synapse-product/synapse/util/caches/lrucache.py
Erik Johnston f85b6ca494 Speed up cache size calculation
Instead of calculating the size of the cache repeatedly, which can take
a long time now that it can use a callback, instead cache the size and
update that on insertion and deletion.

This requires changing the cache descriptors to have two caches, one for
pending deferreds and the other for the actual values. There's no reason
to evict from the pending deferreds as they won't take up any more
memory.
2017-01-17 11:18:13 +00:00

229 lines
6.8 KiB
Python

# -*- coding: utf-8 -*-
# Copyright 2015, 2016 OpenMarket Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from functools import wraps
import threading
from synapse.util.caches.treecache import TreeCache
def enumerate_leaves(node, depth):
if depth == 0:
yield node
else:
for n in node.values():
for m in enumerate_leaves(n, depth - 1):
yield m
class _Node(object):
__slots__ = ["prev_node", "next_node", "key", "value", "callbacks"]
def __init__(self, prev_node, next_node, key, value, callbacks=set()):
self.prev_node = prev_node
self.next_node = next_node
self.key = key
self.value = value
self.callbacks = callbacks
class LruCache(object):
"""
Least-recently-used cache.
Supports del_multi only if cache_type=TreeCache
If cache_type=TreeCache, all keys must be tuples.
Can also set callbacks on objects when getting/setting which are fired
when that key gets invalidated/evicted.
"""
def __init__(self, max_size, keylen=1, cache_type=dict, size_callback=None):
cache = cache_type()
self.cache = cache # Used for introspection.
list_root = _Node(None, None, None, None)
list_root.next_node = list_root
list_root.prev_node = list_root
lock = threading.Lock()
def evict():
while cache_len() > max_size:
todelete = list_root.prev_node
delete_node(todelete)
cache.pop(todelete.key, None)
def synchronized(f):
@wraps(f)
def inner(*args, **kwargs):
with lock:
return f(*args, **kwargs)
return inner
cached_cache_len = [0]
if size_callback is not None:
def cache_len():
return cached_cache_len[0]
else:
def cache_len():
return len(cache)
self.len = synchronized(cache_len)
def add_node(key, value, callbacks=set()):
prev_node = list_root
next_node = prev_node.next_node
node = _Node(prev_node, next_node, key, value, callbacks)
prev_node.next_node = node
next_node.prev_node = node
cache[key] = node
if size_callback:
cached_cache_len[0] += size_callback(node.value)
def move_node_to_front(node):
prev_node = node.prev_node
next_node = node.next_node
prev_node.next_node = next_node
next_node.prev_node = prev_node
prev_node = list_root
next_node = prev_node.next_node
node.prev_node = prev_node
node.next_node = next_node
prev_node.next_node = node
next_node.prev_node = node
def delete_node(node):
prev_node = node.prev_node
next_node = node.next_node
prev_node.next_node = next_node
next_node.prev_node = prev_node
if size_callback:
cached_cache_len[0] -= size_callback(node.value)
for cb in node.callbacks:
cb()
node.callbacks.clear()
@synchronized
def cache_get(key, default=None, callbacks=[]):
node = cache.get(key, None)
if node is not None:
move_node_to_front(node)
node.callbacks.update(callbacks)
return node.value
else:
return default
@synchronized
def cache_set(key, value, callbacks=[]):
node = cache.get(key, None)
if node is not None:
if value != node.value:
for cb in node.callbacks:
cb()
node.callbacks.clear()
if size_callback:
cached_cache_len[0] -= size_callback(node.value)
cached_cache_len[0] += size_callback(value)
node.callbacks.update(callbacks)
move_node_to_front(node)
node.value = value
else:
add_node(key, value, set(callbacks))
evict()
@synchronized
def cache_set_default(key, value):
node = cache.get(key, None)
if node is not None:
evict() # As the new node may be bigger than the old node.
return node.value
else:
add_node(key, value)
evict()
return value
@synchronized
def cache_pop(key, default=None):
node = cache.get(key, None)
if node:
delete_node(node)
cache.pop(node.key, None)
return node.value
else:
return default
@synchronized
def cache_del_multi(key):
"""
This will only work if constructed with cache_type=TreeCache
"""
popped = cache.pop(key)
if popped is None:
return
for leaf in enumerate_leaves(popped, keylen - len(key)):
delete_node(leaf)
@synchronized
def cache_clear():
list_root.next_node = list_root
list_root.prev_node = list_root
for node in cache.values():
for cb in node.callbacks:
cb()
cache.clear()
@synchronized
def cache_contains(key):
return key in cache
self.sentinel = object()
self.get = cache_get
self.set = cache_set
self.setdefault = cache_set_default
self.pop = cache_pop
if cache_type is TreeCache:
self.del_multi = cache_del_multi
self.len = synchronized(cache_len)
self.contains = cache_contains
self.clear = cache_clear
def __getitem__(self, key):
result = self.get(key, self.sentinel)
if result is self.sentinel:
raise KeyError()
else:
return result
def __setitem__(self, key, value):
self.set(key, value)
def __delitem__(self, key, value):
result = self.pop(key, self.sentinel)
if result is self.sentinel:
raise KeyError()
def __len__(self):
return self.len()
def __contains__(self, key):
return self.contains(key)