Branch 2.2

LICENSE

@@ -249,11 +249,11 @@ The text of each license is also included at licenses/LICENSE-[project].txt.
         (Interpreter classes (all .scala files in repl/src/main/scala
         except for Main.Scala, SparkHelper.scala and ExecutorClassLoader.scala),
         and for SerializableMapWrapper in JavaUtils.scala)
-     (BSD-like) Scala Actors library (org.scala-lang:scala-actors:2.11.7 - http://www.scala-lang.org/)
-     (BSD-like) Scala Compiler (org.scala-lang:scala-compiler:2.11.7 - http://www.scala-lang.org/)
-     (BSD-like) Scala Compiler (org.scala-lang:scala-reflect:2.11.7 - http://www.scala-lang.org/)
-     (BSD-like) Scala Library (org.scala-lang:scala-library:2.11.7 - http://www.scala-lang.org/)
-     (BSD-like) Scalap (org.scala-lang:scalap:2.11.7 - http://www.scala-lang.org/)
+     (BSD-like) Scala Actors library (org.scala-lang:scala-actors:2.11.8 - http://www.scala-lang.org/)
+     (BSD-like) Scala Compiler (org.scala-lang:scala-compiler:2.11.8 - http://www.scala-lang.org/)
+     (BSD-like) Scala Compiler (org.scala-lang:scala-reflect:2.11.8 - http://www.scala-lang.org/)
+     (BSD-like) Scala Library (org.scala-lang:scala-library:2.11.8 - http://www.scala-lang.org/)
+     (BSD-like) Scalap (org.scala-lang:scalap:2.11.8 - http://www.scala-lang.org/)
      (BSD-style) scalacheck (org.scalacheck:scalacheck_2.11:1.10.0 - http://www.scalacheck.org)
      (BSD-style) spire (org.spire-math:spire_2.11:0.7.1 - http://spire-math.org)
      (BSD-style) spire-macros (org.spire-math:spire-macros_2.11:0.7.1 - http://spire-math.org)
@@ -263,7 +263,7 @@ The text of each license is also included at licenses/LICENSE-[project].txt.
      (New BSD license) Protocol Buffer Java API (org.spark-project.protobuf:protobuf-java:2.4.1-shaded - http://code.google.com/p/protobuf)
      (The BSD License) Fortran to Java ARPACK (net.sourceforge.f2j:arpack_combined_all:0.1 - http://f2j.sourceforge.net)
      (The BSD License) xmlenc Library (xmlenc:xmlenc:0.52 - http://xmlenc.sourceforge.net)
-     (The New BSD License) Py4J (net.sf.py4j:py4j:0.10.4 - http://py4j.sourceforge.net/)
+     (The New BSD License) Py4J (net.sf.py4j:py4j:0.10.7 - http://py4j.sourceforge.net/)
      (Two-clause BSD-style license) JUnit-Interface (com.novocode:junit-interface:0.10 - http://github.com/szeiger/junit-interface/)
      (BSD licence) sbt and sbt-launch-lib.bash
      (BSD 3 Clause) d3.min.js (https://github.com/mbostock/d3/blob/master/LICENSE)
@@ -297,3 +297,4 @@ The text of each license is also included at licenses/LICENSE-[project].txt.
      (MIT License) RowsGroup (http://datatables.net/license/mit)
      (MIT License) jsonFormatter (http://www.jqueryscript.net/other/jQuery-Plugin-For-Pretty-JSON-Formatting-jsonFormatter.html)
      (MIT License) modernizr (https://github.com/Modernizr/Modernizr/blob/master/LICENSE)
+     (MIT License) machinist (https://github.com/typelevel/machinist)

NOTICE

@@ -5,6 +5,31 @@ This product includes software developed at
 The Apache Software Foundation (http://www.apache.org/).
 
 
+Export Control Notice
+---------------------
+
+This distribution includes cryptographic software. The country in which you currently reside may have
+restrictions on the import, possession, use, and/or re-export to another country, of encryption software.
+BEFORE using any encryption software, please check your country's laws, regulations and policies concerning
+the import, possession, or use, and re-export of encryption software, to see if this is permitted. See
+<http://www.wassenaar.org/> for more information.
+
+The U.S. Government Department of Commerce, Bureau of Industry and Security (BIS), has classified this
+software as Export Commodity Control Number (ECCN) 5D002.C.1, which includes information security software
+using or performing cryptographic functions with asymmetric algorithms. The form and manner of this Apache
+Software Foundation distribution makes it eligible for export under the License Exception ENC Technology
+Software Unrestricted (TSU) exception (see the BIS Export Administration Regulations, Section 740.13) for
+both object code and source code.
+
+The following provides more details on the included cryptographic software:
+
+This software uses Apache Commons Crypto (https://commons.apache.org/proper/commons-crypto/) to
+support authentication, and encryption and decryption of data sent across the network between
+services.
+
+This software includes Bouncy Castle (http://bouncycastle.org/) to support the jets3t library.
+
+
 ========================================================================
 Common Development and Distribution License 1.0
 ========================================================================

R/README.md

@@ -66,11 +66,7 @@ To run one of them, use `./bin/spark-submit <filename> <args>`. For example:
 ```bash
 ./bin/spark-submit examples/src/main/r/dataframe.R
 ```
-You can also run the unit tests for SparkR by running. You need to install the [testthat](http://cran.r-project.org/web/packages/testthat/index.html) package first:
-```bash
-R -e 'install.packages("testthat", repos="http://cran.us.r-project.org")'
-./R/run-tests.sh
-```
+You can run R unit tests by following the instructions under [Running R Tests](http://spark.apache.org/docs/latest/building-spark.html#running-r-tests).
 
 ### Running on YARN
 

R/WINDOWS.md

@@ -34,10 +34,9 @@ To run the SparkR unit tests on Windows, the following steps are required —ass
 
 4. Set the environment variable `HADOOP_HOME` to the full path to the newly created `hadoop` directory.
 
-5. Run unit tests for SparkR by running the command below. You need to install the [testthat](http://cran.r-project.org/web/packages/testthat/index.html) package first:
+5. Run unit tests for SparkR by running the command below. You need to install the needed packages following the instructions under [Running R Tests](http://spark.apache.org/docs/latest/building-spark.html#running-r-tests) first:
 
     ```
-    R -e "install.packages('testthat', repos='http://cran.us.r-project.org')"
     .\bin\spark-submit2.cmd --conf spark.hadoop.fs.defaultFS="file:///" R\pkg\tests\run-all.R
     ```
 

R/install-dev.sh

@@ -28,6 +28,7 @@
 
 set -o pipefail
 set -e
+set -x
 
 FWDIR="$(cd "`dirname "${BASH_SOURCE[0]}"`"; pwd)"
 LIB_DIR="$FWDIR/lib"

R/pkg/.Rbuildignore

@@ -6,3 +6,4 @@
 ^README\.Rmd$
 ^src-native$
 ^html$
+^tests/fulltests/*

R/pkg/DESCRIPTION

@@ -1,8 +1,8 @@
 Package: SparkR
 Type: Package
-Version: 2.2.0
+Version: 2.2.3
 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 = "[email protected]"),
              person("Xiangrui", "Meng", role = "aut",

R/pkg/NAMESPACE

@@ -122,6 +122,7 @@ exportMethods("arrange",
               "group_by",
               "groupBy",
               "head",
+              "hint",
               "insertInto",
               "intersect",
               "isLocal",

R/pkg/R/DataFrame.R

@@ -591,7 +591,7 @@ setMethod("cache",
 #'
 #' Persist this SparkDataFrame with the specified storage level. For details of the
 #' supported storage levels, refer to
-#' \url{http://spark.apache.org/docs/latest/programming-guide.html#rdd-persistence}.
+#' \url{http://spark.apache.org/docs/latest/rdd-programming-guide.html#rdd-persistence}.
 #'
 #' @param x the SparkDataFrame to persist.
 #' @param newLevel storage level chosen for the persistance. See available options in
@@ -1174,6 +1174,9 @@ setMethod("collect",
                     vec <- do.call(c, col)
                     stopifnot(class(vec) != "list")
                     class(vec) <- PRIMITIVE_TYPES[[colType]]
+                    if (is.character(vec) && stringsAsFactors) {
+                      vec <- as.factor(vec)
+                    }
                     df[[colIndex]] <- vec
                   } else {
                     df[[colIndex]] <- col
@@ -2642,6 +2645,7 @@ generateAliasesForIntersectedCols <- function (x, intersectedColNames, suffix) {
 #' Input SparkDataFrames can have different schemas (names and data types).
 #'
 #' Note: This does not remove duplicate rows across the two SparkDataFrames.
+#' Also as standard in SQL, this function resolves columns by position (not by name).
 #'
 #' @param x A SparkDataFrame
 #' @param y A SparkDataFrame
@@ -3114,7 +3118,7 @@ setMethod("as.data.frame",
 #'
 #' @family SparkDataFrame functions
 #' @rdname attach
-#' @aliases attach,SparkDataFrame-method
+#' @aliases attach attach,SparkDataFrame-method
 #' @param what (SparkDataFrame) The SparkDataFrame to attach
 #' @param pos (integer) Specify position in search() where to attach.
 #' @param name (character) Name to use for the attached SparkDataFrame. Names
@@ -3130,9 +3134,12 @@ setMethod("as.data.frame",
 #' @note attach since 1.6.0
 setMethod("attach",
           signature(what = "SparkDataFrame"),
-          function(what, pos = 2, name = deparse(substitute(what)), warn.conflicts = TRUE) {
-            newEnv <- assignNewEnv(what)
-            attach(newEnv, pos = pos, name = name, warn.conflicts = warn.conflicts)
+          function(what, pos = 2L, name = deparse(substitute(what), backtick = FALSE),
+                   warn.conflicts = TRUE) {
+            args <- as.list(environment()) # capture all parameters - this must be the first line
+            newEnv <- assignNewEnv(args$what)
+            args$what <- newEnv
+            do.call(attach, args)
           })
 
 #' Evaluate a R expression in an environment constructed from a SparkDataFrame
@@ -3642,3 +3649,33 @@ setMethod("checkpoint",
             df <- callJMethod(x@sdf, "checkpoint", as.logical(eager))
             dataFrame(df)
           })
+
+#' hint
+#'
+#' Specifies execution plan hint and return a new SparkDataFrame.
+#'
+#' @param x a SparkDataFrame.
+#' @param name a name of the hint.
+#' @param ... optional parameters for the hint.
+#' @return A SparkDataFrame.
+#' @family SparkDataFrame functions
+#' @aliases hint,SparkDataFrame,character-method
+#' @rdname hint
+#' @name hint
+#' @export
+#' @examples
+#' \dontrun{
+#' df <- createDataFrame(mtcars)
+#' avg_mpg <- mean(groupBy(createDataFrame(mtcars), "cyl"), "mpg")
+#'
+#' head(join(df, hint(avg_mpg, "broadcast"), df$cyl == avg_mpg$cyl))
+#' }
+#' @note hint since 2.2.0
+setMethod("hint",
+          signature(x = "SparkDataFrame", name = "character"),
+          function(x, name, ...) {
+            parameters <- list(...)
+            stopifnot(all(sapply(parameters, is.character)))
+            jdf <- callJMethod(x@sdf, "hint", name, parameters)
+            dataFrame(jdf)
+          })

R/pkg/R/RDD.R

@@ -227,7 +227,7 @@ setMethod("cacheRDD",
 #'
 #' Persist this RDD with the specified storage level. For details of the
 #' supported storage levels, refer to
-#'\url{http://spark.apache.org/docs/latest/programming-guide.html#rdd-persistence}.
+#'\url{http://spark.apache.org/docs/latest/rdd-programming-guide.html#rdd-persistence}.
 #'
 #' @param x The RDD to persist
 #' @param newLevel The new storage level to be assigned

R/pkg/R/SQLContext.R

@@ -334,7 +334,7 @@ setMethod("toDF", signature(x = "RDD"),
 #'
 #' Loads a JSON file, returning the result as a SparkDataFrame
 #' By default, (\href{http://jsonlines.org/}{JSON Lines text format or newline-delimited JSON}
-#' ) is supported. For JSON (one record per file), set a named property \code{wholeFile} to
+#' ) is supported. For JSON (one record per file), set a named property \code{multiLine} to
 #' \code{TRUE}.
 #' It goes through the entire dataset once to determine the schema.
 #'
@@ -348,7 +348,7 @@ setMethod("toDF", signature(x = "RDD"),
 #' sparkR.session()
 #' path <- "path/to/file.json"
 #' df <- read.json(path)
-#' df <- read.json(path, wholeFile = TRUE)
+#' df <- read.json(path, multiLine = TRUE)
 #' df <- jsonFile(path)
 #' }
 #' @name read.json
@@ -598,7 +598,7 @@ tableToDF <- function(tableName) {
 #' df1 <- read.df("path/to/file.json", source = "json")
 #' schema <- structType(structField("name", "string"),
 #'                      structField("info", "map<string,double>"))
-#' df2 <- read.df(mapTypeJsonPath, "json", schema, wholeFile = TRUE)
+#' df2 <- read.df(mapTypeJsonPath, "json", schema, multiLine = TRUE)
 #' df3 <- loadDF("data/test_table", "parquet", mergeSchema = "true")
 #' }
 #' @name read.df

R/pkg/R/client.R

@@ -19,7 +19,7 @@
 
 # Creates a SparkR client connection object
 # if one doesn't already exist
-connectBackend <- function(hostname, port, timeout) {
+connectBackend <- function(hostname, port, timeout, authSecret) {
   if (exists(".sparkRcon", envir = .sparkREnv)) {
     if (isOpen(.sparkREnv[[".sparkRCon"]])) {
       cat("SparkRBackend client connection already exists\n")
@@ -29,7 +29,7 @@ connectBackend <- function(hostname, port, timeout) {
 
   con <- socketConnection(host = hostname, port = port, server = FALSE,
                           blocking = TRUE, open = "wb", timeout = timeout)
-
+  doServerAuth(con, authSecret)
   assign(".sparkRCon", con, envir = .sparkREnv)
   con
 }

R/pkg/R/deserialize.R

@@ -60,14 +60,18 @@ readTypedObject <- function(con, type) {
     stop(paste("Unsupported type for deserialization", type)))
 }
 
-readString <- function(con) {
-  stringLen <- readInt(con)
-  raw <- readBin(con, raw(), stringLen, endian = "big")
+readStringData <- function(con, len) {
+  raw <- readBin(con, raw(), len, endian = "big")
   string <- rawToChar(raw)
   Encoding(string) <- "UTF-8"
   string
 }
 
+readString <- function(con) {
+  stringLen <- readInt(con)
+  readStringData(con, stringLen)
+}
+
 readInt <- function(con) {
   readBin(con, integer(), n = 1, endian = "big")
 }

R/pkg/R/generics.R

@@ -398,7 +398,8 @@ setGeneric("as.data.frame",
              standardGeneric("as.data.frame")
            })
 
-#' @rdname attach
+# Do not document the generic because of signature changes across R versions
+#' @noRd
 #' @export
 setGeneric("attach")
 
@@ -572,6 +573,10 @@ setGeneric("group_by", function(x, ...) { standardGeneric("group_by") })
 #' @export
 setGeneric("groupBy", function(x, ...) { standardGeneric("groupBy") })
 
+#' @rdname hint
+#' @export
+setGeneric("hint", function(x, name, ...) { standardGeneric("hint") })
+
 #' @rdname insertInto
 #' @export
 setGeneric("insertInto", function(x, tableName, ...) { standardGeneric("insertInto") })
@@ -1356,12 +1361,9 @@ setGeneric("year", function(x) { standardGeneric("year") })
 #' @export
 setGeneric("fitted")
 
-#' @param x,y For \code{glm}: logical values indicating whether the response vector
-#'          and model matrix used in the fitting process should be returned as
-#'          components of the returned value.
-#' @inheritParams stats::glm
-#' @rdname glm
+# Do not carry stats::glm usage and param here, and do not document the generic
 #' @export
+#' @noRd
 setGeneric("glm")
 
 #' @param object a fitted ML model object.
@@ -1469,7 +1471,7 @@ setGeneric("write.ml", function(object, path, ...) { standardGeneric("write.ml")
 
 #' @rdname awaitTermination
 #' @export
-setGeneric("awaitTermination", function(x, timeout) { standardGeneric("awaitTermination") })
+setGeneric("awaitTermination", function(x, timeout = NULL) { standardGeneric("awaitTermination") })
 
 #' @rdname isActive
 #' @export