[SPARK-11210][SPARKR] Add window functions into SparkR [step 2].

R/pkg/NAMESPACE

@@ -126,6 +126,7 @@ exportMethods("%in%",
               "datediff",
               "dayofmonth",
               "dayofyear",
+              "denseRank",
               "desc",
               "endsWith",
               "exp",
@@ -182,16 +183,19 @@ exportMethods("%in%",
               "next_day",
               "ntile",
               "otherwise",
+              "percentRank",
               "pmod",
               "quarter",
               "rand",
               "randn",
+              "rank",
               "regexp_extract",
               "regexp_replace",
               "reverse",
               "rint",
               "rlike",
               "round",
+              "rowNumber",
               "rpad",
               "rtrim",
               "second",

R/pkg/R/functions.R

@@ -2038,6 +2038,28 @@ setMethod("cumeDist",
             column(jc)
           })
 
+#' denseRank
+#' 
+#' Window function: returns the rank of rows within a window partition, without any gaps.
+#' The difference between rank and denseRank is that denseRank leaves no gaps in ranking
+#' sequence when there are ties. That is, if you were ranking a competition using denseRank
+#' and had three people tie for second place, you would say that all three were in second
+#' place and that the next person came in third.
+#' 
+#' This is equivalent to the DENSE_RANK function in SQL.
+#'
+#' @rdname denseRank
+#' @name denseRank
+#' @family window_funcs
+#' @export
+#' @examples \dontrun{denseRank()}
+setMethod("denseRank",
+          signature(x = "missing"),
+          function() {
+            jc <- callJStatic("org.apache.spark.sql.functions", "denseRank")
+            column(jc)
+          })
+
 #' lag
 #'
 #' Window function: returns the value that is `offset` rows before the current row, and
@@ -2111,3 +2133,73 @@ setMethod("ntile",
             jc <- callJStatic("org.apache.spark.sql.functions", "ntile", as.integer(x))
             column(jc)
           })
+
+#' percentRank
+#'
+#' Window function: returns the relative rank (i.e. percentile) of rows within a window partition.
+#' 
+#' This is computed by:
+#' 
+#'   (rank of row in its partition - 1) / (number of rows in the partition - 1)
+#'
+#' This is equivalent to the PERCENT_RANK function in SQL.
+#'
+#' @rdname percentRank
+#' @name percentRank
+#' @family window_funcs
+#' @export
+#' @examples \dontrun{percentRank()}
+setMethod("percentRank",
+          signature(x = "missing"),
+          function() {
+            jc <- callJStatic("org.apache.spark.sql.functions", "percentRank")
+            column(jc)
+          })
+
+#' rank
+#'
+#' Window function: returns the rank of rows within a window partition.
+#' 
+#' The difference between rank and denseRank is that denseRank leaves no gaps in ranking
+#' sequence when there are ties. That is, if you were ranking a competition using denseRank
+#' and had three people tie for second place, you would say that all three were in second
+#' place and that the next person came in third.
+#' 
+#' This is equivalent to the RANK function in SQL.
+#'
+#' @rdname rank
+#' @name rank
+#' @family window_funcs
+#' @export
+#' @examples \dontrun{rank()}
+setMethod("rank",
+          signature(x = "missing"),
+          function() {
+            jc <- callJStatic("org.apache.spark.sql.functions", "rank")
+            column(jc)
+          })
+
+# Expose rank() in the R base package
+setMethod("rank",
+          signature(x = "ANY"),
+          function(x, ...) {
+            base::rank(x, ...)
+          })
+
+#' rowNumber
+#'
+#' Window function: returns a sequential number starting at 1 within a window partition.
+#' 
+#' This is equivalent to the ROW_NUMBER function in SQL.
+#'
+#' @rdname rowNumber
+#' @name rowNumber
+#' @family window_funcs
+#' @export
+#' @examples \dontrun{rowNumber()}
+setMethod("rowNumber",
+          signature(x = "missing"),
+          function() {
+            jc <- callJStatic("org.apache.spark.sql.functions", "rowNumber")
+            column(jc)
+          })

R/pkg/R/generics.R

@@ -742,6 +742,10 @@ setGeneric("dayofmonth", function(x) { standardGeneric("dayofmonth") })
 #' @export
 setGeneric("dayofyear", function(x) { standardGeneric("dayofyear") })
 
+#' @rdname denseRank
+#' @export
+setGeneric("denseRank", function(x) { standardGeneric("denseRank") })
+
 #' @rdname explode
 #' @export
 setGeneric("explode", function(x) { standardGeneric("explode") })
@@ -878,6 +882,10 @@ setGeneric("ntile", function(x) { standardGeneric("ntile") })
 #' @export
 setGeneric("n_distinct", function(x, ...) { standardGeneric("n_distinct") })
 
+#' @rdname percentRank
+#' @export
+setGeneric("percentRank", function(x) { standardGeneric("percentRank") })
+
 #' @rdname pmod
 #' @export
 setGeneric("pmod", function(y, x) { standardGeneric("pmod") })
@@ -894,6 +902,10 @@ setGeneric("rand", function(seed) { standardGeneric("rand") })
 #' @export
 setGeneric("randn", function(seed) { standardGeneric("randn") })
 
+#' @rdname rank
+#' @export
+setGeneric("rank", function(x, ...) { standardGeneric("rank") })
+
 #' @rdname regexp_extract
 #' @export
 setGeneric("regexp_extract", function(x, pattern, idx) { standardGeneric("regexp_extract") })
@@ -911,6 +923,10 @@ setGeneric("reverse", function(x) { standardGeneric("reverse") })
 #' @export
 setGeneric("rint", function(x, ...) { standardGeneric("rint") })
 
+#' @rdname rowNumber
+#' @export
+setGeneric("rowNumber", function(x) { standardGeneric("rowNumber") })
+
 #' @rdname rpad
 #' @export
 setGeneric("rpad", function(x, len, pad) { standardGeneric("rpad") })

R/pkg/inst/tests/test_sparkSQL.R

@@ -831,6 +831,11 @@ test_that("column functions", {
   c11 <- to_date(c) + trim(c) + unbase64(c) + unhex(c) + upper(c)
   c12 <- lead("col", 1) + lead(c, 1) + lag("col", 1) + lag(c, 1)
   c13 <- cumeDist() + ntile(1)
+  c14 <- denseRank() + percentRank() + rank() + rowNumber()
+
+  # Test if base::rank() is exposed
+  expect_equal(class(rank())[[1]], "Column")
+  expect_equal(rank(1:3), as.numeric(c(1:3)))
 
   df <- jsonFile(sqlContext, jsonPath)
   df2 <- select(df, between(df$age, c(20, 30)), between(df$age, c(10, 20)))