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Retry well-known lookup before expiry.

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This gives a bit of a grace period where we can attempt to refetch a
remote `well-known`, while still using the cached result if that fails.

Hopefully this will make the well-known resolution a bit more torelant
of failures, rather than it immediately treating failures as "no result"
and caching that for an hour.
This commit is contained in:
Erik Johnston 2019-08-12 15:39:14 +01:00
parent 0b6fbb28a8
commit 17e1e80726
4 changed files with 136 additions and 27 deletions
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8
synapse/util/caches/ttlcache.py
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@ -55,7 +55,7 @@ class TTLCache(object):
if e != SENTINEL:
self._expiry_list.remove(e)
entry = _CacheEntry(expiry_time=expiry, key=key, value=value)
entry = _CacheEntry(expiry_time=expiry, ttl=ttl, key=key, value=value)
self._data[key] = entry
self._expiry_list.add(entry)
@ -87,7 +87,8 @@ class TTLCache(object):
key: key to look up
Returns:
Tuple[Any, float]: the value from the cache, and the expiry time
Tuple[Any, float, float]: the value from the cache, the expiry time
and the TTL
Raises:
KeyError if the entry is not found
@ -99,7 +100,7 @@ class TTLCache(object):
self._metrics.inc_misses()
raise
self._metrics.inc_hits()
return e.value, e.expiry_time
return e.value, e.expiry_time, e.ttl
def pop(self, key, default=SENTINEL):
"""Remove a value from the cache
@ -158,5 +159,6 @@ class _CacheEntry(object):
# expiry_time is the first attribute, so that entries are sorted by expiry.
expiry_time = attr.ib()
ttl = attr.ib()
key = attr.ib()
value = attr.ib()