Before we were pulling out *all* read receipts for a user for every
event we pushed. Instead let's only pull out the relevant receipts.
This also pulled out the event rows for each receipt, causing load on
the events table.
Fixes https://github.com/element-hq/synapse/issues/16680, as well as a
related bug, where servers which we had *never* successfully sent an
event to would not be retried.
In order to fix the case of pending to-device messages, we hook into the
existing `wake_destinations_needing_catchup` process, by extending it to
look for destinations that have pending to-device messages. The
federation transmission loop then attempts to send the pending to-device
messages as normal.
We do this by adding support to the LRU cache for "extra indices" based
on the cached value. This allows us to efficiently map from room ID to
the cached events and only invalidate those.
This basically reverts a change that was in
https://github.com/element-hq/synapse/pull/16833, where we reduced the
batching.
The smaller batching can cause performance issues on busy servers and
databases.
During the migration the automated script to update the copyright
headers accidentally got rid of some of the existing copyright lines.
Reinstate them.
The current query supports passing in a list of users, which generates a
query using `user_id = ANY(..)`. This is generates a less efficient
query plan that is notably slower than a simple `user_id = ?` condition.
Note: The new function is mostly a copy and paste and then a
simplification of the existing function.
The crux of the change is to try and make the queries simpler and pull
out fewer rows. Before, there were quite a few joins against subqueries,
which caused postgres to pull out more rows than necessary.
Instead, let's simplify the query and do some of the filtering out in
Python instead, letting Postgres do better optimizations now that it
doesn't have to deal with joins against subqueries.
Review note: this is a complete rewrite of the function, so not sure how
useful the diff is.
---------
Co-authored-by: Andrew Morgan <1342360+anoadragon453@users.noreply.github.com>
There are two changes here:
1. Only pull out the required state when handling the request.
2. Change the get filtered state return type to check that we're only
querying state that was requested
---------
Co-authored-by: reivilibre <oliverw@matrix.org>
There are a couple of things we need to be careful of here:
1. The current python code does no validation when loading from the DB,
so we need to be careful to ignore such errors (at least on jki.re there
are some old events with internal metadata fields of the wrong type).
2. We want to be memory efficient, as we often have many hundreds of
thousands of events in the cache at a time.
---------
Co-authored-by: Quentin Gliech <quenting@element.io>
We remove these fields as they're just duplicating data the event
already stores, and (for reasons 🤫) I'd like to simplify
the class to only store simple types.
I'm not entirely convinced that we shouldn't instead add helper methods
to the event class to generate stream tokens, but I don't really think
that's where they belong either
* Describe `insert_client_ip`
* Pull out client_ips and MAU tracking to BaseAuth
* Define HAS_AUTHLIB once in tests
sick of copypasting
* Track ips and token usage when delegating auth
* Test that we track MAU and user_ips
* Don't track `__oidc_admin`
Keeping track of a lower bound of stream ID where we've deleted everything below makes the queries much faster. Otherwise, every time we scan for rows to delete we'd re-scan across all the rows that have previously deleted (until the next table VACUUM).
If simple_{insert,upsert,update}_many_txn is called without any data
to modify then return instead of executing the query.
This matches the behavior of simple_{select,delete}_many_txn.
Fetch information needed for push rule evaluation in parallel.
Ideally this would use query pipelining, but this is not
available in psycopg2.
Due to the database thread pool this may result in little
to no parallelization.
The event persistence code used to handle multiple rooms
at a time, but was simplified to only ever be called with a
single room at a time (different rooms are now handled in
parallel). The code is still generic to multiple rooms causing
a lot of work that is unnecessary (e.g. unnecessary loops, and
partitioning data by room).
This strips out the ability to handle multiple rooms at once, greatly
simplifying the code.
Just to standardize on the normal helpers, it might also have
a slight perf improvement on PostgreSQL which will now use
`ANY (?)` instead of `IN (?, ?, ...)`.
