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Creates the distribution package of the RAPIDS plugin for Apache Spark
#
# 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.
#
import os
import signal
import select
import socket
import sys
import traceback
import time
import gc
from errno import EINTR, EAGAIN
from socket import AF_INET, SOCK_STREAM, SOMAXCONN
from signal import SIGHUP, SIGTERM, SIGCHLD, SIG_DFL, SIG_IGN
from pyspark.serializers import read_int, write_int
from pyspark.daemon import worker
from rapids.worker import initialize_gpu_mem
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.socket(AF_INET, SOCK_STREAM)
listen_sock.bind(('127.0.0.1', 0))
listen_sock.listen(max(1024, SOMAXCONN))
listen_host, listen_port = listen_sock.getsockname()
# re-open stdin/stdout in 'wb' mode
stdin_bin = os.fdopen(sys.stdin.fileno(), 'rb', 4)
stdout_bin = os.fdopen(sys.stdout.fileno(), 'wb', 4)
write_int(listen_port, stdout_bin)
stdout_bin.flush()
def shutdown(code):
signal.signal(SIGTERM, SIG_DFL)
# Send SIGHUP to notify workers of shutdown
os.kill(0, SIGHUP)
sys.exit(code)
def handle_sigterm(*args):
shutdown(1)
signal.signal(SIGTERM, handle_sigterm) # Gracefully exit on SIGTERM
signal.signal(SIGHUP, SIG_IGN) # Don't die on SIGHUP
signal.signal(SIGCHLD, SIG_IGN)
reuse = os.environ.get("SPARK_REUSE_WORKER")
# Initialization complete
try:
while True:
try:
ready_fds = select.select([0, listen_sock], [], [], 1)[0]
except select.error as ex:
if ex[0] == EINTR:
continue
else:
raise
if 0 in ready_fds:
try:
worker_pid = read_int(stdin_bin)
except EOFError:
# Spark told us to exit by closing stdin
shutdown(0)
try:
os.kill(worker_pid, signal.SIGKILL)
except OSError:
pass # process already died
if listen_sock in ready_fds:
try:
sock, _ = listen_sock.accept()
except OSError as e:
if e.errno == EINTR:
continue
raise
# Launch a worker process
try:
pid = os.fork()
except OSError as e:
if e.errno in (EAGAIN, EINTR):
time.sleep(1)
pid = os.fork() # error here will shutdown daemon
else:
outfile = sock.makefile(mode='wb')
write_int(e.errno, outfile) # Signal that the fork failed
outfile.flush()
outfile.close()
sock.close()
continue
if pid == 0:
# in child process
listen_sock.close()
# It should close the standard input in the child process so that
# Python native function executions stay intact.
#
# Note that if we just close the standard input (file descriptor 0),
# the lowest file descriptor (file descriptor 0) will be allocated,
# later when other file descriptors should happen to open.
#
# Therefore, here we redirects it to '/dev/null' by duplicating
# another file descriptor for '/dev/null' to the standard input (0).
# See SPARK-26175.
devnull = open(os.devnull, 'r')
os.dup2(devnull.fileno(), 0)
devnull.close()
try:
# GPU context setup
initialize_gpu_mem()
# Acknowledge that the fork was successful
outfile = sock.makefile(mode="wb")
write_int(os.getpid(), outfile)
outfile.flush()
outfile.close()
authenticated = False
while True:
code = worker(sock, authenticated)
if code == 0:
authenticated = True
if not reuse or code:
# wait for closing
try:
while sock.recv(1024):
pass
except Exception:
pass
break
gc.collect()
except:
traceback.print_exc()
os._exit(1)
else:
os._exit(0)
else:
sock.close()
finally:
shutdown(1)
if __name__ == '__main__':
manager()