diff --git a/R/pkg/R/DataFrame.R b/R/pkg/R/DataFrame.R index e33d0d8e29d49c996892cc2a1ff8759a01e92629..97e0c9edeab48322b24d016660b1bff97d531574 100644 --- a/R/pkg/R/DataFrame.R +++ b/R/pkg/R/DataFrame.R @@ -2642,6 +2642,7 @@ generateAliasesForIntersectedCols <- function (x, intersectedColNames, suffix) { #' #' Return a new SparkDataFrame containing the union of rows in this SparkDataFrame #' and another SparkDataFrame. This is equivalent to \code{UNION ALL} in SQL. +#' Input SparkDataFrames can have different schemas (names and data types). #' #' Note: This does not remove duplicate rows across the two SparkDataFrames. #' @@ -2685,7 +2686,8 @@ setMethod("unionAll", #' Union two or more SparkDataFrames #' -#' Union two or more SparkDataFrames. This is equivalent to \code{UNION ALL} in SQL. +#' Union two or more SparkDataFrames by row. As in R's \code{rbind}, this method +#' requires that the input SparkDataFrames have the same column names. #' #' Note: This does not remove duplicate rows across the two SparkDataFrames. #' @@ -2709,6 +2711,10 @@ setMethod("unionAll", setMethod("rbind", signature(... = "SparkDataFrame"), function(x, ..., deparse.level = 1) { + nm <- lapply(list(x, ...), names) + if (length(unique(nm)) != 1) { + stop("Names of input data frames are different.") + } if (nargs() == 3) { union(x, ...) } else { diff --git a/R/pkg/inst/tests/testthat/test_sparkSQL.R b/R/pkg/inst/tests/testthat/test_sparkSQL.R index 7c096597fea661458e1d7402e03a0ebc276c76f8..620b633637138e1659e72b58e3ef711c841e94bf 100644 --- a/R/pkg/inst/tests/testthat/test_sparkSQL.R +++ b/R/pkg/inst/tests/testthat/test_sparkSQL.R @@ -1850,6 +1850,13 @@ test_that("union(), rbind(), except(), and intersect() on a DataFrame", { expect_equal(count(unioned2), 12) expect_equal(first(unioned2)$name, "Michael") + df3 <- df2 + names(df3)[1] <- "newName" + expect_error(rbind(df, df3), + "Names of input data frames are different.") + expect_error(rbind(df, df2, df3), + "Names of input data frames are different.") + excepted <- arrange(except(df, df2), desc(df$age)) expect_is(unioned, "SparkDataFrame") expect_equal(count(excepted), 2)