[GitHub] [spark] deshanxiao commented on a diff in pull request #37549: [SPARK-40103][R][FEATURE] Support read/write.csv() in SparkR

[GitBox <gi...@apache.org>]

deshanxiao commented on code in PR #37549:
URL: https://github.com/apache/spark/pull/37549#discussion_r947573399


##########
R/pkg/R/SQLContext.R:
##########
@@ -492,6 +492,37 @@ read.text <- function(path, ...) {
   dataFrame(sdf)
 }
 
+#' Create a SparkDataFrame from a csv file.
+#'
+#' Loads a Parquet file, returning the result as a SparkDataFrame.
+#'
+#' @param path Path of file to read. A vector of multiple paths is allowed.
+#' @param ... additional external data source specific named properties.
+#'            You can find the csv-specific options for reading csv files in
+# nolint start
+#'            \url{https://spark.apache.org/docs/latest/sql-data-sources-csv.html#data-source-option}{Data Source Option} in the version you use.
+# nolint end
+#' @return SparkDataFrame
+#' @rdname read.spark.csv
+#' @examples
+#'\dontrun{
+#' sparkR.session()
+#' path <- "path/to/file.csv"
+#' df <- read.spark.csv(path)
+#' }
+#' @name read.spark.csv
+#' @note read.spark.csv since 3.3.0
+read.spark.csv <- function(path, ...) {

Review Comment:
   Yes, We can read csv file by following code:
   `df <- read.df("examples/src/main/resources/people.csv", "csv", sep = ";", inferSchema = TRUE, header = TRUE)
   `
   
   However, considering that other formats have corresponding advanced functions(read.text() etc.), it is necessary to add a high-level api here.



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