Merge branch 'master' into kafka-rdd-count

Author: koeninger

.rat-excludes

@@ -28,6 +28,7 @@ spark-env.sh
 spark-env.cmd
 spark-env.sh.template
 log4j-defaults.properties
+log4j-defaults-repl.properties
 bootstrap-tooltip.js
 jquery-1.11.1.min.js
 d3.min.js

LICENSE

@@ -950,3 +950,4 @@ The following components are provided under the MIT License. See project link fo
      (MIT License) scopt (com.github.scopt:scopt_2.10:3.2.0 - https://github.com/scopt/scopt)
      (The MIT License) Mockito (org.mockito:mockito-all:1.8.5 - http://www.mockito.org)
      (MIT License) jquery (https://jquery.org/license/)
+     (MIT License) AnchorJS (https://github.com/bryanbraun/anchorjs)

R/create-docs.sh

@@ -23,14 +23,14 @@
 # After running this script the html docs can be found in 
 # $SPARK_HOME/R/pkg/html
 
+set -o pipefail
+set -e
+
 # Figure out where the script is
 export FWDIR="$(cd "`dirname "$0"`"; pwd)"
 pushd $FWDIR
 
-# Generate Rd file
-Rscript -e 'library(devtools); devtools::document(pkg="./pkg", roclets=c("rd"))'
-
-# Install the package
+# Install the package (this will also generate the Rd files)
 ./install-dev.sh
 
 # Now create HTML files

R/install-dev.sh

@@ -26,11 +26,20 @@
 # NOTE(shivaram): Right now we use $SPARK_HOME/R/lib to be the installation directory
 # to load the SparkR package on the worker nodes.
 
+set -o pipefail
+set -e
 
 FWDIR="$(cd `dirname $0`; pwd)"
 LIB_DIR="$FWDIR/lib"
 
 mkdir -p $LIB_DIR
 
-# Install R
+pushd $FWDIR
+
+# 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

R/log4j.properties

@@ -19,7 +19,7 @@
 log4j.rootCategory=INFO, file
 log4j.appender.file=org.apache.log4j.FileAppender
 log4j.appender.file.append=true
-log4j.appender.file.file=R-unit-tests.log
+log4j.appender.file.file=R/target/unit-tests.log
 log4j.appender.file.layout=org.apache.log4j.PatternLayout
 log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
 

R/pkg/R/SQLContext.R

@@ -452,7 +452,7 @@ dropTempTable <- function(sqlContext, tableName) {
 #' df <- read.df(sqlContext, "path/to/file.json", source = "json")
 #' }
 
-read.df <- function(sqlContext, path = NULL, source = NULL, ...) {
+read.df <- function(sqlContext, path = NULL, source = NULL, schema = NULL, ...) {
   options <- varargsToEnv(...)
   if (!is.null(path)) {
     options[['path']] <- path
@@ -462,15 +462,21 @@ read.df <- function(sqlContext, path = NULL, source = NULL, ...) {
     source <- callJMethod(sqlContext, "getConf", "spark.sql.sources.default",
                           "org.apache.spark.sql.parquet")
   }
-  sdf <- callJMethod(sqlContext, "load", source, options)
+  if (!is.null(schema)) {
+    stopifnot(class(schema) == "structType")
+    sdf <- callJStatic("org.apache.spark.sql.api.r.SQLUtils", "loadDF", sqlContext, source,
+                       schema$jobj, options)
+  } else {
+    sdf <- callJStatic("org.apache.spark.sql.api.r.SQLUtils", "loadDF", sqlContext, source, options)
+  }
   dataFrame(sdf)
 }
 
 #' @aliases loadDF
 #' @export
 
-loadDF <- function(sqlContext, path = NULL, source = NULL, ...) {
-  read.df(sqlContext, path, source, ...)
+loadDF <- function(sqlContext, path = NULL, source = NULL, schema = NULL, ...) {
+  read.df(sqlContext, path, source, schema, ...)
 }
 
 #' Create an external table

R/pkg/R/serialize.R

@@ -37,6 +37,14 @@ writeObject <- function(con, object, writeType = TRUE) {
   # passing in vectors as arrays and instead require arrays to be passed
   # as lists.
   type <- class(object)[[1]]  # class of POSIXlt is c("POSIXlt", "POSIXt")
+  # Checking types is needed here, since ‘is.na’ only handles atomic vectors,
+  # lists and pairlists
+  if (type %in% c("integer", "character", "logical", "double", "numeric")) {
+    if (is.na(object)) {
+      object <- NULL
+      type <- "NULL"
+    }
+  }
   if (writeType) {
     writeType(con, type)
   }

R/pkg/inst/tests/test_sparkSQL.R

@@ -101,6 +101,43 @@ test_that("create DataFrame from RDD", {
   expect_equal(dtypes(df), list(c("a", "int"), c("b", "string")))
 })
 
+test_that("convert NAs to null type in DataFrames", {
+  rdd <- parallelize(sc, list(list(1L, 2L), list(NA, 4L)))
+  df <- createDataFrame(sqlContext, rdd, list("a", "b"))
+  expect_true(is.na(collect(df)[2, "a"]))
+  expect_equal(collect(df)[2, "b"], 4L)
+
+  l <- data.frame(x = 1L, y = c(1L, NA_integer_, 3L))
+  df <- createDataFrame(sqlContext, l)
+  expect_equal(collect(df)[2, "x"], 1L)
+  expect_true(is.na(collect(df)[2, "y"]))
+
+  rdd <- parallelize(sc, list(list(1, 2), list(NA, 4)))
+  df <- createDataFrame(sqlContext, rdd, list("a", "b"))
+  expect_true(is.na(collect(df)[2, "a"]))
+  expect_equal(collect(df)[2, "b"], 4)
+
+  l <- data.frame(x = 1, y = c(1, NA_real_, 3))
+  df <- createDataFrame(sqlContext, l)
+  expect_equal(collect(df)[2, "x"], 1)
+  expect_true(is.na(collect(df)[2, "y"]))
+
+  l <- list("a", "b", NA, "d")
+  df <- createDataFrame(sqlContext, l)
+  expect_true(is.na(collect(df)[3, "_1"]))
+  expect_equal(collect(df)[4, "_1"], "d")
+
+  l <- list("a", "b", NA_character_, "d")
+  df <- createDataFrame(sqlContext, l)
+  expect_true(is.na(collect(df)[3, "_1"]))
+  expect_equal(collect(df)[4, "_1"], "d")
+
+  l <- list(TRUE, FALSE, NA, TRUE)
+  df <- createDataFrame(sqlContext, l)
+  expect_true(is.na(collect(df)[3, "_1"]))
+  expect_equal(collect(df)[4, "_1"], TRUE)
+})
+
 test_that("toDF", {
   rdd <- lapply(parallelize(sc, 1:10), function(x) { list(x, as.character(x)) })
   df <- toDF(rdd, list("a", "b"))
@@ -504,6 +541,19 @@ test_that("read.df() from json file", {
   df <- read.df(sqlContext, jsonPath, "json")
   expect_true(inherits(df, "DataFrame"))
   expect_true(count(df) == 3)
+
+  # Check if we can apply a user defined schema
+  schema <- structType(structField("name", type = "string"),
+                       structField("age", type = "double"))
+
+  df1 <- read.df(sqlContext, jsonPath, "json", schema)
+  expect_true(inherits(df1, "DataFrame"))
+  expect_equal(dtypes(df1), list(c("name", "string"), c("age", "double")))
+
+  # Run the same with loadDF
+  df2 <- loadDF(sqlContext, jsonPath, "json", schema)
+  expect_true(inherits(df2, "DataFrame"))
+  expect_equal(dtypes(df2), list(c("name", "string"), c("age", "double")))
 })
 
 test_that("write.df() as parquet file", {

bin/pyspark

@@ -17,24 +17,10 @@
 # limitations under the License.
 #
 
-# Figure out where Spark is installed
 export SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
 
 source "$SPARK_HOME"/bin/load-spark-env.sh
-
-function usage() {
-  if [ -n "$1" ]; then
-    echo $1
-  fi
-  echo "Usage: ./bin/pyspark [options]" 1>&2
-  "$SPARK_HOME"/bin/spark-submit --help 2>&1 | grep -v Usage 1>&2
-  exit $2
-}
-export -f usage
-
-if [[ "$@" = *--help ]] || [[ "$@" = *-h ]]; then
-  usage
-fi
+export _SPARK_CMD_USAGE="Usage: ./bin/pyspark [options]"
 
 # In Spark <= 1.1, setting IPYTHON=1 would cause the driver to be launched using the `ipython`
 # executable, while the worker would still be launched using PYSPARK_PYTHON.

bin/pyspark2.cmd

@@ -21,6 +21,7 @@ rem Figure out where the Spark framework is installed
 set SPARK_HOME=%~dp0..
 
 call %SPARK_HOME%\bin\load-spark-env.cmd
+set _SPARK_CMD_USAGE=Usage: bin\pyspark.cmd [options]
 
 rem Figure out which Python to use.
 if "x%PYSPARK_DRIVER_PYTHON%"=="x" (

bin/spark-class

@@ -16,18 +16,12 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 #
-set -e
 
 # Figure out where Spark is installed
 export SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
 
 . "$SPARK_HOME"/bin/load-spark-env.sh
 
-if [ -z "$1" ]; then
-  echo "Usage: spark-class <class> [<args>]" 1>&2
-  exit 1
-fi
-
 # Find the java binary
 if [ -n "${JAVA_HOME}" ]; then
   RUNNER="${JAVA_HOME}/bin/java"
@@ -64,24 +58,6 @@ fi
 
 SPARK_ASSEMBLY_JAR="${ASSEMBLY_DIR}/${ASSEMBLY_JARS}"
 
-# Verify that versions of java used to build the jars and run Spark are compatible
-if [ -n "$JAVA_HOME" ]; then
-  JAR_CMD="$JAVA_HOME/bin/jar"
-else
-  JAR_CMD="jar"
-fi
-
-if [ $(command -v "$JAR_CMD") ] ; then
-  jar_error_check=$("$JAR_CMD" -tf "$SPARK_ASSEMBLY_JAR" nonexistent/class/path 2>&1)
-  if [[ "$jar_error_check" =~ "invalid CEN header" ]]; then
-    echo "Loading Spark jar with '$JAR_CMD' failed. " 1>&2
-    echo "This is likely because Spark was compiled with Java 7 and run " 1>&2
-    echo "with Java 6. (see SPARK-1703). Please use Java 7 to run Spark " 1>&2
-    echo "or build Spark with Java 6." 1>&2
-    exit 1
-  fi
-fi
-
 LAUNCH_CLASSPATH="$SPARK_ASSEMBLY_JAR"
 
 # Add the launcher build dir to the classpath if requested.
@@ -98,9 +74,4 @@ CMD=()
 while IFS= read -d '' -r ARG; do
   CMD+=("$ARG")
 done < <("$RUNNER" -cp "$LAUNCH_CLASSPATH" org.apache.spark.launcher.Main "$@")
-
-if [ "${CMD[0]}" = "usage" ]; then
-  "${CMD[@]}"
-else
-  exec "${CMD[@]}"
-fi
+exec "${CMD[@]}"

bin/spark-shell

@@ -29,20 +29,7 @@ esac
 set -o posix
 
 export FWDIR="$(cd "`dirname "$0"`"/..; pwd)"
-
-usage() {
-  if [ -n "$1" ]; then
-    echo "$1"
-  fi
-  echo "Usage: ./bin/spark-shell [options]"
-  "$FWDIR"/bin/spark-submit --help 2>&1 | grep -v Usage 1>&2
-  exit "$2"
-}
-export -f usage
-
-if [[ "$@" = *--help ]] || [[ "$@" = *-h ]]; then
-  usage "" 0
-fi
+export _SPARK_CMD_USAGE="Usage: ./bin/spark-shell [options]"
 
 # SPARK-4161: scala does not assume use of the java classpath,
 # so we need to add the "-Dscala.usejavacp=true" flag manually. We

bin/spark-shell2.cmd

@@ -18,12 +18,7 @@ rem limitations under the License.
 rem
 
 set SPARK_HOME=%~dp0..
-
-echo "%*" | findstr " \<--help\> \<-h\>" >nul
-if %ERRORLEVEL% equ 0 (
-  call :usage
-  exit /b 0
-)
+set _SPARK_CMD_USAGE=Usage: .\bin\spark-shell.cmd [options]
 
 rem SPARK-4161: scala does not assume use of the java classpath,
 rem so we need to add the "-Dscala.usejavacp=true" flag manually. We
@@ -37,16 +32,4 @@ if "x%SPARK_SUBMIT_OPTS%"=="x" (
 set SPARK_SUBMIT_OPTS="%SPARK_SUBMIT_OPTS% -Dscala.usejavacp=true"
 
 :run_shell
-call %SPARK_HOME%\bin\spark-submit2.cmd --class org.apache.spark.repl.Main %*
-set SPARK_ERROR_LEVEL=%ERRORLEVEL%
-if not "x%SPARK_LAUNCHER_USAGE_ERROR%"=="x" (
-  call :usage
-  exit /b 1
-)
-exit /b %SPARK_ERROR_LEVEL%
-
-:usage
-echo %SPARK_LAUNCHER_USAGE_ERROR%
-echo "Usage: .\bin\spark-shell.cmd [options]" >&2
-call %SPARK_HOME%\bin\spark-submit2.cmd --help 2>&1 | findstr /V "Usage" 1>&2
-goto :eof
+%SPARK_HOME%\bin\spark-submit2.cmd --class org.apache.spark.repl.Main %*

bin/spark-sql

@@ -17,41 +17,6 @@
 # limitations under the License.
 #
 
-#
-# Shell script for starting the Spark SQL CLI
-
-# Enter posix mode for bash
-set -o posix
-
-# NOTE: This exact class name is matched downstream by SparkSubmit.
-# Any changes need to be reflected there.
-export CLASS="org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver"
-
-# Figure out where Spark is installed
 export FWDIR="$(cd "`dirname "$0"`"/..; pwd)"
-
-function usage {
-  if [ -n "$1" ]; then
-    echo "$1"
-  fi
-  echo "Usage: ./bin/spark-sql [options] [cli option]"
-  pattern="usage"
-  pattern+="\|Spark assembly has been built with Hive"
-  pattern+="\|NOTE: SPARK_PREPEND_CLASSES is set"
-  pattern+="\|Spark Command: "
-  pattern+="\|--help"
-  pattern+="\|======="
-
-  "$FWDIR"/bin/spark-submit --help 2>&1 | grep -v Usage 1>&2
-  echo
-  echo "CLI options:"
-  "$FWDIR"/bin/spark-class "$CLASS" --help 2>&1 | grep -v "$pattern" 1>&2
-  exit "$2"
-}
-export -f usage
-
-if [[ "$@" = *--help ]] || [[ "$@" = *-h ]]; then
-  usage "" 0
-fi
-
-exec "$FWDIR"/bin/spark-submit --class "$CLASS" "$@"
+export _SPARK_CMD_USAGE="Usage: ./bin/spark-sql [options] [cli option]"
+exec "$FWDIR"/bin/spark-submit --class org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver "$@"

bin/spark-submit

@@ -22,16 +22,4 @@ SPARK_HOME="$(cd "`dirname "$0"`"/..; pwd)"
 # disable randomized hash for string in Python 3.3+
 export PYTHONHASHSEED=0
 
-# Only define a usage function if an upstream script hasn't done so.
-if ! type -t usage >/dev/null 2>&1; then
-  usage() {
-    if [ -n "$1" ]; then
-      echo "$1"
-    fi
-    "$SPARK_HOME"/bin/spark-class org.apache.spark.deploy.SparkSubmit --help
-    exit "$2"
-  }
-  export -f usage
-fi
-
 exec "$SPARK_HOME"/bin/spark-class org.apache.spark.deploy.SparkSubmit "$@"

bin/spark-submit2.cmd

@@ -24,15 +24,4 @@ rem disable randomized hash for string in Python 3.3+
 set PYTHONHASHSEED=0
 
 set CLASS=org.apache.spark.deploy.SparkSubmit
-call %~dp0spark-class2.cmd %CLASS% %*
-set SPARK_ERROR_LEVEL=%ERRORLEVEL%
-if not "x%SPARK_LAUNCHER_USAGE_ERROR%"=="x" (
-  call :usage
-  exit /b 1
-)
-exit /b %SPARK_ERROR_LEVEL%
-
-:usage
-echo %SPARK_LAUNCHER_USAGE_ERROR%
-call %SPARK_HOME%\bin\spark-class2.cmd %CLASS% --help
-goto :eof
+%~dp0spark-class2.cmd %CLASS% %*