[SPARK-19395][SPARKR] Convert coefficients in summary to matrix

## What changes were proposed in this pull request?
The `coefficients` component in model summary should be 'matrix' but the underlying structure is indeed list. This affects several models except for 'AFTSurvivalRegressionModel' which has the correct implementation. The fix is to first `unlist` the coefficients returned from the `callJMethod` before converting to matrix. An example illustrates the issues:

```
data(iris)
df <- createDataFrame(iris)
model <- spark.glm(df, Sepal_Length ~ Sepal_Width, family = "gaussian")
s <- summary(model)

> str(s$coefficients)
List of 8
 $ : num 6.53
 $ : num -0.223
 $ : num 0.479
 $ : num 0.155
 $ : num 13.6
 $ : num -1.44
 $ : num 0
 $ : num 0.152
 - attr(*, "dim")= int [1:2] 2 4
 - attr(*, "dimnames")=List of 2
  ..$ : chr [1:2] "(Intercept)" "Sepal_Width"
  ..$ : chr [1:4] "Estimate" "Std. Error" "t value" "Pr(>|t|)"
> s$coefficients[, 2]
$`(Intercept)`
[1] 0.4788963

$Sepal_Width
[1] 0.1550809
```

This  shows that the underlying structure of coefficients is still `list`.

felixcheung wangmiao1981

Author: actuaryzhang <actuaryzhang10@gmail.com>

Closes #16730 from actuaryzhang/sparkRCoef.

3 files changed, 30 insertions, 18 deletions

diff --git a/R/pkg/inst/tests/testthat/test_mllib_classification.R b/R/pkg/inst/tests/testthat/test_mllib_classification.R
index 2e0dea321e..5f84a620c1 100644
--- a/R/pkg/inst/tests/testthat/test_mllib_classification.R
+++ b/R/pkg/inst/tests/testthat/test_mllib_classification.R
@@ -68,12 +68,17 @@ test_that("spark.logit", {
   df <- suppressWarnings(createDataFrame(iris))
   model <- spark.logit(df, Species ~ ., regParam = 0.5)
   summary <- summary(model)
+
+  # test summary coefficients return matrix type
+  expect_true(class(summary$coefficients) == "matrix")
+  expect_true(class(summary$coefficients[, 1]) == "numeric")
+
   versicolorCoefsR <- c(1.52, 0.03, -0.53, 0.04, 0.00)
   virginicaCoefsR <- c(-2.62, 0.27, -0.02, 0.16, 0.42)
   setosaCoefsR <- c(1.10, -0.29, 0.55, -0.19, -0.42)
-  versicolorCoefs <- unlist(summary$coefficients[, "versicolor"])
-  virginicaCoefs <- unlist(summary$coefficients[, "virginica"])
-  setosaCoefs <- unlist(summary$coefficients[, "setosa"])
+  versicolorCoefs <- summary$coefficients[, "versicolor"]
+  virginicaCoefs <- summary$coefficients[, "virginica"]
+  setosaCoefs <- summary$coefficients[, "setosa"]
   expect_true(all(abs(versicolorCoefsR - versicolorCoefs) < 0.1))
   expect_true(all(abs(virginicaCoefsR - virginicaCoefs) < 0.1))
   expect_true(all(abs(setosaCoefs - setosaCoefs) < 0.1))
@@ -136,8 +141,8 @@ test_that("spark.logit", {
   summary <- summary(model)
   versicolorCoefsR <- c(3.94, -0.16, -0.02, -0.35, -0.78)
   virginicaCoefsR <- c(-3.94, 0.16, -0.02, 0.35, 0.78)
-  versicolorCoefs <- unlist(summary$coefficients[, "versicolor"])
-  virginicaCoefs <- unlist(summary$coefficients[, "virginica"])
+  versicolorCoefs <- summary$coefficients[, "versicolor"]
+  virginicaCoefs <- summary$coefficients[, "virginica"]
   expect_true(all(abs(versicolorCoefsR - versicolorCoefs) < 0.1))
   expect_true(all(abs(virginicaCoefsR - virginicaCoefs) < 0.1))
 
@@ -145,7 +150,7 @@ test_that("spark.logit", {
   model <- spark.logit(training, Species ~ ., regParam = 0.5)
   summary <- summary(model)
   coefsR <- c(-6.08, 0.25, 0.16, 0.48, 1.04)
-  coefs <- unlist(summary$coefficients[, "Estimate"])
+  coefs <- summary$coefficients[, "Estimate"]
   expect_true(all(abs(coefsR - coefs) < 0.1))
 
   # Test prediction with string label
diff --git a/R/pkg/inst/tests/testthat/test_mllib_clustering.R b/R/pkg/inst/tests/testthat/test_mllib_clustering.R
index aad834bb64..28a6eeba2c 100644
--- a/R/pkg/inst/tests/testthat/test_mllib_clustering.R
+++ b/R/pkg/inst/tests/testthat/test_mllib_clustering.R
@@ -166,6 +166,10 @@ test_that("spark.kmeans", {
   expect_equal(k, 2)
   expect_equal(sort(collect(distinct(select(cluster, "prediction")))$prediction), c(0, 1))
 
+  # test summary coefficients return matrix type
+  expect_true(class(summary.model$coefficients) == "matrix")
+  expect_true(class(summary.model$coefficients[1, ]) == "numeric")
+
   # Test model save/load
   modelPath <- tempfile(pattern = "spark-kmeans", fileext = ".tmp")
   write.ml(model, modelPath)
diff --git a/R/pkg/inst/tests/testthat/test_mllib_regression.R b/R/pkg/inst/tests/testthat/test_mllib_regression.R
index c450a15171..81a5bdc414 100644
--- a/R/pkg/inst/tests/testthat/test_mllib_regression.R
+++ b/R/pkg/inst/tests/testthat/test_mllib_regression.R
@@ -87,11 +87,14 @@ test_that("spark.glm summary", {
   # gaussian family
   training <- suppressWarnings(createDataFrame(iris))
   stats <- summary(spark.glm(training, Sepal_Width ~ Sepal_Length + Species))
-
   rStats <- summary(glm(Sepal.Width ~ Sepal.Length + Species, data = iris))
 
-  coefs <- unlist(stats$coefficients)
-  rCoefs <- unlist(rStats$coefficients)
+  # test summary coefficients return matrix type
+  expect_true(class(stats$coefficients) == "matrix")
+  expect_true(class(stats$coefficients[, 1]) == "numeric")
+
+  coefs <- stats$coefficients
+  rCoefs <- rStats$coefficients
   expect_true(all(abs(rCoefs - coefs) < 1e-4))
   expect_true(all(
     rownames(stats$coefficients) ==
@@ -117,8 +120,8 @@ test_that("spark.glm summary", {
   rStats <- summary(glm(Species ~ Sepal.Length + Sepal.Width, data = rTraining,
                         family = binomial(link = "logit")))
 
-  coefs <- unlist(stats$coefficients)
-  rCoefs <- unlist(rStats$coefficients)
+  coefs <- stats$coefficients
+  rCoefs <- rStats$coefficients
   expect_true(all(abs(rCoefs - coefs) < 1e-4))
   expect_true(all(
     rownames(stats$coefficients) ==
@@ -141,8 +144,8 @@ test_that("spark.glm summary", {
   stats <- summary(spark.glm(df, b ~ a1 + a2, family = "binomial", weightCol = "w"))
   rStats <- summary(glm(b ~ a1 + a2, family = "binomial", data = data, weights = w))
 
-  coefs <- unlist(stats$coefficients)
-  rCoefs <- unlist(rStats$coefficients)
+  coefs <- stats$coefficients
+  rCoefs <- rStats$coefficients
   expect_true(all(abs(rCoefs - coefs) < 1e-3))
   expect_true(all(rownames(stats$coefficients) == c("(Intercept)", "a1", "a2")))
   expect_equal(stats$dispersion, rStats$dispersion)
@@ -169,7 +172,7 @@ test_that("spark.glm summary", {
   data <- as.data.frame(cbind(A, b))
   df <- createDataFrame(data)
   stats <- summary(spark.glm(df, b ~ . - 1))
-  coefs <- unlist(stats$coefficients)
+  coefs <- stats$coefficients
   expect_true(all(abs(c(0.5, 0.25) - coefs) < 1e-4))
 })
 
@@ -259,8 +262,8 @@ test_that("glm summary", {
 
   rStats <- summary(glm(Sepal.Width ~ Sepal.Length + Species, data = iris))
 
-  coefs <- unlist(stats$coefficients)
-  rCoefs <- unlist(rStats$coefficients)
+  coefs <- stats$coefficients
+  rCoefs <- rStats$coefficients
   expect_true(all(abs(rCoefs - coefs) < 1e-4))
   expect_true(all(
     rownames(stats$coefficients) ==
@@ -282,8 +285,8 @@ test_that("glm summary", {
   rStats <- summary(glm(Species ~ Sepal.Length + Sepal.Width, data = rTraining,
                         family = binomial(link = "logit")))
 
-  coefs <- unlist(stats$coefficients)
-  rCoefs <- unlist(rStats$coefficients)
+  coefs <- stats$coefficients
+  rCoefs <- rStats$coefficients
   expect_true(all(abs(rCoefs - coefs) < 1e-4))
   expect_true(all(
     rownames(stats$coefficients) ==