Fix a bug where the `get_joined_users` cache could be corrupted by custom
status events (or other state events with a state_key matching the user ID).
The bug was introduced by #2229, but has largely gone unnoticed since then.
Fixes#7099, #7373.
For the record, the reason we need this is as follows:
each RDATA command comes down the redis pipe as a subscription message. txredisapi as written needs at least three reactor ticks to read each subscription message from the tcp buffer. Hence, once the process gets loaded, it starts getting behind, and eventually redis knifes the connection. it then takes ages for the master to work its way through the backlog, before it reconnects again, during which any commands from any workers are dropped.
We forgot to set the password on the subscriber connection, as well as
not calling super methods for overridden connectionMade/connectionLost
functions.
For in memory streams when fetching updates on workers we need to query the source of the stream, which currently is hard coded to be master. This PR threads through the source instance we received via `POSITION` through to the update function in each stream, which can then be passed to the replication client for in memory streams.
We move the processing of typing and federation replication traffic into their handlers so that `Stream.current_token()` points to a valid token. This allows us to remove `get_streams_to_replicate()` and `stream_positions()`.
By persisting the user interactive authentication sessions to the database, this fixes
situations where a user hits different works throughout their auth session and also
allows sessions to persist through restarts of Synapse.
This is primarily for allowing us to send those commands from workers, but for now simply allows us to ignore echoed RDATA/POSITION commands that we sent (we get echoes of sent commands when using redis). Currently we log a WARNING on the master process every time we receive an echoed RDATA.
For direct TCP connections we need the master to relay REMOTE_SERVER_UP
commands to the other connections so that all instances get notified
about it. The old implementation just relayed to all connections,
assuming that sending back to the original sender of the command was
safe. This is not true for redis, where commands sent get echoed back to
the sender, which was causing master to effectively infinite loop
sending and then re-receiving REMOTE_SERVER_UP commands that it sent.
The fix is to ensure that we only relay to *other* connections and not
to the connection we received the notification from.
Fixes#7334.
* Factor out functions for injecting events into database
I want to add some more flexibility to the tools for injecting events into the
database, and I don't want to clutter up HomeserverTestCase with them, so let's
factor them out to a new file.
* Rework TestReplicationDataHandler
This wasn't very easy to work with: the mock wrapping was largely superfluous,
and it's useful to be able to inspect the received rows, and clear out the
received list.
* Fix AssertionErrors being thrown by EventsStream
Part of the problem was that there was an off-by-one error in the assertion,
but also the limit logic was too simple. Fix it all up and add some tests.
If the admin adds a `.yaml` file that's either empty or doesn't parse into a dict to a config directory (e.g. `conf.d` for debs installs), stuff like https://github.com/matrix-org/synapse/issues/7322 would happen. This PR checks that the file is correctly parsed into a dict, or ignores it with a warning if it parses into any other type (including `None` for empty files).
Fixes https://github.com/matrix-org/synapse/issues/7322
Figuring out how to correctly limit updates from this stream without dropping
entries is far more complicated than just counting the number of rows being
returned. We need to consider each query separately and, if any one query hits
the limit, truncate the results from the others.
I think this also fixes some potentially long-standing bugs where events or
state changes could get missed if we hit the limit on either query.
