comparison mercurial/context.py @ 29861:2f6d5c60f6fc stable

annotate: pre-calculate the "needed" dictionary (issue5360)

The "needed" dict is used as a reference counter to free items in the giant
"hist" dict. However, currently it is not very accurate and can lead to
dropping "hist" items unnecessarily, for example, with the following DAG,

       -3-
      /   \
  0--1--2--4--

The current algorithm will visit and calculate rev 1 twice, undesired. And
it tries to be smart by clearing rev 1's parents: "pcache[1] = []" at the
time hist[1] being accessed (note: hist[1] needs to be used twice, by rev 2
and rev 3). It can result in incorrect results if p1 of rev 4 deletes chunks
belonging to rev 0.

However, simply removing "needed" is not okay, because it will consume 10x
memory:

  # without any change
  % HGRCPATH= lrun ./hg annotate mercurial/commands.py -r d130a38 3>&2 [1]
  MEMORY   49074176
  CPUTIME  9.213
  REALTIME 9.270

  # with "needed" removed
  MEMORY   637673472
  CPUTIME  8.164
  REALTIME 8.249

This patch moves "needed" (and "pcache") calculation to a separate DFS to
address the issue. It improves perf and fixes issue5360 by correctly reusing
hist, while maintaining low memory usage. Some additional attempt has been
made to further reduce memory usage, like changing "pcache[f] = []" to "del
pcache[f]". Therefore the result can be both faster and lower memory usage:

  # with this patch applied
  MEMORY   47575040
  CPUTIME  7.870
  REALTIME 7.926

[1]: lrun is a lightweight sandbox built on Linux cgroup and namespace. It's
     used to measure CPU and memory usage here. Source code is available at
     github.com/quark-zju/lrun.

29853:d3b2da20a9c5

        # This algorithm would prefer to be recursive, but Python is a
        # bit recursion-hostile. Instead we do an iterative
        # depth-first search.

        visit = [base]
        hist = {}
        pcache = {}
        needed = {base: 1}
        while visit:
            f = visit[-1]
            pcached = f in pcache
            if not pcached:
                pcache[f] = parents(f)

            ready = True
            pl = pcache[f]
            for p in pl:
                if p not in hist:
                    ready = False
                    visit.append(p)
                if not pcached:
                    needed[p] = needed.get(p, 0) + 1
            if ready:
                visit.pop()
                reusable = f in hist
                if reusable:
                    curr = hist[f]
                else:
                    curr = decorate(f.data(), f)
                for p in pl:
                    if not reusable:
                        curr = pair(hist[p], curr)
                    if needed[p] == 1:
                        del hist[p]
                        del needed[p]
                    else:
                        needed[p] -= 1

                hist[f] = curr
                pcache[f] = []

        return zip(hist[base][0], hist[base][1].splitlines(True))

    def ancestors(self, followfirst=False):
        visit = {}

29861:2f6d5c60f6fc

        # This algorithm would prefer to be recursive, but Python is a
        # bit recursion-hostile. Instead we do an iterative
        # depth-first search.

        # 1st DFS pre-calculates pcache and needed
        visit = [base]
        pcache = {}
        needed = {base: 1}
        while visit:
            f = visit.pop()
            if f in pcache:
                continue
            pl = parents(f)
            pcache[f] = pl
            for p in pl:
                needed[p] = needed.get(p, 0) + 1
                if p not in pcache:
                    visit.append(p)

        # 2nd DFS does the actual annotate
        visit[:] = [base]
        hist = {}
        while visit:
            f = visit[-1]
            if f in hist:
                visit.pop()
                continue

            ready = True
            pl = pcache[f]
            for p in pl:
                if p not in hist:
                    ready = False
                    visit.append(p)
            if ready:
                visit.pop()
                curr = decorate(f.data(), f)
                for p in pl:
                    curr = pair(hist[p], curr)
                    if needed[p] == 1:
                        del hist[p]
                        del needed[p]
                    else:
                        needed[p] -= 1

                hist[f] = curr
                del pcache[f]

        return zip(hist[base][0], hist[base][1].splitlines(True))

    def ancestors(self, followfirst=False):
        visit = {}