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# Copyright 2015, 2016 OpenMarket Ltd
# Copyright 2019, 2020 The 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 logging
from sys import intern
from typing import Callable, Dict, Optional, Sized
import attr
from prometheus_client.core import Gauge
from synapse.config.cache import add_resizable_cache
logger = logging.getLogger(__name__)
# Whether to track estimated memory usage of the LruCaches.
TRACK_MEMORY_USAGE = False
caches_by_name: Dict[str, Sized] = {}
collectors_by_name: Dict[str, "CacheMetric"] = {}
cache_size = Gauge("synapse_util_caches_cache:size", "", ["name"])
cache_hits = Gauge("synapse_util_caches_cache:hits", "", ["name"])
cache_evicted = Gauge("synapse_util_caches_cache:evicted_size", "", ["name"])
cache_total = Gauge("synapse_util_caches_cache:total", "", ["name"])
cache_max_size = Gauge("synapse_util_caches_cache_max_size", "", ["name"])
cache_memory_usage = Gauge(
"synapse_util_caches_cache_size_bytes",
"Estimated memory usage of the caches",
["name"],
)
response_cache_size = Gauge("synapse_util_caches_response_cache:size", "", ["name"])
response_cache_hits = Gauge("synapse_util_caches_response_cache:hits", "", ["name"])
response_cache_evicted = Gauge(
"synapse_util_caches_response_cache:evicted_size", "", ["name"]
)
response_cache_total = Gauge("synapse_util_caches_response_cache:total", "", ["name"])
@attr.s(slots=True)
class CacheMetric:
_cache = attr.ib()
_cache_type = attr.ib(type=str)
_cache_name = attr.ib(type=str)
_collect_callback = attr.ib(type=Optional[Callable])
hits = attr.ib(default=0)
misses = attr.ib(default=0)
evicted_size = attr.ib(default=0)
memory_usage = attr.ib(default=None)
def inc_hits(self):
self.hits += 1
def inc_misses(self):
self.misses += 1
def inc_evictions(self, size=1):
self.evicted_size += size
def inc_memory_usage(self, memory: int):
if self.memory_usage is None:
self.memory_usage = 0
self.memory_usage += memory
def dec_memory_usage(self, memory: int):
self.memory_usage -= memory
def clear_memory_usage(self):
if self.memory_usage is not None:
self.memory_usage = 0
def describe(self):
return []
def collect(self):
try:
if self._cache_type == "response_cache":
response_cache_size.labels(self._cache_name).set(len(self._cache))
response_cache_hits.labels(self._cache_name).set(self.hits)
response_cache_evicted.labels(self._cache_name).set(self.evicted_size)
response_cache_total.labels(self._cache_name).set(
self.hits + self.misses
)
else:
cache_size.labels(self._cache_name).set(len(self._cache))
cache_hits.labels(self._cache_name).set(self.hits)
cache_evicted.labels(self._cache_name).set(self.evicted_size)
cache_total.labels(self._cache_name).set(self.hits + self.misses)
if getattr(self._cache, "max_size", None):
cache_max_size.labels(self._cache_name).set(self._cache.max_size)
if TRACK_MEMORY_USAGE:
# self.memory_usage can be None if nothing has been inserted
# into the cache yet.
cache_memory_usage.labels(self._cache_name).set(
self.memory_usage or 0
)
if self._collect_callback:
self._collect_callback()
except Exception as e:
logger.warning("Error calculating metrics for %s: %s", self._cache_name, e)
raise
def register_cache(
cache_type: str,
cache_name: str,
cache: Sized,
collect_callback: Optional[Callable] = None,
resizable: bool = True,
resize_callback: Optional[Callable] = None,
) -> CacheMetric:
"""Register a cache object for metric collection and resizing.
Args:
cache_type: a string indicating the "type" of the cache. This is used
only for deduplication so isn't too important provided it's constant.
cache_name: name of the cache
cache: cache itself, which must implement __len__(), and may optionally implement
a max_size property
collect_callback: If given, a function which is called during metric
collection to update additional metrics.
resizable: Whether this cache supports being resized, in which case either
resize_callback must be provided, or the cache must support set_max_size().
resize_callback: A function which can be called to resize the cache.
Returns:
CacheMetric: an object which provides inc_{hits,misses,evictions} methods
"""
if resizable:
if not resize_callback:
resize_callback = cache.set_cache_factor # type: ignore
add_resizable_cache(cache_name, resize_callback)
metric = CacheMetric(cache, cache_type, cache_name, collect_callback)
metric_name = "cache_%s_%s" % (cache_type, cache_name)
caches_by_name[cache_name] = cache
collectors_by_name[metric_name] = metric
return metric
KNOWN_KEYS = {
key: key
for key in (
"auth_events",
"content",
"depth",
"event_id",
"hashes",
"origin",
"origin_server_ts",
"prev_events",
"room_id",
"sender",
"signatures",
"state_key",
"type",
"unsigned",
"user_id",
)
}
def intern_string(string):
"""Takes a (potentially) unicode string and interns it if it's ascii"""
if string is None:
return None
try:
return intern(string)
except UnicodeEncodeError:
return string
def intern_dict(dictionary):
"""Takes a dictionary and interns well known keys and their values"""
return {
KNOWN_KEYS.get(key, key): _intern_known_values(key, value)
for key, value in dictionary.items()
}
def _intern_known_values(key, value):
intern_keys = ("event_id", "room_id", "sender", "user_id", "type", "state_key")
if key in intern_keys:
return intern_string(value)
return value
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