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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