Merge remote-tracking branch 'apache/master' into UDAF

Author: marmbrus

.rat-excludes

@@ -91,3 +91,5 @@ help/*
 html/*
 INDEX
 .lintr
+gen-java.*
+.*avpr

R/README.md

@@ -6,7 +6,7 @@ SparkR is an R package that provides a light-weight frontend to use Spark from R
 
 #### Build Spark
 
-Build Spark with [Maven](http://spark.apache.org/docs/latest/building-spark.html#building-with-buildmvn) and include the `-PsparkR` profile to build the R package. For example to use the default Hadoop versions you can run
+Build Spark with [Maven](http://spark.apache.org/docs/latest/building-spark.html#building-with-buildmvn) and include the `-Psparkr` profile to build the R package. For example to use the default Hadoop versions you can run
 ```
   build/mvn -DskipTests -Psparkr package
 ```

R/install-dev.bat

@@ -25,3 +25,8 @@ set SPARK_HOME=%~dp0..
 MKDIR %SPARK_HOME%\R\lib
 
 R.exe CMD INSTALL --library="%SPARK_HOME%\R\lib"  %SPARK_HOME%\R\pkg\
+
+rem Zip the SparkR package so that it can be distributed to worker nodes on YARN
+pushd %SPARK_HOME%\R\lib
+%JAVA_HOME%\bin\jar.exe cfM "%SPARK_HOME%\R\lib\sparkr.zip" SparkR
+popd

R/install-dev.sh

@@ -34,12 +34,16 @@ LIB_DIR="$FWDIR/lib"
 
 mkdir -p $LIB_DIR
 
-pushd $FWDIR
+pushd $FWDIR > /dev/null
 
 # Generate Rd files if devtools is installed
 Rscript -e ' if("devtools" %in% rownames(installed.packages())) { library(devtools); devtools::document(pkg="./pkg", roclets=c("rd")) }'
 
 # Install SparkR to $LIB_DIR
 R CMD INSTALL --library=$LIB_DIR $FWDIR/pkg/
 
-popd
+# Zip the SparkR package so that it can be distributed to worker nodes on YARN
+cd $LIB_DIR
+jar cfM "$LIB_DIR/sparkr.zip" SparkR
+
+popd > /dev/null

R/pkg/DESCRIPTION

@@ -32,4 +32,3 @@ Collate:
     'serialize.R'
     'sparkR.R'
     'utils.R'
-    'zzz.R'

R/pkg/R/RDD.R

@@ -165,7 +165,6 @@ setMethod("getJRDD", signature(rdd = "PipelinedRDD"),
                                    serializedFuncArr,
                                    rdd@env$prev_serializedMode,
                                    packageNamesArr,
-                                   as.character(.sparkREnv[["libname"]]),
                                    broadcastArr,
                                    callJMethod(prev_jrdd, "classTag"))
             } else {
@@ -175,7 +174,6 @@ setMethod("getJRDD", signature(rdd = "PipelinedRDD"),
                                    rdd@env$prev_serializedMode,
                                    serializedMode,
                                    packageNamesArr,
-                                   as.character(.sparkREnv[["libname"]]),
                                    broadcastArr,
                                    callJMethod(prev_jrdd, "classTag"))
             }

R/pkg/R/SQLContext.R

@@ -86,7 +86,9 @@ infer_type <- function(x) {
 createDataFrame <- function(sqlContext, data, schema = NULL, samplingRatio = 1.0) {
   if (is.data.frame(data)) {
       # get the names of columns, they will be put into RDD
-      schema <- names(data)
+      if (is.null(schema)) {
+        schema <- names(data)
+      }
       n <- nrow(data)
       m <- ncol(data)
       # get rid of factor type

R/pkg/R/pairRDD.R

@@ -215,7 +215,6 @@ setMethod("partitionBy",
                                        serializedHashFuncBytes,
                                        getSerializedMode(x),
                                        packageNamesArr,
-                                       as.character(.sparkREnv$libname),
                                        broadcastArr,
                                        callJMethod(jrdd, "classTag"))
 

R/pkg/R/sparkR.R

@@ -17,10 +17,6 @@
 
 .sparkREnv <- new.env()
 
-sparkR.onLoad <- function(libname, pkgname) {
-  .sparkREnv$libname <- libname
-}
-
 # Utility function that returns TRUE if we have an active connection to the
 # backend and FALSE otherwise
 connExists <- function(env) {
@@ -80,7 +76,6 @@ sparkR.stop <- function() {
 #' @param sparkEnvir Named list of environment variables to set on worker nodes.
 #' @param sparkExecutorEnv Named list of environment variables to be used when launching executors.
 #' @param sparkJars Character string vector of jar files to pass to the worker nodes.
-#' @param sparkRLibDir The path where R is installed on the worker nodes.
 #' @param sparkPackages Character string vector of packages from spark-packages.org
 #' @export
 #' @examples
@@ -101,7 +96,6 @@ sparkR.init <- function(
   sparkEnvir = list(),
   sparkExecutorEnv = list(),
   sparkJars = "",
-  sparkRLibDir = "",
   sparkPackages = "") {
 
   if (exists(".sparkRjsc", envir = .sparkREnv)) {
@@ -170,10 +164,6 @@ sparkR.init <- function(
     sparkHome <- normalizePath(sparkHome)
   }
 
-  if (nchar(sparkRLibDir) != 0) {
-    .sparkREnv$libname <- sparkRLibDir
-  }
-
   sparkEnvirMap <- new.env()
   for (varname in names(sparkEnvir)) {
     sparkEnvirMap[[varname]] <- sparkEnvir[[varname]]

R/pkg/inst/profile/general.R

@@ -16,7 +16,7 @@
 #
 
 .First <- function() {
-  home <- Sys.getenv("SPARK_HOME")
-  .libPaths(c(file.path(home, "R", "lib"), .libPaths()))
+  packageDir <- Sys.getenv("SPARKR_PACKAGE_DIR")
+  .libPaths(c(packageDir, .libPaths()))
   Sys.setenv(NOAWT=1)
 }