Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/22666#discussion_r226814727
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/functions.scala ---
@@ -3886,6 +3886,31 @@ object functions {
withExpr(new CsvToStructs(e.expr, schema.expr, options.asScala.toMap))
}
+ /**
+ * Parses a column containing a CSV string and infers its schema.
+ *
+ * @param e a string column containing CSV data.
+ *
+ * @group collection_funcs
+ * @since 3.0.0
+ */
+ def schema_of_csv(e: Column): Column = withExpr(new SchemaOfCsv(e.expr))
+
+ /**
+ * Parses a column containing a CSV string and infers its schema using
options.
+ *
+ * @param e a string column containing CSV data.
+ * @param options options to control how the CSV is parsed. accepts the
same options and the
+ * json data source. See [[DataFrameReader#csv]].
+ * @return a column with string literal containing schema in DDL format.
+ *
+ * @group collection_funcs
+ * @since 3.0.0
+ */
+ def schema_of_csv(e: Column, options: java.util.Map[String, String]):
Column = {
--- End diff --
`schema_of_json` also has only Java specific (I actually suggested to
minimise exposed functions) since Java specific one can be used in Scala side
but Scala specific can't be used in Java side.
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