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# -*- coding: utf-8 -*-
# Copyright 2019 Matrix.org Foundation C.I.C.
#
# 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 os
from typing import Callable, Dict
from ._base import Config, ConfigError
# The prefix for all cache factor-related environment variables
_CACHES = {}
_CACHE_PREFIX = "SYNAPSE_CACHE_FACTOR"
_DEFAULT_FACTOR_SIZE = 0.5
_DEFAULT_EVENT_CACHE_SIZE = "10K"
class CacheProperties(object):
def __init__(self):
# The default factor size for all caches
self.default_factor_size = float(
os.environ.get(_CACHE_PREFIX, _DEFAULT_FACTOR_SIZE)
)
self.resize_all_caches_func = None
properties = CacheProperties()
def add_resizable_cache(cache_name: str, cache_resize_callback: Callable):
"""Register a cache that's size can dynamically change
Args:
cache_name: A reference to the cache
cache_resize_callback: A callback function that will be ran whenever
the cache needs to be resized
"""
_CACHES[cache_name.lower()] = cache_resize_callback
# Ensure all loaded caches are sized appropriately
#
# This method should only run once the config has been read,
# as it uses values read from it
if properties.resize_all_caches_func:
properties.resize_all_caches_func()
class CacheConfig(Config):
section = "caches"
_environ = os.environ
@staticmethod
def reset():
"""Resets the caches to their defaults. Used for tests."""
properties.default_factor_size = float(
os.environ.get(_CACHE_PREFIX, _DEFAULT_FACTOR_SIZE)
)
properties.resize_all_caches_func = None
_CACHES.clear()
def generate_config_section(self, **kwargs):
return """\
## Caching ##
# Caching can be configured through the following options.
#
# A cache 'factor' is a multiplier that can be applied to each of
# Synapse's caches in order to increase or decrease the maximum
# number of entries that can be stored.
# The number of events to cache in memory. Not affected by
# caches.global_factor.
#
#event_cache_size: 10K
caches:
# Controls the global cache factor, which is the default cache factor
# for all caches if a specific factor for that cache is not otherwise
# set.
#
# This can also be set by the "SYNAPSE_CACHE_FACTOR" environment
# variable. Setting by environment variable takes priority over
# setting through the config file.
#
# Defaults to 0.5, which will half the size of all caches.
#
#global_factor: 1.0
# A dictionary of cache name to cache factor for that individual
# cache. Overrides the global cache factor for a given cache.
#
# These can also be set through environment variables comprised
# of "SYNAPSE_CACHE_FACTOR_" + the name of the cache in capital
# letters and underscores. Setting by environment variable
# takes priority over setting through the config file.
# Ex. SYNAPSE_CACHE_FACTOR_GET_USERS_WHO_SHARE_ROOM_WITH_USER=2.0
#
per_cache_factors:
#get_users_who_share_room_with_user: 2.0
"""
def read_config(self, config, **kwargs):
self.event_cache_size = self.parse_size(
config.get("event_cache_size", _DEFAULT_EVENT_CACHE_SIZE)
)
self.cache_factors = {} # type: Dict[str, float]
cache_config = config.get("caches") or {}
self.global_factor = cache_config.get(
"global_factor", properties.default_factor_size
)
if not isinstance(self.global_factor, (int, float)):
raise ConfigError("caches.global_factor must be a number.")
# Set the global one so that it's reflected in new caches
properties.default_factor_size = self.global_factor
# Load cache factors from the config
individual_factors = cache_config.get("per_cache_factors") or {}
if not isinstance(individual_factors, dict):
raise ConfigError("caches.per_cache_factors must be a dictionary")
# Override factors from environment if necessary
individual_factors.update(
{
key[len(_CACHE_PREFIX) + 1 :].lower(): float(val)
for key, val in self._environ.items()
if key.startswith(_CACHE_PREFIX + "_")
}
)
for cache, factor in individual_factors.items():
if not isinstance(factor, (int, float)):
raise ConfigError(
"caches.per_cache_factors.%s must be a number" % (cache.lower(),)
)
self.cache_factors[cache.lower()] = factor
# Resize all caches (if necessary) with the new factors we've loaded
self.resize_all_caches()
# Store this function so that it can be called from other classes without
# needing an instance of Config
properties.resize_all_caches_func = self.resize_all_caches
def resize_all_caches(self):
"""Ensure all cache sizes are up to date
For each cache, run the mapped callback function with either
a specific cache factor or the default, global one.
"""
for cache_name, callback in _CACHES.items():
new_factor = self.cache_factors.get(cache_name, self.global_factor)
callback(new_factor)
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