Github user pwendell commented on a diff in the pull request:
https://github.com/apache/spark/pull/300#discussion_r11721049
--- Diff:
streaming/src/main/scala/org/apache/spark/streaming/receiver/NetworkReceiver.scala
---
@@ -0,0 +1,209 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.streaming.receiver
+
+import java.nio.ByteBuffer
+
+import scala.collection.mutable.ArrayBuffer
+
+import org.apache.spark.storage.StorageLevel
+
+/**
+ * Abstract class of a receiver that can be run on worker nodes to receive
external data. A
+ * custom receiver can be defined by defining the functions onStart() and
onStop(). onStart()
+ * should define the setup steps necessary to start receiving data,
+ * and onStop() should define the cleanup steps necessary to stop
receiving data. A custom
+ * receiver would look something like this.
+ *
+ * class MyReceiver(storageLevel) extends
NetworkReceiver[String](storageLevel) {
+ * def onStart() {
+ * // Setup stuff (start threads, open sockets, etc.) to start
receiving data.
+ * // Must start new thread to receive data, as onStart() must be
non-blocking.
+ *
+ * // Call store(...) in those threads to store received data into
Spark's memory.
+ *
+ * // Call stop(...), restart() or reportError(...) on any thread
based on how
+ * // different errors should be handled.
+ *
+ * // See corresponding method documentation for more details.
+ * }
+ *
+ * def onStop() {
+ * // Cleanup stuff (stop threads, close sockets, etc.) to stop
receiving data.
+ * }
+ * }
+ */
+abstract class NetworkReceiver[T](val storageLevel: StorageLevel) extends
Serializable {
--- End diff --
Since you are doing a refactoring here, is there any reason not to just
call this `Receiver` instead of `NetworkReceiver`? I always found this a bit
strange. In Spark most components communicate somehow over the network, but we
don't call them e.g. `NetworkBlockManager`, `NetworkExecutor`, etc...
Also since this is a very general interface, there is no reason someone
couldn't build one of these that e.g. read data from a filesystem.
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