Mercurial > public > mercurial-scm > hg
annotate mercurial/worker.py @ 45892:06b64fabf91c
copies: cache the ancestor checking call when tracing copy
A good share of the time spent in this function is spent doing ancestors
checking. To avoid spending time in duplicated call, we cache the result of
calls.
In the slower case, this provide a quite significant performance boost. Below
are the result for a set of selected pairs (many of them pathological):
(And further down is another table that summarize the current state of filelog
based vs changeset base copy tracing)
The benchmark have been configured to be killed after 6 minutes of runtime,
which mean that any detect slower than 2 minutes will be marked as "killed".
This drop some useful information about how much slower these case are? but also
prevent 99% of the benchmark time to be spent on case that can be labelled "very
slow" anyway.
Repo Case Source-Rev Dest-Rev Old-Time New-Time Difference Factor
------------------------------------------------------------------------------------------------------------------------------------
mercurial x_revs_x_added_0_copies ad6b123de1c7 39cfcef4f463 : 0.000044 s, 0.000044 s, +0.000000 s, ? 1.0000
mercurial x_revs_x_added_x_copies 2b1c78674230 0c1d10351869 : 0.000138 s, 0.000138 s, +0.000000 s, ? 1.0000
mercurial x000_revs_x000_added_x_copies 81f8ff2a9bf2 dd3267698d84 : 0.005067 s, 0.005052 s, -0.000015 s, ? 0.9970
pypy x_revs_x_added_0_copies aed021ee8ae8 099ed31b181b : 0.000218 s, 0.000219 s, +0.000001 s, ? 1.0046
pypy x_revs_x000_added_0_copies 4aa4e1f8e19a 359343b9ac0e : 0.000053 s, 0.000055 s, +0.000002 s, ? 1.0377
pypy x_revs_x_added_x_copies ac52eb7bbbb0 72e022663155 : 0.000125 s, 0.000128 s, +0.000003 s, ? 1.0240
pypy x_revs_x00_added_x_copies c3b14617fbd7 ace7255d9a26 : 0.001098 s, 0.001089 s, -0.000009 s, ? 0.9918
pypy x_revs_x000_added_x000_copies df6f7a526b60 a83dc6a2d56f : 0.017546 s, 0.017407 s, -0.000139 s, ? 0.9921
pypy x000_revs_xx00_added_0_copies 89a76aede314 2f22446ff07e : 0.096723 s, 0.094175 s, -0.002548 s, ? 0.9737
pypy x000_revs_x000_added_x_copies 8a3b5bfd266e 2c68e87c3efe : 0.271796 s, 0.238009 s, -0.033787 s, ? 0.8757
pypy x000_revs_x000_added_x000_copies 89a76aede314 7b3dda341c84 : 0.128602 s, 0.125876 s, -0.002726 s, ? 0.9788
pypy x0000_revs_x_added_0_copies d1defd0dc478 c9cb1334cc78 : 7.086742 s, 3.581556 s, -3.505186 s, ? 0.5054
pypy x0000_revs_xx000_added_0_copies bf2c629d0071 4ffed77c095c : 0.016634 s, 0.016721 s, +0.000087 s, ? 1.0052
pypy x0000_revs_xx000_added_x000_copies 08ea3258278e d9fa043f30c0 : 0.254225 s, 0.242367 s, -0.011858 s, ? 0.9534
netbeans x_revs_x_added_0_copies fb0955ffcbcd a01e9239f9e7 : 0.000166 s, 0.000165 s, -0.000001 s, ? 0.9940
netbeans x_revs_x000_added_0_copies 6f360122949f 20eb231cc7d0 : 0.000118 s, 0.000114 s, -0.000004 s, ? 0.9661
netbeans x_revs_x_added_x_copies 1ada3faf6fb6 5a39d12eecf4 : 0.000296 s, 0.000296 s, +0.000000 s, ? 1.0000
netbeans x_revs_x00_added_x_copies 35be93ba1e2c 9eec5e90c05f : 0.001137 s, 0.001124 s, -0.000013 s, ? 0.9886
netbeans x000_revs_xx00_added_0_copies eac3045b4fdd 51d4ae7f1290 : 0.014133 s, 0.013060 s, -0.001073 s, ? 0.9241
netbeans x000_revs_x000_added_x_copies e2063d266acd 6081d72689dc : 0.016988 s, 0.017112 s, +0.000124 s, ? 1.0073
netbeans x000_revs_x000_added_x000_copies ff453e9fee32 411350406ec2 : 0.676361 s, 0.660350 s, -0.016011 s, ? 0.9763
netbeans x0000_revs_xx000_added_x000_copies 588c2d1ced70 1aad62e59ddd : 12.515149 s, 10.032499 s, -2.482650 s, ? 0.8016
mozilla-central x_revs_x_added_0_copies 3697f962bb7b 7015fcdd43a2 : 0.000186 s, 0.000189 s, +0.000003 s, ? 1.0161
mozilla-central x_revs_x000_added_0_copies dd390860c6c9 40d0c5bed75d : 0.000459 s, 0.000462 s, +0.000003 s, ? 1.0065
mozilla-central x_revs_x_added_x_copies 8d198483ae3b 14207ffc2b2f : 0.000273 s, 0.000270 s, -0.000003 s, ? 0.9890
mozilla-central x_revs_x00_added_x_copies 98cbc58cc6bc 446a150332c3 : 0.001503 s, 0.001474 s, -0.000029 s, ? 0.9807
mozilla-central x_revs_x000_added_x000_copies 3c684b4b8f68 0a5e72d1b479 : 0.004862 s, 0.004806 s, -0.000056 s, ? 0.9885
mozilla-central x_revs_x0000_added_x0000_copies effb563bb7e5 c07a39dc4e80 : 0.088291 s, 0.085150 s, -0.003141 s, ? 0.9644
mozilla-central x000_revs_xx00_added_0_copies 6100d773079a 04a55431795e : 0.007113 s, 0.007064 s, -0.000049 s, ? 0.9931
mozilla-central x000_revs_x000_added_x_copies 9f17a6fc04f9 2d37b966abed : 0.004687 s, 0.004741 s, +0.000054 s, ? 1.0115
mozilla-central x000_revs_x000_added_x000_copies 7c97034feb78 4407bd0c6330 : 0.198710 s, 0.190133 s, -0.008577 s, ? 0.9568
mozilla-central x0000_revs_xx000_added_0_copies 9eec5917337d 67118cc6dcad : 0.036068 s, 0.035651 s, -0.000417 s, ? 0.9884
mozilla-central x0000_revs_xx000_added_x000_copies f78c615a656c 96a38b690156 : 0.465362 s, 0.440694 s, -0.024668 s, ? 0.9470
mozilla-central x00000_revs_x0000_added_x0000_copies 6832ae71433c 4c222a1d9a00 : 24.519684 s, 18.454163 s, -6.065521 s, ? 0.7526
mozilla-central x00000_revs_x00000_added_x000_copies 76caed42cf7c 1daa622bbe42 : 42.711897 s, 31.562719 s, -11.149178 s, ? 0.7390
mozilla-try x_revs_x_added_0_copies aaf6dde0deb8 9790f499805a : 0.001201 s, 0.001189 s, -0.000012 s, ? 0.9900
mozilla-try x_revs_x000_added_0_copies d8d0222927b4 5bb8ce8c7450 : 0.001216 s, 0.001204 s, -0.000012 s, ? 0.9901
mozilla-try x_revs_x_added_x_copies 092fcca11bdb 936255a0384a : 0.000595 s, 0.000586 s, -0.000009 s, ? 0.9849
mozilla-try x_revs_x00_added_x_copies b53d2fadbdb5 017afae788ec : 0.001856 s, 0.001845 s, -0.000011 s, ? 0.9941
mozilla-try x_revs_x000_added_x000_copies 20408ad61ce5 6f0ee96e21ad : 0.064936 s, 0.063822 s, -0.001114 s, ? 0.9828
mozilla-try x_revs_x0000_added_x0000_copies effb563bb7e5 c07a39dc4e80 : 0.090601 s, 0.088038 s, -0.002563 s, ? 0.9717
mozilla-try x000_revs_xx00_added_0_copies 6100d773079a 04a55431795e : 0.007510 s, 0.007389 s, -0.000121 s, ? 0.9839
mozilla-try x000_revs_x000_added_x_copies 9f17a6fc04f9 2d37b966abed : 0.004911 s, 0.004868 s, -0.000043 s, ? 0.9912
mozilla-try x000_revs_x000_added_x000_copies 1346fd0130e4 4c65cbdabc1f : 0.233231 s, 0.222450 s, -0.010781 s, ? 0.9538
mozilla-try x0000_revs_x_added_0_copies 63519bfd42ee a36a2a865d92 : 0.419989 s, 0.370675 s, -0.049314 s, ? 0.8826
mozilla-try x0000_revs_x_added_x_copies 9fe69ff0762d bcabf2a78927 : 0.401521 s, 0.358020 s, -0.043501 s, ? 0.8917
mozilla-try x0000_revs_xx000_added_x_copies 156f6e2674f2 4d0f2c178e66 : 0.179555 s, 0.145235 s, -0.034320 s, ? 0.8089
mozilla-try x0000_revs_xx000_added_0_copies 9eec5917337d 67118cc6dcad : 0.038004 s, 0.037606 s, -0.000398 s, ? 0.9895
mozilla-try x0000_revs_xx000_added_x000_copies 89294cd501d9 7ccb2fc7ccb5 : 52.838482 s, 7.382439 s, -45.456043 s, ? 0.1397
mozilla-try x0000_revs_x0000_added_x0000_copies e928c65095ed e951f4ad123a : 8.705874 s, 7.273506 s, -1.432368 s, ? 0.8355
mozilla-try x00000_revs_x00000_added_0_copies dc8a3ca7010e d16fde900c9c : 1.126708 s, 1.074593 s, -0.052115 s, ? 0.9537
mozilla-try x00000_revs_x0000_added_x0000_copies 8d3fafa80d4b eb884023b810 : 83.854020 s, 27.746195 s, -56.107825 s, ? 0.3309
Below is a table comparing the runtime of the current "filelog centric"
algorithm, with the "changeset centric" one, we just modified.
The changeset centric algorithm is a significant win in many scenario, but they
are still various cases where it is quite slower. When many revision has to be
considered the cost of retrieving the copy information, creating new
dictionaries, merging dictionaries and checking if revision are ancestors of
each other can slow things down.
The rest of this series, will introduce a rust version of the copy tracing code
to deal with most of theses issues.
Repo Case Source-Rev Dest-Rev filelog sidedata Difference Factor
---------------------------------------------------------------------------------------------------------------------------------------
mercurial x_revs_x_added_0_copies ad6b123de1c7 39cfcef4f463 : 0.000914 s, 0.000044 s, - 0.000870 s, ? 0.048140
mercurial x_revs_x_added_x_copies 2b1c78674230 0c1d10351869 : 0.001812 s, 0.000138 s, - 0.001674 s, ? 0.076159
mercurial x000_revs_x000_added_x_copies 81f8ff2a9bf2 dd3267698d84 : 0.017954 s, 0.005052 s, - 0.012902 s, ? 0.281386
pypy x_revs_x_added_0_copies aed021ee8ae8 099ed31b181b : 0.001509 s, 0.000219 s, - 0.001290 s, ? 0.145129
pypy x_revs_x000_added_0_copies 4aa4e1f8e19a 359343b9ac0e : 0.206881 s, 0.000055 s, - 0.206826 s, ? 0.000266
pypy x_revs_x_added_x_copies ac52eb7bbbb0 72e022663155 : 0.016951 s, 0.000128 s, - 0.016823 s, ? 0.007551
pypy x_revs_x00_added_x_copies c3b14617fbd7 ace7255d9a26 : 0.019096 s, 0.001089 s, - 0.018007 s, ? 0.057028
pypy x_revs_x000_added_x000_copies df6f7a526b60 a83dc6a2d56f : 0.762506 s, 0.017407 s, - 0.745099 s, ? 0.022829
pypy x000_revs_xx00_added_0_copies 89a76aede314 2f22446ff07e : 1.179211 s, 0.094175 s, - 1.085036 s, ? 0.079863
pypy x000_revs_x000_added_x_copies 8a3b5bfd266e 2c68e87c3efe : 1.249058 s, 0.238009 s, - 1.011049 s, ? 0.190551
pypy x000_revs_x000_added_x000_copies 89a76aede314 7b3dda341c84 : 1.614107 s, 0.125876 s, - 1.488231 s, ? 0.077985
pypy x0000_revs_x_added_0_copies d1defd0dc478 c9cb1334cc78 : 0.001064 s, 3.581556 s, + 3.580492 s, ? 3366.124060
pypy x0000_revs_xx000_added_0_copies bf2c629d0071 4ffed77c095c : 1.061275 s, 0.016721 s, - 1.044554 s, ? 0.015756
pypy x0000_revs_xx000_added_x000_copies 08ea3258278e d9fa043f30c0 : 1.341119 s, 0.242367 s, - 1.098752 s, ? 0.180720
netbeans x_revs_x_added_0_copies fb0955ffcbcd a01e9239f9e7 : 0.027803 s, 0.000165 s, - 0.027638 s, ? 0.005935
netbeans x_revs_x000_added_0_copies 6f360122949f 20eb231cc7d0 : 0.130014 s, 0.000114 s, - 0.129900 s, ? 0.000877
netbeans x_revs_x_added_x_copies 1ada3faf6fb6 5a39d12eecf4 : 0.024990 s, 0.000296 s, - 0.024694 s, ? 0.011845
netbeans x_revs_x00_added_x_copies 35be93ba1e2c 9eec5e90c05f : 0.052201 s, 0.001124 s, - 0.051077 s, ? 0.021532
netbeans x000_revs_xx00_added_0_copies eac3045b4fdd 51d4ae7f1290 : 0.037642 s, 0.013060 s, - 0.024582 s, ? 0.346953
netbeans x000_revs_x000_added_x_copies e2063d266acd 6081d72689dc : 0.197086 s, 0.017112 s, - 0.179974 s, ? 0.086825
netbeans x000_revs_x000_added_x000_copies ff453e9fee32 411350406ec2 : 0.935148 s, 0.660350 s, - 0.274798 s, ? 0.706145
netbeans x0000_revs_xx000_added_x000_copies 588c2d1ced70 1aad62e59ddd : 3.920674 s, 10.032499 s, + 6.111825 s, ? 2.558871
mozilla-central x_revs_x_added_0_copies 3697f962bb7b 7015fcdd43a2 : 0.024232 s, 0.000189 s, - 0.024043 s, ? 0.007800
mozilla-central x_revs_x000_added_0_copies dd390860c6c9 40d0c5bed75d : 0.141483 s, 0.000462 s, - 0.141021 s, ? 0.003265
mozilla-central x_revs_x_added_x_copies 8d198483ae3b 14207ffc2b2f : 0.025775 s, 0.000270 s, - 0.025505 s, ? 0.010475
mozilla-central x_revs_x00_added_x_copies 98cbc58cc6bc 446a150332c3 : 0.084922 s, 0.001474 s, - 0.083448 s, ? 0.017357
mozilla-central x_revs_x000_added_x000_copies 3c684b4b8f68 0a5e72d1b479 : 0.194784 s, 0.004806 s, - 0.189978 s, ? 0.024673
mozilla-central x_revs_x0000_added_x0000_copies effb563bb7e5 c07a39dc4e80 : 2.161103 s, 0.085150 s, - 2.075953 s, ? 0.039401
mozilla-central x000_revs_xx00_added_0_copies 6100d773079a 04a55431795e : 0.089347 s, 0.007064 s, - 0.082283 s, ? 0.079063
mozilla-central x000_revs_x000_added_x_copies 9f17a6fc04f9 2d37b966abed : 0.732171 s, 0.004741 s, - 0.727430 s, ? 0.006475
mozilla-central x000_revs_x000_added_x000_copies 7c97034feb78 4407bd0c6330 : 1.157287 s, 0.190133 s, - 0.967154 s, ? 0.164292
mozilla-central x0000_revs_xx000_added_0_copies 9eec5917337d 67118cc6dcad : 6.726568 s, 0.035651 s, - 6.690917 s, ? 0.005300
mozilla-central x0000_revs_xx000_added_x000_copies f78c615a656c 96a38b690156 : 3.266229 s, 0.440694 s, - 2.825535 s, ? 0.134924
mozilla-central x00000_revs_x0000_added_x0000_copies 6832ae71433c 4c222a1d9a00 : 15.860534 s, 18.454163 s, + 2.593629 s, ? 1.163527
mozilla-central x00000_revs_x00000_added_x000_copies 76caed42cf7c 1daa622bbe42 : 20.450475 s, 31.562719 s, +11.112244 s, ? 1.543373
mozilla-try x_revs_x_added_0_copies aaf6dde0deb8 9790f499805a : 0.080442 s, 0.001189 s, - 0.079253 s, ? 0.014781
mozilla-try x_revs_x000_added_0_copies d8d0222927b4 5bb8ce8c7450 : 0.497672 s, 0.001204 s, - 0.496468 s, ? 0.002419
mozilla-try x_revs_x_added_x_copies 092fcca11bdb 936255a0384a : 0.021183 s, 0.000586 s, - 0.020597 s, ? 0.027664
mozilla-try x_revs_x00_added_x_copies b53d2fadbdb5 017afae788ec : 0.230991 s, 0.001845 s, - 0.229146 s, ? 0.007987
mozilla-try x_revs_x000_added_x000_copies 20408ad61ce5 6f0ee96e21ad : 1.118461 s, 0.063822 s, - 1.054639 s, ? 0.057062
mozilla-try x_revs_x0000_added_x0000_copies effb563bb7e5 c07a39dc4e80 : 2.206083 s, 0.088038 s, - 2.118045 s, ? 0.039907
mozilla-try x000_revs_xx00_added_0_copies 6100d773079a 04a55431795e : 0.089404 s, 0.007389 s, - 0.082015 s, ? 0.082647
mozilla-try x000_revs_x000_added_x_copies 9f17a6fc04f9 2d37b966abed : 0.733043 s, 0.004868 s, - 0.728175 s, ? 0.006641
mozilla-try x000_revs_x000_added_x000_copies 1346fd0130e4 4c65cbdabc1f : 1.163367 s, 0.222450 s, - 0.940917 s, ? 0.191212
mozilla-try x0000_revs_x_added_0_copies 63519bfd42ee a36a2a865d92 : 0.085456 s, 0.370675 s, + 0.285219 s, ? 4.337612
mozilla-try x0000_revs_x_added_x_copies 9fe69ff0762d bcabf2a78927 : 0.083601 s, 0.358020 s, + 0.274419 s, ? 4.282485
mozilla-try x0000_revs_xx000_added_x_copies 156f6e2674f2 4d0f2c178e66 : 7.366614 s, 0.145235 s, - 7.221379 s, ? 0.019715
mozilla-try x0000_revs_xx000_added_0_copies 9eec5917337d 67118cc6dcad : 6.664464 s, 0.037606 s, - 6.626858 s, ? 0.005643
mozilla-try x0000_revs_xx000_added_x000_copies 89294cd501d9 7ccb2fc7ccb5 : 7.467836 s, 7.382439 s, - 0.085397 s, ? 0.988565
mozilla-try x0000_revs_x0000_added_x0000_copies e928c65095ed e951f4ad123a : 9.801294 s, 7.273506 s, - 2.527788 s, ? 0.742097
mozilla-try x00000_revs_x_added_0_copies 6a320851d377 1ebb79acd503 : 0.091886 s, killed
mozilla-try x00000_revs_x00000_added_0_copies dc8a3ca7010e d16fde900c9c : 26.491140 s, 1.074593 s, -25.416547 s, ? 0.040564
mozilla-try x00000_revs_x_added_x_copies 5173c4b6f97c 95d83ee7242d : 0.092863 s, killed
mozilla-try x00000_revs_x000_added_x_copies 9126823d0e9c ca82787bb23c : 0.226823 s, killed
mozilla-try x00000_revs_x0000_added_x0000_copies 8d3fafa80d4b eb884023b810 : 18.914630 s, 27.746195 s, + 8.831565 s, ? 1.466917
mozilla-try x00000_revs_x00000_added_x0000_copies 1b661134e2ca 1ae03d022d6d : 21.198903 s, killed
mozilla-try x00000_revs_x00000_added_x000_copies 9b2a99adc05e 8e29777b48e6 : 24.952268 s, killed
Differential Revision: https://phab.mercurial-scm.org/D9296
author | Pierre-Yves David <pierre-yves.david@octobus.net> |
---|---|
date | Mon, 02 Nov 2020 11:03:56 +0100 |
parents | 8f07f5a9c3de |
children | 89a2afe31e82 |
rev | line source |
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18635
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worker: count the number of CPUs
Bryan O'Sullivan <bryano@fb.com>
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1 # worker.py - master-slave parallelism support |
fed06dd07665
worker: count the number of CPUs
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2 # |
fed06dd07665
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3 # Copyright 2013 Facebook, Inc. |
fed06dd07665
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4 # |
fed06dd07665
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5 # This software may be used and distributed according to the terms of the |
fed06dd07665
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6 # GNU General Public License version 2 or any later version. |
fed06dd07665
worker: count the number of CPUs
Bryan O'Sullivan <bryano@fb.com>
parents:
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7 |
25992
2d76f8a2d831
worker: use absolute_import
Gregory Szorc <gregory.szorc@gmail.com>
parents:
25660
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8 from __future__ import absolute_import |
2d76f8a2d831
worker: use absolute_import
Gregory Szorc <gregory.szorc@gmail.com>
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9 |
2d76f8a2d831
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Gregory Szorc <gregory.szorc@gmail.com>
parents:
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10 import errno |
2d76f8a2d831
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Gregory Szorc <gregory.szorc@gmail.com>
parents:
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11 import os |
2d76f8a2d831
worker: use absolute_import
Gregory Szorc <gregory.szorc@gmail.com>
parents:
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12 import signal |
2d76f8a2d831
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13 import sys |
35427
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workers: implemented worker on windows
Wojciech Lis <wlis@fb.com>
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14 import threading |
35432
86b8cc1f244e
worker: make windows workers daemons
Wojciech Lis <wlis@fb.com>
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15 import time |
25992
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16 |
38729
9e6afe7fca31
worker: use one pipe per posix worker and select() in parent process
Danny Hooper <hooper@google.com>
parents:
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17 try: |
9e6afe7fca31
worker: use one pipe per posix worker and select() in parent process
Danny Hooper <hooper@google.com>
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18 import selectors |
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19 |
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20 selectors.BaseSelector |
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21 except ImportError: |
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22 from .thirdparty import selectors2 as selectors |
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23 |
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24 from .i18n import _ |
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26 encoding, |
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28 pycompat, |
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29 scmutil, |
30396 | 30 util, |
31 ) | |
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32 |
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33 |
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34 def countcpus(): |
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35 '''try to count the number of CPUs on the system''' |
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36 |
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37 # posix |
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38 try: |
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39 n = int(os.sysconf('SC_NPROCESSORS_ONLN')) |
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40 if n > 0: |
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41 return n |
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42 except (AttributeError, ValueError): |
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43 pass |
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44 |
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45 # windows |
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46 try: |
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47 n = int(encoding.environ[b'NUMBER_OF_PROCESSORS']) |
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48 if n > 0: |
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49 return n |
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50 except (KeyError, ValueError): |
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51 pass |
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52 |
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53 return 1 |
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54 |
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55 |
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56 def _numworkers(ui): |
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57 s = ui.config(b'worker', b'numcpus') |
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58 if s: |
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59 try: |
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60 n = int(s) |
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61 if n >= 1: |
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62 return n |
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63 except ValueError: |
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64 raise error.Abort(_(b'number of cpus must be an integer')) |
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65 return min(max(countcpus(), 4), 32) |
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66 |
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67 |
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68 if pycompat.ispy3: |
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69 |
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70 class _blockingreader(object): |
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71 def __init__(self, wrapped): |
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72 self._wrapped = wrapped |
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73 |
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74 # Do NOT implement readinto() by making it delegate to |
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75 # _wrapped.readinto(), since that is unbuffered. The unpickler is fine |
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76 # with just read() and readline(), so we don't need to implement it. |
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77 |
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78 def readline(self): |
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79 return self._wrapped.readline() |
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80 |
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81 # issue multiple reads until size is fulfilled |
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82 def read(self, size=-1): |
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83 if size < 0: |
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84 return self._wrapped.readall() |
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85 |
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86 buf = bytearray(size) |
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87 view = memoryview(buf) |
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88 pos = 0 |
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89 |
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90 while pos < size: |
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91 ret = self._wrapped.readinto(view[pos:]) |
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92 if not ret: |
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93 break |
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94 pos += ret |
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95 |
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96 del view |
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97 del buf[pos:] |
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98 return bytes(buf) |
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99 |
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100 |
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101 else: |
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102 |
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103 def _blockingreader(wrapped): |
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104 return wrapped |
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105 |
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106 |
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107 if pycompat.isposix or pycompat.iswindows: |
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108 _STARTUP_COST = 0.01 |
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109 # The Windows worker is thread based. If tasks are CPU bound, threads |
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110 # in the presence of the GIL result in excessive context switching and |
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111 # this overhead can slow down execution. |
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112 _DISALLOW_THREAD_UNSAFE = pycompat.iswindows |
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113 else: |
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114 _STARTUP_COST = 1e30 |
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115 _DISALLOW_THREAD_UNSAFE = False |
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116 |
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117 |
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118 def worthwhile(ui, costperop, nops, threadsafe=True): |
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119 '''try to determine whether the benefit of multiple processes can |
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120 outweigh the cost of starting them''' |
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121 |
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122 if not threadsafe and _DISALLOW_THREAD_UNSAFE: |
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123 return False |
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124 |
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125 linear = costperop * nops |
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126 workers = _numworkers(ui) |
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127 benefit = linear - (_STARTUP_COST * workers + linear / workers) |
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128 return benefit >= 0.15 |
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129 |
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130 |
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131 def worker( |
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132 ui, costperarg, func, staticargs, args, hasretval=False, threadsafe=True |
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133 ): |
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134 '''run a function, possibly in parallel in multiple worker |
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135 processes. |
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136 |
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137 returns a progress iterator |
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138 |
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139 costperarg - cost of a single task |
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140 |
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141 func - function to run. It is expected to return a progress iterator. |
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142 |
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143 staticargs - arguments to pass to every invocation of the function |
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144 |
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145 args - arguments to split into chunks, to pass to individual |
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146 workers |
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147 |
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148 hasretval - when True, func and the current function return an progress |
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149 iterator then a dict (encoded as an iterator that yield many (False, ..) |
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150 then a (True, dict)). The dicts are joined in some arbitrary order, so |
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151 overlapping keys are a bad idea. |
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152 |
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153 threadsafe - whether work items are thread safe and can be executed using |
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154 a thread-based worker. Should be disabled for CPU heavy tasks that don't |
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155 release the GIL. |
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156 ''' |
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157 enabled = ui.configbool(b'worker', b'enabled') |
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158 if enabled and worthwhile(ui, costperarg, len(args), threadsafe=threadsafe): |
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159 return _platformworker(ui, func, staticargs, args, hasretval) |
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160 return func(*staticargs + (args,)) |
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161 |
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162 |
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163 def _posixworker(ui, func, staticargs, args, hasretval): |
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164 workers = _numworkers(ui) |
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165 oldhandler = signal.getsignal(signal.SIGINT) |
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166 signal.signal(signal.SIGINT, signal.SIG_IGN) |
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168 |
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169 def killworkers(): |
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170 # unregister SIGCHLD handler as all children will be killed. This |
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171 # function shouldn't be interrupted by another SIGCHLD; otherwise pids |
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172 # could be updated while iterating, which would cause inconsistency. |
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173 signal.signal(signal.SIGCHLD, oldchldhandler) |
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174 # if one worker bails, there's no good reason to wait for the rest |
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175 for p in pids: |
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176 try: |
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177 os.kill(p, signal.SIGTERM) |
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178 except OSError as err: |
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179 if err.errno != errno.ESRCH: |
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180 raise |
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181 |
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182 def waitforworkers(blocking=True): |
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183 for pid in pids.copy(): |
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184 p = st = 0 |
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185 while True: |
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186 try: |
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187 p, st = os.waitpid(pid, (0 if blocking else os.WNOHANG)) |
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188 break |
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189 except OSError as e: |
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190 if e.errno == errno.EINTR: |
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191 continue |
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192 elif e.errno == errno.ECHILD: |
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193 # child would already be reaped, but pids yet been |
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194 # updated (maybe interrupted just after waitpid) |
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195 pids.discard(pid) |
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196 break |
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197 else: |
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198 raise |
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199 if not p: |
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200 # skip subsequent steps, because child process should |
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201 # be still running in this case |
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202 continue |
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203 pids.discard(p) |
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204 st = _exitstatus(st) |
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205 if st and not problem[0]: |
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206 problem[0] = st |
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207 |
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208 def sigchldhandler(signum, frame): |
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209 waitforworkers(blocking=False) |
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210 if problem[0]: |
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211 killworkers() |
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212 |
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213 oldchldhandler = signal.signal(signal.SIGCHLD, sigchldhandler) |
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214 ui.flush() |
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215 parentpid = os.getpid() |
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216 pipes = [] |
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217 retval = {} |
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218 for pargs in partition(args, min(workers, len(args))): |
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219 # Every worker gets its own pipe to send results on, so we don't have to |
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220 # implement atomic writes larger than PIPE_BUF. Each forked process has |
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221 # its own pipe's descriptors in the local variables, and the parent |
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222 # process has the full list of pipe descriptors (and it doesn't really |
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223 # care what order they're in). |
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224 rfd, wfd = os.pipe() |
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225 pipes.append((rfd, wfd)) |
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226 # make sure we use os._exit in all worker code paths. otherwise the |
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227 # worker may do some clean-ups which could cause surprises like |
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228 # deadlock. see sshpeer.cleanup for example. |
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229 # override error handling *before* fork. this is necessary because |
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230 # exception (signal) may arrive after fork, before "pid =" assignment |
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231 # completes, and other exception handler (dispatch.py) can lead to |
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232 # unexpected code path without os._exit. |
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233 ret = -1 |
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234 try: |
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235 pid = os.fork() |
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236 if pid == 0: |
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237 signal.signal(signal.SIGINT, oldhandler) |
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238 signal.signal(signal.SIGCHLD, oldchldhandler) |
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239 |
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240 def workerfunc(): |
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241 for r, w in pipes[:-1]: |
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242 os.close(r) |
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243 os.close(w) |
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244 os.close(rfd) |
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245 for result in func(*(staticargs + (pargs,))): |
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246 os.write(wfd, util.pickle.dumps(result)) |
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247 return 0 |
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248 |
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249 ret = scmutil.callcatch(ui, workerfunc) |
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250 except: # parent re-raises, child never returns |
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251 if os.getpid() == parentpid: |
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252 raise |
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253 exctype = sys.exc_info()[0] |
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254 force = not issubclass(exctype, KeyboardInterrupt) |
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255 ui.traceback(force=force) |
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256 finally: |
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257 if os.getpid() != parentpid: |
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258 try: |
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259 ui.flush() |
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260 except: # never returns, no re-raises |
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261 pass |
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262 finally: |
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263 os._exit(ret & 255) |
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265 selector = selectors.DefaultSelector() |
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266 for rfd, wfd in pipes: |
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267 os.close(wfd) |
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268 selector.register(os.fdopen(rfd, 'rb', 0), selectors.EVENT_READ) |
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269 |
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270 def cleanup(): |
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271 signal.signal(signal.SIGINT, oldhandler) |
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272 waitforworkers() |
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273 signal.signal(signal.SIGCHLD, oldchldhandler) |
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274 selector.close() |
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275 return problem[0] |
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276 |
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277 try: |
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278 openpipes = len(pipes) |
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279 while openpipes > 0: |
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280 for key, events in selector.select(): |
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281 try: |
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282 res = util.pickle.load(_blockingreader(key.fileobj)) |
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283 if hasretval and res[0]: |
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284 retval.update(res[1]) |
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285 else: |
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286 yield res |
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287 except EOFError: |
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288 selector.unregister(key.fileobj) |
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289 key.fileobj.close() |
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290 openpipes -= 1 |
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291 except IOError as e: |
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292 if e.errno == errno.EINTR: |
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293 continue |
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294 raise |
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295 except: # re-raises |
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296 killworkers() |
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297 cleanup() |
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298 raise |
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299 status = cleanup() |
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300 if status: |
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301 if status < 0: |
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302 os.kill(os.getpid(), -status) |
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303 raise error.WorkerError(status) |
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304 if hasretval: |
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305 yield True, retval |
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306 |
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307 |
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308 def _posixexitstatus(code): |
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309 '''convert a posix exit status into the same form returned by |
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310 os.spawnv |
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311 |
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312 returns None if the process was stopped instead of exiting''' |
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313 if os.WIFEXITED(code): |
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314 return os.WEXITSTATUS(code) |
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315 elif os.WIFSIGNALED(code): |
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316 return -(os.WTERMSIG(code)) |
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317 |
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318 |
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319 def _windowsworker(ui, func, staticargs, args, hasretval): |
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320 class Worker(threading.Thread): |
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321 def __init__( |
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322 self, taskqueue, resultqueue, func, staticargs, *args, **kwargs |
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323 ): |
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324 threading.Thread.__init__(self, *args, **kwargs) |
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325 self._taskqueue = taskqueue |
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326 self._resultqueue = resultqueue |
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327 self._func = func |
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328 self._staticargs = staticargs |
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329 self._interrupted = False |
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330 self.daemon = True |
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331 self.exception = None |
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332 |
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333 def interrupt(self): |
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334 self._interrupted = True |
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335 |
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336 def run(self): |
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337 try: |
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338 while not self._taskqueue.empty(): |
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339 try: |
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340 args = self._taskqueue.get_nowait() |
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341 for res in self._func(*self._staticargs + (args,)): |
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342 self._resultqueue.put(res) |
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343 # threading doesn't provide a native way to |
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344 # interrupt execution. handle it manually at every |
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345 # iteration. |
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346 if self._interrupted: |
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347 return |
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348 except pycompat.queue.Empty: |
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349 break |
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350 except Exception as e: |
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351 # store the exception such that the main thread can resurface |
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352 # it as if the func was running without workers. |
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353 self.exception = e |
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354 raise |
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355 |
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356 threads = [] |
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357 |
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358 def trykillworkers(): |
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359 # Allow up to 1 second to clean worker threads nicely |
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360 cleanupend = time.time() + 1 |
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361 for t in threads: |
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362 t.interrupt() |
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363 for t in threads: |
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364 remainingtime = cleanupend - time.time() |
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365 t.join(remainingtime) |
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366 if t.is_alive(): |
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367 # pass over the workers joining failure. it is more |
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368 # important to surface the inital exception than the |
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369 # fact that one of workers may be processing a large |
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370 # task and does not get to handle the interruption. |
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371 ui.warn( |
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372 _( |
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373 b"failed to kill worker threads while " |
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374 b"handling an exception\n" |
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375 ) |
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376 ) |
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377 return |
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378 |
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379 workers = _numworkers(ui) |
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380 resultqueue = pycompat.queue.Queue() |
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381 taskqueue = pycompat.queue.Queue() |
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382 retval = {} |
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383 # partition work to more pieces than workers to minimize the chance |
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384 # of uneven distribution of large tasks between the workers |
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385 for pargs in partition(args, workers * 20): |
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386 taskqueue.put(pargs) |
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387 for _i in range(workers): |
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388 t = Worker(taskqueue, resultqueue, func, staticargs) |
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389 threads.append(t) |
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390 t.start() |
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391 try: |
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392 while len(threads) > 0: |
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393 while not resultqueue.empty(): |
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394 res = resultqueue.get() |
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395 if hasretval and res[0]: |
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396 retval.update(res[1]) |
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397 else: |
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398 yield res |
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399 threads[0].join(0.05) |
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400 finishedthreads = [_t for _t in threads if not _t.is_alive()] |
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401 for t in finishedthreads: |
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402 if t.exception is not None: |
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403 raise t.exception |
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404 threads.remove(t) |
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405 except (Exception, KeyboardInterrupt): # re-raises |
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406 trykillworkers() |
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407 raise |
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408 while not resultqueue.empty(): |
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409 res = resultqueue.get() |
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410 if hasretval and res[0]: |
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411 retval.update(res[1]) |
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412 else: |
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413 yield res |
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414 if hasretval: |
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415 yield True, retval |
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416 |
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417 |
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418 if pycompat.iswindows: |
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419 _platformworker = _windowsworker |
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420 else: |
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421 _platformworker = _posixworker |
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422 _exitstatus = _posixexitstatus |
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423 |
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424 |
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425 def partition(lst, nslices): |
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426 '''partition a list into N slices of roughly equal size |
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427 |
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428 The current strategy takes every Nth element from the input. If |
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429 we ever write workers that need to preserve grouping in input |
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430 we should consider allowing callers to specify a partition strategy. |
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431 |
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432 mpm is not a fan of this partitioning strategy when files are involved. |
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433 In his words: |
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434 |
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435 Single-threaded Mercurial makes a point of creating and visiting |
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436 files in a fixed order (alphabetical). When creating files in order, |
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437 a typical filesystem is likely to allocate them on nearby regions on |
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438 disk. Thus, when revisiting in the same order, locality is maximized |
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439 and various forms of OS and disk-level caching and read-ahead get a |
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440 chance to work. |
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441 |
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442 This effect can be quite significant on spinning disks. I discovered it |
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443 circa Mercurial v0.4 when revlogs were named by hashes of filenames. |
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444 Tarring a repo and copying it to another disk effectively randomized |
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445 the revlog ordering on disk by sorting the revlogs by hash and suddenly |
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446 performance of my kernel checkout benchmark dropped by ~10x because the |
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447 "working set" of sectors visited no longer fit in the drive's cache and |
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448 the workload switched from streaming to random I/O. |
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449 |
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450 What we should really be doing is have workers read filenames from a |
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451 ordered queue. This preserves locality and also keeps any worker from |
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452 getting more than one file out of balance. |
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453 ''' |
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454 for i in range(nslices): |
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455 yield lst[i::nslices] |