# -*- coding: utf-8 -*- # Copyright 2015, 2016 OpenMarket Ltd # Copyright 2018 New Vector 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. import functools import inspect import logging import threading from collections import namedtuple import six from six import itervalues, string_types from twisted.internet import defer from synapse.util import logcontext, unwrapFirstError from synapse.util.async_helpers import ObservableDeferred from synapse.util.caches import get_cache_factor_for from synapse.util.caches.lrucache import LruCache from synapse.util.caches.treecache import TreeCache, iterate_tree_cache_entry from synapse.util.stringutils import to_ascii from . import register_cache logger = logging.getLogger(__name__) _CacheSentinel = object() class CacheEntry(object): __slots__ = ["deferred", "callbacks", "invalidated"] def __init__(self, deferred, callbacks): self.deferred = deferred self.callbacks = set(callbacks) self.invalidated = False def invalidate(self): if not self.invalidated: self.invalidated = True for callback in self.callbacks: callback() self.callbacks.clear() class Cache(object): __slots__ = ( "cache", "max_entries", "name", "keylen", "thread", "metrics", "_pending_deferred_cache", ) def __init__(self, name, max_entries=1000, keylen=1, tree=False, iterable=False): cache_type = TreeCache if tree else dict self._pending_deferred_cache = cache_type() self.cache = LruCache( max_size=max_entries, keylen=keylen, cache_type=cache_type, size_callback=(lambda d: len(d)) if iterable else None, evicted_callback=self._on_evicted, ) self.name = name self.keylen = keylen self.thread = None self.metrics = register_cache("cache", name, self.cache) def _on_evicted(self, evicted_count): self.metrics.inc_evictions(evicted_count) def check_thread(self): expected_thread = self.thread if expected_thread is None: self.thread = threading.current_thread() else: if expected_thread is not threading.current_thread(): raise ValueError( "Cache objects can only be accessed from the main thread" ) def get(self, key, default=_CacheSentinel, callback=None, update_metrics=True): """Looks the key up in the caches. Args: key(tuple) default: What is returned if key is not in the caches. If not specified then function throws KeyError instead callback(fn): Gets called when the entry in the cache is invalidated update_metrics (bool): whether to update the cache hit rate metrics Returns: Either a Deferred or the raw result """ callbacks = [callback] if callback else [] val = self._pending_deferred_cache.get(key, _CacheSentinel) if val is not _CacheSentinel: val.callbacks.update(callbacks) if update_metrics: self.metrics.inc_hits() return val.deferred val = self.cache.get(key, _CacheSentinel, callbacks=callbacks) if val is not _CacheSentinel: self.metrics.inc_hits() return val if update_metrics: self.metrics.inc_misses() if default is _CacheSentinel: raise KeyError() else: return default def set(self, key, value, callback=None): callbacks = [callback] if callback else [] self.check_thread() entry = CacheEntry(deferred=value, callbacks=callbacks) existing_entry = self._pending_deferred_cache.pop(key, None) if existing_entry: existing_entry.invalidate() self._pending_deferred_cache[key] = entry def shuffle(result): existing_entry = self._pending_deferred_cache.pop(key, None) if existing_entry is entry: self.cache.set(key, result, entry.callbacks) else: # oops, the _pending_deferred_cache has been updated since # we started our query, so we are out of date. # # Better put back whatever we took out. (We do it this way # round, rather than peeking into the _pending_deferred_cache # and then removing on a match, to make the common case faster) if existing_entry is not None: self._pending_deferred_cache[key] = existing_entry # we're not going to put this entry into the cache, so need # to make sure that the invalidation callbacks are called. # That was probably done when _pending_deferred_cache was # updated, but it's possible that `set` was called without # `invalidate` being previously called, in which case it may # not have been. Either way, let's double-check now. entry.invalidate() return result entry.deferred.addCallback(shuffle) def prefill(self, key, value, callback=None): callbacks = [callback] if callback else [] self.cache.set(key, value, callbacks=callbacks) def invalidate(self, key): self.check_thread() self.cache.pop(key, None) # if we have a pending lookup for this key, remove it from the # _pending_deferred_cache, which will (a) stop it being returned # for future queries and (b) stop it being persisted as a proper entry # in self.cache. entry = self._pending_deferred_cache.pop(key, None) # run the invalidation callbacks now, rather than waiting for the # deferred to resolve. if entry: entry.invalidate() def invalidate_many(self, key): self.check_thread() if not isinstance(key, tuple): raise TypeError("The cache key must be a tuple not %r" % (type(key),)) self.cache.del_multi(key) # if we have a pending lookup for this key, remove it from the # _pending_deferred_cache, as above entry_dict = self._pending_deferred_cache.pop(key, None) if entry_dict is not None: for entry in iterate_tree_cache_entry(entry_dict): entry.invalidate() def invalidate_all(self): self.check_thread() self.cache.clear() for entry in itervalues(self._pending_deferred_cache): entry.invalidate() self._pending_deferred_cache.clear() class _CacheDescriptorBase(object): def __init__(self, orig, num_args, inlineCallbacks, cache_context=False): self.orig = orig if inlineCallbacks: self.function_to_call = defer.inlineCallbacks(orig) else: self.function_to_call = orig arg_spec = inspect.getargspec(orig) all_args = arg_spec.args if "cache_context" in all_args: if not cache_context: raise ValueError( "Cannot have a 'cache_context' arg without setting" " cache_context=True" ) elif cache_context: raise ValueError( "Cannot have cache_context=True without having an arg" " named `cache_context`" ) if num_args is None: num_args = len(all_args) - 1 if cache_context: num_args -= 1 if len(all_args) < num_args + 1: raise Exception( "Not enough explicit positional arguments to key off for %r: " "got %i args, but wanted %i. (@cached cannot key off *args or " "**kwargs)" % (orig.__name__, len(all_args), num_args) ) self.num_args = num_args # list of the names of the args used as the cache key self.arg_names = all_args[1 : num_args + 1] # self.arg_defaults is a map of arg name to its default value for each # argument that has a default value if arg_spec.defaults: self.arg_defaults = dict( zip(all_args[-len(arg_spec.defaults) :], arg_spec.defaults) ) else: self.arg_defaults = {} if "cache_context" in self.arg_names: raise Exception("cache_context arg cannot be included among the cache keys") self.add_cache_context = cache_context class CacheDescriptor(_CacheDescriptorBase): """ A method decorator that applies a memoizing cache around the function. This caches deferreds, rather than the results themselves. Deferreds that fail are removed from the cache. The function is presumed to take zero or more arguments, which are used in a tuple as the key for the cache. Hits are served directly from the cache; misses use the function body to generate the value. The wrapped function has an additional member, a callable called "invalidate". This can be used to remove individual entries from the cache. The wrapped function has another additional callable, called "prefill", which can be used to insert values into the cache specifically, without calling the calculation function. Cached functions can be "chained" (i.e. a cached function can call other cached functions and get appropriately invalidated when they called caches are invalidated) by adding a special "cache_context" argument to the function and passing that as a kwarg to all caches called. For example:: @cachedInlineCallbacks(cache_context=True) def foo(self, key, cache_context): r1 = yield self.bar1(key, on_invalidate=cache_context.invalidate) r2 = yield self.bar2(key, on_invalidate=cache_context.invalidate) defer.returnValue(r1 + r2) Args: num_args (int): number of positional arguments (excluding ``self`` and ``cache_context``) to use as cache keys. Defaults to all named args of the function. """ def __init__( self, orig, max_entries=1000, num_args=None, tree=False, inlineCallbacks=False, cache_context=False, iterable=False, ): super(CacheDescriptor, self).__init__( orig, num_args=num_args, inlineCallbacks=inlineCallbacks, cache_context=cache_context, ) max_entries = int(max_entries * get_cache_factor_for(orig.__name__)) self.max_entries = max_entries self.tree = tree self.iterable = iterable def __get__(self, obj, objtype=None): cache = Cache( name=self.orig.__name__, max_entries=self.max_entries, keylen=self.num_args, tree=self.tree, iterable=self.iterable, ) def get_cache_key_gen(args, kwargs): """Given some args/kwargs return a generator that resolves into the cache_key. We loop through each arg name, looking up if its in the `kwargs`, otherwise using the next argument in `args`. If there are no more args then we try looking the arg name up in the defaults """ pos = 0 for nm in self.arg_names: if nm in kwargs: yield kwargs[nm] elif pos < len(args): yield args[pos] pos += 1 else: yield self.arg_defaults[nm] # By default our cache key is a tuple, but if there is only one item # then don't bother wrapping in a tuple. This is to save memory. if self.num_args == 1: nm = self.arg_names[0] def get_cache_key(args, kwargs): if nm in kwargs: return kwargs[nm] elif len(args): return args[0] else: return self.arg_defaults[nm] else: def get_cache_key(args, kwargs): return tuple(get_cache_key_gen(args, kwargs)) @functools.wraps(self.orig) def wrapped(*args, **kwargs): # If we're passed a cache_context then we'll want to call its invalidate() # whenever we are invalidated invalidate_callback = kwargs.pop("on_invalidate", None) cache_key = get_cache_key(args, kwargs) # Add our own `cache_context` to argument list if the wrapped function # has asked for one if self.add_cache_context: kwargs["cache_context"] = _CacheContext(cache, cache_key) try: cached_result_d = cache.get(cache_key, callback=invalidate_callback) if isinstance(cached_result_d, ObservableDeferred): observer = cached_result_d.observe() else: observer = cached_result_d except KeyError: ret = defer.maybeDeferred( logcontext.preserve_fn(self.function_to_call), obj, *args, **kwargs ) def onErr(f): cache.invalidate(cache_key) return f ret.addErrback(onErr) # If our cache_key is a string on py2, try to convert to ascii # to save a bit of space in large caches. Py3 does this # internally automatically. if six.PY2 and isinstance(cache_key, string_types): cache_key = to_ascii(cache_key) result_d = ObservableDeferred(ret, consumeErrors=True) cache.set(cache_key, result_d, callback=invalidate_callback) observer = result_d.observe() if isinstance(observer, defer.Deferred): return logcontext.make_deferred_yieldable(observer) else: return observer if self.num_args == 1: wrapped.invalidate = lambda key: cache.invalidate(key[0]) wrapped.prefill = lambda key, val: cache.prefill(key[0], val) else: wrapped.invalidate = cache.invalidate wrapped.invalidate_all = cache.invalidate_all wrapped.invalidate_many = cache.invalidate_many wrapped.prefill = cache.prefill wrapped.invalidate_all = cache.invalidate_all wrapped.cache = cache wrapped.num_args = self.num_args obj.__dict__[self.orig.__name__] = wrapped return wrapped class CacheListDescriptor(_CacheDescriptorBase): """Wraps an existing cache to support bulk fetching of keys. Given a list of keys it looks in the cache to find any hits, then passes the list of missing keys to the wrapped function. Once wrapped, the function returns either a Deferred which resolves to the list of results, or (if all results were cached), just the list of results. """ def __init__( self, orig, cached_method_name, list_name, num_args=None, inlineCallbacks=False ): """ Args: orig (function) cached_method_name (str): The name of the chached method. list_name (str): Name of the argument which is the bulk lookup list num_args (int): number of positional arguments (excluding ``self``, but including list_name) to use as cache keys. Defaults to all named args of the function. inlineCallbacks (bool): Whether orig is a generator that should be wrapped by defer.inlineCallbacks """ super(CacheListDescriptor, self).__init__( orig, num_args=num_args, inlineCallbacks=inlineCallbacks ) self.list_name = list_name self.list_pos = self.arg_names.index(self.list_name) self.cached_method_name = cached_method_name self.sentinel = object() if self.list_name not in self.arg_names: raise Exception( "Couldn't see arguments %r for %r." % (self.list_name, cached_method_name) ) def __get__(self, obj, objtype=None): cached_method = getattr(obj, self.cached_method_name) cache = cached_method.cache num_args = cached_method.num_args @functools.wraps(self.orig) def wrapped(*args, **kwargs): # If we're passed a cache_context then we'll want to call its # invalidate() whenever we are invalidated invalidate_callback = kwargs.pop("on_invalidate", None) arg_dict = inspect.getcallargs(self.orig, obj, *args, **kwargs) keyargs = [arg_dict[arg_nm] for arg_nm in self.arg_names] list_args = arg_dict[self.list_name] results = {} def update_results_dict(res, arg): results[arg] = res # list of deferreds to wait for cached_defers = [] missing = set() # If the cache takes a single arg then that is used as the key, # otherwise a tuple is used. if num_args == 1: def arg_to_cache_key(arg): return arg else: keylist = list(keyargs) def arg_to_cache_key(arg): keylist[self.list_pos] = arg return tuple(keylist) for arg in list_args: try: res = cache.get(arg_to_cache_key(arg), callback=invalidate_callback) if not isinstance(res, ObservableDeferred): results[arg] = res elif not res.has_succeeded(): res = res.observe() res.addCallback(update_results_dict, arg) cached_defers.append(res) else: results[arg] = res.get_result() except KeyError: missing.add(arg) if missing: # we need an observable deferred for each entry in the list, # which we put in the cache. Each deferred resolves with the # relevant result for that key. deferreds_map = {} for arg in missing: deferred = defer.Deferred() deferreds_map[arg] = deferred key = arg_to_cache_key(arg) observable = ObservableDeferred(deferred) cache.set(key, observable, callback=invalidate_callback) def complete_all(res): # the wrapped function has completed. It returns a # a dict. We can now resolve the observable deferreds in # the cache and update our own result map. for e in missing: val = res.get(e, None) deferreds_map[e].callback(val) results[e] = val def errback(f): # the wrapped function has failed. Invalidate any cache # entries we're supposed to be populating, and fail # their deferreds. for e in missing: key = arg_to_cache_key(e) cache.invalidate(key) deferreds_map[e].errback(f) # return the failure, to propagate to our caller. return f args_to_call = dict(arg_dict) args_to_call[self.list_name] = list(missing) cached_defers.append( defer.maybeDeferred( logcontext.preserve_fn(self.function_to_call), **args_to_call ).addCallbacks(complete_all, errback) ) if cached_defers: d = defer.gatherResults(cached_defers, consumeErrors=True).addCallbacks( lambda _: results, unwrapFirstError ) return logcontext.make_deferred_yieldable(d) else: return results obj.__dict__[self.orig.__name__] = wrapped return wrapped class _CacheContext(namedtuple("_CacheContext", ("cache", "key"))): # We rely on _CacheContext implementing __eq__ and __hash__ sensibly, # which namedtuple does for us (i.e. two _CacheContext are the same if # their caches and keys match). This is important in particular to # dedupe when we add callbacks to lru cache nodes, otherwise the number # of callbacks would grow. def invalidate(self): self.cache.invalidate(self.key) def cached( max_entries=1000, num_args=None, tree=False, cache_context=False, iterable=False ): return lambda orig: CacheDescriptor( orig, max_entries=max_entries, num_args=num_args, tree=tree, cache_context=cache_context, iterable=iterable, ) def cachedInlineCallbacks( max_entries=1000, num_args=None, tree=False, cache_context=False, iterable=False ): return lambda orig: CacheDescriptor( orig, max_entries=max_entries, num_args=num_args, tree=tree, inlineCallbacks=True, cache_context=cache_context, iterable=iterable, ) def cachedList(cached_method_name, list_name, num_args=None, inlineCallbacks=False): """Creates a descriptor that wraps a function in a `CacheListDescriptor`. Used to do batch lookups for an already created cache. A single argument is specified as a list that is iterated through to lookup keys in the original cache. A new list consisting of the keys that weren't in the cache get passed to the original function, the result of which is stored in the cache. Args: cached_method_name (str): The name of the single-item lookup method. This is only used to find the cache to use. list_name (str): The name of the argument that is the list to use to do batch lookups in the cache. num_args (int): Number of arguments to use as the key in the cache (including list_name). Defaults to all named parameters. inlineCallbacks (bool): Should the function be wrapped in an `defer.inlineCallbacks`? Example: class Example(object): @cached(num_args=2) def do_something(self, first_arg): ... @cachedList(do_something.cache, list_name="second_args", num_args=2) def batch_do_something(self, first_arg, second_args): ... """ return lambda orig: CacheListDescriptor( orig, cached_method_name=cached_method_name, list_name=list_name, num_args=num_args, inlineCallbacks=inlineCallbacks, )