mercurial/revlog.py

38717:aa21a9ad46ea

        return self._data[rev]

    def length(self, rev):
        return self.end(rev) - self.start(rev)

def _trimchunk(revlog, revs, startidx, endidx=None):
    """returns revs[startidx:endidx] without empty trailing revs

    Doctest Setup
    >>> revlog = _testrevlog([

    """
    if not revs:
        return 0
    return revlog.end(revs[-1]) - revlog.start(revs[0])

def _slicechunk(revlog, revs, targetsize=None):
    """slice revs to reduce the amount of unrelated data to be read from disk.

    ``revs`` is sliced into groups that should be read in one time.
    Assume that revs are sorted.

    [[0], [11, 13, 15]]
    >>> list(_slicechunk(revlog, [1, 2, 3, 5, 8, 10, 11, 14]))
    [[1, 2], [5, 8, 10, 11], [14]]

    Slicing with a maximum chunk size
    >>> list(_slicechunk(revlog, [0, 11, 13, 15], 15))
    [[0], [11], [13], [15]]
    >>> list(_slicechunk(revlog, [0, 11, 13, 15], 20))
    [[0], [11], [13, 15]]
    """
    if targetsize is not None:
        targetsize = max(targetsize, revlog._srmingapsize)
    for chunk in _slicechunktodensity(revlog, revs,
                                      revlog._srdensitythreshold,
                                      revlog._srmingapsize):
        for subchunk in _slicechunktosize(revlog, chunk, targetsize):
            yield subchunk

def _slicechunktosize(revlog, revs, targetsize):
    """slice revs to match the target size

    This is intended to be used on chunk that density slicing selected by that
    are still too large compared to the read garantee of revlog. This might
    happens when "minimal gap size" interrupted the slicing or when chain are

            startrevidx = idx
            startdata = revlog.start(r)
            endrevidx = idx
    yield _trimchunk(revlog, revs, startrevidx)

def _slicechunktodensity(revlog, revs, targetdensity=0.5, mingapsize=0):
    """slice revs to reduce the amount of unrelated data to be read from disk.

    ``revs`` is sliced into groups that should be read in one time.
    Assume that revs are sorted.

    The initial chunk is sliced until the overall density (payload/chunks-span
    ratio) is above `targetdensity`. No gap smaller than `mingapsize` is
    skipped.

    if len(revs) <= 1:
        yield revs
        return

    readdata = deltachainspan = _segmentspan(revlog, revs)

    if deltachainspan < mingapsize:
        yield revs
        return

    chainpayload = sum(length(r) for r in revs)

    if deltachainspan:
        density = chainpayload / float(deltachainspan)
    else:
        density = 1.0

    if density >= targetdensity:
        yield revs
        return

    # Store the gaps in a heap to have them sorted by decreasing size
    gapsheap = []
    heapq.heapify(gapsheap)
    prevend = None
    for i, rev in enumerate(revs):
        revstart = start(rev)
        revlen = length(rev)

        # Skip empty revisions to form larger holes
        if revlen == 0:
            continue

        ladd = l.append

        if not self._withsparseread:
            slicedchunks = (revs,)
        else:
            slicedchunks = _slicechunk(self, revs, targetsize)

        for revschunk in slicedchunks:
            firstrev = revschunk[0]
            # Skip trailing revisions with empty diff
            for lastrev in revschunk[::-1]:

        #   bounding it limits the amount of I/O we need to do.
        # - 'deltainfo.compresseddeltalen' is the sum of the total size of
        #   deltas we need to apply -- bounding it limits the amount of CPU
        #   we consume.

        distance = deltainfo.distance
        textlen = revinfo.textlen
        defaultmax = textlen * 4
        maxdist = self._maxdeltachainspan
        if not maxdist:
            maxdist = distance # ensure the conditional pass
        maxdist = max(maxdist, defaultmax)
        if (distance > maxdist or deltainfo.deltalen > textlen or
            deltainfo.compresseddeltalen > textlen * 2 or
            (self._maxchainlen and deltainfo.chainlen > self._maxchainlen)):
            return False

38718:f8762ea73e0d

        return self._data[rev]

    def length(self, rev):
        return self.end(rev) - self.start(rev)

    def __len__(self):
        return len(self._data)

def _trimchunk(revlog, revs, startidx, endidx=None):
    """returns revs[startidx:endidx] without empty trailing revs

    Doctest Setup
    >>> revlog = _testrevlog([

    """
    if not revs:
        return 0
    return revlog.end(revs[-1]) - revlog.start(revs[0])

def _slicechunk(revlog, revs, deltainfo=None, targetsize=None):
    """slice revs to reduce the amount of unrelated data to be read from disk.

    ``revs`` is sliced into groups that should be read in one time.
    Assume that revs are sorted.

    [[0], [11, 13, 15]]
    >>> list(_slicechunk(revlog, [1, 2, 3, 5, 8, 10, 11, 14]))
    [[1, 2], [5, 8, 10, 11], [14]]

    Slicing with a maximum chunk size
    >>> list(_slicechunk(revlog, [0, 11, 13, 15], targetsize=15))
    [[0], [11], [13], [15]]
    >>> list(_slicechunk(revlog, [0, 11, 13, 15], targetsize=20))
    [[0], [11], [13, 15]]
    """
    if targetsize is not None:
        targetsize = max(targetsize, revlog._srmingapsize)
    # targetsize should not be specified when evaluating delta candidates:
    # * targetsize is used to ensure we stay within specification when reading,
    # * deltainfo is used to pick are good delta chain when writing.
    if not (deltainfo is None or targetsize is None):
        msg = 'cannot use `targetsize` with a `deltainfo`'
        raise error.ProgrammingError(msg)
    for chunk in _slicechunktodensity(revlog, revs,
                                      deltainfo,
                                      revlog._srdensitythreshold,
                                      revlog._srmingapsize):
        for subchunk in _slicechunktosize(revlog, chunk, targetsize):
            yield subchunk

def _slicechunktosize(revlog, revs, targetsize=None):
    """slice revs to match the target size

    This is intended to be used on chunk that density slicing selected by that
    are still too large compared to the read garantee of revlog. This might
    happens when "minimal gap size" interrupted the slicing or when chain are

            startrevidx = idx
            startdata = revlog.start(r)
            endrevidx = idx
    yield _trimchunk(revlog, revs, startrevidx)

def _slicechunktodensity(revlog, revs, deltainfo=None, targetdensity=0.5,
                         mingapsize=0):
    """slice revs to reduce the amount of unrelated data to be read from disk.

    ``revs`` is sliced into groups that should be read in one time.
    Assume that revs are sorted.

    ``deltainfo`` is a _deltainfo instance of a revision that we would append
    to the top of the revlog.

    The initial chunk is sliced until the overall density (payload/chunks-span
    ratio) is above `targetdensity`. No gap smaller than `mingapsize` is
    skipped.

    if len(revs) <= 1:
        yield revs
        return

    nextrev = len(revlog)
    nextoffset = revlog.end(nextrev - 1)

    if deltainfo is None:
        deltachainspan = _segmentspan(revlog, revs)
        chainpayload = sum(length(r) for r in revs)
    else:
        deltachainspan = deltainfo.distance
        chainpayload = deltainfo.compresseddeltalen

    if deltachainspan < mingapsize:
        yield revs
        return

    readdata = deltachainspan

    if deltachainspan:
        density = chainpayload / float(deltachainspan)
    else:
        density = 1.0

    if density >= targetdensity:
        yield revs
        return

    if deltainfo is not None:
        revs = list(revs)
        revs.append(nextrev)

    # Store the gaps in a heap to have them sorted by decreasing size
    gapsheap = []
    heapq.heapify(gapsheap)
    prevend = None
    for i, rev in enumerate(revs):
        if rev < nextrev:
            revstart = start(rev)
            revlen = length(rev)
        else:
            revstart = nextoffset
            revlen = deltainfo.deltalen

        # Skip empty revisions to form larger holes
        if revlen == 0:
            continue

        ladd = l.append

        if not self._withsparseread:
            slicedchunks = (revs,)
        else:
            slicedchunks = _slicechunk(self, revs, targetsize=targetsize)

        for revschunk in slicedchunks:
            firstrev = revschunk[0]
            # Skip trailing revisions with empty diff
            for lastrev in revschunk[::-1]:

        #   bounding it limits the amount of I/O we need to do.
        # - 'deltainfo.compresseddeltalen' is the sum of the total size of
        #   deltas we need to apply -- bounding it limits the amount of CPU
        #   we consume.

        if self._sparserevlog:
            # As sparse-read will be used, we can consider that the distance,
            # instead of being the span of the whole chunk,
            # is the span of the largest read chunk
            base = deltainfo.base

            if base != nullrev:
                deltachain = self._deltachain(base)[0]
            else:
                deltachain = []

            chunks = _slicechunk(self, deltachain, deltainfo)
            distance = max(map(lambda revs:_segmentspan(self, revs), chunks))
        else:
            distance = deltainfo.distance

        textlen = revinfo.textlen
        defaultmax = textlen * 4
        maxdist = self._maxdeltachainspan
        if not maxdist:
            maxdist = distance # ensure the conditional pass
        maxdist = max(maxdist, defaultmax)
        if self._sparserevlog and maxdist < self._srmingapsize:
            # In multiple place, we are ignoring irrelevant data range below a
            # certain size. Be also apply this tradeoff here and relax span
            # constraint for small enought content.
            maxdist = self._srmingapsize
        if (distance > maxdist or deltainfo.deltalen > textlen or
            deltainfo.compresseddeltalen > textlen * 2 or
            (self._maxchainlen and deltainfo.chainlen > self._maxchainlen)):
            return False