Fix R style checks.

R/pkg/R/DataFrame.R

@@ -661,15 +661,15 @@ setMethod("collect",
               # listCols is a list of columns
               listCols <- callJStatic("org.apache.spark.sql.api.r.SQLUtils", "dfToCols", x@sdf)
               stopifnot(length(listCols) == ncol)
-              
+
               # An empty data.frame with 0 columns and number of rows as collected
               nrow <- length(listCols[[1]])
               if (nrow <= 0) {
                 df <- data.frame()
               } else {
-                df <- data.frame(row.names = 1 : nrow)                
+                df <- data.frame(row.names = 1 : nrow)
               }
-              
+
               # Append columns one by one
               for (colIndex in 1 : ncol) {
                 # Note: appending a column of list type into a data.frame so that
@@ -683,7 +683,7 @@ setMethod("collect",
                   # TODO: more robust check on column of primitive types
                   vec <- do.call(c, col)
                   if (class(vec) != "list") {
-                    df[[names[colIndex]]] <- vec                  
+                    df[[names[colIndex]]] <- vec
                   } else {
                     # For columns of complex type, be careful to access them.
                     # Get a column of complex type returns a list.

R/pkg/R/schema.R

@@ -155,7 +155,7 @@ structField.character <- function(x, type, nullable = TRUE) {
   }
 
   checkType(type)
-  
+
   sfObj <- callJStatic("org.apache.spark.sql.api.r.SQLUtils",
                        "createStructField",
                        x,

R/pkg/inst/tests/test_Serde.R

@@ -23,18 +23,18 @@ test_that("SerDe of primitive types", {
   x <- callJStatic("SparkRHandler", "echo", 1L)
   expect_equal(x, 1L)
   expect_equal(class(x), "integer")
-  
+
   x <- callJStatic("SparkRHandler", "echo", 1)
   expect_equal(x, 1)
   expect_equal(class(x), "numeric")
 
   x <- callJStatic("SparkRHandler", "echo", TRUE)
   expect_true(x)
   expect_equal(class(x), "logical")
-  
+
   x <- callJStatic("SparkRHandler", "echo", "abc")
   expect_equal(x, "abc")
-  expect_equal(class(x), "character")  
+  expect_equal(class(x), "character")
 })
 
 test_that("SerDe of list of primitive types", {
@@ -47,17 +47,17 @@ test_that("SerDe of list of primitive types", {
   y <- callJStatic("SparkRHandler", "echo", x)
   expect_equal(x, y)
   expect_equal(class(y[[1]]), "numeric")
-  
+
   x <- list(TRUE, FALSE)
   y <- callJStatic("SparkRHandler", "echo", x)
   expect_equal(x, y)
   expect_equal(class(y[[1]]), "logical")
-  
+
   x <- list("a", "b", "c")
   y <- callJStatic("SparkRHandler", "echo", x)
   expect_equal(x, y)
   expect_equal(class(y[[1]]), "character")
-  
+
   # Empty list
   x <- list()
   y <- callJStatic("SparkRHandler", "echo", x)

R/pkg/inst/tests/test_sparkSQL.R

@@ -50,7 +50,7 @@ jsonPathNa <- tempfile(pattern="sparkr-test", fileext=".tmp")
 writeLines(mockLinesNa, jsonPathNa)
 
 # For test complex types in DataFrame
-mockLinesComplexType <- 
+mockLinesComplexType <-
   c("{\"c1\":[1, 2, 3], \"c2\":[\"a\", \"b\", \"c\"], \"c3\":[1.0, 2.0, 3.0]}",
     "{\"c1\":[4, 5, 6], \"c2\":[\"d\", \"e\", \"f\"], \"c3\":[4.0, 5.0, 6.0]}",
     "{\"c1\":[7, 8, 9], \"c2\":[\"g\", \"h\", \"i\"], \"c3\":[7.0, 8.0, 9.0]}")
@@ -253,7 +253,7 @@ test_that("create DataFrame with nested array and struct", {
 #  ldf <- collect(df)
 #  expect_equal(ldf[1,], l[[1]])
 
-  
+
   #  ArrayType only for now
   l <- list(as.list(1:10), list("a", "b"))
   df <- createDataFrame(sqlContext, list(l), c("a", "b"))
@@ -269,7 +269,7 @@ test_that("Collect DataFrame with complex types", {
   # only ArrayType now
   # TODO: tests for StructType and MapType after they are supported
   df <- jsonFile(sqlContext, complexTypeJsonPath)
-  
+
   ldf <- collect(df)
   expect_equal(nrow(ldf), 3)
   expect_equal(ncol(ldf), 3)
@@ -638,7 +638,7 @@ test_that("subsetting", {
   df4 <- df[df$age %in% c(19, 30), 1:2]
   expect_equal(count(df4), 2)
   expect_equal(columns(df4), c("name", "age"))
-  
+
   df5 <- df[df$age %in% c(19), c(1,2)]
   expect_equal(count(df5), 1)
   expect_equal(columns(df5), c("name", "age"))