forked-synapse/synapse/util/caches/dictionary_cache.py

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# Copyright 2015, 2016 OpenMarket Ltd
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#
# 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.
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import enum
import logging
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import threading
from typing import Any, Dict, Generic, Iterable, Optional, Set, Tuple, TypeVar, Union
import attr
from typing_extensions import Literal
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from synapse.util.caches.lrucache import LruCache
from synapse.util.caches.treecache import TreeCache
logger = logging.getLogger(__name__)
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# The type of the cache keys.
KT = TypeVar("KT")
# The type of the dictionary keys.
DKT = TypeVar("DKT")
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# The type of the dictionary values.
DV = TypeVar("DV")
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# This class can't be generic because it uses slots with attrs.
# See: https://github.com/python-attrs/attrs/issues/313
@attr.s(slots=True, frozen=True, auto_attribs=True)
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class DictionaryEntry: # should be: Generic[DKT, DV].
"""Returned when getting an entry from the cache
If `full` is true then `known_absent` will be the empty set.
Attributes:
full: Whether the cache has the full or dict or just some keys.
If not full then not all requested keys will necessarily be present
in `value`
known_absent: Keys that were looked up in the dict and were not there.
value: The full or partial dict value
"""
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full: bool
known_absent: Set[Any] # should be: Set[DKT]
value: Dict[Any, Any] # should be: Dict[DKT, DV]
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def __len__(self) -> int:
return len(self.value)
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class _FullCacheKey(enum.Enum):
"""The key we use to cache the full dict."""
KEY = object()
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class _Sentinel(enum.Enum):
# defining a sentinel in this way allows mypy to correctly handle the
# type of a dictionary lookup.
sentinel = object()
class _PerKeyValue(Generic[DV]):
"""The cached value of a dictionary key. If `value` is the sentinel,
indicates that the requested key is known to *not* be in the full dict.
"""
__slots__ = ["value"]
def __init__(self, value: Union[DV, Literal[_Sentinel.sentinel]]) -> None:
self.value = value
def __len__(self) -> int:
# We add a `__len__` implementation as we use this class in a cache
# where the values are variable length.
return 1
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class DictionaryCache(Generic[KT, DKT, DV]):
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"""Caches key -> dictionary lookups, supporting caching partial dicts, i.e.
fetching a subset of dictionary keys for a particular key.
This cache has two levels of key. First there is the "cache key" (of type
`KT`), which maps to a dict. The keys to that dict are the "dict key" (of
type `DKT`). The overall structure is therefore `KT->DKT->DV`. For
example, it might look like:
{
1: { 1: "a", 2: "b" },
2: { 1: "c" },
}
It is possible to look up either individual dict keys, or the *complete*
dict for a given cache key.
Each dict item, and the complete dict is treated as a separate LRU
entry for the purpose of cache expiry. For example, given:
dict_cache.get(1, None) -> DictionaryEntry({1: "a", 2: "b"})
dict_cache.get(1, [1]) -> DictionaryEntry({1: "a"})
dict_cache.get(1, [2]) -> DictionaryEntry({2: "b"})
... then the cache entry for the complete dict will expire first,
followed by the cache entry for the '1' dict key, and finally that
for the '2' dict key.
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"""
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def __init__(self, name: str, max_entries: int = 1000):
# We use a single LruCache to store two different types of entries:
# 1. Map from (key, dict_key) -> dict value (or sentinel, indicating
# the key doesn't exist in the dict); and
# 2. Map from (key, _FullCacheKey.KEY) -> full dict.
#
# The former is used when explicit keys of the dictionary are looked up,
# and the latter when the full dictionary is requested.
#
# If when explicit keys are requested and not in the cache, we then look
# to see if we have the full dict and use that if we do. If found in the
# full dict each key is added into the cache.
#
# This set up allows the `LruCache` to prune the full dict entries if
# they haven't been used in a while, even when there have been recent
# queries for subsets of the dict.
#
# Typing:
# * A key of `(KT, DKT)` has a value of `_PerKeyValue`
# * A key of `(KT, _FullCacheKey.KEY)` has a value of `Dict[DKT, DV]`
self.cache: LruCache[
Tuple[KT, Union[DKT, Literal[_FullCacheKey.KEY]]],
Union[_PerKeyValue, Dict[DKT, DV]],
] = LruCache(
max_size=max_entries,
cache_name=name,
cache_type=TreeCache,
size_callback=len,
)
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self.name = name
self.sequence = 0
self.thread: Optional[threading.Thread] = None
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def check_thread(self) -> None:
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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: KT, dict_keys: Optional[Iterable[DKT]] = None
) -> DictionaryEntry:
"""Fetch an entry out of the cache
Args:
key
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dict_keys: If given a set of keys then return only those keys
that exist in the cache. If None then returns the full dict
if it is in the cache.
Returns:
If `dict_keys` is not None then `DictionaryEntry` will contain include
the keys that are in the cache.
If None then will either return the full dict if in the cache, or the
empty dict (with `full` set to False) if it isn't.
"""
if dict_keys is None:
# The caller wants the full set of dictionary keys for this cache key
return self._get_full_dict(key)
# We are being asked for a subset of keys.
# First go and check for each requested dict key in the cache, tracking
# which we couldn't find.
values = {}
known_absent = set()
missing = []
for dict_key in dict_keys:
entry = self.cache.get((key, dict_key), _Sentinel.sentinel)
if entry is _Sentinel.sentinel:
missing.append(dict_key)
continue
assert isinstance(entry, _PerKeyValue)
if entry.value is _Sentinel.sentinel:
known_absent.add(dict_key)
else:
values[dict_key] = entry.value
# If we found everything we can return immediately.
if not missing:
return DictionaryEntry(False, known_absent, values)
# We are missing some keys, so check if we happen to have the full dict in
# the cache.
#
# We don't update the last access time for this cache fetch, as we
# aren't explicitly interested in the full dict and so we don't want
# requests for explicit dict keys to keep the full dict in the cache.
entry = self.cache.get(
(key, _FullCacheKey.KEY),
_Sentinel.sentinel,
update_last_access=False,
)
if entry is _Sentinel.sentinel:
# Not in the cache, return the subset of keys we found.
return DictionaryEntry(False, known_absent, values)
# We have the full dict!
assert isinstance(entry, dict)
for dict_key in missing:
# We explicitly add each dict key to the cache, so that cache hit
# rates and LRU times for each key can be tracked separately.
value = entry.get(dict_key, _Sentinel.sentinel) # type: ignore[arg-type]
self.cache[(key, dict_key)] = _PerKeyValue(value)
if value is not _Sentinel.sentinel:
values[dict_key] = value
return DictionaryEntry(True, set(), values)
def _get_full_dict(
self,
key: KT,
) -> DictionaryEntry:
"""Fetch the full dict for the given key."""
# First we check if we have cached the full dict.
entry = self.cache.get((key, _FullCacheKey.KEY), _Sentinel.sentinel)
if entry is not _Sentinel.sentinel:
assert isinstance(entry, dict)
return DictionaryEntry(True, set(), entry)
return DictionaryEntry(False, set(), {})
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def invalidate(self, key: KT) -> None:
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self.check_thread()
# Increment the sequence number so that any SELECT statements that
# raced with the INSERT don't update the cache (SYN-369)
self.sequence += 1
# We want to drop all information about the dict for the given key, so
# we use `del_multi` to delete it all in one go.
#
# We ignore the type error here: `del_multi` accepts a truncated key
# (when the key type is a tuple).
self.cache.del_multi((key,)) # type: ignore[arg-type]
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def invalidate_all(self) -> None:
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self.check_thread()
self.sequence += 1
self.cache.clear()
def update(
self,
sequence: int,
key: KT,
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value: Dict[DKT, DV],
fetched_keys: Optional[Iterable[DKT]] = None,
) -> None:
"""Updates the entry in the cache.
Note: This does *not* invalidate any existing entries for the `key`.
In particular, if we add an entry for the cached "full dict" with
`fetched_keys=None`, existing entries for individual dict keys are
not invalidated. Likewise, adding entries for individual keys does
not invalidate any cached value for the full dict.
In other words: if the underlying data is *changed*, the cache must
be explicitly invalidated via `.invalidate()`.
Args:
sequence
key
value: The value to update the cache with.
fetched_keys: All of the dictionary keys which were
fetched from the database.
If None, this is the complete value for key K. Otherwise, it
is used to infer a list of keys which we know don't exist in
the full dict.
"""
self.check_thread()
if self.sequence == sequence:
# Only update the cache if the caches sequence number matches the
# number that the cache had before the SELECT was started (SYN-369)
if fetched_keys is None:
self.cache[(key, _FullCacheKey.KEY)] = value
else:
self._update_subset(key, value, fetched_keys)
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def _update_subset(
self, key: KT, value: Dict[DKT, DV], fetched_keys: Iterable[DKT]
) -> None:
"""Add the given dictionary values as explicit keys in the cache.
Args:
key: top-level cache key
value: The dictionary with all the values that we should cache
fetched_keys: The full set of dict keys that were looked up. Any keys
here not in `value` should be marked as "known absent".
"""
for dict_key, dict_value in value.items():
self.cache[(key, dict_key)] = _PerKeyValue(dict_value)
for dict_key in fetched_keys:
if dict_key in value:
continue
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self.cache[(key, dict_key)] = _PerKeyValue(_Sentinel.sentinel)