.. | ||
cursor.h | ||
error.h | ||
event.h | ||
filter.h | ||
id.h | ||
io.h | ||
keys.h | ||
m.h | ||
query.h | ||
README.md | ||
room.h | ||
sig.h | ||
txn.h | ||
user.h | ||
vm.h |
Matrix Protocol
Introduction
The authoritative place for learning about matrix is at matrix.org but it may be worthwhile to spend a moment and consider this introduction which explains things by distilling the formal core of the protocol before introducing all of the networking and communicative accoutrements...
Identity
The Matrix-ID or mxid
is a universally unique plain-text string allowing
an entity to be addressed internet-wide which is fundamental to the matrix
federation in contrast to the traditional IRC server/network. An example of an
mxid: "@user:host" where host
is a public DNS name, user
is a party to
host
, and the '@' character is replaced to convey type information. The
character, called a sigil
, is defined to be '!' for room_id
identifiers,
'$' for event_id
identifiers, '#' for room aliases, and '@' for users.
Event
The fundamental primitive of this protocol is the event
object. This object
contains some set of key/value pairs and the protocol defines a list of such keys
which are meaningful to the protocol. Other keys which are not meaningful to the
protocol can be included directly in the event
object but there are no guarantees
for if and how a party will pass these keys. To dive right in, here's the list
of recognized keys for an event
:
auth_events
content
depth
event_id
hashes
membership
origin
origin_server_ts
prev_events
prev_state
room_id
sender
signatures
state_key
type
In the event structure, the value for sender
and room_id
and event_id
are
all an mxid
of the appropriate type.
The event
object is also the only fundamental primitive of the protocol; in other
words: everything is an event
. All information is conveyed in events, and governed
by rules for proper values behind these keys. The rest of the protocol specification
describes an abstract state machine which has its state updated by an event, in
addition to providing a standard means for communication of events between parties
over the internet. That's it.
Timeline
The data tape of the matrix machine consists of a singly-linked list of event
objects with each referencing the event_id
of its preceding parent somewhere
in the prev_
keys; this is called the timeline
. Each event is signed by its
creator and affirms all events in the chain preceding it. This is a very similar
structure to that used by software like Git, and Bitcoin. It allows looking back
into the past from any point, but doesn't force a party to accept a future and
leaves dispute resolution open-ended (which will be explained later).
State
The state
consists of a subset of events which are accumulated according to a
few rules when playing the tape through the machine. Events which are selected
as state
will overwrite a matching previously selected state event
and thus
reduce the number of events in this set to far less than the entire timeline
.
The state
is then used to satisfy queries for deciding valid transitions for
the machine. This is like the "work tree" in Git when positioned at some commit.
-
Events with a
state_key
are considered state. -
The identity of a
state event
is the concatenation of theroom_id
value with thetype
value with thestate_key
value. Thus an event with the sameroom_id, type, state_key
replaces an older event instate
. -
Some
state_key
values are empty strings""
. This is a convention for singletonstate
events, like anm.room.create
event. Thestate_key
is used to represent a set, like withm.room.member
events, where the value of thestate_key
is a usermxid
.
Rooms
The room
structure encapsulates an instance of the matrix machine. A room
is a container of event
objects in the form of a timeline. The query
complexity for information in a room timeline is as follows:
-
Message (non-state) events in the timeline have a linear lookup time: the timeline must be iterated in sequence to find a satisfying message.
-
State events in the timeline have a logarithmic lookup: the implementation is expected to maintain a map of the
type
,state_key
values for events present in the timeline.
The matrix protocol specifies certain event
types which are recognized to
affect the behavior of the room
; here is a list of some types:
m.room.name
m.room.create
m.room.topic
m.room.avatar
m.room.aliases
m.room.canonical_alias
m.room.join_rules
m.room.power_levels
m.room.member
m.room.message
...
Some of these events are state
events and some are ephemeral. These will be
detailed later. All m.room.*
namespaced events govern the functionality of the
room. Rooms may contain events of any type, but we don't invent new m.room.*
type events ourselves. This project tends to create events in the namespace
ircd.*
These events should not alter the room's functionality for a client
with knowledge of only the published m.room.*
events wouldn't understand.
Coherence
Matrix is specified as a directed acyclic graph of messages. The conversation of messages moves in one direction: past to future. Messages only reference other messages which have a lower degree of separation (depth) from the first message in the graph (m.room.create). Specifically, each message makes a reference to all known messages at the last depth.
-
The strong ordering of this system contributes to an intuitive "light cone" read coherence. Knowledge of any piece of information (like an event) offers coherent knowledge of all known information which preceded it at that point.
-
Write consistency is relaxed. Multiple messages may be issued at the same depth from independent actors and multiple reference chains may form independent of others. This provides the scalar for performance in a large distributed internet system.
-
Write incoherence must then be resolved with entry consistency because of the relaxed release sequence. While parties broadcast all of their new messages, they make no guarantees for their arrival integration with destinations at the point of release. This wouldn't be as practical. This means a write which wishes to be coherent can only use the best available state they have been made aware of and commit a new message to it.
The system has no other method of resolving incoherence. As a future thought, some form of release commitment will have to be integrated among at least a subset of actors for a few important updates to the graph. For example, a two-phase commit of an important state event or the re-introduction of the classic IRC mode change indicating a commitment to change state.
References to previous events:
[A0] <-- [A1] <-- [A2] | A has seen B1 and includes a reference in A2
^ |
| <---<----<
| |
^------ [B1] <-- [B2] | B hasn't yet seen A1 or A2
[T0] A release A0 :
[T1] A release A1 : B acquire A0
[T2] : B release B1
[T3] A acquire B1 : B release B2
[T4] A release A2 :
Both actors will have their clock (depth) now set to 2 and will issue the next new message at clock cycle 3 referencing all messages from cycle 2 to merge the split in the illustration above which is happening.
[A0] <-- [A1] <-- [A2] [A4] | A now sees B3, B2, and B1
^ | | |
| <---<----< ^--<--< <--<
| | | |
^------- [B1] <-- [B2] <-- [B3] | B now sees A2, A1, and A0
Implementation
Model
This system embraces the fact that "everything is an event." It then follows that everything is a room. We use rooms for both communication and storage of everything.
There is only one† backend database and it stores events. For example: there
is no "user accounts database" holding all of the user data for the server-
instead there is an !accounts
room. To use these rooms as efficient
databases we categorize a piece of data with an event type
and key it with
the event state_key
and the value is the event content
. Iteration of these
events is also possible. This is now a sufficient key-value store as good as
any other approach; better though, since such a databasing room retains all
features and distributed capabilities of any other room. We then focus our
efforts to optimize the behavior of a room, to the benefit of all rooms, and
all things.
† Under special circumstances other databases may exist but they are purely
slave to the events database: i.e one could rm -rf
a slave database and it
would be rebuilt from the events database. These databases only exist if an
event is truly inappropriate and doesn't fit the model even by a stretch.
An example of this is the search-terms database which specializes in indexing
individual words to the events where they are found so content searches can be
efficient.
Flow
This is a single-writer/multiple-reader approach. The "core" is the only writer. The write itself is just the saving of an event. This serves as a transaction advancing the state of the machine with effects visible to all future transactions and external actors.
The core takes the pattern of
evaluate + exclude -> write commitment -> release sequence
. The single
writer approach means that we resolve all incoherence using exclusion or
reordering or rejection on entry and before any writing and release of the
event. Many ircd::ctx's can orbit the inner core resolving their evaluation
with the tightest exclusion occurring around the write at the inner core.
This also gives us the benefit of a total serialization at this point.
:::::::
||||||| <-- evaluation + rejection
\|/ <-- evaluation + exclusion / reordering
!
* <-- actor serialized core write commitment
//|||\\
//|// \\|\\
::::::::::::: <-- release sequence propagation cone
The evaluation phase ensures the event commitment will work: that the event is valid, and that the event is a valid transition of the machine according to the rules. This process may take some time and many yields and IO, even network IO -- if the server lacks a warm cache. During the evaluation phase locks and exclusions may be acquired to maintain the validity of the evaluation state through writing at the expense of other contexts contending for that resource.
Many ircd::ctx are concurrently working their way through the core. The "velocity" is low when an ircd::ctx on this path may yield a lot for various IO and allow other events to be processed. The velocity increases when concurrent evaluation and reordering is no longer viable to maintain coherence. Any yielding of an ircd::ctx at a higher velocity risks stalling the whole core.
::::::: <-- event input (low velocity)
||||||| <-- evaluation process (low velocity)
\|/ <-- serialization process (higher velocity)
The write commitment saves the event to the database. This is a relatively fast operation which probably won't even yield the ircd::ctx, and all future reads to the database will see this write.
! <-- serial write commitment (highest velocity)
The release sequence broadcasts the event so its effects can be consumed. This works by yielding the ircd::ctx so all consumers can view the event and apply its effects for their feature module or send the event out to clients. This is usually faster than it sounds, as the consumers try not to hold up the release sequence for more than their first execution-slice, and copy the event if their output rate is slower.
* <-- event revelation (higher velocity)
//|||\\
//|// \\|\\
::::::::::::: <-- release sequence propagation cone (low velocity)
The entire core commitment process relative to an event riding through it on an ircd::ctx has a duration tolerable for something like a REST interface, so the response to the user can wait for the commitment to succeed or fail and properly inform them after.
The core process is then optimized by the following facts:
* The resource exclusion zone around most matrix events is either
small or non-existent because of its relaxed write consistency.
* Writes in this implementation will not delay.
"Core dilation" is a phenomenon which occurs when large numbers of events which have relaxed dependence are processed concurrently because none of them acquire any exclusivity which impede the others.
:::::::
|||||||
||||||| <-- Core dilation; flow shape optimized for volume.
|||||||
/|||||\
///|||\\\
//|/|||\|\\
:::::::::::::
Close up of the charybdis's write head when tight to one schwarzschild-radius of matrix room surface which propagates only one event through at a time. Vertical tracks are contexts on their journey through each evaluation and exclusion step to the core.
Input Events Phase
:::::::::::::::::::::::::::::::::::::::::::::::::::::: validation / dupcheck
|||||||||||||||||||||||||||||||||||||||||||||||||||||| identity/key resolution
|||||||||||||||||||||||||||||||||||||||||||||||||||||| verification
|||| ||||||||||||||| ||||||||||||||| ||||||||||||||||| head resolution
--|--|----|-|---|--|--|---|---|---|---------|---|---|- graph resolutions
----------|-|---|---------|-------|-----------------|- module evaluations
\ | | | | /
== ==============| | == Lowest velocity locks
\ | | /
== | | == Mid velocity locks
\ | | /
== | / == High velocity locks
\ | / /
== =====/= == Highest velocity lock
\ / /
\__ / __/
_ | _
! Write commitment
Above, two contexts are illustrated as contending for the highest velocity lock. The highest velocity lock is not held for significant time, as the holder has very little work left to be done within the core, and will release the lock to the other context quickly. The lower velocity locks may have to be held longer, but are also less exclusive to all contexts.
* Singularity
[ ]
/-------------[---]-------------\
/ : : \ Federation send
/ /---------[---]---------\ \
/ : : \ Client sync
out / /------[---]------\ \ out
/ / : : \ \
/ out / | | \ out \
/ out / \ out \
/ \
return
| result to |
| evaluator |
-------------
Above, a close-up of the release sequence. The new event is being "viewed" by each consumer context separated by the horizontal lines representing a context switch from the perspective of the event travelling down. Each consumer performs its task for how to propagate the commissioned event.
Each consumer has a shared-lock of the event which will hold up the completion of the commitment until all consumers release that. The ideal consumer will only hold their lock for a single context-slice while they play their part in applying the event, like non-blocking copies to sockets etc. These consumers then go on to do the rest of their output without the original event data which was memory supplied by the evaluator (like an HTTP client). Then all locks acquired on the entry side of the core can be released. The evaluator then gets the result of the successful commitment.
Scaling
Scaling beyond the limit of a single CPU core can be done with multiple instances of IRCd which form a cluster of independent actors. This cluster can extend to other machines on the network too. The independent actors leverage the weak write consistency and strong ordering of the matrix protocol to scale the same way the federation scales.
Interference pattern of two IRCd'en:
::::::::::::::::::::::::::::::::::::
--------\:::::::/--\:::::::/--------
||||||| |||||||
\|/ \|/
! !
* *
//|||\\ //|||\\
//|// \\|\\//|// \\|\\
/|/|/|\|\|\/|/|/|\|\|\|\