80 lines
3.0 KiB
Markdown
80 lines
3.0 KiB
Markdown
# 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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## Forward extremity
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Most-recent-in-time events in the DAG which are not referenced by any other events' `prev_events` yet.
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The forward extremities of a room are used as the `prev_events` when the next event is sent.
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## Backwards extremity
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The current marker of where we have backfilled up to and will generally be the
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oldest-in-time events we know of in the DAG.
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This is an event where we haven't fetched all of the `prev_events` for.
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Once we have fetched all of its `prev_events`, it's unmarked as a backwards
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extremity (although we may have formed new backwards extremities from the prev
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events during the backfilling process).
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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.
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We won't *necessarily* have the `prev_events` of an `outlier` in the database,
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but it's entirely possible that we *might*. The status of whether we have all of
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the `prev_events` is marked as a [backwards extremity](#backwards-extremity).
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For example, when we fetch the event auth chain or state for a given event, we
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mark all of those claimed auth events as outliers because we haven't done the
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state calculation ourself.
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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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