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new b3c11ef8e090 Revert "Revert "[SPARK-45302][PYTHON] Remove PID
communication between Python workers when no demon is used""
b3c11ef8e090 is described below
commit b3c11ef8e09082e0091ed9f459b432208a3ccd43
Author: Hyukjin Kwon <gurwls...@apache.org>
AuthorDate: Wed Apr 24 09:54:41 2024 +0900
Revert "Revert "[SPARK-45302][PYTHON] Remove PID communication between
Python workers when no demon is used""
This reverts commit e8f529bb89a6edfcedbca7a08993e6e8d9612009.
---
core/src/main/scala/org/apache/spark/SparkEnv.scala | 4 ++--
.../main/scala/org/apache/spark/api/python/PythonRunner.scala | 10 +++++-----
.../org/apache/spark/api/python/PythonWorkerFactory.scala | 11 +++++------
python/pyspark/daemon.py | 4 ++--
.../sql/connect/streaming/worker/foreach_batch_worker.py | 2 --
.../pyspark/sql/connect/streaming/worker/listener_worker.py | 2 --
python/pyspark/sql/worker/analyze_udtf.py | 3 ---
python/pyspark/worker.py | 3 ---
.../apache/spark/sql/execution/python/PythonArrowOutput.scala | 2 +-
.../apache/spark/sql/execution/python/PythonUDFRunner.scala | 2 +-
10 files changed, 16 insertions(+), 27 deletions(-)
diff --git a/core/src/main/scala/org/apache/spark/SparkEnv.scala
b/core/src/main/scala/org/apache/spark/SparkEnv.scala
index 34c7d955fedd..50d0358004d4 100644
--- a/core/src/main/scala/org/apache/spark/SparkEnv.scala
+++ b/core/src/main/scala/org/apache/spark/SparkEnv.scala
@@ -142,7 +142,7 @@ class SparkEnv (
workerModule: String,
daemonModule: String,
envVars: Map[String, String],
- useDaemon: Boolean): (PythonWorker, Option[Int]) = {
+ useDaemon: Boolean): (PythonWorker, Option[Long]) = {
synchronized {
val key = PythonWorkersKey(pythonExec, workerModule, daemonModule,
envVars)
val workerFactory = pythonWorkers.getOrElseUpdate(key, new
PythonWorkerFactory(
@@ -161,7 +161,7 @@ class SparkEnv (
pythonExec: String,
workerModule: String,
envVars: Map[String, String],
- useDaemon: Boolean): (PythonWorker, Option[Int]) = {
+ useDaemon: Boolean): (PythonWorker, Option[Long]) = {
createPythonWorker(
pythonExec, workerModule, PythonWorkerFactory.defaultDaemonModule,
envVars, useDaemon)
}
diff --git a/core/src/main/scala/org/apache/spark/api/python/PythonRunner.scala
b/core/src/main/scala/org/apache/spark/api/python/PythonRunner.scala
index 7ff782db210d..17cb0c5a55dd 100644
--- a/core/src/main/scala/org/apache/spark/api/python/PythonRunner.scala
+++ b/core/src/main/scala/org/apache/spark/api/python/PythonRunner.scala
@@ -88,7 +88,7 @@ private object BasePythonRunner {
private lazy val faultHandlerLogDir = Utils.createTempDir(namePrefix =
"faulthandler")
- private def faultHandlerLogPath(pid: Int): Path = {
+ private def faultHandlerLogPath(pid: Long): Path = {
new File(faultHandlerLogDir, pid.toString).toPath
}
}
@@ -204,7 +204,7 @@ private[spark] abstract class BasePythonRunner[IN, OUT](
envVars.put("SPARK_JOB_ARTIFACT_UUID",
jobArtifactUUID.getOrElse("default"))
- val (worker: PythonWorker, pid: Option[Int]) = env.createPythonWorker(
+ val (worker: PythonWorker, pid: Option[Long]) = env.createPythonWorker(
pythonExec, workerModule, daemonModule, envVars.asScala.toMap)
// Whether is the worker released into idle pool or closed. When any codes
try to release or
// close a worker, they should use `releasedOrClosed.compareAndSet` to
flip the state to make
@@ -257,7 +257,7 @@ private[spark] abstract class BasePythonRunner[IN, OUT](
startTime: Long,
env: SparkEnv,
worker: PythonWorker,
- pid: Option[Int],
+ pid: Option[Long],
releasedOrClosed: AtomicBoolean,
context: TaskContext): Iterator[OUT]
@@ -465,7 +465,7 @@ private[spark] abstract class BasePythonRunner[IN, OUT](
startTime: Long,
env: SparkEnv,
worker: PythonWorker,
- pid: Option[Int],
+ pid: Option[Long],
releasedOrClosed: AtomicBoolean,
context: TaskContext)
extends Iterator[OUT] {
@@ -842,7 +842,7 @@ private[spark] class PythonRunner(
startTime: Long,
env: SparkEnv,
worker: PythonWorker,
- pid: Option[Int],
+ pid: Option[Long],
releasedOrClosed: AtomicBoolean,
context: TaskContext): Iterator[Array[Byte]] = {
new ReaderIterator(
diff --git
a/core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala
b/core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala
index 875cf6bc2770..eb740b72987c 100644
--- a/core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala
+++ b/core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala
@@ -92,7 +92,7 @@ private[spark] class PythonWorkerFactory(
envVars.getOrElse("PYTHONPATH", ""),
sys.env.getOrElse("PYTHONPATH", ""))
- def create(): (PythonWorker, Option[Int]) = {
+ def create(): (PythonWorker, Option[Long]) = {
if (useDaemon) {
self.synchronized {
// Pull from idle workers until we one that is alive, otherwise create
a new one.
@@ -122,9 +122,9 @@ private[spark] class PythonWorkerFactory(
* processes itself to avoid the high cost of forking from Java. This
currently only works
* on UNIX-based systems.
*/
- private def createThroughDaemon(): (PythonWorker, Option[Int]) = {
+ private def createThroughDaemon(): (PythonWorker, Option[Long]) = {
- def createWorker(): (PythonWorker, Option[Int]) = {
+ def createWorker(): (PythonWorker, Option[Long]) = {
val socketChannel = SocketChannel.open(new InetSocketAddress(daemonHost,
daemonPort))
// These calls are blocking.
val pid = new
DataInputStream(Channels.newInputStream(socketChannel)).readInt()
@@ -165,7 +165,7 @@ private[spark] class PythonWorkerFactory(
/**
* Launch a worker by executing worker.py (by default) directly and telling
it to connect to us.
*/
- private[spark] def createSimpleWorker(blockingMode: Boolean): (PythonWorker,
Option[Int]) = {
+ private[spark] def createSimpleWorker(blockingMode: Boolean): (PythonWorker,
Option[Long]) = {
var serverSocketChannel: ServerSocketChannel = null
try {
serverSocketChannel = ServerSocketChannel.open()
@@ -209,8 +209,7 @@ private[spark] class PythonWorkerFactory(
"Timed out while waiting for the Python worker to connect back")
}
authHelper.authClient(socketChannel.socket())
- // TODO: When we drop JDK 8, we can just use workerProcess.pid()
- val pid = new
DataInputStream(Channels.newInputStream(socketChannel)).readInt()
+ val pid = workerProcess.toHandle.pid()
if (pid < 0) {
throw new IllegalStateException("Python failed to launch worker with
code " + pid)
}
diff --git a/python/pyspark/daemon.py b/python/pyspark/daemon.py
index bbbc495d053e..b0e06d13beda 100644
--- a/python/pyspark/daemon.py
+++ b/python/pyspark/daemon.py
@@ -28,7 +28,7 @@ from errno import EINTR, EAGAIN
from socket import AF_INET, AF_INET6, SOCK_STREAM, SOMAXCONN
from signal import SIGHUP, SIGTERM, SIGCHLD, SIG_DFL, SIG_IGN, SIGINT
-from pyspark.serializers import read_int, write_int, write_with_length,
UTF8Deserializer
+from pyspark.serializers import read_long, write_int, write_with_length,
UTF8Deserializer
if len(sys.argv) > 1:
import importlib
@@ -139,7 +139,7 @@ def manager():
if 0 in ready_fds:
try:
- worker_pid = read_int(stdin_bin)
+ worker_pid = read_long(stdin_bin)
except EOFError:
# Spark told us to exit by closing stdin
shutdown(0)
diff --git
a/python/pyspark/sql/connect/streaming/worker/foreach_batch_worker.py
b/python/pyspark/sql/connect/streaming/worker/foreach_batch_worker.py
index 0c92de6372b6..80cc69126916 100644
--- a/python/pyspark/sql/connect/streaming/worker/foreach_batch_worker.py
+++ b/python/pyspark/sql/connect/streaming/worker/foreach_batch_worker.py
@@ -96,6 +96,4 @@ if __name__ == "__main__":
(sock_file, sock) = local_connect_and_auth(java_port, auth_secret)
# There could be a long time between each micro batch.
sock.settimeout(None)
- write_int(os.getpid(), sock_file)
- sock_file.flush()
main(sock_file, sock_file)
diff --git a/python/pyspark/sql/connect/streaming/worker/listener_worker.py
b/python/pyspark/sql/connect/streaming/worker/listener_worker.py
index a7a5066ca0d7..3709e50ba026 100644
--- a/python/pyspark/sql/connect/streaming/worker/listener_worker.py
+++ b/python/pyspark/sql/connect/streaming/worker/listener_worker.py
@@ -110,6 +110,4 @@ if __name__ == "__main__":
(sock_file, sock) = local_connect_and_auth(java_port, auth_secret)
# There could be a long time between each listener event.
sock.settimeout(None)
- write_int(os.getpid(), sock_file)
- sock_file.flush()
main(sock_file, sock_file)
diff --git a/python/pyspark/sql/worker/analyze_udtf.py
b/python/pyspark/sql/worker/analyze_udtf.py
index 7dafb87c4221..d0a24363c0c1 100644
--- a/python/pyspark/sql/worker/analyze_udtf.py
+++ b/python/pyspark/sql/worker/analyze_udtf.py
@@ -264,7 +264,4 @@ if __name__ == "__main__":
java_port = int(os.environ["PYTHON_WORKER_FACTORY_PORT"])
auth_secret = os.environ["PYTHON_WORKER_FACTORY_SECRET"]
(sock_file, _) = local_connect_and_auth(java_port, auth_secret)
- # TODO: Remove the following two lines and use `Process.pid()` when we
drop JDK 8.
- write_int(os.getpid(), sock_file)
- sock_file.flush()
main(sock_file, sock_file)
diff --git a/python/pyspark/worker.py b/python/pyspark/worker.py
index e9c259e68a27..41f6c35bc445 100644
--- a/python/pyspark/worker.py
+++ b/python/pyspark/worker.py
@@ -1868,7 +1868,4 @@ if __name__ == "__main__":
java_port = int(os.environ["PYTHON_WORKER_FACTORY_PORT"])
auth_secret = os.environ["PYTHON_WORKER_FACTORY_SECRET"]
(sock_file, _) = local_connect_and_auth(java_port, auth_secret)
- # TODO: Remove the following two lines and use `Process.pid()` when we
drop JDK 8.
- write_int(os.getpid(), sock_file)
- sock_file.flush()
main(sock_file, sock_file)
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/execution/python/PythonArrowOutput.scala
b/sql/core/src/main/scala/org/apache/spark/sql/execution/python/PythonArrowOutput.scala
index e7d4aa9f0460..90922d89ad10 100644
---
a/sql/core/src/main/scala/org/apache/spark/sql/execution/python/PythonArrowOutput.scala
+++
b/sql/core/src/main/scala/org/apache/spark/sql/execution/python/PythonArrowOutput.scala
@@ -49,7 +49,7 @@ private[python] trait PythonArrowOutput[OUT <: AnyRef] {
self: BasePythonRunner[
startTime: Long,
env: SparkEnv,
worker: PythonWorker,
- pid: Option[Int],
+ pid: Option[Long],
releasedOrClosed: AtomicBoolean,
context: TaskContext): Iterator[OUT] = {
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/execution/python/PythonUDFRunner.scala
b/sql/core/src/main/scala/org/apache/spark/sql/execution/python/PythonUDFRunner.scala
index 87ff5a0ec433..bbe9fbfc748d 100644
---
a/sql/core/src/main/scala/org/apache/spark/sql/execution/python/PythonUDFRunner.scala
+++
b/sql/core/src/main/scala/org/apache/spark/sql/execution/python/PythonUDFRunner.scala
@@ -80,7 +80,7 @@ abstract class BasePythonUDFRunner(
startTime: Long,
env: SparkEnv,
worker: PythonWorker,
- pid: Option[Int],
+ pid: Option[Long],
releasedOrClosed: AtomicBoolean,
context: TaskContext): Iterator[Array[Byte]] = {
new ReaderIterator(
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