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Make DictionaryCache have better expiry properties (#13292)

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Erik Johnston 2022-07-21 17:13:44 +01:00 committed by GitHub
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commit 0b87eb8e0c
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7 changed files with 358 additions and 43 deletions

1
changelog.d/13292.misc Normal file
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@ -0,0 +1 @@
Make `DictionaryCache` expire full entries if they haven't been queried in a while, even if specific keys have been queried recently.

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@ -202,7 +202,14 @@ class StateGroupDataStore(StateBackgroundUpdateStore, SQLBaseStore):
requests state from the cache, if False we need to query the DB for the
missing state.
"""
cache_entry = cache.get(group)
# If we are asked explicitly for a subset of keys, we only ask for those
# from the cache. This ensures that the `DictionaryCache` can make
# better decisions about what to cache and what to expire.
dict_keys = None
if not state_filter.has_wildcards():
dict_keys = state_filter.concrete_types()
cache_entry = cache.get(group, dict_keys=dict_keys)
state_dict_ids = cache_entry.value
if cache_entry.full or state_filter.is_full():

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@ -14,11 +14,13 @@
import enum
import logging
import threading
from typing import Any, Dict, Generic, Iterable, Optional, Set, TypeVar
from typing import Any, Dict, Generic, Iterable, Optional, Set, Tuple, TypeVar, Union
import attr
from typing_extensions import Literal
from synapse.util.caches.lrucache import LruCache
from synapse.util.caches.treecache import TreeCache
logger = logging.getLogger(__name__)
@ -33,10 +35,12 @@ DV = TypeVar("DV")
# 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, auto_attribs=True)
@attr.s(slots=True, frozen=True, auto_attribs=True)
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
@ -53,20 +57,90 @@ class DictionaryEntry: # should be: Generic[DKT, DV].
return len(self.value)
class _FullCacheKey(enum.Enum):
"""The key we use to cache the full dict."""
KEY = object()
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
class DictionaryCache(Generic[KT, DKT, DV]):
"""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.
"""
def __init__(self, name: str, max_entries: int = 1000):
self.cache: LruCache[KT, DictionaryEntry] = LruCache(
max_size=max_entries, cache_name=name, size_callback=len
# 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,
)
self.name = name
@ -91,23 +165,83 @@ class DictionaryCache(Generic[KT, DKT, DV]):
Args:
key
dict_keys: If given a set of keys then return only those keys
that exist in the cache.
that exist in the cache. If None then returns the full dict
if it is in the cache.
Returns:
DictionaryEntry
DictionaryEntry: 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.
"""
entry = self.cache.get(key, _Sentinel.sentinel)
if entry is not _Sentinel.sentinel:
if dict_keys is None:
return DictionaryEntry(
entry.full, entry.known_absent, dict(entry.value)
)
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:
return DictionaryEntry(
entry.full,
entry.known_absent,
{k: entry.value[k] for k in dict_keys if k in entry.value},
)
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(), {})
@ -117,7 +251,13 @@ class DictionaryCache(Generic[KT, DKT, DV]):
# Increment the sequence number so that any SELECT statements that
# raced with the INSERT don't update the cache (SYN-369)
self.sequence += 1
self.cache.pop(key, None)
# 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]
def invalidate_all(self) -> None:
self.check_thread()
@ -131,7 +271,16 @@ class DictionaryCache(Generic[KT, DKT, DV]):
value: Dict[DKT, DV],
fetched_keys: Optional[Iterable[DKT]] = None,
) -> None:
"""Updates the entry in the cache
"""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
@ -149,20 +298,27 @@ class DictionaryCache(Generic[KT, DKT, DV]):
# 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._insert(key, value, set())
self.cache[(key, _FullCacheKey.KEY)] = value
else:
self._update_or_insert(key, value, fetched_keys)
self._update_subset(key, value, fetched_keys)
def _update_or_insert(
self, key: KT, value: Dict[DKT, DV], known_absent: Iterable[DKT]
def _update_subset(
self, key: KT, value: Dict[DKT, DV], fetched_keys: Iterable[DKT]
) -> None:
# We pop and reinsert as we need to tell the cache the size may have
# changed
"""Add the given dictionary values as explicit keys in the cache.
entry: DictionaryEntry = self.cache.pop(key, DictionaryEntry(False, set(), {}))
entry.value.update(value)
entry.known_absent.update(known_absent)
self.cache[key] = entry
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".
"""
def _insert(self, key: KT, value: Dict[DKT, DV], known_absent: Set[DKT]) -> None:
self.cache[key] = DictionaryEntry(True, known_absent, value)
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
self.cache[(key, dict_key)] = _PerKeyValue(_Sentinel.sentinel)

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@ -25,8 +25,10 @@ from typing import (
Collection,
Dict,
Generic,
Iterable,
List,
Optional,
Tuple,
Type,
TypeVar,
Union,
@ -44,7 +46,11 @@ from synapse.metrics.background_process_metrics import wrap_as_background_proces
from synapse.metrics.jemalloc import get_jemalloc_stats
from synapse.util import Clock, caches
from synapse.util.caches import CacheMetric, EvictionReason, register_cache
from synapse.util.caches.treecache import TreeCache, iterate_tree_cache_entry
from synapse.util.caches.treecache import (
TreeCache,
iterate_tree_cache_entry,
iterate_tree_cache_items,
)
from synapse.util.linked_list import ListNode
if TYPE_CHECKING:
@ -537,6 +543,7 @@ class LruCache(Generic[KT, VT]):
default: Literal[None] = None,
callbacks: Collection[Callable[[], None]] = ...,
update_metrics: bool = ...,
update_last_access: bool = ...,
) -> Optional[VT]:
...
@ -546,6 +553,7 @@ class LruCache(Generic[KT, VT]):
default: T,
callbacks: Collection[Callable[[], None]] = ...,
update_metrics: bool = ...,
update_last_access: bool = ...,
) -> Union[T, VT]:
...
@ -555,10 +563,27 @@ class LruCache(Generic[KT, VT]):
default: Optional[T] = None,
callbacks: Collection[Callable[[], None]] = (),
update_metrics: bool = True,
update_last_access: bool = True,
) -> Union[None, T, VT]:
"""Look up a key in the cache
Args:
key
default
callbacks: A collection of callbacks that will fire when the
node is removed from the cache (either due to invalidation
or expiry).
update_metrics: Whether to update the hit rate metrics
update_last_access: Whether to update the last access metrics
on a node if successfully fetched. These metrics are used
to determine when to remove the node from the cache. Set
to False if this fetch should *not* prevent a node from
being expired.
"""
node = cache.get(key, None)
if node is not None:
move_node_to_front(node)
if update_last_access:
move_node_to_front(node)
node.add_callbacks(callbacks)
if update_metrics and metrics:
metrics.inc_hits()
@ -568,6 +593,65 @@ class LruCache(Generic[KT, VT]):
metrics.inc_misses()
return default
@overload
def cache_get_multi(
key: tuple,
default: Literal[None] = None,
update_metrics: bool = True,
) -> Union[None, Iterable[Tuple[KT, VT]]]:
...
@overload
def cache_get_multi(
key: tuple,
default: T,
update_metrics: bool = True,
) -> Union[T, Iterable[Tuple[KT, VT]]]:
...
@synchronized
def cache_get_multi(
key: tuple,
default: Optional[T] = None,
update_metrics: bool = True,
) -> Union[None, T, Iterable[Tuple[KT, VT]]]:
"""Returns a generator yielding all entries under the given key.
Can only be used if backed by a tree cache.
Example:
cache = LruCache(10, cache_type=TreeCache)
cache[(1, 1)] = "a"
cache[(1, 2)] = "b"
cache[(2, 1)] = "c"
items = cache.get_multi((1,))
assert list(items) == [((1, 1), "a"), ((1, 2), "b")]
Returns:
Either default if the key doesn't exist, or a generator of the
key/value pairs.
"""
assert isinstance(cache, TreeCache)
node = cache.get(key, None)
if node is not None:
if update_metrics and metrics:
metrics.inc_hits()
# We store entries in the `TreeCache` with values of type `_Node`,
# which we need to unwrap.
return (
(full_key, lru_node.value)
for full_key, lru_node in iterate_tree_cache_items(key, node)
)
else:
if update_metrics and metrics:
metrics.inc_misses()
return default
@synchronized
def cache_set(
key: KT, value: VT, callbacks: Collection[Callable[[], None]] = ()
@ -674,6 +758,8 @@ class LruCache(Generic[KT, VT]):
self.setdefault = cache_set_default
self.pop = cache_pop
self.del_multi = cache_del_multi
if cache_type is TreeCache:
self.get_multi = cache_get_multi
# `invalidate` is exposed for consistency with DeferredCache, so that it can be
# invalidated by the cache invalidation replication stream.
self.invalidate = cache_del_multi

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@ -64,6 +64,15 @@ class TreeCache:
self.size += 1
def get(self, key, default=None):
"""When `key` is a full key, fetches the value for the given key (if
any).
If `key` is only a partial key (i.e. a truncated tuple) then returns a
`TreeCacheNode`, which can be passed to the `iterate_tree_cache_*`
functions to iterate over all entries in the cache with keys that start
with the given partial key.
"""
node = self.root
for k in key[:-1]:
node = node.get(k, None)
@ -139,3 +148,32 @@ def iterate_tree_cache_entry(d):
yield from iterate_tree_cache_entry(value_d)
else:
yield d
def iterate_tree_cache_items(key, value):
"""Helper function to iterate over the leaves of a tree, i.e. a dict of that
can contain dicts.
The provided key is a tuple that will get prepended to the returned keys.
Example:
cache = TreeCache()
cache[(1, 1)] = "a"
cache[(1, 2)] = "b"
cache[(2, 1)] = "c"
tree_node = cache.get((1,))
items = iterate_tree_cache_items((1,), tree_node)
assert list(items) == [((1, 1), "a"), ((1, 2), "b")]
Returns:
A generator yielding key/value pairs.
"""
if isinstance(value, TreeCacheNode):
for sub_key, sub_value in value.items():
yield from iterate_tree_cache_items((*key, sub_key), sub_value)
else:
# we've reached a leaf of the tree.
yield key, value

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@ -369,8 +369,8 @@ class StateStoreTestCase(HomeserverTestCase):
state_dict_ids = cache_entry.value
self.assertEqual(cache_entry.full, False)
self.assertEqual(cache_entry.known_absent, {(e1.type, e1.state_key)})
self.assertDictEqual(state_dict_ids, {(e1.type, e1.state_key): e1.event_id})
self.assertEqual(cache_entry.known_absent, set())
self.assertDictEqual(state_dict_ids, {})
############################################
# test that things work with a partial cache
@ -387,7 +387,7 @@ class StateStoreTestCase(HomeserverTestCase):
)
self.assertEqual(is_all, False)
self.assertDictEqual({(e1.type, e1.state_key): e1.event_id}, state_dict)
self.assertDictEqual({}, state_dict)
room_id = self.room.to_string()
(state_dict, is_all,) = self.state_datastore._get_state_for_group_using_cache(
@ -412,7 +412,7 @@ class StateStoreTestCase(HomeserverTestCase):
)
self.assertEqual(is_all, False)
self.assertDictEqual({(e1.type, e1.state_key): e1.event_id}, state_dict)
self.assertDictEqual({}, state_dict)
(state_dict, is_all,) = self.state_datastore._get_state_for_group_using_cache(
self.state_datastore._state_group_members_cache,
@ -443,7 +443,7 @@ class StateStoreTestCase(HomeserverTestCase):
)
self.assertEqual(is_all, False)
self.assertDictEqual({(e1.type, e1.state_key): e1.event_id}, state_dict)
self.assertDictEqual({}, state_dict)
(state_dict, is_all,) = self.state_datastore._get_state_for_group_using_cache(
self.state_datastore._state_group_members_cache,

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@ -20,7 +20,7 @@ from tests import unittest
class DictCacheTestCase(unittest.TestCase):
def setUp(self):
self.cache = DictionaryCache("foobar")
self.cache = DictionaryCache("foobar", max_entries=10)
def test_simple_cache_hit_full(self):
key = "test_simple_cache_hit_full"
@ -76,13 +76,13 @@ class DictCacheTestCase(unittest.TestCase):
seq = self.cache.sequence
test_value_1 = {"test": "test_simple_cache_hit_miss_partial"}
self.cache.update(seq, key, test_value_1, fetched_keys=set("test"))
self.cache.update(seq, key, test_value_1, fetched_keys={"test"})
seq = self.cache.sequence
test_value_2 = {"test2": "test_simple_cache_hit_miss_partial2"}
self.cache.update(seq, key, test_value_2, fetched_keys=set("test2"))
self.cache.update(seq, key, test_value_2, fetched_keys={"test2"})
c = self.cache.get(key)
c = self.cache.get(key, dict_keys=["test", "test2"])
self.assertEqual(
{
"test": "test_simple_cache_hit_miss_partial",
@ -90,3 +90,30 @@ class DictCacheTestCase(unittest.TestCase):
},
c.value,
)
self.assertEqual(c.full, False)
def test_invalidation(self):
"""Test that the partial dict and full dicts get invalidated
separately.
"""
key = "some_key"
seq = self.cache.sequence
# start by populating a "full dict" entry
self.cache.update(seq, key, {"a": "b", "c": "d"})
# add a bunch of individual entries, also keeping the individual
# entry for "a" warm.
for i in range(20):
self.cache.get(key, ["a"])
self.cache.update(seq, f"key{i}", {1: 2})
# We should have evicted the full dict...
r = self.cache.get(key)
self.assertFalse(r.full)
self.assertTrue("c" not in r.value)
# ... but kept the "a" entry that we kept querying.
r = self.cache.get(key, dict_keys=["a"])
self.assertFalse(r.full)
self.assertEqual(r.value, {"a": "b"})