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![Erik Johnston](/assets/img/avatar_default.png)
This is already correctly done when we instansiate the cache, but wasn't when it got reloaded (which always happens at least once on startup).
307 lines
9.7 KiB
Python
307 lines
9.7 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright 2015, 2016 OpenMarket Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import threading
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from functools import wraps
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from typing import Callable, Optional, Type, Union
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from synapse.config import cache as cache_config
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from synapse.util.caches.treecache import TreeCache
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def enumerate_leaves(node, depth):
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if depth == 0:
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yield node
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else:
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for n in node.values():
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for m in enumerate_leaves(n, depth - 1):
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yield m
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class _Node(object):
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__slots__ = ["prev_node", "next_node", "key", "value", "callbacks"]
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def __init__(self, prev_node, next_node, key, value, callbacks=set()):
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self.prev_node = prev_node
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self.next_node = next_node
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self.key = key
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self.value = value
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self.callbacks = callbacks
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class LruCache(object):
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"""
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Least-recently-used cache.
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Supports del_multi only if cache_type=TreeCache
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If cache_type=TreeCache, all keys must be tuples.
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Can also set callbacks on objects when getting/setting which are fired
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when that key gets invalidated/evicted.
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"""
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def __init__(
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self,
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max_size: int,
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keylen: int = 1,
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cache_type: Type[Union[dict, TreeCache]] = dict,
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size_callback: Optional[Callable] = None,
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evicted_callback: Optional[Callable] = None,
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apply_cache_factor_from_config: bool = True,
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):
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"""
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Args:
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max_size: The maximum amount of entries the cache can hold
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keylen: The length of the tuple used as the cache key
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cache_type (type):
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type of underlying cache to be used. Typically one of dict
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or TreeCache.
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size_callback (func(V) -> int | None):
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evicted_callback (func(int)|None):
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if not None, called on eviction with the size of the evicted
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entry
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apply_cache_factor_from_config (bool): If true, `max_size` will be
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multiplied by a cache factor derived from the homeserver config
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"""
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cache = cache_type()
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self.cache = cache # Used for introspection.
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self.apply_cache_factor_from_config = apply_cache_factor_from_config
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# Save the original max size, and apply the default size factor.
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self._original_max_size = max_size
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# We previously didn't apply the cache factor here, and as such some caches were
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# not affected by the global cache factor. Add an option here to disable applying
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# the cache factor when a cache is created
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if apply_cache_factor_from_config:
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self.max_size = int(max_size * cache_config.properties.default_factor_size)
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else:
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self.max_size = int(max_size)
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list_root = _Node(None, None, None, None)
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list_root.next_node = list_root
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list_root.prev_node = list_root
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lock = threading.Lock()
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def evict():
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while cache_len() > self.max_size:
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todelete = list_root.prev_node
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evicted_len = delete_node(todelete)
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cache.pop(todelete.key, None)
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if evicted_callback:
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evicted_callback(evicted_len)
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def synchronized(f):
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@wraps(f)
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def inner(*args, **kwargs):
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with lock:
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return f(*args, **kwargs)
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return inner
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cached_cache_len = [0]
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if size_callback is not None:
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def cache_len():
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return cached_cache_len[0]
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else:
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def cache_len():
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return len(cache)
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self.len = synchronized(cache_len)
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def add_node(key, value, callbacks=set()):
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prev_node = list_root
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next_node = prev_node.next_node
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node = _Node(prev_node, next_node, key, value, callbacks)
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prev_node.next_node = node
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next_node.prev_node = node
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cache[key] = node
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if size_callback:
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cached_cache_len[0] += size_callback(node.value)
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def move_node_to_front(node):
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prev_node = node.prev_node
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next_node = node.next_node
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prev_node.next_node = next_node
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next_node.prev_node = prev_node
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prev_node = list_root
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next_node = prev_node.next_node
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node.prev_node = prev_node
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node.next_node = next_node
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prev_node.next_node = node
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next_node.prev_node = node
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def delete_node(node):
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prev_node = node.prev_node
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next_node = node.next_node
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prev_node.next_node = next_node
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next_node.prev_node = prev_node
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deleted_len = 1
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if size_callback:
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deleted_len = size_callback(node.value)
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cached_cache_len[0] -= deleted_len
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for cb in node.callbacks:
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cb()
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node.callbacks.clear()
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return deleted_len
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@synchronized
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def cache_get(key, default=None, callbacks=[]):
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node = cache.get(key, None)
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if node is not None:
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move_node_to_front(node)
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node.callbacks.update(callbacks)
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return node.value
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else:
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return default
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@synchronized
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def cache_set(key, value, callbacks=[]):
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node = cache.get(key, None)
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if node is not None:
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# We sometimes store large objects, e.g. dicts, which cause
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# the inequality check to take a long time. So let's only do
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# the check if we have some callbacks to call.
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if node.callbacks and value != node.value:
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for cb in node.callbacks:
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cb()
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node.callbacks.clear()
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# We don't bother to protect this by value != node.value as
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# generally size_callback will be cheap compared with equality
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# checks. (For example, taking the size of two dicts is quicker
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# than comparing them for equality.)
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if size_callback:
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cached_cache_len[0] -= size_callback(node.value)
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cached_cache_len[0] += size_callback(value)
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node.callbacks.update(callbacks)
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move_node_to_front(node)
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node.value = value
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else:
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add_node(key, value, set(callbacks))
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evict()
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@synchronized
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def cache_set_default(key, value):
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node = cache.get(key, None)
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if node is not None:
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return node.value
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else:
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add_node(key, value)
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evict()
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return value
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@synchronized
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def cache_pop(key, default=None):
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node = cache.get(key, None)
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if node:
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delete_node(node)
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cache.pop(node.key, None)
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return node.value
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else:
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return default
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@synchronized
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def cache_del_multi(key):
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"""
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This will only work if constructed with cache_type=TreeCache
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"""
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popped = cache.pop(key)
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if popped is None:
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return
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for leaf in enumerate_leaves(popped, keylen - len(key)):
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delete_node(leaf)
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@synchronized
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def cache_clear():
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list_root.next_node = list_root
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list_root.prev_node = list_root
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for node in cache.values():
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for cb in node.callbacks:
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cb()
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cache.clear()
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if size_callback:
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cached_cache_len[0] = 0
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@synchronized
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def cache_contains(key):
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return key in cache
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self.sentinel = object()
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self._on_resize = evict
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self.get = cache_get
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self.set = cache_set
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self.setdefault = cache_set_default
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self.pop = cache_pop
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if cache_type is TreeCache:
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self.del_multi = cache_del_multi
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self.len = synchronized(cache_len)
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self.contains = cache_contains
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self.clear = cache_clear
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def __getitem__(self, key):
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result = self.get(key, self.sentinel)
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if result is self.sentinel:
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raise KeyError()
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else:
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return result
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def __setitem__(self, key, value):
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self.set(key, value)
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def __delitem__(self, key, value):
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result = self.pop(key, self.sentinel)
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if result is self.sentinel:
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raise KeyError()
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def __len__(self):
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return self.len()
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def __contains__(self, key):
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return self.contains(key)
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def set_cache_factor(self, factor: float) -> bool:
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"""
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Set the cache factor for this individual cache.
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This will trigger a resize if it changes, which may require evicting
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items from the cache.
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Returns:
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bool: Whether the cache changed size or not.
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"""
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if not self.apply_cache_factor_from_config:
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return False
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new_size = int(self._original_max_size * factor)
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if new_size != self.max_size:
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self.max_size = new_size
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self._on_resize()
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return True
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return False
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