[SPARK-7321][SQL] Add Column expression for conditional statements (when/otherwise)

This builds on https://github.com/apache/spark/pull/5932 and should close https://github.com/apache/spark/pull/5932 as well.

As an example:
```python
df.select(when(df['age'] == 2, 3).otherwise(4).alias("age")).collect()
```

Author: Reynold Xin <rxin@databricks.com>
Author: kaka1992 <kaka_1992@163.com>

Closes #6072 from rxin/when-expr and squashes the following commits:

8f49201 [Reynold Xin] Throw exception if otherwise is applied twice.
0455eda [Reynold Xin] Reset run-tests.
bfb9d9f [Reynold Xin] Updated documentation and test cases.
762f6a5 [Reynold Xin] Merge pull request #5932 from kaka1992/IFCASE
95724c6 [kaka1992] Update
8218d0a [kaka1992] Update
801009e [kaka1992] Update
76d6346 [kaka1992] [SPARK-7321][SQL] Add Column expression for conditional statements (if, case)

3 files changed, 57 insertions, 2 deletions

diff --git a/python/pyspark/sql/__init__.py b/python/pyspark/sql/__init__.py
index b60b991dd4..7192c89b3d 100644
--- a/python/pyspark/sql/__init__.py
+++ b/python/pyspark/sql/__init__.py
@@ -32,6 +32,8 @@ Important classes of Spark SQL and DataFrames:
       Aggregation methods, returned by :func:`DataFrame.groupBy`.
     - L{DataFrameNaFunctions}
       Methods for handling missing data (null values).
+    - L{DataFrameStatFunctions}
+      Methods for statistics functionality.
     - L{functions}
       List of built-in functions available for :class:`DataFrame`.
     - L{types}
diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py
index 078acfdf7e..82cb1c2fdb 100644
--- a/python/pyspark/sql/dataframe.py
+++ b/python/pyspark/sql/dataframe.py
@@ -1546,6 +1546,37 @@ class Column(object):
         """
         return (self >= lowerBound) & (self <= upperBound)
 
+    @ignore_unicode_prefix
+    def when(self, condition, value):
+        """Evaluates a list of conditions and returns one of multiple possible result expressions.
+        If :func:`Column.otherwise` is not invoked, None is returned for unmatched conditions.
+
+        See :func:`pyspark.sql.functions.when` for example usage.
+
+        :param condition: a boolean :class:`Column` expression.
+        :param value: a literal value, or a :class:`Column` expression.
+
+        """
+        sc = SparkContext._active_spark_context
+        if not isinstance(condition, Column):
+            raise TypeError("condition should be a Column")
+        v = value._jc if isinstance(value, Column) else value
+        jc = sc._jvm.functions.when(condition._jc, v)
+        return Column(jc)
+
+    @ignore_unicode_prefix
+    def otherwise(self, value):
+        """Evaluates a list of conditions and returns one of multiple possible result expressions.
+        If :func:`Column.otherwise` is not invoked, None is returned for unmatched conditions.
+
+        See :func:`pyspark.sql.functions.when` for example usage.
+
+        :param value: a literal value, or a :class:`Column` expression.
+        """
+        v = value._jc if isinstance(value, Column) else value
+        jc = self._jc.otherwise(value)
+        return Column(jc)
+
     def __repr__(self):
         return 'Column<%s>' % self._jc.toString().encode('utf8')
 
diff --git a/python/pyspark/sql/functions.py b/python/pyspark/sql/functions.py
index 38a043a3c5..d91265ee0b 100644
--- a/python/pyspark/sql/functions.py
+++ b/python/pyspark/sql/functions.py
@@ -32,13 +32,14 @@ from pyspark.sql.dataframe import Column, _to_java_column, _to_seq
 
 __all__ = [
     'approxCountDistinct',
+    'coalesce',
     'countDistinct',
     'monotonicallyIncreasingId',
     'rand',
     'randn',
     'sparkPartitionId',
-    'coalesce',
-    'udf']
+    'udf',
+    'when']
 
 
 def _create_function(name, doc=""):
@@ -291,6 +292,27 @@ def struct(*cols):
     return Column(jc)
 
 
+def when(condition, value):
+    """Evaluates a list of conditions and returns one of multiple possible result expressions.
+    If :func:`Column.otherwise` is not invoked, None is returned for unmatched conditions.
+
+    :param condition: a boolean :class:`Column` expression.
+    :param value: a literal value, or a :class:`Column` expression.
+
+    >>> df.select(when(df['age'] == 2, 3).otherwise(4).alias("age")).collect()
+    [Row(age=3), Row(age=4)]
+
+    >>> df.select(when(df.age == 2, df.age + 1).alias("age")).collect()
+    [Row(age=3), Row(age=None)]
+    """
+    sc = SparkContext._active_spark_context
+    if not isinstance(condition, Column):
+        raise TypeError("condition should be a Column")
+    v = value._jc if isinstance(value, Column) else value
+    jc = sc._jvm.functions.when(condition._jc, v)
+    return Column(jc)
+
+
 class UserDefinedFunction(object):
     """
     User defined function in Python