diff --git a/core/src/main/scala/org/apache/spark/SparkEnv.scala b/core/src/main/scala/org/apache/spark/SparkEnv.scala
index 9461afdc54124a22191cee30e1ae90c96183a423..204f7356f7ef8ecb5c1757e79b5c43a89e3e3bfd 100644
--- a/core/src/main/scala/org/apache/spark/SparkEnv.scala
+++ b/core/src/main/scala/org/apache/spark/SparkEnv.scala
@@ -35,7 +35,7 @@ import org.apache.spark.network.netty.NettyBlockTransferService
 import org.apache.spark.rpc.{RpcEndpoint, RpcEndpointRef, RpcEnv}
 import org.apache.spark.scheduler.{LiveListenerBus, OutputCommitCoordinator}
 import org.apache.spark.scheduler.OutputCommitCoordinator.OutputCommitCoordinatorEndpoint
-import org.apache.spark.serializer.Serializer
+import org.apache.spark.serializer.{JavaSerializer, Serializer}
 import org.apache.spark.shuffle.ShuffleManager
 import org.apache.spark.storage._
 import org.apache.spark.util.{RpcUtils, Utils}
@@ -277,8 +277,7 @@ object SparkEnv extends Logging {
       "spark.serializer", "org.apache.spark.serializer.JavaSerializer")
     logDebug(s"Using serializer: ${serializer.getClass}")
 
-    val closureSerializer = instantiateClassFromConf[Serializer](
-      "spark.closure.serializer", "org.apache.spark.serializer.JavaSerializer")
+    val closureSerializer = new JavaSerializer(conf)
 
     def registerOrLookupEndpoint(
         name: String, endpointCreator: => RpcEndpoint):
diff --git a/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala b/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala
index f869bcd7086192c5e99fec7f8db93215199fe9e2..27d063630be9deb2cfb0f91dde29d00b44a0e877 100644
--- a/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/serializer/KryoSerializerSuite.scala
@@ -282,8 +282,7 @@ class KryoSerializerSuite extends SparkFunSuite with SharedSparkContext {
   test("kryo with fold") {
     val control = 1 :: 2 :: Nil
     // zeroValue must not be a ClassWithoutNoArgConstructor instance because it will be
-    // serialized by spark.closure.serializer but spark.closure.serializer only supports
-    // the default Java serializer.
+    // serialized by the Java serializer.
     val result = sc.parallelize(control, 2).map(new ClassWithoutNoArgConstructor(_))
       .fold(null)((t1, t2) => {
       val t1x = if (t1 == null) 0 else t1.x
diff --git a/docs/configuration.md b/docs/configuration.md
index b07c69cd4c987e6343ff377c4cdaa8440e331602..dd2cde81941db0372f64015c8d9e0fe33d663a28 100644
--- a/docs/configuration.md
+++ b/docs/configuration.md
@@ -586,13 +586,6 @@ Apart from these, the following properties are also available, and may be useful
     Whether to compress broadcast variables before sending them. Generally a good idea.
   </td>
 </tr>
-<tr>
-  <td><code>spark.closure.serializer</code></td>
-  <td>org.apache.spark.serializer.<br />JavaSerializer</td>
-  <td>
-    Serializer class to use for closures. Currently only the Java serializer is supported.
-  </td>
-</tr>
 <tr>
   <td><code>spark.io.compression.codec</code></td>
   <td>lz4</td>
diff --git a/docs/streaming-programming-guide.md b/docs/streaming-programming-guide.md
index 7e681b67cf0c2b9a0e56d7d7826f3a9d1e00cf4a..677f5ff7bea8b4609a158cbcc4d6ae9593ebafa3 100644
--- a/docs/streaming-programming-guide.md
+++ b/docs/streaming-programming-guide.md
@@ -2163,8 +2163,6 @@ If the number of tasks launched per second is high (say, 50 or more per second),
 of sending out tasks to the slaves may be significant and will make it hard to achieve sub-second
 latencies. The overhead can be reduced by the following changes:
 
-* **Task Serialization**: Using Kryo serialization for serializing tasks can reduce the task sizes, and therefore reduce the time taken to send them to the slaves. This is controlled by the ```spark.closure.serializer``` property. However, at this time, Kryo serialization cannot be enabled for closure serialization. This may be resolved in a future release.
-
 * **Execution mode**: Running Spark in Standalone mode or coarse-grained Mesos mode leads to
   better task launch times than the fine-grained Mesos mode. Please refer to the
   [Running on Mesos guide](running-on-mesos.html) for more details.