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)
Events are normally sorted by
(topological_ordering, stream_ordering) where
topological_ordering is just
depth. In other words, we first sort by
and then tie-break based on
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.
/syncreturns things in the order they arrive at the server (
/backfillin the federation API) return them in the order determined by the event graph
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.
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. They are "floating" events that we haven't
yet correlated to the DAG.
Outliers typically arise when we fetch the auth chain or state for a given
event. When that happens, we just grab the events in the state/auth chain,
without calculating the state at those events, or backfilling their
So, typically, we won't have the
prev_events of an
outlier in the database,
(though it's entirely possible that we might have them for some other
reason). Other things that make outliers different from regular events:
We don't have state for them, so there should be no entry in
event_to_state_groupsfor an outlier. (In practice this isn't always the case, though I'm not sure why: see https://github.com/matrix-org/synapse/issues/12201).
We don't record entries for them in the
Since outliers are not tied into the DAG, they do not normally form part of the
timeline sent down to clients via
/messages; however there is an
A special case of outlier events are some membership events for federated rooms that we aren't full members of. For example:
- invites received over federation, before we join the room
- rejections for said invites
- knock events for rooms that we would like to join but have not yet joined.
In all the above cases, we don't have the state for the room, which is why they
are treated as outliers. They are a bit special though, in that they are
proactively sent to clients via
Most-recent-in-time events in the DAG which are not referenced by any other
prev_events yet. (In this definition, outliers, rejected events, and
soft-failed events don't count.)
The forward extremities of a room (or at least, a subset of them, if there are
more than ten) are used as the
prev_events when the next event is sent.
The "current state" of a room (ie: the state which would be used if we generated a new event) is, therefore, the resolution of the room states at each of the forward extremities.
The current marker of where we have backfilled up to and will generally be the
prev_events of the oldest-in-time events we have in the DAG. This gives a starting point when
Note that, unlike forward extremities, we typically don't have any backward extremity events themselves in the database - or, if we do, they will be "outliers" (see above). Either way, we don't expect to have the room state at a backward extremity.
When we persist a non-outlier event, if it was previously a backward extremity,
we clear it as a backward extremity and set all of its
prev_events as the new
backward extremities if they aren't already persisted as non-outliers. This
therefore keeps the backward extremities up-to-date.
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
event_id -> state_group and
state_group -> state.
state_group_edges is a further optimization...
notes from @Azrenbeth, https://pastebin.com/seUGVGeT