This is *not* ready for production yet. Caveats:
1. We should write some tests...
2. The stream token that we use for events can get stalled at the minimum position of all writers. This means that new events may not be processed and e.g. sent down sync streams if a writer isn't writing or is slow.
This fixes a bug where having multiple callers waiting on the same
stream and position will cause it to try and compare two deferreds,
which fails (due to the sorted list having an entry of `Tuple[int,
Deferred]`).
It's just a thin wrapper around two ID gens to make `get_current_token`
and `get_next` return tuples. This can easily be replaced by calling the
appropriate methods on the underlying ID gens directly.
The function is used for two purposes: 1) for subscribers of streams to
get a token they can use to get further updates with, and 2) for
replication to track position of the writers of the stream.
For streams with a single writer the two scenarios produce the same
result, however the situation becomes complicated for streams with
multiple writers. The current `MultiWriterIdGenerator` does not
correctly handle the first case (which is not an issue as its only used
for the `caches` stream which nothing subscribes to outside of
replication).
Most of the stuff we do for replication commands can be done synchronously. There's no point spinning up background processes if we're not going to need them.
Handling of incoming typing stream updates from replication was not
hooked up on master, effecting set ups where typing was handled on a
different worker.
This is really only a problem if the master process is also handling
sync requests, which is unlikely for those that are at the stage of
moving typing off.
The other observable effect is that if a worker restarts or a
replication connect drops then the typing worker will issue a
`POSITION typing`, triggering master process to try and stream *all*
typing updates from position 0.
Fixes#7907
When we get behind on replication, we tend to stack up background processes
behind a linearizer. Bg processes are heavy (particularly with respect to
prometheus metrics) and linearizers aren't terribly efficient once the queue
gets long either.
A better approach is to maintain a queue of requests to be processed, and
nominate a single process to work its way through the queue.
Fixes: #7444
The CI appears to use the latest version of isort, which is a problem when isort gets a major version bump. Rather than try to pin the version, I've done the necessary to make isort5 happy with synapse.
The aim here is to make it easier to reason about when streams are limited and when they're not, by moving the logic into the database functions themselves. This should mean we can kill of `db_query_to_update_function` function.
* Ensure account data stream IDs are unique.
The account data stream is shared between three tables, and the maximum
allocated ID was tracked in a dedicated table. Updating the max ID
happened outside the transaction that allocated the ID, leading to a
race where if the server was restarted then the same ID could be
allocated but the max ID failed to be updated, leading it to be reused.
The ID generators have support for tracking across multiple tables, so
we may as well use that instead of a dedicated table.
* Fix bug in account data replication stream.
If the same stream ID was used in both global and room account data then
the getting updates for the replication stream would fail due to
`heapq.merge(..)` trying to compare a `str` with a `None`. (This is
because you'd have two rows like `(534, '!room')` and `(534, None)` from
the room and global account data tables).
Fix is just to order by stream ID, since we don't rely on the ordering
beyond that. The bug where stream IDs can be reused should be fixed now,
so this case shouldn't happen going forward.
Fixes#7617
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.
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.
Before all streams were only written to from master, so only master needed to respond to `REPLICATE` commands.
Before all instances wrote to the cache invalidation stream, but didn't respond to `REPLICATE`. This was a bug, which could lead to missed rows from cache invalidation stream if an instance is restarted, however all the caches would be empty in that case so it wasn't a problem.
Proactively send out `POSITION` commands (as if we had just received a `REPLICATE`) when we connect to Redis. This is important as other instances won't notice we've connected to issue a `REPLICATE` command (unlike for direct TCP connections). This is only currently an issue if master process reconnects without restarting (if it restarts then it won't have written anything and so other instances probably won't have missed anything).
* release-v1.13.0:
Don't UPGRADE database rows
RST indenting
Put rollback instructions in upgrade notes
Fix changelog typo
Oh yeah, RST
Absolute URL it is then
Fix upgrade notes link
Provide summary of upgrade issues in changelog. Fix )
Move next version notes from changelog to upgrade notes
Changelog fixes
1.13.0rc1
Documentation on setting up redis (#7446)
Rework UI Auth session validation for registration (#7455)
Fix errors from malformed log line (#7454)
Drop support for redis.dbid (#7450)
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()`.
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.
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.
