Merge pull request #2 from apache/master

pull latest from apache spark

Author: rekhajoshm

.gitignore

@@ -65,6 +65,7 @@ scalastyle.txt
 scalastyle-output.xml
 R-unit-tests.log
 R/unit-tests.out
+python/lib/pyspark.zip
 
 # For Hive
 metastore_db/

.rat-excludes

@@ -36,7 +36,6 @@ graphlib-dot.min.js
 sorttable.js
 vis.min.js
 vis.min.css
-vis.map
 .*avsc
 .*txt
 .*json
@@ -80,6 +79,6 @@ local-1422981780767/*
 local-1425081759269/*
 local-1426533911241/*
 local-1426633911242/*
-local-1427397477963/*
+local-1430917381534/*
 DESCRIPTION
 NAMESPACE

R/pkg/DESCRIPTION

@@ -15,11 +15,11 @@ Suggests:
 Description: R frontend for Spark
 License: Apache License (== 2.0)
 Collate:
+    'schema.R'
     'generics.R'
     'jobj.R'
     'RDD.R'
     'pairRDD.R'
-    'schema.R'
     'column.R'
     'group.R'
     'DataFrame.R'

R/pkg/NAMESPACE

@@ -13,6 +13,7 @@ exportMethods("cache",
               "collect",
               "columns",
               "count",
+              "describe",
               "distinct",
               "dtypes",
               "except",
@@ -25,7 +26,6 @@ exportMethods("cache",
               "intersect",
               "isLocal",
               "join",
-              "length",
               "limit",
               "orderBy",
               "names",
@@ -44,8 +44,6 @@ exportMethods("cache",
               "showDF",
               "sortDF",
               "take",
-              "toJSON",
-              "toRDD",
               "unionAll",
               "unpersist",
               "where",
@@ -94,19 +92,14 @@ export("cacheTable",
        "createExternalTable",
        "dropTempTable",
        "jsonFile",
-       "jsonRDD",
        "loadDF",
        "parquetFile",
        "sql",
        "table",
        "tableNames",
        "tables",
-       "toDF",
        "uncacheTable")
 
-export("sparkRSQL.init",
-       "sparkRHive.init")
-
 export("structField",
        "structField.jobj",
        "structField.character",

R/pkg/R/DataFrame.R

@@ -45,6 +45,9 @@ setMethod("initialize", "DataFrame", function(.Object, sdf, isCached) {
 
 #' @rdname DataFrame
 #' @export
+#'
+#' @param sdf A Java object reference to the backing Scala DataFrame
+#' @param isCached TRUE if the dataFrame is cached
 dataFrame <- function(sdf, isCached = FALSE) {
   new("DataFrame", sdf, isCached)
 }
@@ -244,7 +247,7 @@ setMethod("columns",
           })
 
 #' @rdname columns
-#' @export
+#' @aliases names,DataFrame,function-method
 setMethod("names",
           signature(x = "DataFrame"),
           function(x) {
@@ -272,7 +275,7 @@ setMethod("names",
 setMethod("registerTempTable",
           signature(x = "DataFrame", tableName = "character"),
           function(x, tableName) {
-              callJMethod(x@sdf, "registerTempTable", tableName)
+              invisible(callJMethod(x@sdf, "registerTempTable", tableName))
           })
 
 #' insertInto
@@ -399,23 +402,23 @@ setMethod("repartition",
             dataFrame(sdf)     
           })
 
-#' toJSON
-#'
-#' Convert the rows of a DataFrame into JSON objects and return an RDD where
-#' each element contains a JSON string.
-#'
-#' @param x A SparkSQL DataFrame
-#' @return A StringRRDD of JSON objects
-#' @rdname tojson
-#' @export
-#' @examples
-#'\dontrun{
-#' sc <- sparkR.init()
-#' sqlCtx <- sparkRSQL.init(sc)
-#' path <- "path/to/file.json"
-#' df <- jsonFile(sqlCtx, path)
-#' newRDD <- toJSON(df)
-#'}
+# toJSON
+#
+# Convert the rows of a DataFrame into JSON objects and return an RDD where
+# each element contains a JSON string.
+#
+#@param x A SparkSQL DataFrame
+# @return A StringRRDD of JSON objects
+# @rdname tojson
+# @export
+# @examples
+#\dontrun{
+# sc <- sparkR.init()
+# sqlCtx <- sparkRSQL.init(sc)
+# path <- "path/to/file.json"
+# df <- jsonFile(sqlCtx, path)
+# newRDD <- toJSON(df)
+#}
 setMethod("toJSON",
           signature(x = "DataFrame"),
           function(x) {
@@ -578,8 +581,8 @@ setMethod("limit",
             dataFrame(res)
           })
 
-# Take the first NUM rows of a DataFrame and return a the results as a data.frame
-
+#' Take the first NUM rows of a DataFrame and return a the results as a data.frame
+#' 
 #' @rdname take
 #' @export
 #' @examples
@@ -644,22 +647,22 @@ setMethod("first",
             take(x, 1)
           })
 
-#' toRDD()
-#' 
-#' Converts a Spark DataFrame to an RDD while preserving column names.
-#' 
-#' @param x A Spark DataFrame
-#' 
-#' @rdname DataFrame
-#' @export
-#' @examples
-#'\dontrun{
-#' sc <- sparkR.init()
-#' sqlCtx <- sparkRSQL.init(sc)
-#' path <- "path/to/file.json"
-#' df <- jsonFile(sqlCtx, path)
-#' rdd <- toRDD(df)
-#' }
+# toRDD()
+# 
+# Converts a Spark DataFrame to an RDD while preserving column names.
+# 
+# @param x A Spark DataFrame
+# 
+# @rdname DataFrame
+# @export
+# @examples
+#\dontrun{
+# sc <- sparkR.init()
+# sqlCtx <- sparkRSQL.init(sc)
+# path <- "path/to/file.json"
+# df <- jsonFile(sqlCtx, path)
+# rdd <- toRDD(df)
+# }
 setMethod("toRDD",
           signature(x = "DataFrame"),
           function(x) {
@@ -706,6 +709,7 @@ setMethod("groupBy",
 #'
 #' Compute aggregates by specifying a list of columns
 #'
+#' @param x a DataFrame
 #' @rdname DataFrame
 #' @export
 setMethod("agg",
@@ -721,53 +725,53 @@ setMethod("agg",
 # the requested map function.                                                     #
 ###################################################################################
 
-#' @rdname lapply
+# @rdname lapply
 setMethod("lapply",
           signature(X = "DataFrame", FUN = "function"),
           function(X, FUN) {
             rdd <- toRDD(X)
             lapply(rdd, FUN)
           })
 
-#' @rdname lapply
+# @rdname lapply
 setMethod("map",
           signature(X = "DataFrame", FUN = "function"),
           function(X, FUN) {
             lapply(X, FUN)
           })
 
-#' @rdname flatMap
+# @rdname flatMap
 setMethod("flatMap",
           signature(X = "DataFrame", FUN = "function"),
           function(X, FUN) {
             rdd <- toRDD(X)
             flatMap(rdd, FUN)
           })
 
-#' @rdname lapplyPartition
+# @rdname lapplyPartition
 setMethod("lapplyPartition",
           signature(X = "DataFrame", FUN = "function"),
           function(X, FUN) {
             rdd <- toRDD(X)
             lapplyPartition(rdd, FUN)
           })
 
-#' @rdname lapplyPartition
+# @rdname lapplyPartition
 setMethod("mapPartitions",
           signature(X = "DataFrame", FUN = "function"),
           function(X, FUN) {
             lapplyPartition(X, FUN)
           })
 
-#' @rdname foreach
+# @rdname foreach
 setMethod("foreach",
           signature(x = "DataFrame", func = "function"),
           function(x, func) {
             rdd <- toRDD(x)
             foreach(rdd, func)
           })
 
-#' @rdname foreach
+# @rdname foreach
 setMethod("foreachPartition",
           signature(x = "DataFrame", func = "function"),
           function(x, func) {
@@ -788,6 +792,7 @@ setMethod("$", signature(x = "DataFrame"),
             getColumn(x, name)
           })
 
+#' @rdname select
 setMethod("$<-", signature(x = "DataFrame"),
           function(x, name, value) {
             stopifnot(class(value) == "Column" || is.null(value))
@@ -1009,7 +1014,7 @@ setMethod("sortDF",
           })
 
 #' @rdname sortDF
-#' @export
+#' @aliases orderBy,DataFrame,function-method
 setMethod("orderBy",
           signature(x = "DataFrame", col = "characterOrColumn"),
           function(x, col) {
@@ -1046,7 +1051,7 @@ setMethod("filter",
           })
 
 #' @rdname filter
-#' @export
+#' @aliases where,DataFrame,function-method
 setMethod("where",
           signature(x = "DataFrame", condition = "characterOrColumn"),
           function(x, condition) {
@@ -1276,3 +1281,40 @@ setMethod("saveAsTable",
             callJMethod(df@sdf, "saveAsTable", tableName, source, jmode, options)
           })
 
+#' describe
+#'
+#' Computes statistics for numeric columns.
+#' If no columns are given, this function computes statistics for all numerical columns.
+#'
+#' @param x A DataFrame to be computed.
+#' @param col A string of name
+#' @param ... Additional expressions
+#' @return A DataFrame
+#' @rdname describe 
+#' @export
+#' @examples
+#'\dontrun{
+#' sc <- sparkR.init()
+#' sqlCtx <- sparkRSQL.init(sc)
+#' path <- "path/to/file.json"
+#' df <- jsonFile(sqlCtx, path)
+#' describe(df)
+#' describe(df, "col1")
+#' describe(df, "col1", "col2")
+#' }
+setMethod("describe",
+          signature(x = "DataFrame", col = "character"),
+          function(x, col, ...) {
+            colList <- list(col, ...)
+            sdf <- callJMethod(x@sdf, "describe", listToSeq(colList))
+            dataFrame(sdf)
+          })
+
+#' @rdname describe
+setMethod("describe",
+          signature(x = "DataFrame"),
+          function(x) {
+            colList <- as.list(c(columns(x)))
+            sdf <- callJMethod(x@sdf, "describe", listToSeq(colList))
+            dataFrame(sdf)
+          })