Fix performance bug with new Python code not using buffered streams

core/src/main/scala/spark/SparkEnv.scala

@@ -59,7 +59,8 @@ class SparkEnv (
 
   def createPythonWorker(pythonExec: String, envVars: Map[String, String]): java.net.Socket = {
     synchronized {
-      pythonWorkers.getOrElseUpdate((pythonExec, envVars), new PythonWorkerFactory(pythonExec, envVars)).create()
+      val key = (pythonExec, envVars)
+      pythonWorkers.getOrElseUpdate(key, new PythonWorkerFactory(pythonExec, envVars)).create()
     }
   }
 

core/src/main/scala/spark/api/python/PythonRDD.scala

@@ -45,37 +45,38 @@ private[spark] class PythonRDD[T: ClassManifest](
     new Thread("stdin writer for " + pythonExec) {
       override def run() {
         SparkEnv.set(env)
-        val out = new PrintWriter(worker.getOutputStream)
-        val dOut = new DataOutputStream(worker.getOutputStream)
+        val stream = new BufferedOutputStream(worker.getOutputStream)
+        val dataOut = new DataOutputStream(stream)
+        val printOut = new PrintWriter(stream)
         // Partition index
-        dOut.writeInt(split.index)
+        dataOut.writeInt(split.index)
         // sparkFilesDir
-        PythonRDD.writeAsPickle(SparkFiles.getRootDirectory, dOut)
+        PythonRDD.writeAsPickle(SparkFiles.getRootDirectory, dataOut)
         // Broadcast variables
-        dOut.writeInt(broadcastVars.length)
+        dataOut.writeInt(broadcastVars.length)
         for (broadcast <- broadcastVars) {
-          dOut.writeLong(broadcast.id)
-          dOut.writeInt(broadcast.value.length)
-          dOut.write(broadcast.value)
-          dOut.flush()
+          dataOut.writeLong(broadcast.id)
+          dataOut.writeInt(broadcast.value.length)
+          dataOut.write(broadcast.value)
         }
+        dataOut.flush()
         // Serialized user code
         for (elem <- command) {
-          out.println(elem)
+          printOut.println(elem)
         }
-        out.flush()
+        printOut.flush()
         // Data values
         for (elem <- parent.iterator(split, context)) {
-          PythonRDD.writeAsPickle(elem, dOut)
+          PythonRDD.writeAsPickle(elem, dataOut)
         }
-        dOut.flush()
-        out.flush()
+        dataOut.flush()
+        printOut.flush()
         worker.shutdownOutput()
       }
     }.start()
 
     // Return an iterator that read lines from the process's stdout
-    val stream = new DataInputStream(worker.getInputStream)
+    val stream = new DataInputStream(new BufferedInputStream(worker.getInputStream))
     return new Iterator[Array[Byte]] {
       def next(): Array[Byte] = {
         val obj = _nextObj
@@ -288,7 +289,7 @@ class PythonAccumulatorParam(@transient serverHost: String, serverPort: Int)
       // This happens on the master, where we pass the updates to Python through a socket
       val socket = new Socket(serverHost, serverPort)
       val in = socket.getInputStream
-      val out = new DataOutputStream(socket.getOutputStream)
+      val out = new DataOutputStream(new BufferedOutputStream(socket.getOutputStream))
       out.writeInt(val2.size)
       for (array <- val2) {
         out.writeInt(array.length)