Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/22939#discussion_r236770223
--- Diff: R/pkg/R/functions.R ---
@@ -2230,6 +2237,32 @@ setMethod("from_json", signature(x = "Column",
schema = "characterOrstructType")
column(jc)
})
+#' @details
+#' \code{schema_of_json}: Parses a JSON string and infers its schema in
DDL format.
+#'
+#' @rdname column_collection_functions
+#' @aliases schema_of_json schema_of_json,characterOrColumn-method
+#' @examples
+#'
+#' \dontrun{
+#' json <- '{"name":"Bob"}'
+#' df <- sql("SELECT * FROM range(1)")
+#' head(select(df, schema_of_json(json)))}
+#' @note schema_of_json since 3.0.0
+setMethod("schema_of_json", signature(x = "characterOrColumn"),
+ function(x, ...) {
+ if (class(x) == "character") {
+ col <- callJStatic("org.apache.spark.sql.functions", "lit",
x)
+ } else {
+ col <- x@jc
--- End diff --
maybe to think about the design of API in R and Scala and else where - what
does it look like when the user passes in a column that is not a literal
string? probably worthwhile to follow up separately.
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