Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/22954#discussion_r232619364
--- Diff: R/pkg/R/SQLContext.R ---
@@ -172,36 +257,72 @@ getDefaultSqlSource <- function() {
createDataFrame <- function(data, schema = NULL, samplingRatio = 1.0,
numPartitions = NULL) {
sparkSession <- getSparkSession()
-
+ arrowEnabled <- sparkR.conf("spark.sql.execution.arrow.enabled")[[1]] ==
"true"
+ shouldUseArrow <- FALSE
+ firstRow <- NULL
if (is.data.frame(data)) {
- # Convert data into a list of rows. Each row is a list.
-
- # get the names of columns, they will be put into RDD
- if (is.null(schema)) {
- schema <- names(data)
- }
+ # get the names of columns, they will be put into RDD
+ if (is.null(schema)) {
+ schema <- names(data)
+ }
- # get rid of factor type
- cleanCols <- function(x) {
- if (is.factor(x)) {
- as.character(x)
- } else {
- x
- }
+ # get rid of factor type
+ cleanCols <- function(x) {
+ if (is.factor(x)) {
+ as.character(x)
+ } else {
+ x
}
+ }
+ data[] <- lapply(data, cleanCols)
+
+ args <- list(FUN = list, SIMPLIFY = FALSE, USE.NAMES = FALSE)
+ if (arrowEnabled) {
+ shouldUseArrow <- tryCatch({
--- End diff --
When `shouldUseArrow` is true, I think it means we already done using
arrow? Maybe just `useArrow`?
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