doc

Author: aray

R/pkg/R/DataFrame.R

@@ -2930,7 +2930,7 @@ setMethod("saveAsTable",
             invisible(callJMethod(write, "saveAsTable", tableName))
           })
 
-#' summary
+#' describe
 #'
 #' Computes statistics for numeric and string columns.
 #' If no columns are given, this function computes statistics for all numerical or string columns.
@@ -2941,7 +2941,7 @@ setMethod("saveAsTable",
 #' @return A SparkDataFrame.
 #' @family SparkDataFrame functions
 #' @aliases describe,SparkDataFrame,character-method describe,SparkDataFrame,ANY-method
-#' @rdname summary
+#' @rdname describe
 #' @name describe
 #' @export
 #' @examples
@@ -2953,6 +2953,7 @@ setMethod("saveAsTable",
 #' describe(df, "col1")
 #' describe(df, "col1", "col2")
 #' }
+#' @seealso Ues \code{\link{summary}} for expanded statistics and control over which statistics to compute.
 #' @note describe(SparkDataFrame, character) since 1.4.0
 setMethod("describe",
           signature(x = "SparkDataFrame", col = "character"),
@@ -2962,7 +2963,7 @@ setMethod("describe",
             dataFrame(sdf)
           })
 
-#' @rdname summary
+#' @rdname describe
 #' @name describe
 #' @aliases describe,SparkDataFrame-method
 #' @note describe(SparkDataFrame) since 1.4.0
@@ -2973,15 +2974,47 @@ setMethod("describe",
             dataFrame(sdf)
           })
 
+#' summary
+#'
+#' Computes specified statistics for numeric and string columns.
+#'
+#' Available statistics are:
+#'
+#' - count
+#' - mean
+#' - stddev
+#' - min
+#' - max
+#' - arbitrary approximate percentiles specified as a percentage (eg, 75%)
+#'
+#' If no statistics are given, this function computes count, mean, stddev, min,
+#' approximate quartiles (percentiles at 25%, 50%, and 75%), and max.
+#'
+#' This function is meant for exploratory data analysis, as we make no guarantee about the
+#' backward compatibility of the schema of the resulting Dataset. If you want to
+#' programmatically compute summary statistics, use the `agg` function instead.
+#'
+#'
 #' @param object a SparkDataFrame to be summarized.
 #' @param ... (optional) statistics to be computed for all columns.
 #' @rdname summary
 #' @name summary
 #' @aliases summary,SparkDataFrame-method
+#' @export
+#' @examples
+#'\dontrun{
+#' sparkR.session()
+#' path <- "path/to/file.json"
+#' df <- read.json(path)
+#' summary(df)
+#' summary(df, "min", "25%", "75%", "max")
+#' summary(select(df, "age", "height"))
+#' }
 #' @note summary(SparkDataFrame) since 1.5.0
-#' @note the statistics provided by this method were change in 2.3.0 use describe for previous defaults.
+#' @note The statistics provided by \code{summary} were change in 2.3.0 use \code{\link{describe}} for previous defaults.
+#' @seealso \code{\link{describe}}
 setMethod("summary",
-          signature(object = "SparkDataFrame", ... = "character"),
+          signature(object = "SparkDataFrame"), #, ... = "character"),
           function(object, ...) {
             statisticsList <- list(...)
             sdf <- callJMethod(object@sdf, "summary", statisticsList)

R/pkg/R/generics.R

@@ -521,7 +521,7 @@ setGeneric("gapplyCollect", function(x, ...) { standardGeneric("gapplyCollect")
 # @export
 setGeneric("getNumPartitions", function(x) { standardGeneric("getNumPartitions") })
 
-#' @rdname summary
+#' @rdname describe
 #' @export
 setGeneric("describe", function(x, col, ...) { standardGeneric("describe") })