diff --git a/python/pyspark/sql.py b/python/pyspark/sql.py
index 3814108471a9d..04c7740ef1c6e 100644
--- a/python/pyspark/sql.py
+++ b/python/pyspark/sql.py
@@ -527,7 +527,6 @@ def _parse_datatype_json_string(json_string):
     ...                           complex_arraytype, False)
     >>> check_datatype(complex_maptype)
     True
-    >>> from pyspark.tests import ExamplePointUDT
     >>> check_datatype(ExamplePointUDT())
     True
     >>> structtype_with_udt = StructType([StructField("label", DoubleType(), False),
@@ -581,7 +580,6 @@ def _parse_datatype_json_value(json_value):
 def _infer_type(obj):
     """Infer the DataType from obj
 
-    >>> from pyspark.tests import ExamplePoint
     >>> p = ExamplePoint(1.0, 2.0)
     >>> _infer_type(p)
     ExamplePointUDT
@@ -648,7 +646,6 @@ def _need_python_to_sql_conversion(dataType):
     ...                       StructField("values", ArrayType(DoubleType(), False), False)])
     >>> _need_python_to_sql_conversion(schema0)
     False
-    >>> from pyspark.tests import ExamplePointUDT
     >>> _need_python_to_sql_conversion(ExamplePointUDT())
     True
     >>> schema1 = ArrayType(ExamplePointUDT(), False)
@@ -682,7 +679,6 @@ def _python_to_sql_converter(dataType):
     >>> conv = _python_to_sql_converter(ArrayType(DoubleType(), False))
     >>> conv([1.0, 2.0])
     [1.0, 2.0]
-    >>> from pyspark.tests import ExamplePointUDT, ExamplePoint
     >>> conv = _python_to_sql_converter(ExamplePointUDT())
     >>> conv(ExamplePoint(1.0, 2.0))
     [1.0, 2.0]
@@ -953,7 +949,6 @@ def _verify_type(obj, dataType):
     Traceback (most recent call last):
         ...
     ValueError:...
-    >>> from pyspark.tests import ExamplePoint, ExamplePointUDT
     >>> _verify_type(ExamplePoint(1.0, 2.0), ExamplePointUDT())
     >>> _verify_type([1.0, 2.0], ExamplePointUDT()) # doctest: +IGNORE_EXCEPTION_DETAIL
     Traceback (most recent call last):
@@ -2015,6 +2010,7 @@ def _test():
     # let doctest run in pyspark.sql, so DataTypes can be picklable
     import pyspark.sql
     from pyspark.sql import Row, SQLContext
+    from pyspark.tests import ExamplePoint, ExamplePointUDT
     globs = pyspark.sql.__dict__.copy()
     # The small batch size here ensures that we see multiple batches,
     # even in these small test examples:
@@ -2026,6 +2022,8 @@ def _test():
          Row(field1=2, field2="row2"),
          Row(field1=3, field2="row3")]
     )
+    globs['ExamplePoint'] = ExamplePoint
+    globs['ExamplePointUDT'] = ExamplePointUDT
     jsonStrings = [
         '{"field1": 1, "field2": "row1", "field3":{"field4":11}}',
         '{"field1" : 2, "field3":{"field4":22, "field5": [10, 11]},'
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
index 83d18daf7a259..84eaf401f240c 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
@@ -484,7 +484,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
       case ArrayType(_, _) => true
       case MapType(_, _, _) => true
       case StructType(_) => true
-      case _: UserDefinedType[_] => true
+      case udt: UserDefinedType[_] => needsConversion(udt.sqlType)
       case other => false
     }