annotate mercurial/worker.py @ 18709:9955fc5ee24b

worker: handle worker failures more aggressively We now wait for worker processes in a separate thread, so that we can spot failures in a timely way, wihout waiting for the progress pipe to drain. If a worker fails, we recover the pre-parallel-update behaviour of failing early by killing its peers before propagating the failure.
author Bryan O'Sullivan <bryano@fb.com>
date Wed, 20 Feb 2013 11:31:34 -0800
parents 86524a70c0f6
children 779e3d9b7a1d
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1 # worker.py - master-slave parallelism support
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2 #
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3 # Copyright 2013 Facebook, Inc.
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4 #
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5 # This software may be used and distributed according to the terms of the
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6 # GNU General Public License version 2 or any later version.
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7
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8 from i18n import _
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9 import os, signal, sys, threading, util
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10
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11 def countcpus():
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12 '''try to count the number of CPUs on the system'''
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13
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14 # posix
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15 try:
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16 n = int(os.sysconf('SC_NPROCESSORS_ONLN'))
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17 if n > 0:
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18 return n
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19 except (AttributeError, ValueError):
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20 pass
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21
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22 # windows
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23 try:
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24 n = int(os.environ['NUMBER_OF_PROCESSORS'])
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25 if n > 0:
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26 return n
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27 except (KeyError, ValueError):
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28 pass
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29
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30 return 1
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31
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32 def _numworkers(ui):
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33 s = ui.config('worker', 'numcpus')
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34 if s:
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35 try:
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36 n = int(s)
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37 if n >= 1:
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38 return n
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39 except ValueError:
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40 raise util.Abort(_('number of cpus must be an integer'))
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41 return min(max(countcpus(), 4), 32)
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42
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43 if os.name == 'posix':
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44 _startupcost = 0.01
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45 else:
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46 _startupcost = 1e30
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47
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48 def worthwhile(ui, costperop, nops):
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49 '''try to determine whether the benefit of multiple processes can
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50 outweigh the cost of starting them'''
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51 linear = costperop * nops
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52 workers = _numworkers(ui)
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53 benefit = linear - (_startupcost * workers + linear / workers)
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54 return benefit >= 0.15
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55
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56 def worker(ui, costperarg, func, staticargs, args):
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57 '''run a function, possibly in parallel in multiple worker
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58 processes.
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59
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60 returns a progress iterator
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61
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62 costperarg - cost of a single task
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63
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64 func - function to run
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65
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66 staticargs - arguments to pass to every invocation of the function
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67
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68 args - arguments to split into chunks, to pass to individual
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69 workers
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70 '''
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71 if worthwhile(ui, costperarg, len(args)):
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72 return _platformworker(ui, func, staticargs, args)
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73 return func(*staticargs + (args,))
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74
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75 def _posixworker(ui, func, staticargs, args):
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76 rfd, wfd = os.pipe()
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77 workers = _numworkers(ui)
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78 oldhandler = signal.getsignal(signal.SIGINT)
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79 signal.signal(signal.SIGINT, signal.SIG_IGN)
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80 pids, problem = [], [0]
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81 for pargs in partition(args, workers):
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82 pid = os.fork()
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83 if pid == 0:
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84 signal.signal(signal.SIGINT, oldhandler)
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85 try:
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86 os.close(rfd)
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87 for i, item in func(*(staticargs + (pargs,))):
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88 os.write(wfd, '%d %s\n' % (i, item))
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89 os._exit(0)
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90 except KeyboardInterrupt:
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91 os._exit(255)
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92 pids.append(pid)
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93 pids.reverse()
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94 os.close(wfd)
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95 fp = os.fdopen(rfd, 'rb', 0)
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96 def killworkers():
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97 # if one worker bails, there's no good reason to wait for the rest
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98 for p in pids:
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99 try:
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100 os.kill(p, signal.SIGTERM)
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101 except OSError, err:
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102 if err.errno != errno.ESRCH:
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103 raise
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104 def waitforworkers():
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105 for _ in pids:
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106 st = _exitstatus(os.wait()[1])
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107 if st and not problem:
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108 problem[0] = st
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109 killworkers()
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110 t = threading.Thread(target=waitforworkers)
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111 t.start()
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112 def cleanup():
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113 signal.signal(signal.SIGINT, oldhandler)
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114 t.join()
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115 status = problem[0]
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116 if status:
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117 if status < 0:
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118 os.kill(os.getpid(), -status)
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119 sys.exit(status)
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120 try:
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121 for line in fp:
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122 l = line.split(' ', 1)
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123 yield int(l[0]), l[1][:-1]
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124 except: # re-raises
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125 killworkers()
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126 cleanup()
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127 raise
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128 cleanup()
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129
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130 def _posixexitstatus(code):
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131 '''convert a posix exit status into the same form returned by
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132 os.spawnv
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133
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134 returns None if the process was stopped instead of exiting'''
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135 if os.WIFEXITED(code):
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136 return os.WEXITSTATUS(code)
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137 elif os.WIFSIGNALED(code):
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138 return -os.WTERMSIG(code)
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139
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140 if os.name != 'nt':
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141 _platformworker = _posixworker
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142 _exitstatus = _posixexitstatus
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143
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144 def partition(lst, nslices):
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145 '''partition a list into N slices of equal size'''
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146 n = len(lst)
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147 chunk, slop = n / nslices, n % nslices
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148 end = 0
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149 for i in xrange(nslices):
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150 start = end
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151 end = start + chunk
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152 if slop:
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153 end += 1
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154 slop -= 1
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155 yield lst[start:end]