cloud-fan commented on code in PR #42462:
URL: https://github.com/apache/spark/pull/42462#discussion_r1296727683
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connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/functions.scala:
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@@ -7227,6 +7227,150 @@ object functions {
*/
def to_csv(e: Column): Column = to_csv(e, Collections.emptyMap())
+ // scalastyle:off line.size.limit
+ /**
+ * Parses a column containing a XML string into a `StructType` with the
specified schema.
+ * Returns `null`, in the case of an unparseable string.
+ *
+ * @param e
+ * a string column containing XML data.
+ * @param schema
+ * the schema to use when parsing the XML string
+ * @param options
+ * options to control how the XML is parsed. accepts the same options and
the XML data source.
+ * See <a href=
+ *
"https://spark.apache.org/docs/latest/sql-data-sources-xml.html#data-source-option">
Data
+ * Source Option</a> in the version you use.
+ * @group collection_funcs
+ *
+ * @since 4.0.0
+ */
+ // scalastyle:on line.size.limit
+ def from_xml(e: Column, schema: StructType, options: Map[String, String]):
Column =
+ from_xml(e, lit(schema.toDDL), options.iterator)
+
+ // scalastyle:off line.size.limit
+
+ /**
+ * Parses a column containing a XML string into a `StructType` with the
specified schema.
+ * Returns `null`, in the case of an unparseable string.
+ *
+ * @param e
+ * a string column containing XML data.
+ * @param schema
+ * the schema to use when parsing the xml string
+ * @param options
+ * options to control how the xml is parsed. accepts the same options and
the XML data source.
+ * See <a href=
+ *
"https://spark.apache.org/docs/latest/sql-data-sources-xml.html#data-source-option">
Data
+ * Source Option</a> in the version you use.
+ * @group collection_funcs
+ *
+ * @since 4.0.0
+ */
+ // scalastyle:on line.size.limit
+ def from_xml(e: Column, schema: DataType, options: Map[String, String]):
Column =
+ from_xml(e, lit(schema.json), options.iterator)
Review Comment:
for `StructType`, we call `lit(schema.toDDL)`, why we use json string here
for `DataType`?
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