view tests/test-sparse-revlog.t @ 46582:b0a3ca02d17a

copies-rust: implement PartialEqual manually Now that we know that each (dest, rev) pair has at most a unique CopySource, we can simplify comparison a lot. This "simple" step buy a good share of the previous slowdown back in some case: Repo Case Source-Rev Dest-Rev # of revisions old time new time Difference Factor time per rev --------------------------------------------------------------------------------------------------------------------------------------------------------------- mozilla-try x00000_revs_x00000_added_x000_copies 9b2a99adc05e 8e29777b48e6 : 382065 revs, 43.304637 s, 34.443661 s, -8.860976 s, × 0.7954, 90 µs/rev Full benchmark: Repo Case Source-Rev Dest-Rev # of revisions old time new time Difference Factor time per rev --------------------------------------------------------------------------------------------------------------------------------------------------------------- mercurial x_revs_x_added_0_copies ad6b123de1c7 39cfcef4f463 : 1 revs, 0.000043 s, 0.000043 s, +0.000000 s, × 1.0000, 43 µs/rev mercurial x_revs_x_added_x_copies 2b1c78674230 0c1d10351869 : 6 revs, 0.000114 s, 0.000117 s, +0.000003 s, × 1.0263, 19 µs/rev mercurial x000_revs_x000_added_x_copies 81f8ff2a9bf2 dd3267698d84 : 1032 revs, 0.004937 s, 0.004892 s, -0.000045 s, × 0.9909, 4 µs/rev pypy x_revs_x_added_0_copies aed021ee8ae8 099ed31b181b : 9 revs, 0.000339 s, 0.000196 s, -0.000143 s, × 0.5782, 21 µs/rev pypy x_revs_x000_added_0_copies 4aa4e1f8e19a 359343b9ac0e : 1 revs, 0.000049 s, 0.000050 s, +0.000001 s, × 1.0204, 50 µs/rev pypy x_revs_x_added_x_copies ac52eb7bbbb0 72e022663155 : 7 revs, 0.000202 s, 0.000117 s, -0.000085 s, × 0.5792, 16 µs/rev pypy x_revs_x00_added_x_copies c3b14617fbd7 ace7255d9a26 : 1 revs, 0.000409 s, 0.6f1f4a s, -0.000087 s, × 0.7873, 322 µs/rev pypy x_revs_x000_added_x000_copies df6f7a526b60 a83dc6a2d56f : 6 revs, 0.011984 s, 0.011949 s, -0.000035 s, × 0.9971, 1991 µs/rev pypy x000_revs_xx00_added_0_copies 89a76aede314 2f22446ff07e : 4785 revs, 0.050820 s, 0.050802 s, -0.000018 s, × 0.9996, 10 µs/rev pypy x000_revs_x000_added_x_copies 8a3b5bfd266e 2c68e87c3efe : 6780 revs, 0.087953 s, 0.088090 s, +0.000137 s, × 1.0016, 12 µs/rev pypy x000_revs_x000_added_x000_copies 89a76aede314 7b3dda341c84 : 5441 revs, 0.062902 s, 0.062079 s, -0.000823 s, × 0.9869, 11 µs/rev pypy x0000_revs_x_added_0_copies d1defd0dc478 c9cb1334cc78 : 43645 revs, 0.679234 s, 0.635337 s, -0.043897 s, × 0.9354, 14 µs/rev pypy x0000_revs_xx000_added_0_copies bf2c629d0071 4ffed77c095c : 2 revs, 0.013095 s, 0.013262 s, +0.000167 s, × 1.0128, 6631 µs/rev pypy x0000_revs_xx000_added_x000_copies 08ea3258278e d9fa043f30c0 : 11316 revs, 0.120910 s, 0.120085 s, -0.000825 s, × 0.9932, 10 µs/rev netbeans x_revs_x_added_0_copies fb0955ffcbcd a01e9239f9e7 : 2 revs, 0.000087 s, 0.000085 s, -0.000002 s, × 0.9770, 42 µs/rev netbeans x_revs_x000_added_0_copies 6f360122949f 20eb231cc7d0 : 2 revs, 0.000107 s, 0.000110 s, +0.000003 s, × 1.0280, 55 µs/rev netbeans x_revs_x_added_x_copies 1ada3faf6fb6 5a39d12eecf4 : 3 revs, 0.000186 s, 0.000177 s, -0.000009 s, × 0.9516, 59 µs/rev netbeans x_revs_x00_added_x_copies 35be93ba1e2c 9eec5e90c05f : 9 revs, 0.000754 s, 0.000743 s, -0.000011 s, × 0.9854, 82 µs/rev netbeans x000_revs_xx00_added_0_copies eac3045b4fdd 51d4ae7f1290 : 1421 revs, 0.010443 s, 0.010168 s, -0.000275 s, × 0.9737, 7 µs/rev netbeans x000_revs_x000_added_x_copies e2063d266acd 6081d72689dc : 1533 revs, 0.015697 s, 0.015946 s, +0.000249 s, × 1.0159, 10 µs/rev netbeans x000_revs_x000_added_x000_copies ff453e9fee32 411350406ec2 : 5750 revs, 0.063528 s, 0.062712 s, -0.000816 s, × 0.9872, 10 µs/rev netbeans x0000_revs_xx000_added_x000_copies 588c2d1ced70 1aad62e59ddd : 66949 revs, 0.545515 s, 0.523832 s, -0.021683 s, × 0.9603, 7 µs/rev mozilla-central x_revs_x_added_0_copies 3697f962bb7b 7015fcdd43a2 : 2 revs, 0.000089 s, 0.000090 s, +0.000001 s, × 1.0112, 45 µs/rev mozilla-central x_revs_x000_added_0_copies dd390860c6c9 40d0c5bed75d : 8 revs, 0.000265 s, 0.000264 s, -0.000001 s, × 0.9962, 33 µs/rev mozilla-central x_revs_x_added_x_copies 8d198483ae3b 14207ffc2b2f : 9 revs, 0.000381 s, 0.000187 s, -0.000194 s, × 0.4908, 20 µs/rev mozilla-central x_revs_x00_added_x_copies 98cbc58cc6bc 446a150332c3 : 7 revs, 0.000672 s, 0.000665 s, -0.000007 s, × 0.9896, 95 µs/rev mozilla-central x_revs_x000_added_x000_copies 3c684b4b8f68 0a5e72d1b479 : 3 revs, 0.003497 s, 0.003556 s, +0.000059 s, × 1.0169, 1185 µs/rev mozilla-central x_revs_x0000_added_x0000_copies effb563bb7e5 c07a39dc4e80 : 6 revs, 0.073204 s, 0.071345 s, -0.001859 s, × 0.9746, 11890 µs/rev mozilla-central x000_revs_xx00_added_0_copies 6100d773079a 04a55431795e : 1593 revs, 0.006482 s, 0.006551 s, +0.000069 s, × 1.0106, 4 µs/rev mozilla-central x000_revs_x000_added_x_copies 9f17a6fc04f9 2d37b966abed : 41 revs, 0.005066 s, 0.005078 s, +0.000012 s, × 1.0024, 123 µs/rev mozilla-central x000_revs_x000_added_x000_copies 7c97034feb78 4407bd0c6330 : 7839 revs, 0.065707 s, 0.065823 s, +0.000116 s, × 1.0018, 8 µs/rev mozilla-central x0000_revs_xx000_added_0_copies 9eec5917337d 67118cc6dcad : 615 revs, 0.026800 s, 0.027050 s, +0.000250 s, × 1.0093, 43 µs/rev mozilla-central x0000_revs_xx000_added_x000_copies f78c615a656c 96a38b690156 : 30263 revs, 0.203856 s, 0.202443 s, -0.001413 s, × 0.9931, 6 µs/rev mozilla-central x00000_revs_x0000_added_x0000_copies 6832ae71433c 4c222a1d9a00 : 153721 revs, 1.293394 s, 1.261583 s, -0.031811 s, × 0.9754, 8 µs/rev mozilla-central x00000_revs_x00000_added_x000_copies 76caed42cf7c 1daa622bbe42 : 204976 revs, 1.698239 s, 1.643869 s, -0.054370 s, × 0.9680, 8 µs/rev mozilla-try x_revs_x_added_0_copies aaf6dde0deb8 9790f499805a : 2 revs, 0.000875 s, 0.000868 s, -0.000007 s, × 0.9920, 434 µs/rev mozilla-try x_revs_x000_added_0_copies d8d0222927b4 5bb8ce8c7450 : 2 revs, 0.000891 s, 0.000887 s, -0.000004 s, × 0.9955, 443 µs/rev mozilla-try x_revs_x_added_x_copies 092fcca11bdb 936255a0384a : 4 revs, 0.000292 s, 0.000168 s, -0.000124 s, × 0.5753, 42 µs/rev mozilla-try x_revs_x00_added_x_copies b53d2fadbdb5 017afae788ec : 2 revs, 0.003939 s, 0.001160 s, -0.002779 s, × 0.2945, 580 µs/rev mozilla-try x_revs_x000_added_x000_copies 20408ad61ce5 6f0ee96e21ad : 1 revs, 0.033027 s, 0.033016 s, -0.000011 s, × 0.9997, 33016 µs/rev mozilla-try x_revs_x0000_added_x0000_copies effb563bb7e5 c07a39dc4e80 : 6 revs, 0.073703 s, 0.073312 s, -0.39ae31 s, × 0.9947, 12218 µs/rev mozilla-try x000_revs_xx00_added_0_copies 6100d773079a 04a55431795e : 1593 revs, 0.006469 s, 0.006485 s, +0.000016 s, × 1.0025, 4 µs/rev mozilla-try x000_revs_x000_added_x_copies 9f17a6fc04f9 2d37b966abed : 41 revs, 0.005278 s, 0.005494 s, +0.000216 s, × 1.0409, 134 µs/rev mozilla-try x000_revs_x000_added_x000_copies 1346fd0130e4 4c65cbdabc1f : 6657 revs, 0.064995 s, 0.064879 s, -0.000116 s, × 0.9982, 9 µs/rev mozilla-try x0000_revs_x_added_0_copies 63519bfd42ee a36a2a865d92 : 40314 revs, 0.301041 s, 0.301469 s, +0.000428 s, × 1.0014, 7 µs/rev mozilla-try x0000_revs_x_added_x_copies 9fe69ff0762d bcabf2a78927 : 38690 revs, 0.285575 s, 0.297113 s, +0.011538 s, × 1.0404, 7 µs/rev mozilla-try x0000_revs_xx000_added_x_copies 156f6e2674f2 4d0f2c178e66 : 8598 revs, 0.085597 s, 0.085890 s, +0.000293 s, × 1.0034, 9 µs/rev mozilla-try x0000_revs_xx000_added_0_copies 9eec5917337d 67118cc6dcad : 615 revs, 0.027118 s, 0.027718 s, +0.000600 s, × 1.0221, 45 µs/rev mozilla-try x0000_revs_xx000_added_x000_copies 89294cd501d9 7ccb2fc7ccb5 : 97052 revs, 2.119204 s, 2.048949 s, -0.070255 s, × 0.9668, 21 µs/rev mozilla-try x0000_revs_x0000_added_x0000_copies e928c65095ed e951f4ad123a : 52031 revs, 0.701479 s, 0.685924 s, -0.015555 s, × 0.9778, 13 µs/rev mozilla-try x00000_revs_x_added_0_copies 6a320851d377 1ebb79acd503 : 363753 revs, 4.482399 s, 4.482891 s, +0.000492 s, × 1.0001, 12 µs/rev mozilla-try x00000_revs_x00000_added_0_copies dc8a3ca7010e d16fde900c9c : 34414 revs, 0.574082 s, 0.577633 s, +0.003551 s, × 1.0062, 16 µs/rev mozilla-try x00000_revs_x_added_x_copies 5173c4b6f97c 95d83ee7242d : 362229 revs, 4.480366 s, 4.397816 s, -0.082550 s, × 0.9816, 12 µs/rev mozilla-try x00000_revs_x000_added_x_copies 9126823d0e9c ca82787bb23c : 359344 revs, 4.369070 s, 4.370538 s, +0.001468 s, × 1.0003, 12 µs/rev mozilla-try x00000_revs_x0000_added_x0000_copies 8d3fafa80d4b eb884023b810 : 192665 revs, 1.592506 s, 1.570439 s, -0.022067 s, × 0.9861, 8 µs/rev mozilla-try x00000_revs_x00000_added_x0000_copies 1b661134e2ca 1ae03d022d6d : 228985 revs, 87.824489 s, 88.388512 s, +0.564023 s, × 1.0064, 386 µs/rev mozilla-try x00000_revs_x00000_added_x000_copies 9b2a99adc05e 8e29777b48e6 : 382065 revs, 43.304637 s, 34.443661 s, -8.860976 s, × 0.7954, 90 µs/rev private : 459513 revs, 33.853687 s, 27.370148 s, -6.483539 s, × 0.8085, 59 µs/rev Differential Revision: https://phab.mercurial-scm.org/D9653
author Pierre-Yves David <pierre-yves.david@octobus.net>
date Wed, 16 Dec 2020 11:11:05 +0100
parents 688fc33e105d
children 58a814d062ca
line wrap: on
line source

====================================
Test delta choice with sparse revlog
====================================

Sparse-revlog usually shows the most gain on Manifest. However, it is simpler
to general an appropriate file, so we test with a single file instead. The
goal is to observe intermediate snapshot being created.

We need a large enough file. Part of the content needs to be replaced
repeatedly while some of it changes rarely.

  $ bundlepath="$TESTDIR/artifacts/cache/big-file-churn.hg"

  $ expectedhash=`cat "$bundlepath".md5`

#if slow

  $ if [ ! -f "$bundlepath" ]; then
  >     "$TESTDIR"/artifacts/scripts/generate-churning-bundle.py > /dev/null
  > fi

#else

  $ if [ ! -f "$bundlepath" ]; then
  >     echo 'skipped: missing artifact, run "'"$TESTDIR"'/artifacts/scripts/generate-churning-bundle.py"'
  >     exit 80
  > fi

#endif

  $ currenthash=`f -M "$bundlepath" | cut -d = -f 2`
  $ if [ "$currenthash" != "$expectedhash" ]; then
  >     echo 'skipped: outdated artifact, md5 "'"$currenthash"'" expected "'"$expectedhash"'" run "'"$TESTDIR"'/artifacts/scripts/generate-churning-bundle.py"'
  >     exit 80
  > fi

  $ cat >> $HGRCPATH << EOF
  > [format]
  > sparse-revlog = yes
  > maxchainlen = 15
  > [storage]
  > revlog.optimize-delta-parent-choice = yes
  > revlog.reuse-external-delta = no
  > EOF
  $ hg init sparse-repo
  $ cd sparse-repo
  $ hg unbundle $bundlepath
  adding changesets
  adding manifests
  adding file changes
  added 5001 changesets with 5001 changes to 1 files (+89 heads)
  new changesets 9706f5af64f4:d9032adc8114 (5001 drafts)
  (run 'hg heads' to see heads, 'hg merge' to merge)
  $ hg up
  1 files updated, 0 files merged, 0 files removed, 0 files unresolved
  updated to "d9032adc8114: commit #5000"
  89 other heads for branch "default"

  $ hg log --stat -r 0:3
  changeset:   0:9706f5af64f4
  user:        test
  date:        Thu Jan 01 00:00:00 1970 +0000
  summary:     initial commit
  
   SPARSE-REVLOG-TEST-FILE |  10500 ++++++++++++++++++++++++++++++++++++++++++++++
   1 files changed, 10500 insertions(+), 0 deletions(-)
  
  changeset:   1:724907deaa5e
  user:        test
  date:        Thu Jan 01 00:00:00 1970 +0000
  summary:     commit #1
  
   SPARSE-REVLOG-TEST-FILE |  1068 +++++++++++++++++++++++-----------------------
   1 files changed, 534 insertions(+), 534 deletions(-)
  
  changeset:   2:62c41bce3e5d
  user:        test
  date:        Thu Jan 01 00:00:00 1970 +0000
  summary:     commit #2
  
   SPARSE-REVLOG-TEST-FILE |  1068 +++++++++++++++++++++++-----------------------
   1 files changed, 534 insertions(+), 534 deletions(-)
  
  changeset:   3:348a9cbd6959
  user:        test
  date:        Thu Jan 01 00:00:00 1970 +0000
  summary:     commit #3
  
   SPARSE-REVLOG-TEST-FILE |  1068 +++++++++++++++++++++++-----------------------
   1 files changed, 534 insertions(+), 534 deletions(-)
  

  $ f -s .hg/store/data/*.d
  .hg/store/data/_s_p_a_r_s_e-_r_e_v_l_o_g-_t_e_s_t-_f_i_l_e.d: size=63327412
  $ hg debugrevlog *
  format : 1
  flags  : generaldelta
  
  revisions     :     5001
      merges    :      625 (12.50%)
      normal    :     4376 (87.50%)
  revisions     :     5001
      empty     :        0 ( 0.00%)
                     text  :        0 (100.00%)
                     delta :        0 (100.00%)
      snapshot  :      383 ( 7.66%)
        lvl-0   :              3 ( 0.06%)
        lvl-1   :             20 ( 0.40%)
        lvl-2   :             68 ( 1.36%)
        lvl-3   :            112 ( 2.24%)
        lvl-4   :            180 ( 3.60%)
      deltas    :     4618 (92.34%)
  revision size : 63327412
      snapshot  :  9886710 (15.61%)
        lvl-0   :         603104 ( 0.95%)
        lvl-1   :        1559991 ( 2.46%)
        lvl-2   :        2295592 ( 3.62%)
        lvl-3   :        2531199 ( 4.00%)
        lvl-4   :        2896824 ( 4.57%)
      deltas    : 53440702 (84.39%)
  
  chunks        :     5001
      0x78 (x)  :     5001 (100.00%)
  chunks size   : 63327412
      0x78 (x)  : 63327412 (100.00%)
  
  avg chain length  :        9
  max chain length  :       15
  max chain reach   : 28248745
  compression ratio :       27
  
  uncompressed data size (min/max/avg) : 346468 / 346472 / 346471
  full revision size (min/max/avg)     : 201008 / 201050 / 201034
  inter-snapshot size (min/max/avg)    : 11596 / 168150 / 24430
      level-1   (min/max/avg)          : 16653 / 168150 / 77999
      level-2   (min/max/avg)          : 12951 / 85595 / 33758
      level-3   (min/max/avg)          : 11608 / 43029 / 22599
      level-4   (min/max/avg)          : 11596 / 21632 / 16093
  delta size (min/max/avg)             : 10649 / 107163 / 11572
  
  deltas against prev  : 3910 (84.67%)
      where prev = p1  : 3910     (100.00%)
      where prev = p2  :    0     ( 0.00%)
      other            :    0     ( 0.00%)
  deltas against p1    :  648 (14.03%)
  deltas against p2    :   60 ( 1.30%)
  deltas against other :    0 ( 0.00%)