tests/test-ancestor.py
author Pierre-Yves David <pierre-yves.david@octobus.net>
Sat, 13 Apr 2024 23:40:28 +0200
changeset 51592 24844407fa0d
parent 50928 d718eddf01d9
permissions -rw-r--r--
perf: clear vfs audit_cache before each run When generating a stream clone, we spend a large amount of time auditing path. Before this changes, the first run was warming the vfs cache for the other runs, leading to a large runtime difference and a "faulty" reported timing for the operation. We now clear this important cache between run to get a more realistic timing. Below are some example of median time change when clearing these cases. The maximum time for a run did not changed significantly. ### data-env-vars.name = mozilla-central-2018-08-01-zstd-sparse-revlog # benchmark.name = hg.perf.exchange.stream.generate # bin-env-vars.hg.flavor = default # bin-env-vars.hg.py-re2-module = default # benchmark.variants.version = latest no-clearing: 17.289905 cache-clearing: 21.587965 (+24.86%, +4.30) ## data-env-vars.name = mozilla-central-2024-03-22-zstd-sparse-revlog no-clearing: 32.670748 cache-clearing: 40.467095 (+23.86%, +7.80) ## data-env-vars.name = mozilla-try-2019-02-18-zstd-sparse-revlog no-clearing: 37.838858 cache-clearing: 46.072749 (+21.76%, +8.23) ## data-env-vars.name = mozilla-unified-2024-03-22-zstd-sparse-revlog no-clearing: 32.969395 cache-clearing: 39.646209 (+20.25%, +6.68) In addition, this significantly reduce the timing difference between the performance command, from the perf extensions and a `real `hg bundle` call producing a stream bundle. Some significant differences remain especially on the "mozilla-try" repositories, but they are now smaller. Note that some of that difference will actually not be attributable to the stream generation (like maybe phases or branch map computation). Below are some benchmarks done on a currently draft changeset fixing some unrelated slowness in `hg bundle` (34a78972af409d1ff37c29e60f6ca811ad1a457d) ### data-env-vars.name = mozilla-central-2018-08-01-zstd-sparse-revlog # bin-env-vars.hg.flavor = default # bin-env-vars.hg.py-re2-module = default hg.perf.exchange.stream.generate: 21.587965 hg.command.bundle: 24.301799 (+12.57%, +2.71) ## data-env-vars.name = mozilla-central-2024-03-22-zstd-sparse-revlog hg.perf.exchange.stream.generate: 40.467095 hg.command.bundle: 44.831317 (+10.78%, +4.36) ## data-env-vars.name = mozilla-unified-2024-03-22-zstd-sparse-revlog hg.perf.exchange.stream.generate: 39.646209 hg.command.bundle: 45.395258 (+14.50%, +5.75) ## data-env-vars.name = mozilla-try-2019-02-18-zstd-sparse-revlog hg.perf.exchange.stream.generate: 46.072749 hg.command.bundle: 55.882608 (+21.29%, +9.81) ## data-env-vars.name = mozilla-try-2023-03-22-zlib-general-delta hg.perf.exchange.stream.generate: 334.716708 hg.command.bundle: 377.856767 (+12.89%, +43.14) ## data-env-vars.name = mozilla-try-2023-03-22-zstd-sparse-revlog hg.perf.exchange.stream.generate: 302.972301 hg.command.bundle: 326.098755 (+7.63%, +23.13)

import binascii
import getopt
import math
import os
import random
import sys
import time

from mercurial.node import nullrev
from mercurial import (
    ancestor,
    debugcommands,
    hg,
    ui as uimod,
)


def buildgraph(rng, nodes=100, rootprob=0.05, mergeprob=0.2, prevprob=0.7):
    """nodes: total number of nodes in the graph
    rootprob: probability that a new node (not 0) will be a root
    mergeprob: probability that, excluding a root a node will be a merge
    prevprob: probability that p1 will be the previous node

    return value is a graph represented as an adjacency list.
    """
    graph = [None] * nodes
    for i in range(nodes):
        if i == 0 or rng.random() < rootprob:
            graph[i] = [nullrev]
        elif i == 1:
            graph[i] = [0]
        elif rng.random() < mergeprob:
            if i == 2 or rng.random() < prevprob:
                # p1 is prev
                p1 = i - 1
            else:
                p1 = rng.randrange(i - 1)
            p2 = rng.choice(list(range(0, p1)) + list(range(p1 + 1, i)))
            graph[i] = [p1, p2]
        elif rng.random() < prevprob:
            graph[i] = [i - 1]
        else:
            graph[i] = [rng.randrange(i - 1)]

    return graph


def buildancestorsets(graph):
    ancs = [None] * len(graph)
    for i in range(len(graph)):
        ancs[i] = {i}
        if graph[i] == [nullrev]:
            continue
        for p in graph[i]:
            ancs[i].update(ancs[p])
    return ancs


class naiveincrementalmissingancestors:
    def __init__(self, ancs, bases):
        self.ancs = ancs
        self.bases = set(bases)

    def addbases(self, newbases):
        self.bases.update(newbases)

    def removeancestorsfrom(self, revs):
        for base in self.bases:
            if base != nullrev:
                revs.difference_update(self.ancs[base])
        revs.discard(nullrev)

    def missingancestors(self, revs):
        res = set()
        for rev in revs:
            if rev != nullrev:
                res.update(self.ancs[rev])
        for base in self.bases:
            if base != nullrev:
                res.difference_update(self.ancs[base])
        return sorted(res)


def test_missingancestors(seed, rng):
    # empirically observed to take around 1 second
    graphcount = 100
    testcount = 10
    inccount = 10
    nerrs = [0]
    # the default mu and sigma give us a nice distribution of mostly
    # single-digit counts (including 0) with some higher ones
    def lognormrandom(mu, sigma):
        return int(math.floor(rng.lognormvariate(mu, sigma)))

    def samplerevs(nodes, mu=1.1, sigma=0.8):
        count = min(lognormrandom(mu, sigma), len(nodes))
        return rng.sample(nodes, count)

    def err(seed, graph, bases, seq, output, expected):
        if nerrs[0] == 0:
            print('seed:', hex(seed)[:-1], file=sys.stderr)
        if gerrs[0] == 0:
            print('graph:', graph, file=sys.stderr)
        print('* bases:', bases, file=sys.stderr)
        print('* seq: ', seq, file=sys.stderr)
        print('*  output:  ', output, file=sys.stderr)
        print('*  expected:', expected, file=sys.stderr)
        nerrs[0] += 1
        gerrs[0] += 1

    for g in range(graphcount):
        graph = buildgraph(rng)
        ancs = buildancestorsets(graph)
        gerrs = [0]
        for _ in range(testcount):
            # start from nullrev to include it as a possibility
            graphnodes = range(nullrev, len(graph))
            bases = samplerevs(graphnodes)

            # fast algorithm
            inc = ancestor.incrementalmissingancestors(graph.__getitem__, bases)
            # reference slow algorithm
            naiveinc = naiveincrementalmissingancestors(ancs, bases)
            seq = []
            for _ in range(inccount):
                if rng.random() < 0.2:
                    newbases = samplerevs(graphnodes)
                    seq.append(('addbases', newbases))
                    inc.addbases(newbases)
                    naiveinc.addbases(newbases)
                if rng.random() < 0.4:
                    # larger set so that there are more revs to remove from
                    revs = samplerevs(graphnodes, mu=1.5)
                    seq.append(('removeancestorsfrom', revs))
                    hrevs = set(revs)
                    rrevs = set(revs)
                    inc.removeancestorsfrom(hrevs)
                    naiveinc.removeancestorsfrom(rrevs)
                    if hrevs != rrevs:
                        err(
                            seed,
                            graph,
                            bases,
                            seq,
                            sorted(hrevs),
                            sorted(rrevs),
                        )
                else:
                    revs = samplerevs(graphnodes)
                    seq.append(('missingancestors', revs))
                    h = inc.missingancestors(revs)
                    r = naiveinc.missingancestors(revs)
                    if h != r:
                        err(seed, graph, bases, seq, h, r)


# graph is a dict of child->parent adjacency lists for this graph:
# o  13
# |
# | o  12
# | |
# | | o    11
# | | |\
# | | | | o  10
# | | | | |
# | o---+ |  9
# | | | | |
# o | | | |  8
#  / / / /
# | | o |  7
# | | | |
# o---+ |  6
#  / / /
# | | o  5
# | |/
# | o  4
# | |
# o |  3
# | |
# | o  2
# |/
# o  1
# |
# o  0

graph = {
    0: [-1, -1],
    1: [0, -1],
    2: [1, -1],
    3: [1, -1],
    4: [2, -1],
    5: [4, -1],
    6: [4, -1],
    7: [4, -1],
    8: [-1, -1],
    9: [6, 7],
    10: [5, -1],
    11: [3, 7],
    12: [9, -1],
    13: [8, -1],
}


def test_missingancestors_explicit():
    """A few explicit cases, easier to check for catching errors in refactors.

    The bigger graph at the end has been produced by the random generator
    above, and we have some evidence that the other tests don't cover it.
    """
    for i, (bases, revs) in enumerate(
        (
            ({1, 2, 3, 4, 7}, set(range(10))),
            ({10}, set({11, 12, 13, 14})),
            ({7}, set({1, 2, 3, 4, 5})),
        )
    ):
        print("%% removeancestorsfrom(), example %d" % (i + 1))
        missanc = ancestor.incrementalmissingancestors(graph.get, bases)
        missanc.removeancestorsfrom(revs)
        print("remaining (sorted): %s" % sorted(list(revs)))

    for i, (bases, revs) in enumerate(
        (
            ({10}, {11}),
            ({11}, {10}),
            ({7}, {9, 11}),
        )
    ):
        print("%% missingancestors(), example %d" % (i + 1))
        missanc = ancestor.incrementalmissingancestors(graph.get, bases)
        print("return %s" % missanc.missingancestors(revs))

    print("% removeancestorsfrom(), bigger graph")
    vecgraph = [
        [-1, -1],
        [0, -1],
        [1, 0],
        [2, 1],
        [3, -1],
        [4, -1],
        [5, 1],
        [2, -1],
        [7, -1],
        [8, -1],
        [9, -1],
        [10, 1],
        [3, -1],
        [12, -1],
        [13, -1],
        [14, -1],
        [4, -1],
        [16, -1],
        [17, -1],
        [18, -1],
        [19, 11],
        [20, -1],
        [21, -1],
        [22, -1],
        [23, -1],
        [2, -1],
        [3, -1],
        [26, 24],
        [27, -1],
        [28, -1],
        [12, -1],
        [1, -1],
        [1, 9],
        [32, -1],
        [33, -1],
        [34, 31],
        [35, -1],
        [36, 26],
        [37, -1],
        [38, -1],
        [39, -1],
        [40, -1],
        [41, -1],
        [42, 26],
        [0, -1],
        [44, -1],
        [45, 4],
        [40, -1],
        [47, -1],
        [36, 0],
        [49, -1],
        [-1, -1],
        [51, -1],
        [52, -1],
        [53, -1],
        [14, -1],
        [55, -1],
        [15, -1],
        [23, -1],
        [58, -1],
        [59, -1],
        [2, -1],
        [61, 59],
        [62, -1],
        [63, -1],
        [-1, -1],
        [65, -1],
        [66, -1],
        [67, -1],
        [68, -1],
        [37, 28],
        [69, 25],
        [71, -1],
        [72, -1],
        [50, 2],
        [74, -1],
        [12, -1],
        [18, -1],
        [77, -1],
        [78, -1],
        [79, -1],
        [43, 33],
        [81, -1],
        [82, -1],
        [83, -1],
        [84, 45],
        [85, -1],
        [86, -1],
        [-1, -1],
        [88, -1],
        [-1, -1],
        [76, 83],
        [44, -1],
        [92, -1],
        [93, -1],
        [9, -1],
        [95, 67],
        [96, -1],
        [97, -1],
        [-1, -1],
    ]
    problem_rev = 28
    problem_base = 70
    # problem_rev is a parent of problem_base, but a faulty implementation
    # could forget to remove it.
    bases = {60, 26, 70, 3, 96, 19, 98, 49, 97, 47, 1, 6}
    if problem_rev not in vecgraph[problem_base] or problem_base not in bases:
        print("Conditions have changed")
    missanc = ancestor.incrementalmissingancestors(vecgraph.__getitem__, bases)
    revs = {4, 12, 41, 28, 68, 38, 1, 30, 56, 44}
    missanc.removeancestorsfrom(revs)
    if 28 in revs:
        print("Failed!")
    else:
        print("Ok")


def genlazyancestors(revs, stoprev=0, inclusive=False):
    print(
        (
            "%% lazy ancestor set for %s, stoprev = %s, inclusive = %s"
            % (revs, stoprev, inclusive)
        )
    )
    return ancestor.lazyancestors(
        graph.get, revs, stoprev=stoprev, inclusive=inclusive
    )


def printlazyancestors(s, l):
    print('membership: %r' % [n for n in l if n in s])
    print('iteration:  %r' % list(s))


def test_lazyancestors():
    # Empty revs
    s = genlazyancestors([])
    printlazyancestors(s, [3, 0, -1])

    # Standard example
    s = genlazyancestors([11, 13])
    printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0])

    # Standard with ancestry in the initial set (1 is ancestor of 3)
    s = genlazyancestors([1, 3])
    printlazyancestors(s, [1, -1, 0])

    # Including revs
    s = genlazyancestors([11, 13], inclusive=True)
    printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0])

    # Test with stoprev
    s = genlazyancestors([11, 13], stoprev=6)
    printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0])
    s = genlazyancestors([11, 13], stoprev=6, inclusive=True)
    printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0])

    # Test with stoprev >= min(initrevs)
    s = genlazyancestors([11, 13], stoprev=11, inclusive=True)
    printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0])
    s = genlazyancestors([11, 13], stoprev=12, inclusive=True)
    printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0])

    # Contiguous chains: 5->4, 2->1 (where 1 is in seen set), 1->0
    s = genlazyancestors([10, 1], inclusive=True)
    printlazyancestors(s, [2, 10, 4, 5, -1, 0, 1])


# The C gca algorithm requires a real repo. These are textual descriptions of
# DAGs that have been known to be problematic, and, optionally, known pairs
# of revisions and their expected ancestor list.
dagtests = [
    (b'+2*2*2/*3/2', {}),
    (b'+3*3/*2*2/*4*4/*4/2*4/2*2', {}),
    (b'+2*2*/2*4*/4*/3*2/4', {(6, 7): [3, 5]}),
]


def test_gca():
    u = uimod.ui.load()
    for i, (dag, tests) in enumerate(dagtests):
        repo = hg.repository(u, b'gca%d' % i, create=1)
        cl = repo.changelog
        if not hasattr(cl.index, 'ancestors'):
            # C version not available
            return

        debugcommands.debugbuilddag(u, repo, dag)
        # Compare the results of the Python and C versions. This does not
        # include choosing a winner when more than one gca exists -- we make
        # sure both return exactly the same set of gcas.
        # Also compare against expected results, if available.
        for a in cl:
            for b in cl:
                cgcas = sorted(cl.index.ancestors(a, b))
                pygcas = sorted(ancestor.ancestors(cl.parentrevs, a, b))
                expected = None
                if (a, b) in tests:
                    expected = tests[(a, b)]
                if cgcas != pygcas or (expected and cgcas != expected):
                    print(
                        "test_gca: for dag %s, gcas for %d, %d:" % (dag, a, b)
                    )
                    print("  C returned:      %s" % cgcas)
                    print("  Python returned: %s" % pygcas)
                    if expected:
                        print("  expected:        %s" % expected)


def main():
    seed = None
    opts, args = getopt.getopt(sys.argv[1:], 's:', ['seed='])
    for o, a in opts:
        if o in ('-s', '--seed'):
            seed = int(a, base=0)  # accepts base 10 or 16 strings

    if seed is None:
        try:
            seed = int(binascii.hexlify(os.urandom(16)), 16)
        except AttributeError:
            seed = int(time.time() * 1000)

    rng = random.Random(seed)
    test_missingancestors_explicit()
    test_missingancestors(seed, rng)
    test_lazyancestors()
    test_gca()


if __name__ == '__main__':
    main()