forked-synapse/synapse/util/caches/descriptors.py
2020-09-04 06:54:56 -04:00

725 lines
25 KiB
Python

# -*- 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 typing import Any, Callable, Generic, Optional, Tuple, TypeVar, Union, cast
from weakref import WeakValueDictionary
from prometheus_client import Gauge
from twisted.internet import defer
from synapse.logging.context import make_deferred_yieldable, preserve_fn
from synapse.util import unwrapFirstError
from synapse.util.async_helpers import ObservableDeferred
from synapse.util.caches.lrucache import LruCache
from synapse.util.caches.treecache import TreeCache, iterate_tree_cache_entry
from . import register_cache
logger = logging.getLogger(__name__)
CacheKey = Union[Tuple, Any]
F = TypeVar("F", bound=Callable[..., Any])
class _CachedFunction(Generic[F]):
invalidate = None # type: Any
invalidate_all = None # type: Any
invalidate_many = None # type: Any
prefill = None # type: Any
cache = None # type: Any
num_args = None # type: Any
__name__ = None # type: str
# Note: This function signature is actually fiddled with by the synapse mypy
# plugin to a) make it a bound method, and b) remove any `cache_context` arg.
__call__ = None # type: F
cache_pending_metric = Gauge(
"synapse_util_caches_cache_pending",
"Number of lookups currently pending for this cache",
["name"],
)
_CacheSentinel = object()
class CacheEntry:
__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:
__slots__ = (
"cache",
"name",
"keylen",
"thread",
"metrics",
"_pending_deferred_cache",
)
def __init__(
self,
name: str,
max_entries: int = 1000,
keylen: int = 1,
tree: bool = False,
iterable: bool = False,
apply_cache_factor_from_config: bool = True,
):
"""
Args:
name: The name of the cache
max_entries: Maximum amount of entries that the cache will hold
keylen: The length of the tuple used as the cache key
tree: Use a TreeCache instead of a dict as the underlying cache type
iterable: If True, count each item in the cached object as an entry,
rather than each cached object
apply_cache_factor_from_config: Whether cache factors specified in the
config file affect `max_entries`
Returns:
Cache
"""
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,
apply_cache_factor_from_config=apply_cache_factor_from_config,
)
self.name = name
self.keylen = keylen
self.thread = None # type: Optional[threading.Thread]
self.metrics = register_cache(
"cache",
name,
self.cache,
collect_callback=self._metrics_collection_callback,
)
@property
def max_entries(self):
return self.cache.max_size
def _on_evicted(self, evicted_count):
self.metrics.inc_evictions(evicted_count)
def _metrics_collection_callback(self):
cache_pending_metric.labels(self.name).set(len(self._pending_deferred_cache))
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 an ObservableDeferred 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):
if not isinstance(value, defer.Deferred):
raise TypeError("not a Deferred")
callbacks = [callback] if callback else []
self.check_thread()
observable = ObservableDeferred(value, consumeErrors=True)
observer = observable.observe()
entry = CacheEntry(deferred=observable, callbacks=callbacks)
existing_entry = self._pending_deferred_cache.pop(key, None)
if existing_entry:
existing_entry.invalidate()
self._pending_deferred_cache[key] = entry
def compare_and_pop():
"""Check if our entry is still the one in _pending_deferred_cache, and
if so, pop it.
Returns true if the entries matched.
"""
existing_entry = self._pending_deferred_cache.pop(key, None)
if existing_entry is entry:
return True
# 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
return False
def cb(result):
if compare_and_pop():
self.cache.set(key, result, entry.callbacks)
else:
# 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()
def eb(_fail):
compare_and_pop()
entry.invalidate()
# once the deferred completes, we can move the entry from the
# _pending_deferred_cache to the real cache.
#
observer.addCallbacks(cb, eb)
return observable
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 self._pending_deferred_cache.values():
entry.invalidate()
self._pending_deferred_cache.clear()
class _CacheDescriptorBase:
def __init__(self, orig: _CachedFunction, num_args, cache_context=False):
self.orig = orig
arg_spec = inspect.getfullargspec(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::
@cached(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)
return 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,
cache_context=False,
iterable=False,
):
super().__init__(orig, num_args=num_args, cache_context=cache_context)
self.max_entries = max_entries
self.tree = tree
self.iterable = iterable
def __get__(self, obj, owner):
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.get_instance(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 = defer.succeed(cached_result_d)
except KeyError:
ret = defer.maybeDeferred(preserve_fn(self.orig), obj, *args, **kwargs)
def onErr(f):
cache.invalidate(cache_key)
return f
ret.addErrback(onErr)
result_d = cache.set(cache_key, ret, callback=invalidate_callback)
observer = result_d.observe()
return make_deferred_yieldable(observer)
wrapped = cast(_CachedFunction, _wrapped)
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 a Deferred which resolves to the list
of results.
"""
def __init__(self, orig, cached_method_name, list_name, num_args=None):
"""
Args:
orig (function)
cached_method_name (str): The name of the cached 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.
"""
super().__init__(orig, num_args=num_args)
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 a 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)
cache.set(key, deferred, 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(
preserve_fn(self.orig), **args_to_call
).addCallbacks(complete_all, errback)
)
if cached_defers:
d = defer.gatherResults(cached_defers, consumeErrors=True).addCallbacks(
lambda _: results, unwrapFirstError
)
return make_deferred_yieldable(d)
else:
return defer.succeed(results)
obj.__dict__[self.orig.__name__] = wrapped
return wrapped
class _CacheContext:
"""Holds cache information from the cached function higher in the calling order.
Can be used to invalidate the higher level cache entry if something changes
on a lower level.
"""
_cache_context_objects = (
WeakValueDictionary()
) # type: WeakValueDictionary[Tuple[Cache, CacheKey], _CacheContext]
def __init__(self, cache, cache_key): # type: (Cache, CacheKey) -> None
self._cache = cache
self._cache_key = cache_key
def invalidate(self): # type: () -> None
"""Invalidates the cache entry referred to by the context."""
self._cache.invalidate(self._cache_key)
@classmethod
def get_instance(cls, cache, cache_key): # type: (Cache, CacheKey) -> _CacheContext
"""Returns an instance constructed with the given arguments.
A new instance is only created if none already exists.
"""
# We make sure there are no identical _CacheContext instances. This is
# important in particular to dedupe when we add callbacks to lru cache
# nodes, otherwise the number of callbacks would grow.
return cls._cache_context_objects.setdefault(
(cache, cache_key), cls(cache, cache_key)
)
def cached(
max_entries: int = 1000,
num_args: Optional[int] = None,
tree: bool = False,
cache_context: bool = False,
iterable: bool = False,
) -> Callable[[F], _CachedFunction[F]]:
func = lambda orig: CacheDescriptor(
orig,
max_entries=max_entries,
num_args=num_args,
tree=tree,
cache_context=cache_context,
iterable=iterable,
)
return cast(Callable[[F], _CachedFunction[F]], func)
def cachedList(
cached_method_name: str, list_name: str, num_args: Optional[int] = None
) -> Callable[[F], _CachedFunction[F]]:
"""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: The name of the single-item lookup method.
This is only used to find the cache to use.
list_name: The name of the argument that is the list to use to
do batch lookups in the cache.
num_args: Number of arguments to use as the key in the cache
(including list_name). Defaults to all named parameters.
Example:
class Example:
@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):
...
"""
func = lambda orig: CacheListDescriptor(
orig,
cached_method_name=cached_method_name,
list_name=list_name,
num_args=num_args,
)
return cast(Callable[[F], _CachedFunction[F]], func)