[SPARK-13925][ML][SPARKR] Expose R-like summary statistics in SparkR::glm for more family and link functions

## What changes were proposed in this pull request?
Expose R-like summary statistics in SparkR::glm for more family and link functions.
Note: Not all values in R [summary.glm](http://stat.ethz.ch/R-manual/R-patched/library/stats/html/summary.glm.html) are exposed, we only provide the most commonly used statistics in this PR. More statistics can be added in the followup work.

## How was this patch tested?
Unit tests.

SparkR Output:
```
Deviance Residuals:
(Note: These are approximate quantiles with relative error <= 0.01)
     Min        1Q    Median        3Q       Max
-0.95096  -0.16585  -0.00232   0.17410   0.72918

Coefficients:
                    Estimate  Std. Error  t value  Pr(>|t|)
(Intercept)         1.6765    0.23536     7.1231   4.4561e-11
Sepal_Length        0.34988   0.046301    7.5566   4.1873e-12
Species_versicolor  -0.98339  0.072075    -13.644  0
Species_virginica   -1.0075   0.093306    -10.798  0

(Dispersion parameter for gaussian family taken to be 0.08351462)

    Null deviance: 28.307  on 149  degrees of freedom
Residual deviance: 12.193  on 146  degrees of freedom
AIC: 59.22

Number of Fisher Scoring iterations: 1
```
R output:
```
Deviance Residuals:
     Min        1Q    Median        3Q       Max
-0.95096  -0.16522   0.00171   0.18416   0.72918

Coefficients:
                  Estimate Std. Error t value Pr(>|t|)
(Intercept)        1.67650    0.23536   7.123 4.46e-11 ***
Sepal.Length       0.34988    0.04630   7.557 4.19e-12 ***
Speciesversicolor -0.98339    0.07207 -13.644  < 2e-16 ***
Speciesvirginica  -1.00751    0.09331 -10.798  < 2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for gaussian family taken to be 0.08351462)

    Null deviance: 28.307  on 149  degrees of freedom
Residual deviance: 12.193  on 146  degrees of freedom
AIC: 59.217

Number of Fisher Scoring iterations: 2
```

cc mengxr

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #12393 from yanboliang/spark-13925.

1 files changed, 49 insertions, 0 deletions

diff --git a/R/pkg/inst/tests/testthat/test_mllib.R b/R/pkg/inst/tests/testthat/test_mllib.R
index a9dbd2bdc4..47bbf7e5bd 100644
--- a/R/pkg/inst/tests/testthat/test_mllib.R
+++ b/R/pkg/inst/tests/testthat/test_mllib.R
@@ -77,6 +77,55 @@ test_that("glm and predict", {
   expect_equal(length(predict(lm(y ~ x))), 15)
 })
 
+test_that("glm summary", {
+  # gaussian family
+  training <- suppressWarnings(createDataFrame(sqlContext, iris))
+  stats <- summary(glm(Sepal_Width ~ Sepal_Length + Species, data = training))
+
+  rStats <- summary(glm(Sepal.Width ~ Sepal.Length + Species, data = iris))
+
+  coefs <- unlist(stats$coefficients)
+  rCoefs <- unlist(rStats$coefficients)
+  expect_true(all(abs(rCoefs - coefs) < 1e-4))
+  expect_true(all(
+    rownames(stats$coefficients) ==
+    c("(Intercept)", "Sepal_Length", "Species_versicolor", "Species_virginica")))
+  expect_equal(stats$dispersion, rStats$dispersion)
+  expect_equal(stats$null.deviance, rStats$null.deviance)
+  expect_equal(stats$deviance, rStats$deviance)
+  expect_equal(stats$df.null, rStats$df.null)
+  expect_equal(stats$df.residual, rStats$df.residual)
+  expect_equal(stats$aic, rStats$aic)
+
+  # binomial family
+  df <- suppressWarnings(createDataFrame(sqlContext, iris))
+  training <- df[df$Species %in% c("versicolor", "virginica"), ]
+  stats <- summary(glm(Species ~ Sepal_Length + Sepal_Width, data = training,
+    family = binomial(link = "logit")))
+
+  rTraining <- iris[iris$Species %in% c("versicolor", "virginica"), ]
+  rStats <- summary(glm(Species ~ Sepal.Length + Sepal.Width, data = rTraining,
+    family = binomial(link = "logit")))
+
+  coefs <- unlist(stats$coefficients)
+  rCoefs <- unlist(rStats$coefficients)
+  expect_true(all(abs(rCoefs - coefs) < 1e-4))
+  expect_true(all(
+    rownames(stats$coefficients) ==
+    c("(Intercept)", "Sepal_Length", "Sepal_Width")))
+  expect_equal(stats$dispersion, rStats$dispersion)
+  expect_equal(stats$null.deviance, rStats$null.deviance)
+  expect_equal(stats$deviance, rStats$deviance)
+  expect_equal(stats$df.null, rStats$df.null)
+  expect_equal(stats$df.residual, rStats$df.residual)
+  expect_equal(stats$aic, rStats$aic)
+
+  # Test summary works on base GLM models
+  baseModel <- stats::glm(Sepal.Width ~ Sepal.Length + Species, data = iris)
+  baseSummary <- summary(baseModel)
+  expect_true(abs(baseSummary$deviance - 12.19313) < 1e-4)
+})
+
 test_that("kmeans", {
   newIris <- iris
   newIris$Species <- NULL