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docs: Add a long document explaining the events system. 

This is probably one of Zulip's most important systems, and thus worth
documenting carefully.
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Tim Abbott 2017-02-10 01:09:31 -08:00
parent 092bdc7645
commit 92219aa3dd
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22
docs/architecture-overview.md
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@ -87,10 +87,12 @@ Components
![architecture-simple](images/architecture_simple.png)
### Tornado and Django
### Django and Tornado
We use both the [Tornado](http://www.tornadoweb.org) and
[Django](https://www.djangoproject.com/) Python web frameworks.
Zulip is primarily implemented in the
[Django](https://www.djangoproject.com/) Python web framework. We
also make use of [Tornado](http://www.tornadoweb.org) for the
real-time push system.
Django is the main web application server; Tornado runs the
server-to-client real-time push system. The app servers are configured
@ -114,6 +116,10 @@ click on something) are processed by the Django application server. One
exception to this is that Zulip uses websockets through Tornado to
minimize latency on the code path for **sending** messages.
There is detailed documentation on the
[real-time push and event queue system](events-system.html); most of
the code is in `zerver/tornado`.
### nginx
nginx is the front-end web server to all Zulip traffic; it serves static
@ -198,12 +204,10 @@ and the Tornado push system.
Two simple wrappers around `pika` (the Python RabbitMQ client) are in
`zulip/zerver/lib/queue.py`. There's an asynchronous client for use in
Tornado and a more general client for use elsewhere.
`zerver/tornado/event_queue.py` has helper functions for putting
events into one queue or another. Most of the processes started by
Supervisor are queue processors that continually pull things out of a
RabbitMQ queue and handle them.
Tornado and a more general client for use elsewhere. Most of the
processes started by Supervisor are queue processors that continually
pull things out of a RabbitMQ queue and handle them; they are defined
in `zerver/worker/queue_processors.py`.
Also see [the queuing guide](queuing.html).

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docs/events-system.md Normal file
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@ -0,0 +1,245 @@
# Real-time Push and Events
Zulip's "events system" is the server-to-client push system that
powers our real-time sync. This document explains how it works; to
read an example of how a complete feature using this system works,
check out the
[new application feature tutorial](new-feature-tutorial.html).
Any single-page web application like Zulip needs a story for how
changes made by one client are synced to other clients, though having
a good architecture for this is particularly important for a chat tool
like Zulip, since the state is constantly changing. When we talk
about clients, think a browser tab, mobile app, or API bot that needs
to receive updates to the Zulip data. The simplest example is a new
message being sent by one client; other clients must be notified in
order to display the message. But a complete application like Zulip
has dozens of different types of data that need to be synced to other
clients, whether it be new streams, changes in a user's name or
avatar, settings changes, etc. In Zulip, we call these updates that
need to be sent to other clients **events**.
An important thing to understand when designing such a system is that
events need to be synced to every client that has a copy of the old
data if one wants to avoid clients displaying inaccurate data to
users. So if a user has two browser windows open and sends a message,
every client controlled by that user as well as any recipients of the
message, including both of those two browser windows, will receive
that event. (Technically, we don't need to send events to the client
that triggered the change, but this approach saves a bunch of
unnecessary duplicate UI update code, since the client making the
change can just use the same code as every other client, maybe plus a
little notification that the operation succeeded).
Architecturally, there are a few things needed to make a successful
real-time sync system work:
* **Generation**. Generating events when changes happen to data, and
determining which users should receive each event.
* **Delivery**. Efficiently delivering those events to interested
clients, ideally in an exactly-once fashion.
* **UI updates**. Updating the UI in the client once it has received
events from the server.
Reactive JavaScript libraries like React and Vue can help simplify the
last piece, but there aren't good standard systems for doing
generation and delivery, so we have to build them ourselves.
This document discusses how Zulip solves the generation and delivery
problems in a scalable, correct, and predictable way.
## Generation system
Zulip's generation system is built around a Python function,
`send_event(event, users)`. It accepts an event data structure (just
a Python dictionary with some keys and value; `type` is always one of
the keys but the rest depends on the specific event) and a list of
user IDs for the users whose clients should receive the event. In
special cases such as message delivery, the list of users will instead
be a list of dicts mapping user IDs to user-specific data like whether
that user was mentioned in that message. The data passed to
`send_event` are simply marshalled as JSON and placed in the
`notify_tornado` RabbitMQ queue to be consumed by the delivery system.
Usually, this list of users is one of 3 things:
* A single user (e.g. for user-level settings changes).
* Everyone in the realm (e.g. for organization-level settings changes,
like new realm emoji).
* Everyone who would receive a given message (for messages, emoji
reactions, message editing, etc.); i.e. the subscribers to a stream
or the people on a private message thread.
It is the responsibility of the caller of `send_event` to choose the
list of user IDs correctly. There can be security problems if e.g. an
event containing private message content is sent to the entire
organization. However, if an event isn't sent to enough clients,
there will likely be user-visible real-time sync bugs.
Most of the hard work in event generation is about defining consistent
event dictionaries that are clear, readable, will be useful to the
wide range of possible clients, and make it easy for developers.
## Delivery system
Zulip's event delivery (real-time push) system is based on Tornado,
which is ideal for handling a large number of open requests. Details
on Tornado are available in the
[architecture overview](architecture-overview.html), but in short it
is good at holding open a large number of connections for a long time.
The complete system is about 1500 lines of code in `zerver/tornado/`,
primarily `zerver/tornado/event_queue.py`.
Zulip's event delivery system is based on "long-polling"; basically
clients make `GET /json/events` calls to the server, and the server
doesn't respond to the request until it has an event to deliver to the
client. This approach is reasonably efficient and works everywhere
(unlike websockets, which have a decreasing but nonzero level of
client compatibility problems).
For each connected client, the **Event Queue Server** maintain an
**event queue**, which contains any events that are to be delivered to
that client which have not yet been acknowledged by that client.
Ignoring the subtle details around error handling, the protocol is
pretty simple; when a client does a `GET /json/events` call, the
server checks if there are any events in the queue. If there are, it
returns the events immediately. If there aren't, it records that
queue as having a waiting client (often called a `handler` in the
code).
When it pulls an event off the `notify_tornado` RabbitMQ queue, it
simply delivers the event to each queue associated with one of the
target users. If the queue has a waiting client, it breaks the
long-poll connection by returning an HTTP response to the waiting
client request. If there is no waiting client, it simply pushes the
event onto the queue.
When starting up, each client makes a `POST /json/register` to the
server, which creates a new event queue for that client and return the
`queue_id` as well as an initial `last_event_id` to the client (it can
also, optionally, fetch the initial data to save an RTT and avoid
races; see the below section on initial data fetches for details on
why this is useful). Once the event queue is registered, the client
can just do an infinite loop calling `GET /json/events` with those
parameters, updating `last_event_id` each time to acknowledge any
events it has received (see `call_on_each_event` in the
[Zulip Python API bindings][api-bindings-code] for a complete example
implementation). When handling each `GET /json/events` request, the
queue server can safely delete any events have have an event ID less
than or equal to the client's `last_event_id` (event IDs are just a
counter for the events a given queue has received.)
If network failures were impossible, the `last_event_id` parameter in
the protocol would not be required, but it is important for enabling
exactly-once delivery in the presence of potential failures. (Without
it, the queue server would have to delete events from the queue as
soon as it attempted to send them to the client; if that specific HTTP
response didn't reach the client due to a network TCP failure, then
those events could be lost).
[api-bindings-code]: https://github.com/zulip/zulip/blob/master/api/zulip/__init__.py
The queue servers are a very high-traffic system, processing at a
minimum a request for every message delivered to every Zulip client.
Additionally, as a workaround for low-quality NAT servers that kill
HTTP connections that are open without activity for more than 60s, the
queue servers also send a heartbeat event to each queue at least once
every 45s or so (if no other events have arrived in the meantime).
To avoid a large memory and other resource leak, the queues are
garbage collected after (by default) 10 minutes of inactivity from a
client, under the theory that the client has likely gone off the
Internet (or no longer exists) access; this happens constantly. If
the client returns, it will receive a "queue not found" error when
requesting events; it's handler for this case should just restart the
client / reload the browser so that it refetches initial data the same
way it would on startup. Since clients have to implement their
startup process anyway, this approach adds minimal technical
complexity to clients. A nice side effect is that if the Event Queue
Server server (which stores queues in memory) were to crash and lose
its data, clients would recover, just as if they had lost Internet
access briefly (there is some DoS risk to manage, though).
(The Event Queue Server is designed to save any event queues to disk
and reload them when the server is restarted, and catches exceptions
carefully, so such incidents are very rare, but it's nice to have a
design that handles them without leaving broken out-of-date clients
anyway).
## The initial data fetch
When a client starts up, it usually wants to get 2 things from the
server:
* The "current state" of various pieces of data, e.g. the current
settings, set of users in the organization (for typeahead), stream,
messages, etc. (aka the "initial state").
* A subscription to receive updates to those data when they are
changed by a client (aka an event queue).
Ideally, one would get those two things atomically, i.e. if some other
user changes their name, either the name change happens before the
fetch (and thus the old name is in the initial state and there will be
an event in the queue for the name change) or after (the new name is
in the initial state, and there is no event for that name change in
the queue).
Achieving this atomicity goals means we save a huge amount of work
that the N clients for Zulip don't need to worry about a wide range of
potential rare and hard to reproduce race conditions; we just have to
implement things correctly once in the Zulip server.
This is quite challenging to do technically, because fetching the
initial state for a complex web application like Zulip might involve
dozens of queries to the database, caches, etc. over the course of
100ms or more, and it is thus nearly impossible to do all of those
things together atomically. So instead, we use a more complicated
algorithm that can produce the atomic result from non-atomic
subroutines. Here's how it works when you make a `register` API
request. The request is directly handled by Django:
* Django makes an HTTP request to Tornado, requesting that a new event
queue be created, and records its queue ID.
* Django does all the various database/cache/etc. queries to fetch the
data, non-atomically, from the various data sources (see
the `fetch_initial_state_data` function).
* Django makes a second HTTP request to Tornado, requesting any events
that had been added to the Tornado event queue since it
was created.
* Finally, Django "applies" the events (see the `apply_events`
function) to the initial state that it fetched. E.g. for a name
change event, it finds the user data in the `realm_user` data
struture, and updates it to have the new name.
This achieves everything we desire, at the cost that we need to write
the `apply_events` function. This is a difficult function to
implement correctly, because the situations that it tests for almost
never happen (being race conditions). So we have a special test
class, `EventsRegisterTest`, that is specifically designed to test
this function by ensuring the possible race condition always happens.
In particular, it does the following:
* Call `fetch_initial_state_data` to get the current state.
* Call a state change function that issues an event,
e.g. `do_change_full_name`, and capture any events that are generated.
* Call `apply_events(state, events)`, and compare the result to
calling `fetch_initial_state_data` again now.
The `apply_events` code is correct if those two results are identical.
The final detail we need to ensure that `apply_events` always works
correctly is to make sure that we have `EventsRegisterTest` tests for
every event type that can be generated by Zulip. This can be tested
manually using `test-backend --coverage EventsRegisterTest` and then
checking that all the calls to `send_event` are covered. Someday
we'll add automation that verifies this directly by inspecting the
coverage data.
### Messages
One exception to the protocol described in the last section is the
actual messages. Because Zulip clients usually fetch them in a
separate AJAX call after the rest of the site is loaded, we don't need
them to be included in the initial state data. To handle those
correctly, clients are responsible for discarding events related to
messages that the client has not yet fetched.

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docs/index.rst
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@ -115,6 +115,7 @@ Contents:
:caption: Subsystem documentation
settings
events-system
queuing
bots-guide
custom-apps

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docs/life-of-a-request.md
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@ -40,9 +40,9 @@ location /static/ {
}
```
## Nginx routes other requests [between tornado and django][tornado-django]
## Nginx routes other requests [between django and tornado][tornado-django]
[tornado-django]: architecture-overview.html?highlight=tornado#tornado-and-django
[tornado-django]: architecture-overview.html?highlight=tornado#django-and-tornado
All our connected clients hold open long-polling connections so that
they can receive events (messages, presence notifications, and so on) in

5
docs/new-feature-tutorial.md
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@ -6,6 +6,11 @@ as an example of the specific steps needed to add a new feature: adding
a new option to the application that is dynamically synced through the
data system in real-time to all browsers the user may have open.
As you read this, you may find you need to learn about Zulip's
real-time push system; the
[real-time push and events](events-system.html) documentation has a
detailed explanation of how everything works.
## General Process in brief
### Adding a field to the database