summaryrefslogtreecommitdiff
path: root/synapse/util/caches/__init__.py
blob: e676c2cac46b45197ca3685b93b8b1a27732e1d7 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
# -*- coding: utf-8 -*-
# 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__)

caches_by_name = {}
collectors_by_name = {}  # type: Dict

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"])

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)

    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 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 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 = getattr(cache, "set_cache_factor")
        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