[SPARK-5447][SQL] Replaced reference to SchemaRDD with DataFrame.

and

[SPARK-5448][SQL] Make CacheManager a concrete class and field in SQLContext

Author: Reynold Xin <rxin@databricks.com>

Closes #4242 from rxin/sqlCleanup and squashes the following commits:

e351cb2 [Reynold Xin] Fixed toDataFrame.
6545c42 [Reynold Xin] More changes.
728c017 [Reynold Xin] [SPARK-5447][SQL] Replaced reference to SchemaRDD with DataFrame.

1 files changed, 3 insertions, 3 deletions

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/dataTypes.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/dataTypes.scala
index 9f30f40a17..6ab99aa388 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/types/dataTypes.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/types/dataTypes.scala
@@ -930,13 +930,13 @@ case class MapType(
  *
  * This interface allows a user to make their own classes more interoperable with SparkSQL;
  * e.g., by creating a [[UserDefinedType]] for a class X, it becomes possible to create
- * a SchemaRDD which has class X in the schema.
+ * a `DataFrame` which has class X in the schema.
  *
  * For SparkSQL to recognize UDTs, the UDT must be annotated with
  * [[SQLUserDefinedType]].
  *
- * The conversion via `serialize` occurs when instantiating a `SchemaRDD` from another RDD.
- * The conversion via `deserialize` occurs when reading from a `SchemaRDD`.
+ * The conversion via `serialize` occurs when instantiating a `DataFrame` from another RDD.
+ * The conversion via `deserialize` occurs when reading from a `DataFrame`.
  */
 @DeveloperApi
 abstract class UserDefinedType[UserType] extends DataType with Serializable {