* Add `DeferredCache.get_immediate` method
A bunch of things that are currently calling `DeferredCache.get` are only
really interested in the result if it's completed. We can optimise and simplify
this case.
* Remove unused 'default' parameter to DeferredCache.get()
* another get_immediate instance
Autocommit means that we don't wrap the functions in transactions, and instead get executed directly. Introduced in #8456. This will help:
1. reduce the number of `could not serialize access due to concurrent delete` errors that we see (though there are a few functions that often cause serialization errors that we don't fix here);
2. improve the DB performance, as it no longer needs to deal with the overhead of `REPEATABLE READ` isolation levels; and
3. improve wall clock speed of these functions, as we no longer need to send `BEGIN` and `COMMIT` to the DB.
Some notes about the differences between autocommit mode and our default `REPEATABLE READ` transactions:
1. Currently `autocommit` only applies when using PostgreSQL, and is ignored when using SQLite (due to silliness with [Twisted DB classes](https://twistedmatrix.com/trac/ticket/9998)).
2. Autocommit functions may get retried on error, which means they can get applied *twice* (or more) to the DB (since they are not in a transaction the previous call would not get rolled back). This means that the functions need to be idempotent (or otherwise not care about being called multiple times). Read queries, simple deletes, and updates/upserts that replace rows (rather than generating new values from existing rows) are all idempotent.
3. Autocommit functions no longer get executed in [`REPEATABLE READ`](https://www.postgresql.org/docs/current/transaction-iso.html) isolation level, and so data can change queries, which is fine for single statement queries.
We asserted that the IDs returned by postgres sequence was greater than
any we had seen, however this is technically racey as we may update the
current positions out of order.
We now assert that the sequences are correct on startup, so the
assertion is no longer really required, so we remove them.
Currently background proccesses stream the events stream use the "minimum persisted position" (i.e. `get_current_token()`) rather than the vector clock style tokens. This is broadly fine as it doesn't matter if the background processes lag a small amount. However, in extreme cases (i.e. SyTests) where we only write to one event persister the background processes will never make progress.
This PR changes it so that the `MultiWriterIDGenerator` keeps the current position of a given instance as up to date as possible (i.e using the latest token it sees if its not in the process of persisting anything), and then periodically announces that over replication. This then allows the "minimum persisted position" to advance, albeit with a small lag.
We call `_update_stream_positions_table_txn` a lot, which is an UPSERT
that can conflict in `REPEATABLE READ` isolation level. Instead of doing
a transaction consisting of a single query we may as well run it outside
of a transaction.
Currently when using multiple event persisters we (in the worst case) don't tell clients about events until all event persisters have persisted new events after the original event. This is a suboptimal, especially if one of the event persisters goes down.
To handle this, we encode the position of each event persister in the room tokens so that we can send events to clients immediately. To reduce the size of the token we do two things:
1. We create a unique immutable persistent mapping between instance names and a generated small integer ID, which we can encode in the tokens instead of the instance name; and
2. We encode the "persisted upto position" of the room token and then only explicitly include instances that have positions strictly greater than that.
The new tokens look something like: `m3478~1.3488~2.3489`, where the first number is the min position, and the subsequent `-` separated pairs are the instance ID to positions map. (We use `.` and `~` as separators as they're URL safe and not already used by `StreamToken`).
There's no need for it to be in the dict as well as the events table. Instead,
we store it in a separate attribute in the EventInternalMetadata object, and
populate that on load.
This means that we can rely on it being correctly populated for any event which
has been persited to the database.
This is so we can tell what is going on when things are taking a while to start up.
The main change here is to ensure that transactions that are created during startup get correctly logged like normal transactions.
For negative streams we have to negate the internal stream ID before
querying the DB.
The effect of this bug was to query far too many rows, slowing start up
time, but we would correctly filter the results afterwards so there was
no ill effect.
The idea is that in future tokens will encode a mapping of instance to position. However, we don't want to include the full instance name in the string representation, so instead we'll have a mapping between instance name and an immutable integer ID in the DB that we can use instead. We'll then do the lookup when we serialize/deserialize the token (we could alternatively pass around an `Instance` type that includes both the name and ID, but that turns out to be a lot more invasive).
This was a bit unweildy for what I wanted: in particular, I wanted to assign
each measurement straight into a bucket, rather than storing an intermediate
Counter which didn't do any bucketing at all.
I've replaced it with something that is hopefully a bit easier to use.
(I'm not entirely sure what the difference between a HistogramMetricFamily and
a GaugeHistogramMetricFamily is, but given our counters can go down as well as
up the latter *sounds* more accurate?)
* Fix table scan of events on worker startup.
This happened because we assumed "new" writers had an initial stream
position of 0, so the replication code tried to fetch all events written
by the instance between 0 and the current position.
Instead, set the initial position of new writers to the current
persisted up to position, on the assumption that new writers won't have
written anything before that point.
* Consider old writers coming back as "new".
Otherwise we'd try and fetch entries between the old stale token and the
current position, even though it won't have written any rows.
Co-authored-by: Andrew Morgan <1342360+anoadragon453@users.noreply.github.com>
Co-authored-by: Andrew Morgan <1342360+anoadragon453@users.noreply.github.com>
Co-authored-by: Benjamin Koch <bbbsnowball@gmail.com>
This adds configuration flags that will match a user to pre-existing users
when logging in via OpenID Connect. This is useful when switching to
an existing SSO system.
On startup `MultiWriteIdGenerator` fetches the maximum stream ID for
each instance from the table and uses that as its initial "current
position" for each writer. This is problematic as a) it involves either
a scan of events table or an index (neither of which is ideal), and b)
if rows are being persisted out of order elsewhere while the process
restarts then using the maximum stream ID is not correct. This could
theoretically lead to race conditions where e.g. events that are
persisted out of order are not sent down sync streams.
We fix this by creating a new table that tracks the current positions of
each writer to the stream, and update it each time we finish persisting
a new entry. This is a relatively small overhead when persisting events.
However for the cache invalidation stream this is a much bigger relative
overhead, so instead we note that for invalidation we don't actually
care about reliability over restarts (as there's no caches to
invalidate) and simply don't bother reading and writing to the new table
in that particular case.
Erik Johnston