diff --git a/core/src/main/scala/spark/SparkEnv.scala b/core/src/main/scala/spark/SparkEnv.scala index be1a04d619c1b2a53682d56d38a2bd1d2e30b59f..5691e24c320f678e3ce23d79cc70ba3ddb7aede8 100644 --- a/core/src/main/scala/spark/SparkEnv.scala +++ b/core/src/main/scala/spark/SparkEnv.scala @@ -1,5 +1,8 @@ package spark +import collection.mutable +import serializer.Serializer + import akka.actor.{Actor, ActorRef, Props, ActorSystemImpl, ActorSystem} import akka.remote.RemoteActorRefProvider @@ -9,6 +12,7 @@ import spark.storage.BlockManagerMaster import spark.network.ConnectionManager import spark.serializer.{Serializer, SerializerManager} import spark.util.AkkaUtils +import spark.api.python.PythonWorker /** @@ -37,6 +41,8 @@ class SparkEnv ( // If executorId is NOT found, return defaultHostPort var executorIdToHostPort: Option[(String, String) => String]) { + private val pythonWorkers = mutable.HashMap[(String, Map[String, String]), PythonWorker]() + def stop() { httpFileServer.stop() mapOutputTracker.stop() @@ -50,6 +56,11 @@ class SparkEnv ( actorSystem.awaitTermination() } + def getPythonWorker(pythonExec: String, envVars: Map[String, String]): PythonWorker = { + synchronized { + pythonWorkers.getOrElseUpdate((pythonExec, envVars), new PythonWorker(pythonExec, envVars)) + } + } def resolveExecutorIdToHostPort(executorId: String, defaultHostPort: String): String = { val env = SparkEnv.get diff --git a/core/src/main/scala/spark/api/python/PythonRDD.scala b/core/src/main/scala/spark/api/python/PythonRDD.scala index e9978d713fe4a6b4bdeac5f0ced1e3000035f808..e5acc54c016aa319e38f6360fb3fdd116c779642 100644 --- a/core/src/main/scala/spark/api/python/PythonRDD.scala +++ b/core/src/main/scala/spark/api/python/PythonRDD.scala @@ -2,10 +2,9 @@ package spark.api.python import java.io._ import java.net._ -import java.util.{List => JList, ArrayList => JArrayList, Collections} +import java.util.{List => JList, ArrayList => JArrayList, Map => JMap, Collections} import scala.collection.JavaConversions._ -import scala.io.Source import spark.api.java.{JavaSparkContext, JavaPairRDD, JavaRDD} import spark.broadcast.Broadcast @@ -16,7 +15,7 @@ import spark.rdd.PipedRDD private[spark] class PythonRDD[T: ClassManifest]( parent: RDD[T], command: Seq[String], - envVars: java.util.Map[String, String], + envVars: JMap[String, String], preservePartitoning: Boolean, pythonExec: String, broadcastVars: JList[Broadcast[Array[Byte]]], @@ -25,7 +24,7 @@ private[spark] class PythonRDD[T: ClassManifest]( // Similar to Runtime.exec(), if we are given a single string, split it into words // using a standard StringTokenizer (i.e. by spaces) - def this(parent: RDD[T], command: String, envVars: java.util.Map[String, String], + def this(parent: RDD[T], command: String, envVars: JMap[String, String], preservePartitoning: Boolean, pythonExec: String, broadcastVars: JList[Broadcast[Array[Byte]]], accumulator: Accumulator[JList[Array[Byte]]]) = @@ -36,36 +35,18 @@ private[spark] class PythonRDD[T: ClassManifest]( override val partitioner = if (preservePartitoning) parent.partitioner else None - override def compute(split: Partition, context: TaskContext): Iterator[Array[Byte]] = { - val SPARK_HOME = new ProcessBuilder().environment().get("SPARK_HOME") - - val pb = new ProcessBuilder(Seq(pythonExec, SPARK_HOME + "/python/pyspark/worker.py")) - // Add the environmental variables to the process. - val currentEnvVars = pb.environment() - - for ((variable, value) <- envVars) { - currentEnvVars.put(variable, value) - } + override def compute(split: Partition, context: TaskContext): Iterator[Array[Byte]] = { val startTime = System.currentTimeMillis - val proc = pb.start() + val worker = SparkEnv.get.getPythonWorker(pythonExec, envVars.toMap).create val env = SparkEnv.get - // Start a thread to print the process's stderr to ours - new Thread("stderr reader for " + pythonExec) { - override def run() { - for (line <- Source.fromInputStream(proc.getErrorStream).getLines) { - System.err.println(line) - } - } - }.start() - // Start a thread to feed the process input from our parent's iterator new Thread("stdin writer for " + pythonExec) { override def run() { SparkEnv.set(env) - val out = new PrintWriter(proc.getOutputStream) - val dOut = new DataOutputStream(proc.getOutputStream) + val out = new PrintWriter(worker.getOutputStream) + val dOut = new DataOutputStream(worker.getOutputStream) // Partition index dOut.writeInt(split.index) // sparkFilesDir @@ -89,16 +70,21 @@ private[spark] class PythonRDD[T: ClassManifest]( } dOut.flush() out.flush() - proc.getOutputStream.close() + worker.shutdownOutput() } }.start() // Return an iterator that read lines from the process's stdout - val stream = new DataInputStream(proc.getInputStream) + val stream = new DataInputStream(worker.getInputStream) return new Iterator[Array[Byte]] { def next(): Array[Byte] = { val obj = _nextObj - _nextObj = read() + if (hasNext) { + // FIXME: can deadlock if worker is waiting for us to + // respond to current message (currently irrelevant because + // output is shutdown before we read any input) + _nextObj = read() + } obj } @@ -110,7 +96,7 @@ private[spark] class PythonRDD[T: ClassManifest]( stream.readFully(obj) obj case -3 => - // Timing data from child + // Timing data from worker val bootTime = stream.readLong() val initTime = stream.readLong() val finishTime = stream.readLong() @@ -127,23 +113,21 @@ private[spark] class PythonRDD[T: ClassManifest]( stream.readFully(obj) throw new PythonException(new String(obj)) case -1 => - // We've finished the data section of the output, but we can still read some - // accumulator updates; let's do that, breaking when we get EOFException - while (true) { - val len2 = stream.readInt() + // We've finished the data section of the output, but we can still + // read some accumulator updates; let's do that, breaking when we + // get a negative length record. + var len2 = stream.readInt + while (len2 >= 0) { val update = new Array[Byte](len2) stream.readFully(update) accumulator += Collections.singletonList(update) + len2 = stream.readInt } new Array[Byte](0) } } catch { case eof: EOFException => { - val exitStatus = proc.waitFor() - if (exitStatus != 0) { - throw new Exception("Subprocess exited with status " + exitStatus) - } - new Array[Byte](0) + throw new SparkException("Python worker exited unexpectedly (crashed)", eof) } case e => throw e } @@ -171,7 +155,7 @@ private class PairwiseRDD(prev: RDD[Array[Byte]]) extends override def compute(split: Partition, context: TaskContext) = prev.iterator(split, context).grouped(2).map { case Seq(a, b) => (a, b) - case x => throw new Exception("PairwiseRDD: unexpected value: " + x) + case x => throw new SparkException("PairwiseRDD: unexpected value: " + x) } val asJavaPairRDD : JavaPairRDD[Array[Byte], Array[Byte]] = JavaPairRDD.fromRDD(this) } @@ -227,7 +211,7 @@ private[spark] object PythonRDD { dOut.write(s) dOut.writeByte(Pickle.STOP) } else { - throw new Exception("Unexpected RDD type") + throw new SparkException("Unexpected RDD type") } } diff --git a/core/src/main/scala/spark/api/python/PythonWorker.scala b/core/src/main/scala/spark/api/python/PythonWorker.scala new file mode 100644 index 0000000000000000000000000000000000000000..8ee3c6884f98f0998bd44a5ad43042f79c00f073 --- /dev/null +++ b/core/src/main/scala/spark/api/python/PythonWorker.scala @@ -0,0 +1,89 @@ +package spark.api.python + +import java.io.DataInputStream +import java.net.{Socket, SocketException, InetAddress} + +import scala.collection.JavaConversions._ + +import spark._ + +private[spark] class PythonWorker(pythonExec: String, envVars: Map[String, String]) + extends Logging { + var daemon: Process = null + val daemonHost = InetAddress.getByAddress(Array(127, 0, 0, 1)) + var daemonPort: Int = 0 + + def create(): 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 + } + } + } + + 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) + daemon = pb.start() + daemonPort = new DataInputStream(daemon.getInputStream).readInt + + // Redirect the stderr to ours + new Thread("stderr reader for " + pythonExec) { + override def run() { + // FIXME HACK: We copy the stream on the level of bytes to + // attempt to dodge encoding problems. + val in = daemon.getErrorStream + var 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 + } + } +} diff --git a/python/pyspark/daemon.py b/python/pyspark/daemon.py new file mode 100644 index 0000000000000000000000000000000000000000..642f30b2b9644aff7f105230f57cb56a9639bc30 --- /dev/null +++ b/python/pyspark/daemon.py @@ -0,0 +1,109 @@ +import os +import sys +import multiprocessing +from errno import EINTR, ECHILD +from socket import socket, AF_INET, SOCK_STREAM, SOMAXCONN +from signal import signal, SIGHUP, SIGTERM, SIGCHLD, SIG_DFL, SIG_IGN +from pyspark.worker import main as worker_main +from pyspark.serializers import write_int + +try: + POOLSIZE = multiprocessing.cpu_count() +except NotImplementedError: + POOLSIZE = 4 + +should_exit = False + + +def worker(listen_sock): + # Redirect stdout to stderr + os.dup2(2, 1) + + # Manager sends SIGHUP to request termination of workers in the pool + def handle_sighup(signum, frame): + global should_exit + should_exit = True + signal(SIGHUP, handle_sighup) + + while not should_exit: + # Wait until a client arrives or we have to exit + sock = None + while not should_exit and sock is None: + try: + sock, addr = listen_sock.accept() + except EnvironmentError as err: + if err.errno != EINTR: + raise + + if sock is not None: + # Fork a child to handle the client + if os.fork() == 0: + # Leave the worker pool + signal(SIGHUP, SIG_DFL) + listen_sock.close() + # Handle the client then exit + sockfile = sock.makefile() + worker_main(sockfile, sockfile) + sockfile.close() + sock.close() + os._exit(0) + else: + sock.close() + + assert should_exit + os._exit(0) + + +def manager(): + # Create a new process group to corral our children + os.setpgid(0, 0) + + # Create a listening socket on the AF_INET loopback interface + listen_sock = socket(AF_INET, SOCK_STREAM) + listen_sock.bind(('127.0.0.1', 0)) + listen_sock.listen(max(1024, 2 * POOLSIZE, SOMAXCONN)) + listen_host, listen_port = listen_sock.getsockname() + write_int(listen_port, sys.stdout) + + # Launch initial worker pool + for idx in range(POOLSIZE): + if os.fork() == 0: + worker(listen_sock) + raise RuntimeError("worker() unexpectedly returned") + listen_sock.close() + + def shutdown(): + global should_exit + os.kill(0, SIGHUP) + should_exit = True + + # Gracefully exit on SIGTERM, don't die on SIGHUP + signal(SIGTERM, lambda signum, frame: shutdown()) + signal(SIGHUP, SIG_IGN) + + # Cleanup zombie children + def handle_sigchld(signum, frame): + try: + pid, status = os.waitpid(0, os.WNOHANG) + if (pid, status) != (0, 0) and not should_exit: + raise RuntimeError("pool member crashed: %s, %s" % (pid, status)) + except EnvironmentError as err: + if err.errno not in (ECHILD, EINTR): + raise + signal(SIGCHLD, handle_sigchld) + + # Initialization complete + sys.stdout.close() + while not should_exit: + try: + # Spark tells us to exit by closing stdin + if sys.stdin.read() == '': + shutdown() + except EnvironmentError as err: + if err.errno != EINTR: + shutdown() + raise + + +if __name__ == '__main__': + manager() diff --git a/python/pyspark/worker.py b/python/pyspark/worker.py index 4c33ae49dcc95a4bf0b2aab3d5854653ea9882eb..94d612ea6ed926c42f44f0c57f91078b3aa2afc3 100644 --- a/python/pyspark/worker.py +++ b/python/pyspark/worker.py @@ -1,10 +1,9 @@ """ Worker that receives input from Piped RDD. """ -import time -preboot_time = time.time() import os import sys +import time import traceback from base64 import standard_b64decode # CloudPickler needs to be imported so that depicklers are registered using the @@ -17,57 +16,55 @@ from pyspark.serializers import write_with_length, read_with_length, write_int, read_long, write_long, read_int, dump_pickle, load_pickle, read_from_pickle_file -# Redirect stdout to stderr so that users must return values from functions. -old_stdout = os.fdopen(os.dup(1), 'w') -os.dup2(2, 1) - - -def load_obj(): - return load_pickle(standard_b64decode(sys.stdin.readline().strip())) +def load_obj(infile): + return load_pickle(standard_b64decode(infile.readline().strip())) -def report_times(preboot, boot, init, finish): - write_int(-3, old_stdout) - write_long(1000 * preboot, old_stdout) - write_long(1000 * boot, old_stdout) - write_long(1000 * init, old_stdout) - write_long(1000 * finish, old_stdout) +def report_times(outfile, boot, init, finish): + write_int(-3, outfile) + write_long(1000 * boot, outfile) + write_long(1000 * init, outfile) + write_long(1000 * finish, outfile) -def main(): +def main(infile, outfile): boot_time = time.time() - split_index = read_int(sys.stdin) - spark_files_dir = load_pickle(read_with_length(sys.stdin)) + split_index = read_int(infile) + spark_files_dir = load_pickle(read_with_length(infile)) SparkFiles._root_directory = spark_files_dir SparkFiles._is_running_on_worker = True sys.path.append(spark_files_dir) - num_broadcast_variables = read_int(sys.stdin) + num_broadcast_variables = read_int(infile) for _ in range(num_broadcast_variables): - bid = read_long(sys.stdin) - value = read_with_length(sys.stdin) + bid = read_long(infile) + value = read_with_length(infile) _broadcastRegistry[bid] = Broadcast(bid, load_pickle(value)) - func = load_obj() - bypassSerializer = load_obj() + func = load_obj(infile) + bypassSerializer = load_obj(infile) if bypassSerializer: dumps = lambda x: x else: dumps = dump_pickle init_time = time.time() - iterator = read_from_pickle_file(sys.stdin) + iterator = read_from_pickle_file(infile) try: for obj in func(split_index, iterator): - write_with_length(dumps(obj), old_stdout) + write_with_length(dumps(obj), outfile) except Exception as e: - write_int(-2, old_stdout) - write_with_length(traceback.format_exc(), old_stdout) - sys.exit(-1) + write_int(-2, outfile) + write_with_length(traceback.format_exc(), outfile) + raise finish_time = time.time() - report_times(preboot_time, boot_time, init_time, finish_time) + report_times(outfile, boot_time, init_time, finish_time) # Mark the beginning of the accumulators section of the output - write_int(-1, old_stdout) + write_int(-1, outfile) for aid, accum in _accumulatorRegistry.items(): - write_with_length(dump_pickle((aid, accum._value)), old_stdout) + write_with_length(dump_pickle((aid, accum._value)), outfile) + write_int(-1, outfile) if __name__ == '__main__': - main() + # Redirect stdout to stderr so that users must return values from functions. + old_stdout = os.fdopen(os.dup(1), 'w') + os.dup2(2, 1) + main(sys.stdin, old_stdout)