Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/15354#discussion_r82229892
--- Diff: python/pyspark/sql/functions.py ---
@@ -1729,6 +1729,29 @@ def from_json(col, schema, options={}):
return Column(jc)
+@ignore_unicode_prefix
+@since(2.1)
+def to_json(col, options={}):
+ """
+ Converts a column containing a [[StructType]] into a JSON string.
Returns `null`,
+ in the case of an unsupported type.
+
+ :param col: struct column
+ :param options: options to control converting. accepts the same
options as the json datasource
+
+ >>> from pyspark.sql import Row
+ >>> from pyspark.sql.types import *
+ >>> data = [(1, Row(name='Alice', age=2))]
+ >>> df = spark.createDataFrame(data, ("key", "value"))
+ >>> df.select(to_json(df.value).alias("json")).collect()
+ [Row(json=u'{"age":2,"name":"Alice"}')]
+ """
+
+ sc = SparkContext._active_spark_context
+ jc = sc._jvm.functions.to_json(_to_java_column(col), options)
--- End diff --
This is super minor, but there is a pretty consistent pattern for all of
the other functions here (including `from_json`), it might be good to follow
that same pattern for consistencies sake since there isn't an obvious reason
why that wouldn't work here.
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