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  • # 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.
    
    
    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
    
    `prev_events`. Since we don't have the state at any events fetched in that
    way, we mark them as outliers.
    
    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_groups` for 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 `event_edges`,
       `event_forward_extremeties` or `event_backward_extremities` tables.
    
    Since outliers are not tied into the DAG, they do not normally form part of the
    timeline sent down to clients via `/sync` or `/messages`; however there is an
    exception:
    
    ### Out-of-band membership events
    
    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 `/sync`.
    
    ## Forward extremity
    
    Most-recent-in-time events in the DAG which are not referenced by any other
    events' `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.
    
    ## Backward extremity
    
    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
    backfilling history.
    
    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.
    
    
    ## 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