Add notes describing Synapse's streams (#16015)
Co-authored-by: Patrick Cloke <clokep@users.noreply.github.com>erikj/faster_purge
David Robertson
GitHub
parent
b57630c507
commit
9d3713d6d5
|
|
@ -0,0 +1 @@
|
|||
Add a internal documentation page describing the ["streams" used within Synapse](https://matrix-org.github.io/synapse/v1.90/development/synapse_architecture/streams.html).
|
||||
|
|
@ -97,6 +97,7 @@
|
|||
- [Cancellation](development/synapse_architecture/cancellation.md)
|
||||
- [Log Contexts](log_contexts.md)
|
||||
- [Replication](replication.md)
|
||||
- [Streams](development/synapse_architecture/streams.md)
|
||||
- [TCP Replication](tcp_replication.md)
|
||||
- [Faster remote joins](development/synapse_architecture/faster_joins.md)
|
||||
- [Internal Documentation](development/internal_documentation/README.md)
|
||||
|
|
|
|||
|
|
@ -0,0 +1,157 @@
|
|||
## Streams
|
||||
|
||||
Synapse has a concept of "streams", which are roughly described in [`id_generators.py`](
|
||||
https://github.com/matrix-org/synapse/blob/develop/synapse/storage/util/id_generators.py
|
||||
).
|
||||
Generally speaking, streams are a series of notifications that something in Synapse's database has changed that the application might need to respond to.
|
||||
For example:
|
||||
|
||||
- The events stream reports new events (PDUs) that Synapse creates, or that Synapse accepts from another homeserver.
|
||||
- The account data stream reports changes to users' [account data](https://spec.matrix.org/v1.7/client-server-api/#client-config).
|
||||
- The to-device stream reports when a device has a new [to-device message](https://spec.matrix.org/v1.7/client-server-api/#send-to-device-messaging).
|
||||
|
||||
See [`synapse.replication.tcp.streams`](
|
||||
https://github.com/matrix-org/synapse/blob/develop/synapse/replication/tcp/streams/__init__.py
|
||||
) for the full list of streams.
|
||||
|
||||
It is very helpful to understand the streams mechanism when working on any part of Synapse that needs to respond to changes—especially if those changes are made by different workers.
|
||||
To that end, let's describe streams formally, paraphrasing from the docstring of [`AbstractStreamIdGenerator`](
|
||||
https://github.com/matrix-org/synapse/blob/a719b703d9bd0dade2565ddcad0e2f3a7a9d4c37/synapse/storage/util/id_generators.py#L96
|
||||
).
|
||||
|
||||
### Definition
|
||||
|
||||
A stream is an append-only log `T1, T2, ..., Tn, ...` of facts[^1] which grows over time.
|
||||
Only "writers" can add facts to a stream, and there may be multiple writers.
|
||||
|
||||
Each fact has an ID, called its "stream ID".
|
||||
Readers should only process facts in ascending stream ID order.
|
||||
|
||||
Roughly speaking, each stream is backed by a database table.
|
||||
It should have a `stream_id` (or similar) bigint column holding stream IDs, plus additional columns as necessary to describe the fact.
|
||||
Typically, a fact is expressed with a single row in its backing table.[^2]
|
||||
Within a stream, no two facts may have the same stream_id.
|
||||
|
||||
> _Aside_. Some additional notes on streams' backing tables.
|
||||
>
|
||||
> 1. Rich would like to [ditch the backing tables](https://github.com/matrix-org/synapse/issues/13456).
|
||||
> 2. The backing tables may have other uses.
|
||||
> For example, the events table serves backs the events stream, and is read when processing new events.
|
||||
> But old rows are read from the table all the time, whenever Synapse needs to lookup some facts about an event.
|
||||
> 3. Rich suspects that sometimes the stream is backed by multiple tables, so the stream proper is the union of those tables.
|
||||
|
||||
Stream writers can "reserve" a stream ID, and then later mark it as having being completed.
|
||||
Stream writers need to track the completion of each stream fact.
|
||||
In the happy case, completion means a fact has been written to the stream table.
|
||||
But unhappy cases (e.g. transaction rollback due to an error) also count as completion.
|
||||
Once completed, the rows written with that stream ID are fixed, and no new rows
|
||||
will be inserted with that ID.
|
||||
|
||||
### Current stream ID
|
||||
|
||||
For any given stream reader (including writers themselves), we may define a per-writer current stream ID:
|
||||
|
||||
> The current stream ID _for a writer W_ is the largest stream ID such that
|
||||
> all transactions added by W with equal or smaller ID have completed.
|
||||
|
||||
Similarly, there is a "linear" notion of current stream ID:
|
||||
|
||||
> The "linear" current stream ID is the largest stream ID such that
|
||||
> all facts (added by any writer) with equal or smaller ID have completed.
|
||||
|
||||
Because different stream readers A and B learn about new facts at different times, A and B may disagree about current stream IDs.
|
||||
Put differently: we should think of stream readers as being independent of each other, proceeding through a stream of facts at different rates.
|
||||
|
||||
**NB.** For both senses of "current", that if a writer opens a transaction that never completes, the current stream ID will never advance beyond that writer's last written stream ID.
|
||||
|
||||
For single-writer streams, the per-writer current ID and the linear current ID are the same.
|
||||
Both senses of current ID are monotonic, but they may "skip" or jump over IDs because facts complete out of order.
|
||||
|
||||
|
||||
_Example_.
|
||||
Consider a single-writer stream which is initially at ID 1.
|
||||
|
||||
| Action | Current stream ID | Notes |
|
||||
|------------|-------------------|-------------------------------------------------|
|
||||
| | 1 | |
|
||||
| Reserve 2 | 1 | |
|
||||
| Reserve 3 | 1 | |
|
||||
| Complete 3 | 1 | current ID unchanged, waiting for 2 to complete |
|
||||
| Complete 2 | 3 | current ID jumps from 1 -> 3 |
|
||||
| Reserve 4 | 3 | |
|
||||
| Reserve 5 | 3 | |
|
||||
| Reserve 6 | 3 | |
|
||||
| Complete 5 | 3 | |
|
||||
| Complete 4 | 5 | current ID jumps 3->5, even though 6 is pending |
|
||||
| Complete 6 | 6 | |
|
||||
|
||||
|
||||
### Multi-writer streams
|
||||
|
||||
There are two ways to view a multi-writer stream.
|
||||
|
||||
1. Treat it as a collection of distinct single-writer streams, one
|
||||
for each writer.
|
||||
2. Treat it as a single stream.
|
||||
|
||||
The single stream (option 2) is conceptually simpler, and easier to represent (a single stream id).
|
||||
However, it requires each reader to know about the entire set of writers, to ensures that readers don't erroneously advance their current stream position too early and miss a fact from an unknown writer.
|
||||
In contrast, multiple parallel streams (option 1) are more complex, requiring more state to represent (map from writer to stream id).
|
||||
The payoff for doing so is that readers can "peek" ahead to facts that completed on one writer no matter the state of the others, reducing latency.
|
||||
|
||||
Note that a multi-writer stream can be viewed in both ways.
|
||||
For example, the events stream is treated as multiple single-writer streams (option 1) by the sync handler, so that events are sent to clients as soon as possible.
|
||||
But the background process that works through events treats them as a single linear stream.
|
||||
|
||||
Another useful example is the cache invalidation stream.
|
||||
The facts this stream holds are instructions to "you should now invalidate these cache entries".
|
||||
We only ever treat this as a multiple single-writer streams as there is no important ordering between cache invalidations.
|
||||
(Invalidations are self-contained facts; and the invalidations commute/are idempotent).
|
||||
|
||||
### Writing to streams
|
||||
|
||||
Writers need to track:
|
||||
- track their current position (i.e. its own per-writer stream ID).
|
||||
- their facts currently awaiting completion.
|
||||
|
||||
At startup,
|
||||
- the current position of that writer can be found by querying the database (which suggests that facts need to be written to the database atomically, in a transaction); and
|
||||
- there are no facts awaiting completion.
|
||||
|
||||
To reserve a stream ID, call [`nextval`](https://www.postgresql.org/docs/current/functions-sequence.html) on the appropriate postgres sequence.
|
||||
|
||||
To write a fact to the stream: insert the appropriate rows to the appropriate backing table.
|
||||
|
||||
To complete a fact, first remove it from your map of facts currently awaiting completion.
|
||||
Then, if no earlier fact is awaiting completion, the writer can advance its current position in that stream.
|
||||
Upon doing so it should emit an `RDATA` message[^3], once for every fact between the old and the new stream ID.
|
||||
|
||||
### Subscribing to streams
|
||||
|
||||
Readers need to track the current position of every writer.
|
||||
|
||||
At startup, they can find this by contacting each writer with a `REPLICATE` message,
|
||||
requesting that all writers reply describing their current position in their streams.
|
||||
Writers reply with a `POSITION` message.
|
||||
|
||||
To learn about new facts, readers should listen for `RDATA` messages and process them to respond to the new fact.
|
||||
The `RDATA` itself is not a self-contained representation of the fact;
|
||||
readers will have to query the stream tables for the full details.
|
||||
Readers must also advance their record of the writer's current position for that stream.
|
||||
|
||||
# Summary
|
||||
|
||||
In a nutshell: we have an append-only log with a "buffer/scratchpad" at the end where we have to wait for the sequence to be linear and contiguous.
|
||||
|
||||
|
||||
---
|
||||
|
||||
[^1]: we use the word _fact_ here for two reasons.
|
||||
Firstly, the word "event" is already heavily overloaded (PDUs, EDUs, account data, ...) and we don't need to make that worse.
|
||||
Secondly, "fact" emphasises that the things we append to a stream cannot change after the fact.
|
||||
|
||||
[^2]: A fact might be expressed with 0 rows, e.g. if we opened a transaction to persist an event, but failed and rolled the transaction back before marking the fact as completed.
|
||||
In principle a fact might be expressed with 2 or more rows; if so, each of those rows should share the fact's stream ID.
|
||||
|
||||
[^3]: This communication used to happen directly with the writers [over TCP](../../tcp_replication.md);
|
||||
nowadays it's done via Redis's Pubsub.
|
||||
Loading…
Reference in New Issue