diff --git a/R/pkg/DESCRIPTION b/R/pkg/DESCRIPTION
index b739d423a36cc..d1c846c048274 100644
--- a/R/pkg/DESCRIPTION
+++ b/R/pkg/DESCRIPTION
@@ -2,7 +2,7 @@ Package: SparkR
 Type: Package
 Version: 2.3.0
 Title: R Frontend for Apache Spark
-Description: The SparkR package provides an R Frontend for Apache Spark.
+Description: Provides an R Frontend for Apache Spark.
 Authors@R: c(person("Shivaram", "Venkataraman", role = c("aut", "cre"),
                     email = "shivaram@cs.berkeley.edu"),
              person("Xiangrui", "Meng", role = "aut",
diff --git a/R/pkg/R/install.R b/R/pkg/R/install.R
index ec931befa2854..492dee68e164d 100644
--- a/R/pkg/R/install.R
+++ b/R/pkg/R/install.R
@@ -270,7 +270,11 @@ sparkCachePath <- function() {
   if (is_windows()) {
     winAppPath <- Sys.getenv("LOCALAPPDATA", unset = NA)
     if (is.na(winAppPath)) {
-      stop(paste("%LOCALAPPDATA% not found.",
+      message("%LOCALAPPDATA% not found. Falling back to %USERPROFILE%.")
+      winAppPath <- Sys.getenv("USERPROFILE", unset = NA)
+    }
+    if (is.na(winAppPath)) {
+      stop(paste("%LOCALAPPDATA% and %USERPROFILE% not found.",
                    "Please define the environment variable",
                    "or restart and enter an installation path in localDir."))
     } else {
diff --git a/R/pkg/vignettes/sparkr-vignettes.Rmd b/R/pkg/vignettes/sparkr-vignettes.Rmd
index 2301a64576d0e..caeae72e37bbf 100644
--- a/R/pkg/vignettes/sparkr-vignettes.Rmd
+++ b/R/pkg/vignettes/sparkr-vignettes.Rmd
@@ -27,6 +27,17 @@ vignette: >
  limitations under the License.
 -->
 
+```{r setup, include=FALSE}
+library(knitr)
+opts_hooks$set(eval = function(options) {
+  # override eval to FALSE only on windows
+  if (.Platform$OS.type == "windows") {
+    options$eval = FALSE
+  }
+  options
+})
+```
+
 ## Overview
 
 SparkR is an R package that provides a light-weight frontend to use Apache Spark from R. With Spark `r packageVersion("SparkR")`, SparkR provides a distributed data frame implementation that supports data processing operations like selection, filtering, aggregation etc. and distributed machine learning using [MLlib](http://spark.apache.org/mllib/).