0
0
Fork 1
mirror of https://mau.dev/maunium/synapse.git synced 2024-12-14 09:24:04 +01:00

Add developer documentation to explain room DAG concepts like outliers and state_groups (#10464)

This commit is contained in:
Eric Eastwood 2021-08-03 05:08:57 -05:00 committed by GitHub
parent a6ea32a798
commit 2bae2c632f
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
3 changed files with 81 additions and 0 deletions

1
changelog.d/10464.doc Normal file
View file

@ -0,0 +1 @@
Add some developer docs to explain room DAG concepts like `outliers`, `state_groups`, `depth`, etc.

View file

@ -79,6 +79,7 @@
- [Single Sign-On]() - [Single Sign-On]()
- [SAML](development/saml.md) - [SAML](development/saml.md)
- [CAS](development/cas.md) - [CAS](development/cas.md)
- [Room DAG concepts](development/room-dag-concepts.md)
- [State Resolution]() - [State Resolution]()
- [The Auth Chain Difference Algorithm](auth_chain_difference_algorithm.md) - [The Auth Chain Difference Algorithm](auth_chain_difference_algorithm.md)
- [Media Repository](media_repository.md) - [Media Repository](media_repository.md)

View file

@ -0,0 +1,79 @@
# Room DAG concepts
## Edges
The word "edge" comes from graph theory lingo. An edge is just a connection
between two events. In Synapse, we connect events by specifying their
`prev_events`. A subsequent event points back at a previous event.
```
A (oldest) <---- B <---- C (most recent)
```
## Depth and stream ordering
Events are normally sorted by `(topological_ordering, stream_ordering)` where
`topological_ordering` is just `depth`. In other words, we first sort by `depth`
and then tie-break based on `stream_ordering`. `depth` is incremented as new
messages are added to the DAG. Normally, `stream_ordering` is an auto
incrementing integer, but backfilled events start with `stream_ordering=-1` and decrement.
---
- `/sync` returns things in the order they arrive at the server (`stream_ordering`).
- `/messages` (and `/backfill` in the federation API) return them in the order determined by the event graph `(topological_ordering, stream_ordering)`.
The general idea is that, if you're following a room in real-time (i.e.
`/sync`), you probably want to see the messages as they arrive at your server,
rather than skipping any that arrived late; whereas if you're looking at a
historical section of timeline (i.e. `/messages`), you want to see the best
representation of the state of the room as others were seeing it at the time.
## Forward extremity
Most-recent-in-time events in the DAG which are not referenced by any other events' `prev_events` yet.
The forward extremities of a room are used as the `prev_events` when the next event is sent.
## Backwards extremity
The current marker of where we have backfilled up to and will generally be the
oldest-in-time events we know of in the DAG.
This is an event where we haven't fetched all of the `prev_events` for.
Once we have fetched all of its `prev_events`, it's unmarked as a backwards
extremity (although we may have formed new backwards extremities from the prev
events during the backfilling process).
## Outliers
We mark an event as an `outlier` when we haven't figured out the state for the
room at that point in the DAG yet.
We won't *necessarily* have the `prev_events` of an `outlier` in the database,
but it's entirely possible that we *might*. The status of whether we have all of
the `prev_events` is marked as a [backwards extremity](#backwards-extremity).
For example, when we fetch the event auth chain or state for a given event, we
mark all of those claimed auth events as outliers because we haven't done the
state calculation ourself.
## State groups
For every non-outlier event we need to know the state at that event. Instead of
storing the full state for each event in the DB (i.e. a `event_id -> state`
mapping), which is *very* space inefficient when state doesn't change, we
instead assign each different set of state a "state group" and then have
mappings of `event_id -> state_group` and `state_group -> state`.
### Stage group edges
TODO: `state_group_edges` is a further optimization...
notes from @Azrenbeth, https://pastebin.com/seUGVGeT