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/*
* 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.api.python
import java.io.{OutputStreamWriter, File, DataInputStream, IOException}
import java.net.{ServerSocket, Socket, SocketException, InetAddress}
import scala.collection.JavaConversions._
import org.apache.spark._
private[spark] class PythonWorkerFactory(pythonExec: String, envVars: Map[String, String])
extends Logging {
// Because forking processes from Java is expensive, we prefer to launch a single Python daemon
// (pyspark/daemon.py) and tell it to fork new workers for our tasks. This daemon currently
// only works on UNIX-based systems now because it uses signals for child management, so we can
// also fall back to launching workers (pyspark/worker.py) directly.
val useDaemon = !System.getProperty("os.name").startsWith("Windows")
var daemon: Process = null
val daemonHost = InetAddress.getByAddress(Array(127, 0, 0, 1))
var daemonPort: Int = 0
def create(): Socket = {
if (useDaemon) {
createThroughDaemon()
} else {
createSimpleWorker()
}
}
/**
* Connect to a worker launched through pyspark/daemon.py, which forks python processes itself
* to avoid the high cost of forking from Java. This currently only works on UNIX-based systems.
*/
private def createThroughDaemon(): Socket = {
synchronized {
// Start the daemon if it hasn't been started
startDaemon()
// Attempt to connect, restart and retry once if it fails
try {
new Socket(daemonHost, daemonPort)
} catch {
case exc: SocketException => {
logWarning("Python daemon unexpectedly quit, attempting to restart")
stopDaemon()
startDaemon()
new Socket(daemonHost, daemonPort)
}
case e => throw e
}
}
}
/**
* Launch a worker by executing worker.py directly and telling it to connect to us.
*/
private def createSimpleWorker(): Socket = {
var serverSocket: ServerSocket = null
try {
serverSocket = new ServerSocket(0, 1, InetAddress.getByAddress(Array(127, 0, 0, 1)))
// Create and start the worker
val sparkHome = new ProcessBuilder().environment().get("SPARK_HOME")
val pb = new ProcessBuilder(Seq(pythonExec, sparkHome + "/python/pyspark/worker.py"))
val workerEnv = pb.environment()
workerEnv.putAll(envVars)
val pythonPath = sparkHome + "/python/" + File.pathSeparator + workerEnv.get("PYTHONPATH")
workerEnv.put("PYTHONPATH", pythonPath)
val worker = pb.start()
// Redirect the worker's stderr to ours
new Thread("stderr reader for " + pythonExec) {
setDaemon(true)
override def run() {
scala.util.control.Exception.ignoring(classOf[IOException]) {
// FIXME: We copy the stream on the level of bytes to avoid encoding problems.
val in = worker.getErrorStream
val buf = new Array[Byte](1024)
var len = in.read(buf)
while (len != -1) {
System.err.write(buf, 0, len)
len = in.read(buf)
}
}
}
}.start()
// Redirect worker's stdout to our stderr
new Thread("stdout reader for " + pythonExec) {
setDaemon(true)
override def run() {
scala.util.control.Exception.ignoring(classOf[IOException]) {
// FIXME: We copy the stream on the level of bytes to avoid encoding problems.
val in = worker.getInputStream
val buf = new Array[Byte](1024)
var len = in.read(buf)
while (len != -1) {
System.err.write(buf, 0, len)
len = in.read(buf)
}
}
}
}.start()
// Tell the worker our port
val out = new OutputStreamWriter(worker.getOutputStream)
out.write(serverSocket.getLocalPort + "\n")
out.flush()
// Wait for it to connect to our socket
serverSocket.setSoTimeout(10000)
try {
return serverSocket.accept()
} catch {
case e: Exception =>
throw new SparkException("Python worker did not connect back in time", e)
}
} finally {
if (serverSocket != null) {
serverSocket.close()
}
}
null
}
def stop() {
stopDaemon()
}
private def startDaemon() {
synchronized {
// Is it already running?
if (daemon != null) {
return
}
try {
// Create and start the daemon
val sparkHome = new ProcessBuilder().environment().get("SPARK_HOME")
val pb = new ProcessBuilder(Seq(pythonExec, sparkHome + "/python/pyspark/daemon.py"))
val workerEnv = pb.environment()
workerEnv.putAll(envVars)
val pythonPath = sparkHome + "/python/" + File.pathSeparator + workerEnv.get("PYTHONPATH")
workerEnv.put("PYTHONPATH", pythonPath)
daemon = pb.start()
// Redirect the stderr to ours
new Thread("stderr reader for " + pythonExec) {
setDaemon(true)
override def run() {
scala.util.control.Exception.ignoring(classOf[IOException]) {
// FIXME: We copy the stream on the level of bytes to avoid encoding problems.
val in = daemon.getErrorStream
val buf = new Array[Byte](1024)
var len = in.read(buf)
while (len != -1) {
System.err.write(buf, 0, len)
len = in.read(buf)
}
}
}
}.start()
val in = new DataInputStream(daemon.getInputStream)
daemonPort = in.readInt()
// Redirect further stdout output to our stderr
new Thread("stdout reader for " + pythonExec) {
setDaemon(true)
override def run() {
scala.util.control.Exception.ignoring(classOf[IOException]) {
// FIXME: We copy the stream on the level of bytes to avoid encoding problems.
val buf = new Array[Byte](1024)
var len = in.read(buf)
while (len != -1) {
System.err.write(buf, 0, len)
len = in.read(buf)
}
}
}
}.start()
} catch {
case e => {
stopDaemon()
throw e
}
}
// Important: don't close daemon's stdin (daemon.getOutputStream) so it can correctly
// detect our disappearance.
}
}
private def stopDaemon() {
synchronized {
// Request shutdown of existing daemon by sending SIGTERM
if (daemon != null) {
daemon.destroy()
}
daemon = null
daemonPort = 0
}
}
}
