model save/load
+  modelPath <- tempfile(pattern = "kmeans", fileext = ".tmp")
+  ml.save(model, modelPath)
+  expect_error(ml.save(model, modelPath))
+  ml.save(model, modelPath, overwrite = TRUE)
+  model2 <- ml.load(modelPath)
+  summary2 <- summary(model2)
+  expect_equal(sort(unlist(summary.model$size)), sort(unlist(summary2$size)))
+  expect_equal(summary.model$coefficients, summary2$coefficients)
+  expect_true(!summary.model$is.loaded)
+  expect_true(summary2$is.loaded)
+
+  unlink(modelPath)
 })
 
 test_that("naiveBayes", {