324 lines
12 KiB
Python
324 lines
12 KiB
Python
# Copyright 2015, 2016 OpenMarket Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import enum
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import logging
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import threading
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from typing import Dict, Generic, Iterable, Optional, Set, Tuple, TypeVar, Union
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import attr
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from typing_extensions import Literal
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from synapse.util.caches.lrucache import LruCache
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from synapse.util.caches.treecache import TreeCache
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logger = logging.getLogger(__name__)
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# The type of the cache keys.
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KT = TypeVar("KT")
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# The type of the dictionary keys.
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DKT = TypeVar("DKT")
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# The type of the dictionary values.
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DV = TypeVar("DV")
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@attr.s(slots=True, frozen=True, auto_attribs=True)
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class DictionaryEntry(Generic[DKT, DV]):
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"""Returned when getting an entry from the cache
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If `full` is true then `known_absent` will be the empty set.
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Attributes:
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full: Whether the cache has the full or dict or just some keys.
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If not full then not all requested keys will necessarily be present
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in `value`
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known_absent: Keys that were looked up in the dict and were not there.
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value: The full or partial dict value
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"""
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full: bool
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known_absent: Set[DKT]
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value: Dict[DKT, DV]
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def __len__(self) -> int:
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return len(self.value)
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class _FullCacheKey(enum.Enum):
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"""The key we use to cache the full dict."""
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KEY = object()
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class _Sentinel(enum.Enum):
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# defining a sentinel in this way allows mypy to correctly handle the
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# type of a dictionary lookup.
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sentinel = object()
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class _PerKeyValue(Generic[DV]):
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"""The cached value of a dictionary key. If `value` is the sentinel,
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indicates that the requested key is known to *not* be in the full dict.
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"""
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__slots__ = ["value"]
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def __init__(self, value: Union[DV, Literal[_Sentinel.sentinel]]) -> None:
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self.value = value
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def __len__(self) -> int:
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# We add a `__len__` implementation as we use this class in a cache
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# where the values are variable length.
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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.
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fetching a subset of dictionary keys for a particular key.
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This cache has two levels of key. First there is the "cache key" (of type
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`KT`), which maps to a dict. The keys to that dict are the "dict key" (of
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type `DKT`). The overall structure is therefore `KT->DKT->DV`. For
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example, it might look like:
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{
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1: { 1: "a", 2: "b" },
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2: { 1: "c" },
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}
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It is possible to look up either individual dict keys, or the *complete*
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dict for a given cache key.
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Each dict item, and the complete dict is treated as a separate LRU
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entry for the purpose of cache expiry. For example, given:
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dict_cache.get(1, None) -> DictionaryEntry({1: "a", 2: "b"})
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dict_cache.get(1, [1]) -> DictionaryEntry({1: "a"})
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dict_cache.get(1, [2]) -> DictionaryEntry({2: "b"})
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... then the cache entry for the complete dict will expire first,
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followed by the cache entry for the '1' dict key, and finally that
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for the '2' dict key.
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"""
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def __init__(self, name: str, max_entries: int = 1000):
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# We use a single LruCache to store two different types of entries:
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# 1. Map from (key, dict_key) -> dict value (or sentinel, indicating
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# the key doesn't exist in the dict); and
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# 2. Map from (key, _FullCacheKey.KEY) -> full dict.
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#
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# The former is used when explicit keys of the dictionary are looked up,
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# and the latter when the full dictionary is requested.
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#
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# If when explicit keys are requested and not in the cache, we then look
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# to see if we have the full dict and use that if we do. If found in the
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# full dict each key is added into the cache.
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#
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# This set up allows the `LruCache` to prune the full dict entries if
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# they haven't been used in a while, even when there have been recent
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# queries for subsets of the dict.
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#
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# Typing:
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# * A key of `(KT, DKT)` has a value of `_PerKeyValue`
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# * A key of `(KT, _FullCacheKey.KEY)` has a value of `Dict[DKT, DV]`
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self.cache: LruCache[
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Tuple[KT, Union[DKT, Literal[_FullCacheKey.KEY]]],
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Union[_PerKeyValue, Dict[DKT, DV]],
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] = LruCache(
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max_size=max_entries,
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cache_name=name,
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cache_type=TreeCache,
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size_callback=len,
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)
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self.name = name
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self.sequence = 0
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self.thread: Optional[threading.Thread] = None
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def check_thread(self) -> None:
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expected_thread = self.thread
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if expected_thread is None:
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self.thread = threading.current_thread()
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else:
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if expected_thread is not threading.current_thread():
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raise ValueError(
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"Cache objects can only be accessed from the main thread"
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)
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def get(
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self, key: KT, dict_keys: Optional[Iterable[DKT]] = None
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) -> DictionaryEntry:
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"""Fetch an entry out of the cache
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Args:
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key
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dict_keys: If given a set of keys then return only those keys
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that exist in the cache. If None then returns the full dict
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if it is in the cache.
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Returns:
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If `dict_keys` is not None then `DictionaryEntry` will contain include
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the keys that are in the cache.
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If None then will either return the full dict if in the cache, or the
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empty dict (with `full` set to False) if it isn't.
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"""
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if dict_keys is None:
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# The caller wants the full set of dictionary keys for this cache key
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return self._get_full_dict(key)
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# We are being asked for a subset of keys.
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# First go and check for each requested dict key in the cache, tracking
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# which we couldn't find.
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values = {}
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known_absent = set()
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missing = []
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for dict_key in dict_keys:
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entry = self.cache.get((key, dict_key), _Sentinel.sentinel)
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if entry is _Sentinel.sentinel:
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missing.append(dict_key)
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continue
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assert isinstance(entry, _PerKeyValue)
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if entry.value is _Sentinel.sentinel:
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known_absent.add(dict_key)
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else:
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values[dict_key] = entry.value
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# If we found everything we can return immediately.
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if not missing:
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return DictionaryEntry(False, known_absent, values)
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# We are missing some keys, so check if we happen to have the full dict in
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# the cache.
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#
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# We don't update the last access time for this cache fetch, as we
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# aren't explicitly interested in the full dict and so we don't want
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# requests for explicit dict keys to keep the full dict in the cache.
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entry = self.cache.get(
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(key, _FullCacheKey.KEY),
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_Sentinel.sentinel,
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update_last_access=False,
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)
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if entry is _Sentinel.sentinel:
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# Not in the cache, return the subset of keys we found.
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return DictionaryEntry(False, known_absent, values)
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# We have the full dict!
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assert isinstance(entry, dict)
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for dict_key in missing:
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# We explicitly add each dict key to the cache, so that cache hit
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# rates and LRU times for each key can be tracked separately.
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value = entry.get(dict_key, _Sentinel.sentinel) # type: ignore[arg-type]
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self.cache[(key, dict_key)] = _PerKeyValue(value)
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if value is not _Sentinel.sentinel:
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values[dict_key] = value
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return DictionaryEntry(True, set(), values)
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def _get_full_dict(
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self,
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key: KT,
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) -> DictionaryEntry:
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"""Fetch the full dict for the given key."""
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# First we check if we have cached the full dict.
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entry = self.cache.get((key, _FullCacheKey.KEY), _Sentinel.sentinel)
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if entry is not _Sentinel.sentinel:
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assert isinstance(entry, dict)
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return DictionaryEntry(True, set(), entry)
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return DictionaryEntry(False, set(), {})
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def invalidate(self, key: KT) -> None:
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self.check_thread()
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# Increment the sequence number so that any SELECT statements that
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# raced with the INSERT don't update the cache (SYN-369)
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self.sequence += 1
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# We want to drop all information about the dict for the given key, so
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# we use `del_multi` to delete it all in one go.
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#
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# We ignore the type error here: `del_multi` accepts a truncated key
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# (when the key type is a tuple).
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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()
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self.sequence += 1
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self.cache.clear()
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def update(
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self,
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sequence: int,
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key: KT,
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value: Dict[DKT, DV],
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fetched_keys: Optional[Iterable[DKT]] = None,
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) -> None:
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"""Updates the entry in the cache.
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Note: This does *not* invalidate any existing entries for the `key`.
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In particular, if we add an entry for the cached "full dict" with
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`fetched_keys=None`, existing entries for individual dict keys are
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not invalidated. Likewise, adding entries for individual keys does
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not invalidate any cached value for the full dict.
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In other words: if the underlying data is *changed*, the cache must
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be explicitly invalidated via `.invalidate()`.
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Args:
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sequence
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key
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value: The value to update the cache with.
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fetched_keys: All of the dictionary keys which were
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fetched from the database.
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If None, this is the complete value for key K. Otherwise, it
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is used to infer a list of keys which we know don't exist in
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the full dict.
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"""
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self.check_thread()
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if self.sequence == sequence:
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# Only update the cache if the caches sequence number matches the
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# number that the cache had before the SELECT was started (SYN-369)
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if fetched_keys is None:
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self.cache[(key, _FullCacheKey.KEY)] = value
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else:
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self._update_subset(key, value, fetched_keys)
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def _update_subset(
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self, key: KT, value: Dict[DKT, DV], fetched_keys: Iterable[DKT]
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) -> None:
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"""Add the given dictionary values as explicit keys in the cache.
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Args:
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key: top-level cache key
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value: The dictionary with all the values that we should cache
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fetched_keys: The full set of dict keys that were looked up. Any keys
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here not in `value` should be marked as "known absent".
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"""
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for dict_key, dict_value in value.items():
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self.cache[(key, dict_key)] = _PerKeyValue(dict_value)
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for dict_key in fetched_keys:
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if dict_key in value:
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continue
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self.cache[(key, dict_key)] = _PerKeyValue(_Sentinel.sentinel)
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