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# Room DAG concepts
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## Edges
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The word "edge" comes from graph theory lingo. An edge is just a connection
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between two events. In Synapse, we connect events by specifying their
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`prev_events`. A subsequent event points back at a previous event.
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```
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A (oldest) <---- B <---- C (most recent)
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```
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## Depth and stream ordering
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Events are normally sorted by `(topological_ordering, stream_ordering)` where
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`topological_ordering` is just `depth`. In other words, we first sort by `depth`
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and then tie-break based on `stream_ordering`. `depth` is incremented as new
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messages are added to the DAG. Normally, `stream_ordering` is an auto
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incrementing integer, but backfilled events start with `stream_ordering=-1` and decrement.
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---
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- `/sync` returns things in the order they arrive at the server (`stream_ordering`).
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- `/messages` (and `/backfill` in the federation API) return them in the order determined by the event graph `(topological_ordering, stream_ordering)`.
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The general idea is that, if you're following a room in real-time (i.e.
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`/sync`), you probably want to see the messages as they arrive at your server,
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rather than skipping any that arrived late; whereas if you're looking at a
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historical section of timeline (i.e. `/messages`), you want to see the best
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representation of the state of the room as others were seeing it at the time.
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## Outliers
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We mark an event as an `outlier` when we haven't figured out the state for the
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room at that point in the DAG yet. They are "floating" events that we haven't
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yet correlated to the DAG.
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Outliers typically arise when we fetch the auth chain or state for a given
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event. When that happens, we just grab the events in the state/auth chain,
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without calculating the state at those events, or backfilling their
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`prev_events`.
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So, typically, we won't have the `prev_events` of an `outlier` in the database,
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(though it's entirely possible that we *might* have them for some other
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reason). Other things that make outliers different from regular events:
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* We don't have state for them, so there should be no entry in
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`event_to_state_groups` for an outlier. (In practice this isn't always
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the case, though I'm not sure why: see https://github.com/matrix-org/synapse/issues/12201).
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* We don't record entries for them in the `event_edges`,
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`event_forward_extremeties` or `event_backward_extremities` tables.
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Since outliers are not tied into the DAG, they do not normally form part of the
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timeline sent down to clients via `/sync` or `/messages`; however there is an
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exception:
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### Out-of-band membership events
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A special case of outlier events are some membership events for federated rooms
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that we aren't full members of. For example:
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* invites received over federation, before we join the room
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* *rejections* for said invites
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* knock events for rooms that we would like to join but have not yet joined.
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In all the above cases, we don't have the state for the room, which is why they
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are treated as outliers. They are a bit special though, in that they are
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proactively sent to clients via `/sync`.
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## Forward extremity
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Most-recent-in-time events in the DAG which are not referenced by any other
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events' `prev_events` yet. (In this definition, outliers, rejected events, and
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soft-failed events don't count.)
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The forward extremities of a room (or at least, a subset of them, if there are
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more than ten) are used as the `prev_events` when the next event is sent.
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The "current state" of a room (ie: the state which would be used if we
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generated a new event) is, therefore, the resolution of the room states
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at each of the forward extremities.
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## Backward extremity
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The current marker of where we have backfilled up to and will generally be the
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`prev_events` of the oldest-in-time events we have in the DAG. This gives a starting point when
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backfilling history.
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Note that, unlike forward extremities, we typically don't have any backward
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extremity events themselves in the database - or, if we do, they will be "outliers" (see
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above). Either way, we don't expect to have the room state at a backward extremity.
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When we persist a non-outlier event, if it was previously a backward extremity,
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we clear it as a backward extremity and set all of its `prev_events` as the new
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backward extremities if they aren't already persisted as non-outliers. This
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therefore keeps the backward extremities up-to-date.
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## State groups
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For every non-outlier event we need to know the state at that event. Instead of
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storing the full state for each event in the DB (i.e. a `event_id -> state`
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mapping), which is *very* space inefficient when state doesn't change, we
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instead assign each different set of state a "state group" and then have
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mappings of `event_id -> state_group` and `state_group -> state`.
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### Stage group edges
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TODO: `state_group_edges` is a further optimization...
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notes from @Azrenbeth, https://pastebin.com/seUGVGeT
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