[SPARK-17764][SQL] Add `to_json` supporting to convert nested struct column to JSON string

## What changes were proposed in this pull request?

This PR proposes to add `to_json` function in contrast with `from_json` in Scala, Java and Python.

It'd be useful if we can convert a same column from/to json. Also, some datasources do not support nested types. If we are forced to save a dataframe into those data sources, we might be able to work around by this function.

The usage is as below:

``` scala
val df = Seq(Tuple1(Tuple1(1))).toDF("a")
df.select(to_json($"a").as("json")).show()
```

``` bash
+--------+
|    json|
+--------+
|{"_1":1}|
+--------+
```
## How was this patch tested?

Unit tests in `JsonFunctionsSuite` and `JsonExpressionsSuite`.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #15354 from HyukjinKwon/SPARK-17764.

1 files changed, 23 insertions, 0 deletions

diff --git a/python/pyspark/sql/functions.py b/python/pyspark/sql/functions.py
index 7fa3fd2de7..45e3c22bfc 100644
--- a/python/pyspark/sql/functions.py
+++ b/python/pyspark/sql/functions.py
@@ -1744,6 +1744,29 @@ 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. Throws an exception,
+    in the case of an unsupported type.
+
+    :param col: name of column containing the struct
+    :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)
+    return Column(jc)
+
+
 @since(1.5)
 def size(col):
     """