diff --git a/R/pkg/NAMESPACE b/R/pkg/NAMESPACE
index 4ea05b25ecc9e..25162f3e23b38 100644
--- a/R/pkg/NAMESPACE
+++ b/R/pkg/NAMESPACE
@@ -427,6 +427,7 @@ exportMethods("%<=>%",
               "variance",
               "var_pop",
               "var_samp",
+              "vector_to_array",
               "weekofyear",
               "when",
               "window",
diff --git a/R/pkg/R/functions.R b/R/pkg/R/functions.R
index b216f404a3ca5..61ea90efb348d 100644
--- a/R/pkg/R/functions.R
+++ b/R/pkg/R/functions.R
@@ -345,6 +345,17 @@ NULL
 #' head(tmp)}
 NULL
 
+#' ML functions for Column operations
+#'
+#' ML functions defined for \code{Column}.
+#'
+#' @param x Column to compute on.
+#' @param ... additional argument(s).
+#' @name column_ml_functions
+#' @rdname column_ml_functions
+#' @family ml functions
+NULL
+
 #' @details
 #' \code{lit}: A new Column is created to represent the literal value.
 #' If the parameter is a Column, it is returned unchanged.
@@ -4458,3 +4469,25 @@ setMethod("timestamp_seconds",
             )
             column(jc)
           })
+
+#' @details
+#' \code{vector_to_array} Converts a column of MLlib sparse/dense vectors into
+#' a column of dense arrays.
+#'
+#' @param dtype The data type of the output array. Valid values: "float64" or "float32".
+#'
+#' @rdname column_ml_functions
+#' @aliases vector_to_array vector_to_array,Column-method
+#' @note vector_to_array since 3.1.0
+setMethod("vector_to_array",
+          signature(x = "Column"),
+          function(x, dtype = c("float32", "float64")) {
+            dtype <- match.arg(dtype)
+            jc <- callJStatic(
+              "org.apache.spark.ml.functions",
+              "vector_to_array",
+              x@jc,
+              dtype
+            )
+            column(jc)
+          })
diff --git a/R/pkg/R/generics.R b/R/pkg/R/generics.R
index 985678679dec8..993fc758adbe5 100644
--- a/R/pkg/R/generics.R
+++ b/R/pkg/R/generics.R
@@ -1449,6 +1449,10 @@ setGeneric("var_pop", function(x) { standardGeneric("var_pop") })
 #' @name NULL
 setGeneric("var_samp", function(x) { standardGeneric("var_samp") })
 
+#' @rdname column_ml_functions
+#' @name NULL
+setGeneric("vector_to_array", function(x, ...) { standardGeneric("vector_to_array") })
+
 #' @rdname column_datetime_functions
 #' @name NULL
 setGeneric("weekofyear", function(x) { standardGeneric("weekofyear") })
diff --git a/R/pkg/tests/fulltests/test_sparkSQL.R b/R/pkg/tests/fulltests/test_sparkSQL.R
index c36620227593d..c3b271b1205c5 100644
--- a/R/pkg/tests/fulltests/test_sparkSQL.R
+++ b/R/pkg/tests/fulltests/test_sparkSQL.R
@@ -1424,7 +1424,8 @@ test_that("column functions", {
     date_trunc("quarter", c) + current_date() + current_timestamp()
   c25 <- overlay(c1, c2, c3, c3) + overlay(c1, c2, c3) + overlay(c1, c2, 1) +
     overlay(c1, c2, 3, 4)
-  c26 <- timestamp_seconds(c1)
+  c26 <- timestamp_seconds(c1) + vector_to_array(c) +
+    vector_to_array(c, "float32") + vector_to_array(c, "float64")
   c27 <- nth_value("x", 1L) + nth_value("y", 2, TRUE) +
     nth_value(column("v"), 3) + nth_value(column("z"), 4L, FALSE)