/usr/lib/python2.7/dist-packages/bzrlib/btree_index.py is in python-bzrlib 2.7.0+bzr6622-10.
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#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
#
"""B+Tree indices"""
from __future__ import absolute_import
import cStringIO
from bzrlib.lazy_import import lazy_import
lazy_import(globals(), """
import bisect
import math
import tempfile
import zlib
""")
from bzrlib import (
chunk_writer,
debug,
errors,
fifo_cache,
index,
lru_cache,
osutils,
static_tuple,
trace,
transport,
)
from bzrlib.index import _OPTION_NODE_REFS, _OPTION_KEY_ELEMENTS, _OPTION_LEN
_BTSIGNATURE = "B+Tree Graph Index 2\n"
_OPTION_ROW_LENGTHS = "row_lengths="
_LEAF_FLAG = "type=leaf\n"
_INTERNAL_FLAG = "type=internal\n"
_INTERNAL_OFFSET = "offset="
_RESERVED_HEADER_BYTES = 120
_PAGE_SIZE = 4096
# 4K per page: 4MB - 1000 entries
_NODE_CACHE_SIZE = 1000
class _BuilderRow(object):
"""The stored state accumulated while writing out a row in the index.
:ivar spool: A temporary file used to accumulate nodes for this row
in the tree.
:ivar nodes: The count of nodes emitted so far.
"""
def __init__(self):
"""Create a _BuilderRow."""
self.nodes = 0
self.spool = None# tempfile.TemporaryFile(prefix='bzr-index-row-')
self.writer = None
def finish_node(self, pad=True):
byte_lines, _, padding = self.writer.finish()
if self.nodes == 0:
self.spool = cStringIO.StringIO()
# padded note:
self.spool.write("\x00" * _RESERVED_HEADER_BYTES)
elif self.nodes == 1:
# We got bigger than 1 node, switch to a temp file
spool = tempfile.TemporaryFile(prefix='bzr-index-row-')
spool.write(self.spool.getvalue())
self.spool = spool
skipped_bytes = 0
if not pad and padding:
del byte_lines[-1]
skipped_bytes = padding
self.spool.writelines(byte_lines)
remainder = (self.spool.tell() + skipped_bytes) % _PAGE_SIZE
if remainder != 0:
raise AssertionError("incorrect node length: %d, %d"
% (self.spool.tell(), remainder))
self.nodes += 1
self.writer = None
class _InternalBuilderRow(_BuilderRow):
"""The stored state accumulated while writing out internal rows."""
def finish_node(self, pad=True):
if not pad:
raise AssertionError("Must pad internal nodes only.")
_BuilderRow.finish_node(self)
class _LeafBuilderRow(_BuilderRow):
"""The stored state accumulated while writing out a leaf rows."""
class BTreeBuilder(index.GraphIndexBuilder):
"""A Builder for B+Tree based Graph indices.
The resulting graph has the structure:
_SIGNATURE OPTIONS NODES
_SIGNATURE := 'B+Tree Graph Index 1' NEWLINE
OPTIONS := REF_LISTS KEY_ELEMENTS LENGTH
REF_LISTS := 'node_ref_lists=' DIGITS NEWLINE
KEY_ELEMENTS := 'key_elements=' DIGITS NEWLINE
LENGTH := 'len=' DIGITS NEWLINE
ROW_LENGTHS := 'row_lengths' DIGITS (COMMA DIGITS)*
NODES := NODE_COMPRESSED*
NODE_COMPRESSED:= COMPRESSED_BYTES{4096}
NODE_RAW := INTERNAL | LEAF
INTERNAL := INTERNAL_FLAG POINTERS
LEAF := LEAF_FLAG ROWS
KEY_ELEMENT := Not-whitespace-utf8
KEY := KEY_ELEMENT (NULL KEY_ELEMENT)*
ROWS := ROW*
ROW := KEY NULL ABSENT? NULL REFERENCES NULL VALUE NEWLINE
ABSENT := 'a'
REFERENCES := REFERENCE_LIST (TAB REFERENCE_LIST){node_ref_lists - 1}
REFERENCE_LIST := (REFERENCE (CR REFERENCE)*)?
REFERENCE := KEY
VALUE := no-newline-no-null-bytes
"""
def __init__(self, reference_lists=0, key_elements=1, spill_at=100000):
"""See GraphIndexBuilder.__init__.
:param spill_at: Optional parameter controlling the maximum number
of nodes that BTreeBuilder will hold in memory.
"""
index.GraphIndexBuilder.__init__(self, reference_lists=reference_lists,
key_elements=key_elements)
self._spill_at = spill_at
self._backing_indices = []
# A map of {key: (node_refs, value)}
self._nodes = {}
# Indicate it hasn't been built yet
self._nodes_by_key = None
self._optimize_for_size = False
def add_node(self, key, value, references=()):
"""Add a node to the index.
If adding the node causes the builder to reach its spill_at threshold,
disk spilling will be triggered.
:param key: The key. keys are non-empty tuples containing
as many whitespace-free utf8 bytestrings as the key length
defined for this index.
:param references: An iterable of iterables of keys. Each is a
reference to another key.
:param value: The value to associate with the key. It may be any
bytes as long as it does not contain \\0 or \\n.
"""
# Ensure that 'key' is a StaticTuple
key = static_tuple.StaticTuple.from_sequence(key).intern()
# we don't care about absent_references
node_refs, _ = self._check_key_ref_value(key, references, value)
if key in self._nodes:
raise errors.BadIndexDuplicateKey(key, self)
self._nodes[key] = static_tuple.StaticTuple(node_refs, value)
if self._nodes_by_key is not None and self._key_length > 1:
self._update_nodes_by_key(key, value, node_refs)
if len(self._nodes) < self._spill_at:
return
self._spill_mem_keys_to_disk()
def _spill_mem_keys_to_disk(self):
"""Write the in memory keys down to disk to cap memory consumption.
If we already have some keys written to disk, we will combine them so
as to preserve the sorted order. The algorithm for combining uses
powers of two. So on the first spill, write all mem nodes into a
single index. On the second spill, combine the mem nodes with the nodes
on disk to create a 2x sized disk index and get rid of the first index.
On the third spill, create a single new disk index, which will contain
the mem nodes, and preserve the existing 2x sized index. On the fourth,
combine mem with the first and second indexes, creating a new one of
size 4x. On the fifth create a single new one, etc.
"""
if self._combine_backing_indices:
(new_backing_file, size,
backing_pos) = self._spill_mem_keys_and_combine()
else:
new_backing_file, size = self._spill_mem_keys_without_combining()
# Note: The transport here isn't strictly needed, because we will use
# direct access to the new_backing._file object
new_backing = BTreeGraphIndex(transport.get_transport_from_path('.'),
'<temp>', size)
# GC will clean up the file
new_backing._file = new_backing_file
if self._combine_backing_indices:
if len(self._backing_indices) == backing_pos:
self._backing_indices.append(None)
self._backing_indices[backing_pos] = new_backing
for backing_pos in range(backing_pos):
self._backing_indices[backing_pos] = None
else:
self._backing_indices.append(new_backing)
self._nodes = {}
self._nodes_by_key = None
def _spill_mem_keys_without_combining(self):
return self._write_nodes(self._iter_mem_nodes(), allow_optimize=False)
def _spill_mem_keys_and_combine(self):
iterators_to_combine = [self._iter_mem_nodes()]
pos = -1
for pos, backing in enumerate(self._backing_indices):
if backing is None:
pos -= 1
break
iterators_to_combine.append(backing.iter_all_entries())
backing_pos = pos + 1
new_backing_file, size = \
self._write_nodes(self._iter_smallest(iterators_to_combine),
allow_optimize=False)
return new_backing_file, size, backing_pos
def add_nodes(self, nodes):
"""Add nodes to the index.
:param nodes: An iterable of (key, node_refs, value) entries to add.
"""
if self.reference_lists:
for (key, value, node_refs) in nodes:
self.add_node(key, value, node_refs)
else:
for (key, value) in nodes:
self.add_node(key, value)
def _iter_mem_nodes(self):
"""Iterate over the nodes held in memory."""
nodes = self._nodes
if self.reference_lists:
for key in sorted(nodes):
references, value = nodes[key]
yield self, key, value, references
else:
for key in sorted(nodes):
references, value = nodes[key]
yield self, key, value
def _iter_smallest(self, iterators_to_combine):
if len(iterators_to_combine) == 1:
for value in iterators_to_combine[0]:
yield value
return
current_values = []
for iterator in iterators_to_combine:
try:
current_values.append(iterator.next())
except StopIteration:
current_values.append(None)
last = None
while True:
# Decorate candidates with the value to allow 2.4's min to be used.
candidates = [(item[1][1], item) for item
in enumerate(current_values) if item[1] is not None]
if not len(candidates):
return
selected = min(candidates)
# undecorate back to (pos, node)
selected = selected[1]
if last == selected[1][1]:
raise errors.BadIndexDuplicateKey(last, self)
last = selected[1][1]
# Yield, with self as the index
yield (self,) + selected[1][1:]
pos = selected[0]
try:
current_values[pos] = iterators_to_combine[pos].next()
except StopIteration:
current_values[pos] = None
def _add_key(self, string_key, line, rows, allow_optimize=True):
"""Add a key to the current chunk.
:param string_key: The key to add.
:param line: The fully serialised key and value.
:param allow_optimize: If set to False, prevent setting the optimize
flag when writing out. This is used by the _spill_mem_keys_to_disk
functionality.
"""
new_leaf = False
if rows[-1].writer is None:
# opening a new leaf chunk;
new_leaf = True
for pos, internal_row in enumerate(rows[:-1]):
# flesh out any internal nodes that are needed to
# preserve the height of the tree
if internal_row.writer is None:
length = _PAGE_SIZE
if internal_row.nodes == 0:
length -= _RESERVED_HEADER_BYTES # padded
if allow_optimize:
optimize_for_size = self._optimize_for_size
else:
optimize_for_size = False
internal_row.writer = chunk_writer.ChunkWriter(length, 0,
optimize_for_size=optimize_for_size)
internal_row.writer.write(_INTERNAL_FLAG)
internal_row.writer.write(_INTERNAL_OFFSET +
str(rows[pos + 1].nodes) + "\n")
# add a new leaf
length = _PAGE_SIZE
if rows[-1].nodes == 0:
length -= _RESERVED_HEADER_BYTES # padded
rows[-1].writer = chunk_writer.ChunkWriter(length,
optimize_for_size=self._optimize_for_size)
rows[-1].writer.write(_LEAF_FLAG)
if rows[-1].writer.write(line):
# if we failed to write, despite having an empty page to write to,
# then line is too big. raising the error avoids infinite recursion
# searching for a suitably large page that will not be found.
if new_leaf:
raise errors.BadIndexKey(string_key)
# this key did not fit in the node:
rows[-1].finish_node()
key_line = string_key + "\n"
new_row = True
for row in reversed(rows[:-1]):
# Mark the start of the next node in the node above. If it
# doesn't fit then propagate upwards until we find one that
# it does fit into.
if row.writer.write(key_line):
row.finish_node()
else:
# We've found a node that can handle the pointer.
new_row = False
break
# If we reached the current root without being able to mark the
# division point, then we need a new root:
if new_row:
# We need a new row
if 'index' in debug.debug_flags:
trace.mutter('Inserting new global row.')
new_row = _InternalBuilderRow()
reserved_bytes = 0
rows.insert(0, new_row)
# This will be padded, hence the -100
new_row.writer = chunk_writer.ChunkWriter(
_PAGE_SIZE - _RESERVED_HEADER_BYTES,
reserved_bytes,
optimize_for_size=self._optimize_for_size)
new_row.writer.write(_INTERNAL_FLAG)
new_row.writer.write(_INTERNAL_OFFSET +
str(rows[1].nodes - 1) + "\n")
new_row.writer.write(key_line)
self._add_key(string_key, line, rows, allow_optimize=allow_optimize)
def _write_nodes(self, node_iterator, allow_optimize=True):
"""Write node_iterator out as a B+Tree.
:param node_iterator: An iterator of sorted nodes. Each node should
match the output given by iter_all_entries.
:param allow_optimize: If set to False, prevent setting the optimize
flag when writing out. This is used by the _spill_mem_keys_to_disk
functionality.
:return: A file handle for a temporary file containing a B+Tree for
the nodes.
"""
# The index rows - rows[0] is the root, rows[1] is the layer under it
# etc.
rows = []
# forward sorted by key. In future we may consider topological sorting,
# at the cost of table scans for direct lookup, or a second index for
# direct lookup
key_count = 0
# A stack with the number of nodes of each size. 0 is the root node
# and must always be 1 (if there are any nodes in the tree).
self.row_lengths = []
# Loop over all nodes adding them to the bottom row
# (rows[-1]). When we finish a chunk in a row,
# propagate the key that didn't fit (comes after the chunk) to the
# row above, transitively.
for node in node_iterator:
if key_count == 0:
# First key triggers the first row
rows.append(_LeafBuilderRow())
key_count += 1
string_key, line = _btree_serializer._flatten_node(node,
self.reference_lists)
self._add_key(string_key, line, rows, allow_optimize=allow_optimize)
for row in reversed(rows):
pad = (type(row) != _LeafBuilderRow)
row.finish_node(pad=pad)
lines = [_BTSIGNATURE]
lines.append(_OPTION_NODE_REFS + str(self.reference_lists) + '\n')
lines.append(_OPTION_KEY_ELEMENTS + str(self._key_length) + '\n')
lines.append(_OPTION_LEN + str(key_count) + '\n')
row_lengths = [row.nodes for row in rows]
lines.append(_OPTION_ROW_LENGTHS + ','.join(map(str, row_lengths)) + '\n')
if row_lengths and row_lengths[-1] > 1:
result = tempfile.NamedTemporaryFile(prefix='bzr-index-')
else:
result = cStringIO.StringIO()
result.writelines(lines)
position = sum(map(len, lines))
root_row = True
if position > _RESERVED_HEADER_BYTES:
raise AssertionError("Could not fit the header in the"
" reserved space: %d > %d"
% (position, _RESERVED_HEADER_BYTES))
# write the rows out:
for row in rows:
reserved = _RESERVED_HEADER_BYTES # reserved space for first node
row.spool.flush()
row.spool.seek(0)
# copy nodes to the finalised file.
# Special case the first node as it may be prefixed
node = row.spool.read(_PAGE_SIZE)
result.write(node[reserved:])
if len(node) == _PAGE_SIZE:
result.write("\x00" * (reserved - position))
position = 0 # Only the root row actually has an offset
copied_len = osutils.pumpfile(row.spool, result)
if copied_len != (row.nodes - 1) * _PAGE_SIZE:
if type(row) != _LeafBuilderRow:
raise AssertionError("Incorrect amount of data copied"
" expected: %d, got: %d"
% ((row.nodes - 1) * _PAGE_SIZE,
copied_len))
result.flush()
size = result.tell()
result.seek(0)
return result, size
def finish(self):
"""Finalise the index.
:return: A file handle for a temporary file containing the nodes added
to the index.
"""
return self._write_nodes(self.iter_all_entries())[0]
def iter_all_entries(self):
"""Iterate over all keys within the index
:return: An iterable of (index, key, value, reference_lists). There is
no defined order for the result iteration - it will be in the most
efficient order for the index (in this case dictionary hash order).
"""
if 'evil' in debug.debug_flags:
trace.mutter_callsite(3,
"iter_all_entries scales with size of history.")
# Doing serial rather than ordered would be faster; but this shouldn't
# be getting called routinely anyway.
iterators = [self._iter_mem_nodes()]
for backing in self._backing_indices:
if backing is not None:
iterators.append(backing.iter_all_entries())
if len(iterators) == 1:
return iterators[0]
return self._iter_smallest(iterators)
def iter_entries(self, keys):
"""Iterate over keys within the index.
:param keys: An iterable providing the keys to be retrieved.
:return: An iterable of (index, key, value, reference_lists). There is no
defined order for the result iteration - it will be in the most
efficient order for the index (keys iteration order in this case).
"""
keys = set(keys)
# Note: We don't use keys.intersection() here. If you read the C api,
# set.intersection(other) special cases when other is a set and
# will iterate the smaller of the two and lookup in the other.
# It does *not* do this for any other type (even dict, unlike
# some other set functions.) Since we expect keys is generally <<
# self._nodes, it is faster to iterate over it in a list
# comprehension
nodes = self._nodes
local_keys = [key for key in keys if key in nodes]
if self.reference_lists:
for key in local_keys:
node = nodes[key]
yield self, key, node[1], node[0]
else:
for key in local_keys:
node = nodes[key]
yield self, key, node[1]
# Find things that are in backing indices that have not been handled
# yet.
if not self._backing_indices:
return # We won't find anything there either
# Remove all of the keys that we found locally
keys.difference_update(local_keys)
for backing in self._backing_indices:
if backing is None:
continue
if not keys:
return
for node in backing.iter_entries(keys):
keys.remove(node[1])
yield (self,) + node[1:]
def iter_entries_prefix(self, keys):
"""Iterate over keys within the index using prefix matching.
Prefix matching is applied within the tuple of a key, not to within
the bytestring of each key element. e.g. if you have the keys ('foo',
'bar'), ('foobar', 'gam') and do a prefix search for ('foo', None) then
only the former key is returned.
:param keys: An iterable providing the key prefixes to be retrieved.
Each key prefix takes the form of a tuple the length of a key, but
with the last N elements 'None' rather than a regular bytestring.
The first element cannot be 'None'.
:return: An iterable as per iter_all_entries, but restricted to the
keys with a matching prefix to those supplied. No additional keys
will be returned, and every match that is in the index will be
returned.
"""
# XXX: To much duplication with the GraphIndex class; consider finding
# a good place to pull out the actual common logic.
keys = set(keys)
if not keys:
return
for backing in self._backing_indices:
if backing is None:
continue
for node in backing.iter_entries_prefix(keys):
yield (self,) + node[1:]
if self._key_length == 1:
for key in keys:
# sanity check
if key[0] is None:
raise errors.BadIndexKey(key)
if len(key) != self._key_length:
raise errors.BadIndexKey(key)
try:
node = self._nodes[key]
except KeyError:
continue
if self.reference_lists:
yield self, key, node[1], node[0]
else:
yield self, key, node[1]
return
for key in keys:
# sanity check
if key[0] is None:
raise errors.BadIndexKey(key)
if len(key) != self._key_length:
raise errors.BadIndexKey(key)
# find what it refers to:
key_dict = self._get_nodes_by_key()
elements = list(key)
# find the subdict to return
try:
while len(elements) and elements[0] is not None:
key_dict = key_dict[elements[0]]
elements.pop(0)
except KeyError:
# a non-existant lookup.
continue
if len(elements):
dicts = [key_dict]
while dicts:
key_dict = dicts.pop(-1)
# can't be empty or would not exist
item, value = key_dict.iteritems().next()
if type(value) == dict:
# push keys
dicts.extend(key_dict.itervalues())
else:
# yield keys
for value in key_dict.itervalues():
yield (self, ) + tuple(value)
else:
yield (self, ) + key_dict
def _get_nodes_by_key(self):
if self._nodes_by_key is None:
nodes_by_key = {}
if self.reference_lists:
for key, (references, value) in self._nodes.iteritems():
key_dict = nodes_by_key
for subkey in key[:-1]:
key_dict = key_dict.setdefault(subkey, {})
key_dict[key[-1]] = key, value, references
else:
for key, (references, value) in self._nodes.iteritems():
key_dict = nodes_by_key
for subkey in key[:-1]:
key_dict = key_dict.setdefault(subkey, {})
key_dict[key[-1]] = key, value
self._nodes_by_key = nodes_by_key
return self._nodes_by_key
def key_count(self):
"""Return an estimate of the number of keys in this index.
For InMemoryGraphIndex the estimate is exact.
"""
return len(self._nodes) + sum(backing.key_count() for backing in
self._backing_indices if backing is not None)
def validate(self):
"""In memory index's have no known corruption at the moment."""
class _LeafNode(dict):
"""A leaf node for a serialised B+Tree index."""
__slots__ = ('min_key', 'max_key', '_keys')
def __init__(self, bytes, key_length, ref_list_length):
"""Parse bytes to create a leaf node object."""
# splitlines mangles the \r delimiters.. don't use it.
key_list = _btree_serializer._parse_leaf_lines(bytes,
key_length, ref_list_length)
if key_list:
self.min_key = key_list[0][0]
self.max_key = key_list[-1][0]
else:
self.min_key = self.max_key = None
super(_LeafNode, self).__init__(key_list)
self._keys = dict(self)
def all_items(self):
"""Return a sorted list of (key, (value, refs)) items"""
items = self.items()
items.sort()
return items
def all_keys(self):
"""Return a sorted list of all keys."""
keys = self.keys()
keys.sort()
return keys
class _InternalNode(object):
"""An internal node for a serialised B+Tree index."""
__slots__ = ('keys', 'offset')
def __init__(self, bytes):
"""Parse bytes to create an internal node object."""
# splitlines mangles the \r delimiters.. don't use it.
self.keys = self._parse_lines(bytes.split('\n'))
def _parse_lines(self, lines):
nodes = []
self.offset = int(lines[1][7:])
as_st = static_tuple.StaticTuple.from_sequence
for line in lines[2:]:
if line == '':
break
nodes.append(as_st(map(intern, line.split('\0'))).intern())
return nodes
class BTreeGraphIndex(object):
"""Access to nodes via the standard GraphIndex interface for B+Tree's.
Individual nodes are held in a LRU cache. This holds the root node in
memory except when very large walks are done.
"""
def __init__(self, transport, name, size, unlimited_cache=False,
offset=0):
"""Create a B+Tree index object on the index name.
:param transport: The transport to read data for the index from.
:param name: The file name of the index on transport.
:param size: Optional size of the index in bytes. This allows
compatibility with the GraphIndex API, as well as ensuring that
the initial read (to read the root node header) can be done
without over-reading even on empty indices, and on small indices
allows single-IO to read the entire index.
:param unlimited_cache: If set to True, then instead of using an
LRUCache with size _NODE_CACHE_SIZE, we will use a dict and always
cache all leaf nodes.
:param offset: The start of the btree index data isn't byte 0 of the
file. Instead it starts at some point later.
"""
self._transport = transport
self._name = name
self._size = size
self._file = None
self._recommended_pages = self._compute_recommended_pages()
self._root_node = None
self._base_offset = offset
self._leaf_factory = _LeafNode
# Default max size is 100,000 leave values
self._leaf_value_cache = None # lru_cache.LRUCache(100*1000)
if unlimited_cache:
self._leaf_node_cache = {}
self._internal_node_cache = {}
else:
self._leaf_node_cache = lru_cache.LRUCache(_NODE_CACHE_SIZE)
# We use a FIFO here just to prevent possible blowout. However, a
# 300k record btree has only 3k leaf nodes, and only 20 internal
# nodes. A value of 100 scales to ~100*100*100 = 1M records.
self._internal_node_cache = fifo_cache.FIFOCache(100)
self._key_count = None
self._row_lengths = None
self._row_offsets = None # Start of each row, [-1] is the end
def __eq__(self, other):
"""Equal when self and other were created with the same parameters."""
return (
type(self) == type(other) and
self._transport == other._transport and
self._name == other._name and
self._size == other._size)
def __ne__(self, other):
return not self.__eq__(other)
def _get_and_cache_nodes(self, nodes):
"""Read nodes and cache them in the lru.
The nodes list supplied is sorted and then read from disk, each node
being inserted it into the _node_cache.
Note: Asking for more nodes than the _node_cache can contain will
result in some of the results being immediately discarded, to prevent
this an assertion is raised if more nodes are asked for than are
cachable.
:return: A dict of {node_pos: node}
"""
found = {}
start_of_leaves = None
for node_pos, node in self._read_nodes(sorted(nodes)):
if node_pos == 0: # Special case
self._root_node = node
else:
if start_of_leaves is None:
start_of_leaves = self._row_offsets[-2]
if node_pos < start_of_leaves:
self._internal_node_cache[node_pos] = node
else:
self._leaf_node_cache[node_pos] = node
found[node_pos] = node
return found
def _compute_recommended_pages(self):
"""Convert transport's recommended_page_size into btree pages.
recommended_page_size is in bytes, we want to know how many _PAGE_SIZE
pages fit in that length.
"""
recommended_read = self._transport.recommended_page_size()
recommended_pages = int(math.ceil(recommended_read /
float(_PAGE_SIZE)))
return recommended_pages
def _compute_total_pages_in_index(self):
"""How many pages are in the index.
If we have read the header we will use the value stored there.
Otherwise it will be computed based on the length of the index.
"""
if self._size is None:
raise AssertionError('_compute_total_pages_in_index should not be'
' called when self._size is None')
if self._root_node is not None:
# This is the number of pages as defined by the header
return self._row_offsets[-1]
# This is the number of pages as defined by the size of the index. They
# should be indentical.
total_pages = int(math.ceil(self._size / float(_PAGE_SIZE)))
return total_pages
def _expand_offsets(self, offsets):
"""Find extra pages to download.
The idea is that we always want to make big-enough requests (like 64kB
for http), so that we don't waste round trips. So given the entries
that we already have cached and the new pages being downloaded figure
out what other pages we might want to read.
See also doc/developers/btree_index_prefetch.txt for more details.
:param offsets: The offsets to be read
:return: A list of offsets to download
"""
if 'index' in debug.debug_flags:
trace.mutter('expanding: %s\toffsets: %s', self._name, offsets)
if len(offsets) >= self._recommended_pages:
# Don't add more, we are already requesting more than enough
if 'index' in debug.debug_flags:
trace.mutter(' not expanding large request (%s >= %s)',
len(offsets), self._recommended_pages)
return offsets
if self._size is None:
# Don't try anything, because we don't know where the file ends
if 'index' in debug.debug_flags:
trace.mutter(' not expanding without knowing index size')
return offsets
total_pages = self._compute_total_pages_in_index()
cached_offsets = self._get_offsets_to_cached_pages()
# If reading recommended_pages would read the rest of the index, just
# do so.
if total_pages - len(cached_offsets) <= self._recommended_pages:
# Read whatever is left
if cached_offsets:
expanded = [x for x in xrange(total_pages)
if x not in cached_offsets]
else:
expanded = range(total_pages)
if 'index' in debug.debug_flags:
trace.mutter(' reading all unread pages: %s', expanded)
return expanded
if self._root_node is None:
# ATM on the first read of the root node of a large index, we don't
# bother pre-reading any other pages. This is because the
# likelyhood of actually reading interesting pages is very low.
# See doc/developers/btree_index_prefetch.txt for a discussion, and
# a possible implementation when we are guessing that the second
# layer index is small
final_offsets = offsets
else:
tree_depth = len(self._row_lengths)
if len(cached_offsets) < tree_depth and len(offsets) == 1:
# We haven't read enough to justify expansion
# If we are only going to read the root node, and 1 leaf node,
# then it isn't worth expanding our request. Once we've read at
# least 2 nodes, then we are probably doing a search, and we
# start expanding our requests.
if 'index' in debug.debug_flags:
trace.mutter(' not expanding on first reads')
return offsets
final_offsets = self._expand_to_neighbors(offsets, cached_offsets,
total_pages)
final_offsets = sorted(final_offsets)
if 'index' in debug.debug_flags:
trace.mutter('expanded: %s', final_offsets)
return final_offsets
def _expand_to_neighbors(self, offsets, cached_offsets, total_pages):
"""Expand requests to neighbors until we have enough pages.
This is called from _expand_offsets after policy has determined that we
want to expand.
We only want to expand requests within a given layer. We cheat a little
bit and assume all requests will be in the same layer. This is true
given the current design, but if it changes this algorithm may perform
oddly.
:param offsets: requested offsets
:param cached_offsets: offsets for pages we currently have cached
:return: A set() of offsets after expansion
"""
final_offsets = set(offsets)
first = end = None
new_tips = set(final_offsets)
while len(final_offsets) < self._recommended_pages and new_tips:
next_tips = set()
for pos in new_tips:
if first is None:
first, end = self._find_layer_first_and_end(pos)
previous = pos - 1
if (previous > 0
and previous not in cached_offsets
and previous not in final_offsets
and previous >= first):
next_tips.add(previous)
after = pos + 1
if (after < total_pages
and after not in cached_offsets
and after not in final_offsets
and after < end):
next_tips.add(after)
# This would keep us from going bigger than
# recommended_pages by only expanding the first offsets.
# However, if we are making a 'wide' request, it is
# reasonable to expand all points equally.
# if len(final_offsets) > recommended_pages:
# break
final_offsets.update(next_tips)
new_tips = next_tips
return final_offsets
def clear_cache(self):
"""Clear out any cached/memoized values.
This can be called at any time, but generally it is used when we have
extracted some information, but don't expect to be requesting any more
from this index.
"""
# Note that we don't touch self._root_node or self._internal_node_cache
# We don't expect either of those to be big, and it can save
# round-trips in the future. We may re-evaluate this if InternalNode
# memory starts to be an issue.
self._leaf_node_cache.clear()
def external_references(self, ref_list_num):
if self._root_node is None:
self._get_root_node()
if ref_list_num + 1 > self.node_ref_lists:
raise ValueError('No ref list %d, index has %d ref lists'
% (ref_list_num, self.node_ref_lists))
keys = set()
refs = set()
for node in self.iter_all_entries():
keys.add(node[1])
refs.update(node[3][ref_list_num])
return refs - keys
def _find_layer_first_and_end(self, offset):
"""Find the start/stop nodes for the layer corresponding to offset.
:return: (first, end)
first is the first node in this layer
end is the first node of the next layer
"""
first = end = 0
for roffset in self._row_offsets:
first = end
end = roffset
if offset < roffset:
break
return first, end
def _get_offsets_to_cached_pages(self):
"""Determine what nodes we already have cached."""
cached_offsets = set(self._internal_node_cache.keys())
cached_offsets.update(self._leaf_node_cache.keys())
if self._root_node is not None:
cached_offsets.add(0)
return cached_offsets
def _get_root_node(self):
if self._root_node is None:
# We may not have a root node yet
self._get_internal_nodes([0])
return self._root_node
def _get_nodes(self, cache, node_indexes):
found = {}
needed = []
for idx in node_indexes:
if idx == 0 and self._root_node is not None:
found[0] = self._root_node
continue
try:
found[idx] = cache[idx]
except KeyError:
needed.append(idx)
if not needed:
return found
needed = self._expand_offsets(needed)
found.update(self._get_and_cache_nodes(needed))
return found
def _get_internal_nodes(self, node_indexes):
"""Get a node, from cache or disk.
After getting it, the node will be cached.
"""
return self._get_nodes(self._internal_node_cache, node_indexes)
def _cache_leaf_values(self, nodes):
"""Cache directly from key => value, skipping the btree."""
if self._leaf_value_cache is not None:
for node in nodes.itervalues():
for key, value in node.all_items():
if key in self._leaf_value_cache:
# Don't add the rest of the keys, we've seen this node
# before.
break
self._leaf_value_cache[key] = value
def _get_leaf_nodes(self, node_indexes):
"""Get a bunch of nodes, from cache or disk."""
found = self._get_nodes(self._leaf_node_cache, node_indexes)
self._cache_leaf_values(found)
return found
def iter_all_entries(self):
"""Iterate over all keys within the index.
:return: An iterable of (index, key, value) or (index, key, value, reference_lists).
The former tuple is used when there are no reference lists in the
index, making the API compatible with simple key:value index types.
There is no defined order for the result iteration - it will be in
the most efficient order for the index.
"""
if 'evil' in debug.debug_flags:
trace.mutter_callsite(3,
"iter_all_entries scales with size of history.")
if not self.key_count():
return
if self._row_offsets[-1] == 1:
# There is only the root node, and we read that via key_count()
if self.node_ref_lists:
for key, (value, refs) in self._root_node.all_items():
yield (self, key, value, refs)
else:
for key, (value, refs) in self._root_node.all_items():
yield (self, key, value)
return
start_of_leaves = self._row_offsets[-2]
end_of_leaves = self._row_offsets[-1]
needed_offsets = range(start_of_leaves, end_of_leaves)
if needed_offsets == [0]:
# Special case when we only have a root node, as we have already
# read everything
nodes = [(0, self._root_node)]
else:
nodes = self._read_nodes(needed_offsets)
# We iterate strictly in-order so that we can use this function
# for spilling index builds to disk.
if self.node_ref_lists:
for _, node in nodes:
for key, (value, refs) in node.all_items():
yield (self, key, value, refs)
else:
for _, node in nodes:
for key, (value, refs) in node.all_items():
yield (self, key, value)
@staticmethod
def _multi_bisect_right(in_keys, fixed_keys):
"""Find the positions where each 'in_key' would fit in fixed_keys.
This is equivalent to doing "bisect_right" on each in_key into
fixed_keys
:param in_keys: A sorted list of keys to match with fixed_keys
:param fixed_keys: A sorted list of keys to match against
:return: A list of (integer position, [key list]) tuples.
"""
if not in_keys:
return []
if not fixed_keys:
# no pointers in the fixed_keys list, which means everything must
# fall to the left.
return [(0, in_keys)]
# TODO: Iterating both lists will generally take M + N steps
# Bisecting each key will generally take M * log2 N steps.
# If we had an efficient way to compare, we could pick the method
# based on which has the fewer number of steps.
# There is also the argument that bisect_right is a compiled
# function, so there is even more to be gained.
# iter_steps = len(in_keys) + len(fixed_keys)
# bisect_steps = len(in_keys) * math.log(len(fixed_keys), 2)
if len(in_keys) == 1: # Bisect will always be faster for M = 1
return [(bisect.bisect_right(fixed_keys, in_keys[0]), in_keys)]
# elif bisect_steps < iter_steps:
# offsets = {}
# for key in in_keys:
# offsets.setdefault(bisect_right(fixed_keys, key),
# []).append(key)
# return [(o, offsets[o]) for o in sorted(offsets)]
in_keys_iter = iter(in_keys)
fixed_keys_iter = enumerate(fixed_keys)
cur_in_key = in_keys_iter.next()
cur_fixed_offset, cur_fixed_key = fixed_keys_iter.next()
class InputDone(Exception): pass
class FixedDone(Exception): pass
output = []
cur_out = []
# TODO: Another possibility is that rather than iterating on each side,
# we could use a combination of bisecting and iterating. For
# example, while cur_in_key < fixed_key, bisect to find its
# point, then iterate all matching keys, then bisect (restricted
# to only the remainder) for the next one, etc.
try:
while True:
if cur_in_key < cur_fixed_key:
cur_keys = []
cur_out = (cur_fixed_offset, cur_keys)
output.append(cur_out)
while cur_in_key < cur_fixed_key:
cur_keys.append(cur_in_key)
try:
cur_in_key = in_keys_iter.next()
except StopIteration:
raise InputDone
# At this point cur_in_key must be >= cur_fixed_key
# step the cur_fixed_key until we pass the cur key, or walk off
# the end
while cur_in_key >= cur_fixed_key:
try:
cur_fixed_offset, cur_fixed_key = fixed_keys_iter.next()
except StopIteration:
raise FixedDone
except InputDone:
# We consumed all of the input, nothing more to do
pass
except FixedDone:
# There was some input left, but we consumed all of fixed, so we
# have to add one more for the tail
cur_keys = [cur_in_key]
cur_keys.extend(in_keys_iter)
cur_out = (len(fixed_keys), cur_keys)
output.append(cur_out)
return output
def _walk_through_internal_nodes(self, keys):
"""Take the given set of keys, and find the corresponding LeafNodes.
:param keys: An unsorted iterable of keys to search for
:return: (nodes, index_and_keys)
nodes is a dict mapping {index: LeafNode}
keys_at_index is a list of tuples of [(index, [keys for Leaf])]
"""
# 6 seconds spent in miss_torture using the sorted() line.
# Even with out of order disk IO it seems faster not to sort it when
# large queries are being made.
keys_at_index = [(0, sorted(keys))]
for row_pos, next_row_start in enumerate(self._row_offsets[1:-1]):
node_indexes = [idx for idx, s_keys in keys_at_index]
nodes = self._get_internal_nodes(node_indexes)
next_nodes_and_keys = []
for node_index, sub_keys in keys_at_index:
node = nodes[node_index]
positions = self._multi_bisect_right(sub_keys, node.keys)
node_offset = next_row_start + node.offset
next_nodes_and_keys.extend([(node_offset + pos, s_keys)
for pos, s_keys in positions])
keys_at_index = next_nodes_and_keys
# We should now be at the _LeafNodes
node_indexes = [idx for idx, s_keys in keys_at_index]
# TODO: We may *not* want to always read all the nodes in one
# big go. Consider setting a max size on this.
nodes = self._get_leaf_nodes(node_indexes)
return nodes, keys_at_index
def iter_entries(self, keys):
"""Iterate over keys within the index.
:param keys: An iterable providing the keys to be retrieved.
:return: An iterable as per iter_all_entries, but restricted to the
keys supplied. No additional keys will be returned, and every
key supplied that is in the index will be returned.
"""
# 6 seconds spent in miss_torture using the sorted() line.
# Even with out of order disk IO it seems faster not to sort it when
# large queries are being made.
# However, now that we are doing multi-way bisecting, we need the keys
# in sorted order anyway. We could change the multi-way code to not
# require sorted order. (For example, it bisects for the first node,
# does an in-order search until a key comes before the current point,
# which it then bisects for, etc.)
keys = frozenset(keys)
if not keys:
return
if not self.key_count():
return
needed_keys = []
if self._leaf_value_cache is None:
needed_keys = keys
else:
for key in keys:
value = self._leaf_value_cache.get(key, None)
if value is not None:
# This key is known not to be here, skip it
value, refs = value
if self.node_ref_lists:
yield (self, key, value, refs)
else:
yield (self, key, value)
else:
needed_keys.append(key)
last_key = None
needed_keys = keys
if not needed_keys:
return
nodes, nodes_and_keys = self._walk_through_internal_nodes(needed_keys)
for node_index, sub_keys in nodes_and_keys:
if not sub_keys:
continue
node = nodes[node_index]
for next_sub_key in sub_keys:
if next_sub_key in node:
value, refs = node[next_sub_key]
if self.node_ref_lists:
yield (self, next_sub_key, value, refs)
else:
yield (self, next_sub_key, value)
def _find_ancestors(self, keys, ref_list_num, parent_map, missing_keys):
"""Find the parent_map information for the set of keys.
This populates the parent_map dict and missing_keys set based on the
queried keys. It also can fill out an arbitrary number of parents that
it finds while searching for the supplied keys.
It is unlikely that you want to call this directly. See
"CombinedGraphIndex.find_ancestry()" for a more appropriate API.
:param keys: A keys whose ancestry we want to return
Every key will either end up in 'parent_map' or 'missing_keys'.
:param ref_list_num: This index in the ref_lists is the parents we
care about.
:param parent_map: {key: parent_keys} for keys that are present in this
index. This may contain more entries than were in 'keys', that are
reachable ancestors of the keys requested.
:param missing_keys: keys which are known to be missing in this index.
This may include parents that were not directly requested, but we
were able to determine that they are not present in this index.
:return: search_keys parents that were found but not queried to know
if they are missing or present. Callers can re-query this index for
those keys, and they will be placed into parent_map or missing_keys
"""
if not self.key_count():
# We use key_count() to trigger reading the root node and
# determining info about this BTreeGraphIndex
# If we don't have any keys, then everything is missing
missing_keys.update(keys)
return set()
if ref_list_num >= self.node_ref_lists:
raise ValueError('No ref list %d, index has %d ref lists'
% (ref_list_num, self.node_ref_lists))
# The main trick we are trying to accomplish is that when we find a
# key listing its parents, we expect that the parent key is also likely
# to sit on the same page. Allowing us to expand parents quickly
# without suffering the full stack of bisecting, etc.
nodes, nodes_and_keys = self._walk_through_internal_nodes(keys)
# These are parent keys which could not be immediately resolved on the
# page where the child was present. Note that we may already be
# searching for that key, and it may actually be present [or known
# missing] on one of the other pages we are reading.
# TODO:
# We could try searching for them in the immediate previous or next
# page. If they occur "later" we could put them in a pending lookup
# set, and then for each node we read thereafter we could check to
# see if they are present.
# However, we don't know the impact of keeping this list of things
# that I'm going to search for every node I come across from here on
# out.
# It doesn't handle the case when the parent key is missing on a
# page that we *don't* read. So we already have to handle being
# re-entrant for that.
# Since most keys contain a date string, they are more likely to be
# found earlier in the file than later, but we would know that right
# away (key < min_key), and wouldn't keep searching it on every other
# page that we read.
# Mostly, it is an idea, one which should be benchmarked.
parents_not_on_page = set()
for node_index, sub_keys in nodes_and_keys:
if not sub_keys:
continue
# sub_keys is all of the keys we are looking for that should exist
# on this page, if they aren't here, then they won't be found
node = nodes[node_index]
parents_to_check = set()
for next_sub_key in sub_keys:
if next_sub_key not in node:
# This one is just not present in the index at all
missing_keys.add(next_sub_key)
else:
value, refs = node[next_sub_key]
parent_keys = refs[ref_list_num]
parent_map[next_sub_key] = parent_keys
parents_to_check.update(parent_keys)
# Don't look for things we've already found
parents_to_check = parents_to_check.difference(parent_map)
# this can be used to test the benefit of having the check loop
# inlined.
# parents_not_on_page.update(parents_to_check)
# continue
while parents_to_check:
next_parents_to_check = set()
for key in parents_to_check:
if key in node:
value, refs = node[key]
parent_keys = refs[ref_list_num]
parent_map[key] = parent_keys
next_parents_to_check.update(parent_keys)
else:
# This parent either is genuinely missing, or should be
# found on another page. Perf test whether it is better
# to check if this node should fit on this page or not.
# in the 'everything-in-one-pack' scenario, this *not*
# doing the check is 237ms vs 243ms.
# So slightly better, but I assume the standard 'lots
# of packs' is going to show a reasonable improvement
# from the check, because it avoids 'going around
# again' for everything that is in another index
# parents_not_on_page.add(key)
# Missing for some reason
if key < node.min_key:
# in the case of bzr.dev, 3.4k/5.3k misses are
# 'earlier' misses (65%)
parents_not_on_page.add(key)
elif key > node.max_key:
# This parent key would be present on a different
# LeafNode
parents_not_on_page.add(key)
else:
# assert key != node.min_key and key != node.max_key
# If it was going to be present, it would be on
# *this* page, so mark it missing.
missing_keys.add(key)
parents_to_check = next_parents_to_check.difference(parent_map)
# Might want to do another .difference() from missing_keys
# parents_not_on_page could have been found on a different page, or be
# known to be missing. So cull out everything that has already been
# found.
search_keys = parents_not_on_page.difference(
parent_map).difference(missing_keys)
return search_keys
def iter_entries_prefix(self, keys):
"""Iterate over keys within the index using prefix matching.
Prefix matching is applied within the tuple of a key, not to within
the bytestring of each key element. e.g. if you have the keys ('foo',
'bar'), ('foobar', 'gam') and do a prefix search for ('foo', None) then
only the former key is returned.
WARNING: Note that this method currently causes a full index parse
unconditionally (which is reasonably appropriate as it is a means for
thunking many small indices into one larger one and still supplies
iter_all_entries at the thunk layer).
:param keys: An iterable providing the key prefixes to be retrieved.
Each key prefix takes the form of a tuple the length of a key, but
with the last N elements 'None' rather than a regular bytestring.
The first element cannot be 'None'.
:return: An iterable as per iter_all_entries, but restricted to the
keys with a matching prefix to those supplied. No additional keys
will be returned, and every match that is in the index will be
returned.
"""
keys = sorted(set(keys))
if not keys:
return
# Load if needed to check key lengths
if self._key_count is None:
self._get_root_node()
# TODO: only access nodes that can satisfy the prefixes we are looking
# for. For now, to meet API usage (as this function is not used by
# current bzrlib) just suck the entire index and iterate in memory.
nodes = {}
if self.node_ref_lists:
if self._key_length == 1:
for _1, key, value, refs in self.iter_all_entries():
nodes[key] = value, refs
else:
nodes_by_key = {}
for _1, key, value, refs in self.iter_all_entries():
key_value = key, value, refs
# For a key of (foo, bar, baz) create
# _nodes_by_key[foo][bar][baz] = key_value
key_dict = nodes_by_key
for subkey in key[:-1]:
key_dict = key_dict.setdefault(subkey, {})
key_dict[key[-1]] = key_value
else:
if self._key_length == 1:
for _1, key, value in self.iter_all_entries():
nodes[key] = value
else:
nodes_by_key = {}
for _1, key, value in self.iter_all_entries():
key_value = key, value
# For a key of (foo, bar, baz) create
# _nodes_by_key[foo][bar][baz] = key_value
key_dict = nodes_by_key
for subkey in key[:-1]:
key_dict = key_dict.setdefault(subkey, {})
key_dict[key[-1]] = key_value
if self._key_length == 1:
for key in keys:
# sanity check
if key[0] is None:
raise errors.BadIndexKey(key)
if len(key) != self._key_length:
raise errors.BadIndexKey(key)
try:
if self.node_ref_lists:
value, node_refs = nodes[key]
yield self, key, value, node_refs
else:
yield self, key, nodes[key]
except KeyError:
pass
return
for key in keys:
# sanity check
if key[0] is None:
raise errors.BadIndexKey(key)
if len(key) != self._key_length:
raise errors.BadIndexKey(key)
# find what it refers to:
key_dict = nodes_by_key
elements = list(key)
# find the subdict whose contents should be returned.
try:
while len(elements) and elements[0] is not None:
key_dict = key_dict[elements[0]]
elements.pop(0)
except KeyError:
# a non-existant lookup.
continue
if len(elements):
dicts = [key_dict]
while dicts:
key_dict = dicts.pop(-1)
# can't be empty or would not exist
item, value = key_dict.iteritems().next()
if type(value) == dict:
# push keys
dicts.extend(key_dict.itervalues())
else:
# yield keys
for value in key_dict.itervalues():
# each value is the key:value:node refs tuple
# ready to yield.
yield (self, ) + value
else:
# the last thing looked up was a terminal element
yield (self, ) + key_dict
def key_count(self):
"""Return an estimate of the number of keys in this index.
For BTreeGraphIndex the estimate is exact as it is contained in the
header.
"""
if self._key_count is None:
self._get_root_node()
return self._key_count
def _compute_row_offsets(self):
"""Fill out the _row_offsets attribute based on _row_lengths."""
offsets = []
row_offset = 0
for row in self._row_lengths:
offsets.append(row_offset)
row_offset += row
offsets.append(row_offset)
self._row_offsets = offsets
def _parse_header_from_bytes(self, bytes):
"""Parse the header from a region of bytes.
:param bytes: The data to parse.
:return: An offset, data tuple such as readv yields, for the unparsed
data. (which may be of length 0).
"""
signature = bytes[0:len(self._signature())]
if not signature == self._signature():
raise errors.BadIndexFormatSignature(self._name, BTreeGraphIndex)
lines = bytes[len(self._signature()):].splitlines()
options_line = lines[0]
if not options_line.startswith(_OPTION_NODE_REFS):
raise errors.BadIndexOptions(self)
try:
self.node_ref_lists = int(options_line[len(_OPTION_NODE_REFS):])
except ValueError:
raise errors.BadIndexOptions(self)
options_line = lines[1]
if not options_line.startswith(_OPTION_KEY_ELEMENTS):
raise errors.BadIndexOptions(self)
try:
self._key_length = int(options_line[len(_OPTION_KEY_ELEMENTS):])
except ValueError:
raise errors.BadIndexOptions(self)
options_line = lines[2]
if not options_line.startswith(_OPTION_LEN):
raise errors.BadIndexOptions(self)
try:
self._key_count = int(options_line[len(_OPTION_LEN):])
except ValueError:
raise errors.BadIndexOptions(self)
options_line = lines[3]
if not options_line.startswith(_OPTION_ROW_LENGTHS):
raise errors.BadIndexOptions(self)
try:
self._row_lengths = map(int, [length for length in
options_line[len(_OPTION_ROW_LENGTHS):].split(',')
if len(length)])
except ValueError:
raise errors.BadIndexOptions(self)
self._compute_row_offsets()
# calculate the bytes we have processed
header_end = (len(signature) + sum(map(len, lines[0:4])) + 4)
return header_end, bytes[header_end:]
def _read_nodes(self, nodes):
"""Read some nodes from disk into the LRU cache.
This performs a readv to get the node data into memory, and parses each
node, then yields it to the caller. The nodes are requested in the
supplied order. If possible doing sort() on the list before requesting
a read may improve performance.
:param nodes: The nodes to read. 0 - first node, 1 - second node etc.
:return: None
"""
# may be the byte string of the whole file
bytes = None
# list of (offset, length) regions of the file that should, evenually
# be read in to data_ranges, either from 'bytes' or from the transport
ranges = []
base_offset = self._base_offset
for index in nodes:
offset = (index * _PAGE_SIZE)
size = _PAGE_SIZE
if index == 0:
# Root node - special case
if self._size:
size = min(_PAGE_SIZE, self._size)
else:
# The only case where we don't know the size, is for very
# small indexes. So we read the whole thing
bytes = self._transport.get_bytes(self._name)
num_bytes = len(bytes)
self._size = num_bytes - base_offset
# the whole thing should be parsed out of 'bytes'
ranges = [(start, min(_PAGE_SIZE, num_bytes - start))
for start in xrange(base_offset, num_bytes, _PAGE_SIZE)]
break
else:
if offset > self._size:
raise AssertionError('tried to read past the end'
' of the file %s > %s'
% (offset, self._size))
size = min(size, self._size - offset)
ranges.append((base_offset + offset, size))
if not ranges:
return
elif bytes is not None:
# already have the whole file
data_ranges = [(start, bytes[start:start+size])
for start, size in ranges]
elif self._file is None:
data_ranges = self._transport.readv(self._name, ranges)
else:
data_ranges = []
for offset, size in ranges:
self._file.seek(offset)
data_ranges.append((offset, self._file.read(size)))
for offset, data in data_ranges:
offset -= base_offset
if offset == 0:
# extract the header
offset, data = self._parse_header_from_bytes(data)
if len(data) == 0:
continue
bytes = zlib.decompress(data)
if bytes.startswith(_LEAF_FLAG):
node = self._leaf_factory(bytes, self._key_length,
self.node_ref_lists)
elif bytes.startswith(_INTERNAL_FLAG):
node = _InternalNode(bytes)
else:
raise AssertionError("Unknown node type for %r" % bytes)
yield offset / _PAGE_SIZE, node
def _signature(self):
"""The file signature for this index type."""
return _BTSIGNATURE
def validate(self):
"""Validate that everything in the index can be accessed."""
# just read and parse every node.
self._get_root_node()
if len(self._row_lengths) > 1:
start_node = self._row_offsets[1]
else:
# We shouldn't be reading anything anyway
start_node = 1
node_end = self._row_offsets[-1]
for node in self._read_nodes(range(start_node, node_end)):
pass
_gcchk_factory = _LeafNode
try:
from bzrlib import _btree_serializer_pyx as _btree_serializer
_gcchk_factory = _btree_serializer._parse_into_chk
except ImportError, e:
osutils.failed_to_load_extension(e)
from bzrlib import _btree_serializer_py as _btree_serializer
|