The idea here is that if an instance persists an event via the replication HTTP API it can return before we receive that event over replication, which can lead to races where code assumes that persisting an event immediately updates various caches (e.g. current state of the room).
Most of Synapse doesn't hit such races, so we don't do the waiting automagically, instead we do so where necessary to avoid unnecessary delays. We may decide to change our minds here if it turns out there are a lot of subtle races going on.
People probably want to look at this commit by commit.
Instead of doing a complicated dance of deleting and moving aliases one
by one, which sends a canonical alias update into the old room for each
one, lets do it all in one go.
This also changes the function to move *all* local alias events to the new
room, however that happens later on anyway.
PyPy's gc.get_stats() returns an object containing detailed allocator statistics
which could be beneficial to collect as metrics.
Signed-off-by: Ivan Shapovalov <intelfx@intelfx.name>
When a call to `user_device_resync` fails, we don't currently mark the remote user's device list as out of sync, nor do we retry to sync it.
https://github.com/matrix-org/synapse/pull/6776 introduced some code infrastructure to mark device lists as stale/out of sync.
This commit uses that code infrastructure to mark device lists as out of sync if processing an incoming device list update makes the device handler realise that the device list is out of sync, but we can't resync right now.
It also adds a looping call to retry all failed resync every 30s. This shouldn't cause too much spam in the logs as this commit also removes the "Failed to handle device list update for..." warning logs when catching `NotRetryingDestination`.
Fixes#7418
We don't really make any promises about returning accurate presence data when
presence is disabled, so we may as well just return a static response, rather
than making the master handle a request.
`_is_server_still_joined` will throw if it is given state updates with non-user ID state keys with local user leaves. This is actually rarely a problem since local leaves almost always get persisted by themselves.
(I discovered this on a branch that was otherwise broken, so I haven't seen this in the wild)
* If an error occurs when stopping a process synctl now logs a warning.
* During a restart, synctl will avoid attempting to start Synapse if an error
occurs during stopping Synapse.
Make sure that the AccountDataStream presents complete updates, in the right
order.
This is much the same fix as #7337 and #7358, but applied to a different stream.
This is required as both event persistence and the background update needs access to this function. It should be perfectly safe for two workers to write to that table at the same time.
This allows us to have the logic on both master and workers, which is necessary to move event persistence off master.
We also combine the instantiation of ID generators from DataStore and slave stores to the base worker stores. This allows us to select which process writes events independently of the master/worker splits.
The specific headers that are passed using this new configuration format
are Host and X-Forwarded-For, which should be all that's required.
Note that for production another matcher should be added in the first
section to properly handle the base_url lookup:
reverse_proxy /.well-known/matrix/* http://localhost:8008
Signed-off-by: Jeff Peeler <jpeeler@gmail.com>
The aim here is to get to a stage where we have a `PersistEventStore` that holds all the write methods used during event persistence, so that we can take that class out of the `DataStore` mixin and instansiate it separately. This will allow us to instansiate it on processes other than master, while also ensuring it is only available on processes that are configured to write to events stream.
This is a bit of an architectural change, where we end up with multiple classes per data store (rather than one per data store we have now). We end up having:
1. Storage classes that provide high level APIs that can talk to multiple data stores.
2. Data store modules that consist of classes that must point at the same database instance.
3. Classes in a data store that can be instantiated on processes depending on config.
Erik Johnston