Background: we have a `matrixdotorg/synapse-workers` docker image, which
is intended for running multiple workers within the same container. That
image includes a `prefix-log` script which, for each line printed to
stdout or stderr by one of the processes, prepends the name of the
process.
This commit disables buffering in that script, so that lines are logged
quickly after they are printed. This makes it much easier to understand
the output, since they then come out in a natural order.
This PR aims to fix#16895, caused by a regression in #7 and not fixed
by #16903. The PR #16903 only fixes a starvation issue, where the CPU
isn't released. There is a second issue, where the execution is blocked.
This theory is supported by the flame graphs provided in #16895 and the
fact that I see the CPU usage reducing and far below the limit.
Since the changes in #7, the method `check_state_independent_auth_rules`
is called with the additional parameter `batched_auth_events`:
6fa13b4f92/synapse/handlers/federation_event.py (L1741-L1743)
It makes the execution enter this if clause, introduced with #151956fa13b4f92/synapse/event_auth.py (L178-L189)
There are two issues in the above code snippet.
First, there is the blocking issue. I'm not entirely sure if this is a
deadlock, starvation, or something different. In the beginning, I
thought the copy operation was responsible. It wasn't. Then I
investigated the nested `store.get_events` inside the function `update`.
This was also not causing the blocking issue. Only when I replaced the
set difference operation (`-` ) with a list comprehension, the blocking
was resolved. Creating and comparing sets with a very large amount of
events seems to be problematic.
This is how the flamegraph looks now while persisting outliers. As you
can see, the execution no longer locks up in the above function.
![output_2024-02-28_13-59-40](https://github.com/element-hq/synapse/assets/13143850/6db9c9ac-484f-47d0-bdde-70abfbd773ec)
Second, the copying here doesn't serve any purpose, because only a
shallow copy is created. This means the same objects from the original
dict are referenced. This fails the intention of protecting these
objects from mutation. The review of the original PR
https://github.com/matrix-org/synapse/pull/15195 had an extensive
discussion about this matter.
Various approaches to copying the auth_events were attempted:
1) Implementing a deepcopy caused issues due to
builtins.EventInternalMetadata not being pickleable.
2) Creating a dict with new objects akin to a deepcopy.
3) Creating a dict with new objects containing only necessary
attributes.
Concluding, there is no easy way to create an actual copy of the
objects. Opting for a deepcopy can significantly strain memory and CPU
resources, making it an inefficient choice. I don't see why the copy is
necessary in the first place. Therefore I'm proposing to remove it
altogether.
After these changes, I was able to successfully join these rooms,
without the main worker locking up:
- #synapse:matrix.org
- #element-android:matrix.org
- #element-web:matrix.org
- #ecips:matrix.org
- #ipfs-chatter:ipfs.io
- #python:matrix.org
- #matrix:matrix.org
Since Synapse 1.76.0, any module which registers a `on_new_event`
callback would brick the ability to join remote rooms.
This is because this callback tried to get the full state of the room,
which would end up in a deadlock.
Related:
https://github.com/matrix-org/synapse-auto-accept-invite/issues/18
The following module would brick the ability to join remote rooms:
```python
from typing import Any, Dict, Literal, Union
import logging
from synapse.module_api import ModuleApi, EventBase
logger = logging.getLogger(__name__)
class MyModule:
def __init__(self, config: None, api: ModuleApi):
self._api = api
self._config = config
self._api.register_third_party_rules_callbacks(
on_new_event=self.on_new_event,
)
async def on_new_event(self, event: EventBase, _state_map: Any) -> None:
logger.info(f"Received new event: {event}")
@staticmethod
def parse_config(_config: Dict[str, Any]) -> None:
return None
```
This is technically a breaking change, as we are now passing partial
state on the `on_new_event` callback.
However, this callback was broken for federated rooms since 1.76.0, and
local rooms have full state anyway, so it's unlikely that it would
change anything.
This adds a counter `synapse_emails_sent_total` for emails sent. They
are broken down by `type`, which are `password_reset`, `registration`,
`add_threepid`, `notification` (matching the methods of `Mailer`).
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.
List of users not to send out device list updates for when they register
new devices. This is useful to handle bot accounts.
This is undocumented as its mostly a hack to test on matrix.org.
Note: This will still send out device list updates if the device is
later updated, e.g. end to end keys are added.
Bumps [bcrypt](https://github.com/pyca/bcrypt) from 4.0.1 to 4.1.2.
<details>
<summary>Commits</summary>
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Try building py39 wheels to see if that helps with reinitialization
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Bump syn from 2.0.40 to 2.0.41 in /src/_bcrypt (<a
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Bump syn from 2.0.39 to 2.0.40 in /src/_bcrypt (<a
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Bump libc from 0.2.150 to 0.2.151 in /src/_bcrypt (<a
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Bump once_cell from 1.18.0 to 1.19.0 in /src/_bcrypt (<a
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<li><a
href="61b32039d4"><code>61b3203</code></a>
Bump actions/setup-python from 4.7.1 to 4.8.0 (<a
href="https://redirect.github.com/pyca/bcrypt/issues/688">#688</a>)</li>
<li><a
href="1c3159a28a"><code>1c3159a</code></a>
Fixed wheels for older versions of macOS (<a
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<li><a
href="1a41437d3a"><code>1a41437</code></a>
Update README.rst (<a
href="https://redirect.github.com/pyca/bcrypt/issues/682">#682</a>)</li>
<li><a
href="7881c5beef"><code>7881c5b</code></a>
Fix building windows abi3 wheels (<a
href="https://redirect.github.com/pyca/bcrypt/issues/681">#681</a>)</li>
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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.