worker: allow waitforworkers to be non-blocking

This patch adds a boolean flag to waitforworkers and makes it non-blocking
if set to True.

This is to make it possible that we can reap our workers while keep other
unrelated children untouched, after receiving SIGCHLD.

mercurial/worker.py

@@ -1,187 +1,189 b''
 # worker.py - master-slave parallelism support
 #
 # Copyright 2013 Facebook, Inc.
 #
 # This software may be used and distributed according to the terms of the
 # GNU General Public License version 2 or any later version.
 
 from __future__ import absolute_import
 
 import errno
 import os
 import signal
 import sys
 import threading
 
 from .i18n import _
 from . import (
     error,
     util,
 )
 
 def countcpus():
     '''try to count the number of CPUs on the system'''
 
     # posix
     try:
         n = int(os.sysconf('SC_NPROCESSORS_ONLN'))
         if n > 0:
             return n
     except (AttributeError, ValueError):
         pass
 
     # windows
     try:
         n = int(os.environ['NUMBER_OF_PROCESSORS'])
         if n > 0:
             return n
     except (KeyError, ValueError):
         pass
 
     return 1
 
 def _numworkers(ui):
     s = ui.config('worker', 'numcpus')
     if s:
         try:
             n = int(s)
             if n >= 1:
                 return n
         except ValueError:
             raise error.Abort(_('number of cpus must be an integer'))
     return min(max(countcpus(), 4), 32)
 
 if os.name == 'posix':
     _startupcost = 0.01
 else:
     _startupcost = 1e30
 
 def worthwhile(ui, costperop, nops):
     '''try to determine whether the benefit of multiple processes can
     outweigh the cost of starting them'''
     linear = costperop * nops
     workers = _numworkers(ui)
     benefit = linear - (_startupcost * workers + linear / workers)
     return benefit >= 0.15
 
 def worker(ui, costperarg, func, staticargs, args):
     '''run a function, possibly in parallel in multiple worker
     processes.
 
     returns a progress iterator
 
     costperarg - cost of a single task
 
     func - function to run
 
     staticargs - arguments to pass to every invocation of the function
 
     args - arguments to split into chunks, to pass to individual
     workers
     '''
     if worthwhile(ui, costperarg, len(args)):
         return _platformworker(ui, func, staticargs, args)
     return func(*staticargs + (args,))
 
 def _posixworker(ui, func, staticargs, args):
     rfd, wfd = os.pipe()
     workers = _numworkers(ui)
     oldhandler = signal.getsignal(signal.SIGINT)
     signal.signal(signal.SIGINT, signal.SIG_IGN)
     pids, problem = [], [0]
     def killworkers():
         # if one worker bails, there's no good reason to wait for the rest
         for p in pids:
             try:
                 os.kill(p, signal.SIGTERM)
             except OSError as err:
                 if err.errno != errno.ESRCH:
                     raise
-    def waitforworkers():
+    def waitforworkers(blocking=True):
         for pid in pids:
-            st = _exitstatus(os.waitpid(pid, 0)[1])
+            p, st = os.waitpid(pid, 0 if blocking else os.WNOHANG)
+            if p:
+                st = _exitstatus(st)
             if st and not problem[0]:
                 problem[0] = st
                 killworkers()
     for pargs in partition(args, workers):
         pid = os.fork()
         if pid == 0:
             signal.signal(signal.SIGINT, oldhandler)
             try:
                 os.close(rfd)
                 for i, item in func(*(staticargs + (pargs,))):
                     os.write(wfd, '%d %s\n' % (i, item))
                 os._exit(0)
             except KeyboardInterrupt:
                 os._exit(255)
                 # other exceptions are allowed to propagate, we rely
                 # on lock.py's pid checks to avoid release callbacks
         pids.append(pid)
     pids.reverse()
     os.close(wfd)
     fp = os.fdopen(rfd, 'rb', 0)
     t = threading.Thread(target=waitforworkers)
     t.start()
     def cleanup():
         signal.signal(signal.SIGINT, oldhandler)
         t.join()
         status = problem[0]
         if status:
             if status < 0:
                 os.kill(os.getpid(), -status)
             sys.exit(status)
     try:
         for line in util.iterfile(fp):
             l = line.split(' ', 1)
             yield int(l[0]), l[1][:-1]
     except: # re-raises
         killworkers()
         cleanup()
         raise
     cleanup()
 
 def _posixexitstatus(code):
     '''convert a posix exit status into the same form returned by
     os.spawnv
 
     returns None if the process was stopped instead of exiting'''
     if os.WIFEXITED(code):
         return os.WEXITSTATUS(code)
     elif os.WIFSIGNALED(code):
         return -os.WTERMSIG(code)
 
 if os.name != 'nt':
     _platformworker = _posixworker
     _exitstatus = _posixexitstatus
 
 def partition(lst, nslices):
     '''partition a list into N slices of roughly equal size
 
     The current strategy takes every Nth element from the input. If
     we ever write workers that need to preserve grouping in input
     we should consider allowing callers to specify a partition strategy.
 
     mpm is not a fan of this partitioning strategy when files are involved.
     In his words:
 
         Single-threaded Mercurial makes a point of creating and visiting
         files in a fixed order (alphabetical). When creating files in order,
         a typical filesystem is likely to allocate them on nearby regions on
         disk. Thus, when revisiting in the same order, locality is maximized
         and various forms of OS and disk-level caching and read-ahead get a
         chance to work.
 
         This effect can be quite significant on spinning disks. I discovered it
         circa Mercurial v0.4 when revlogs were named by hashes of filenames.
         Tarring a repo and copying it to another disk effectively randomized
         the revlog ordering on disk by sorting the revlogs by hash and suddenly
         performance of my kernel checkout benchmark dropped by ~10x because the
         "working set" of sectors visited no longer fit in the drive's cache and
         the workload switched from streaming to random I/O.
 
         What we should really be doing is have workers read filenames from a
         ordered queue. This preserves locality and also keeps any worker from
         getting more than one file out of balance.
     '''
     for i in range(nslices):
         yield lst[i::nslices]