mirror of https://github.com/zulip/zulip.git
385 lines
20 KiB
Markdown
385 lines
20 KiB
Markdown
# Sending messages
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While sending a message in a chat product might seem simple, there's a
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lot of underlying complexity required to make a professional-quality
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experience.
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This document aims to explain conceptually what happens when a message
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is sent in Zulip, and why that is correct behavior. It assumes the
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reader is familiar with our
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[real-time sync system](../subsystems/events-system.md) for
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server-to-client communication and
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[new application feature tutorial](../tutorials/new-feature-tutorial.md),
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and we generally don't repeat the content discussed there.
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## Message lists
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This is just a bit of terminology: A "message list" is what Zulip
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calls the frontend concept of a (potentially narrowed) message feed.
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There are 3 related structures:
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* A `message_list_data` just has the sequencing data of which message
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IDs go in what order.
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* A `message_list` is built on top of `message_list_data` and
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additionally contains the data for a visible-to-the-user message list
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(E.g. where trailing bookends should appear, a selected message,
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etc.).
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* A `message_list_view` is built on top of `message_list` and
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additionally contains rendering details like a window of up to 400
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messages that is present in the DOM at the time, scroll position
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controls, etc.
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(This should later be expanded into a full article on message lists
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and narrowing).
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## Compose area
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The compose box does a lot of fancy things that are out of scope for
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this article. But it also does a decent amount of client-side
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validation before sending a message off to the server, especially
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around mentions (E.g. checking the stream name is a valid stream,
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displaying a warning about the number of recipients before a user can
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use `@**all**` or mention a user who is not subscribed to the current
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stream, etc.).
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## Backend implementation
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The backend flow for sending messages is similar in many ways to the
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process described in our
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[new application feature tutorial](../tutorials/new-feature-tutorial.md).
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This section details the ways in which it is different:
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* There is significant custom code inside the `process_message_event`
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function in `zerver/tornado/event_queue.py`. This custom code has a
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number of purposes:
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* Triggering email and mobile push notifications for any users who
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do not have active clients and have settings of the form "push
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notifications when offline". In order to avoid doing any real
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computational work inside the Tornado codebase, this logic aims
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to just do the check for whether a notification should be
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generated, and then put an event into an appropriate
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[queue](../subsystems/queuing.md) to actually send the
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message. See `maybe_enqueue_notifications` and related code for
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this part of the logic.
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* Splicing user-dependent data (E.g. `flags` such as when the user
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was `mentioned`) into the events.
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* Handling the [local echo details](#local-echo).
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* Handling certain client configuration options that affect
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messages. E.g. determining whether to send the
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plaintext/markdown raw content or the rendered HTML (e.g. the
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`apply_markdown` and `client_gravatar` features in our
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[events API docs](https://zulip.com/api/register-queue)).
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* Following our standard naming convention, input validation is done
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inside the `check_message` function, which is responsible for
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validating the user can send to the recipient,
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[rendering the markdown](../subsystems/markdown.md), etc. --
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basically everything that can fail due to bad user input.
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* The core `do_send_messages` function (which handles actually sending
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the message) is one of the most optimized and thus complex parts of
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the system. But in short, its job is to atomically do a few key
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things:
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* Store a `Message` row in the database.
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* Store one `UserMessage` row in the database for each user who is
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a recipient of the message (including the sender), with
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appropriate `flags` for whether the user was mentioned, an alert
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word appears, etc. See
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[the section on soft deactivation](#soft-deactivation) for
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a clever optimization we use here that is important for large
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open organizations.
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* Do all the database queries to fetch relevant data for and then
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send a `message` event to the
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[events system](../subsystems/events-system.md) containing the
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data it will need for the calculations described above. This
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step adds a lot of complexity, because the events system cannot
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make queries to the database directly.
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* Trigger any other deferred work caused by the current message,
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e.g. [outgoing webhooks](https://zulip.com/api/outgoing-webhooks)
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or embedded bots.
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* Every query is designed to be a bulk query; we carefully
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unit-test this system for how many database and memcached queries
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it makes when sending messages with large numbers of recipients,
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to ensure its performance.
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## Local echo
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An essential feature for a good chat is experience is local echo
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(i.e. having the message appear in the feed the moment the user hits
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send, before the network round trip to the server). This is essential
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both for freeing up the compose box (for the user to send more
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messages) as well as for the experience to feel snappy.
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A sloppy local echo experience (like Google Chat had for over a decade
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for emoji) would just render the raw text the user entered in the
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browser, and then replace it with data from the server when it
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changes.
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Zulip aims for a near-perfect local echo experience, which requires is
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why our [markdown system](../subsystems/markdown.md) requires both
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an authoritative (backend) markdown implementation and a secondary
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(frontend) markdown implementation, the latter used only for the local
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echo feature. Read our markdown documentation for all the tricky
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details on how that works and is tested.
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The rest of this section details how Zulip manages locally echoed
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messages.
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* The core function in the frontend codebase
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`echo.try_deliver_locally`. This checks whether correct local echo
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is possible (via `markdown.contains_backend_only_syntax`) and useful
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(whether the message would appear in the current view), and if so,
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causes Zulip to insert the message into the relevant feed(s).
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* Since the message hasn't been confirmed by the server yet, it
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doesn't have a message ID. The frontend makes one up, via
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`local_message.next_local_id`, by taking the highest message ID it
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has seen and adding the decimal `0.01`. The use of a floating point
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value is critical, because it means the message should sort
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correctly with other messages (at the bottom) and also won't be
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duplicated by a real confirmed-by-the-backend message ID. We choose
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just above the `max_message_id`, because we want any new messages
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that other users send to the current view to be placed after it in
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the feed (this decision is someone arbitrary; in any case we'll
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resort it to its proper place once it is confirmed by the server.
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We do it this way to minimize messages jumping around/reordering
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visually).
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* The `POST /messages` API request to the server to send the message
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is passed two special parameters that clients not implementing local
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echo don't use: `queue_id` and `local_id`. The `queue_id` is the ID
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of the client's event queue; here, it is used just as a unique
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identifier for the specific client (e.g. a browser tab) that sent
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the message. And the `local_id` is, by the construction above, a
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unique value within that namespace identifying the message.
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* The `do_send_messages` backend code path includes the `queue_id` and
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`local_id` in the data it passes to the
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[events system](../subsystems/events-system.md). The events
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system will extend the `message` event dictionary it delivers to
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the client containing the `queue_id` with `local_message_id` field,
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containing the `local_id` that the relevant client used when sending
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the message. This allows the client to know that the `message`
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event it is receiving is the same message it itself had sent.
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* Using that information, rather than adding the "new message" to the
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relevant message feed, it updates the (locally echoed) message's
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properties (at the very least, message ID and timestamp) and
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rerenders it in any message lists where it appears. This is
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primarily done in `exports.process_from_server` in
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`static/js/echo.js`.
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### Local echo in message editing
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Zulip also supports local echo in the message editing code path for
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edits to just the content of a message. The approach is analogous
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(using `markdown.contains_backend_only_syntax`, etc.)), except we
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don't need any of the `local_id` tracking logic, because the message
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already has a permanent message id; as a result, the whole
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implementation was under 150 lines of code.
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## Putting it all together
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This section just has a brief review of the sequence of steps all in
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one place:
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* User hits send in the compose box.
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* Compose box validation runs; if it passes, the browser locally
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echoes the message and then sends a request to the `POST /messages`
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API endpoint.
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* The Django URL routes and middleware run, and eventually call the
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`send_message_backend` view function in `zerver/views/messages.py`.
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(Alternatively, for an API request to send a message via Zulip's
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REST API, things start here).
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* `send_message_backend` does some validation before triggering the
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`check_message` + `do_send_messages` backend flow.
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* That backend flow saves the data to the database and triggers a
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`message` event in the `notify_tornado` queue (part of the events
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system).
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* The events system processes, and dispatches that event to all
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clients subscribed to receive notifications for users who should
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receive the message (including the sender). As a side effect, it
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adds queue items to the email and push notification queues (which,
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in turn, may trigger those notifications).
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* Other receive the event and display the new message.
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* For the client that sent the message, it instead replaces its
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locally echoed message with the final message it received back
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from the server (it indicates this to the sender by adding a
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display timestamp to the message).
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* The `send_message_backend` view function returns
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a 200 `HTTP` response; the client receives that response and mostly
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does nothing with it other than update some logging details. (This
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may happen before or after the client receives the event notifying
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it about the new message via its event queue.)
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## Message editing
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Message editing uses a very similar principle to how sending messages
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works. A few details are worth mentioning:
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* `maybe_enqueue_notifications_for_message_update` is an analogue of
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`maybe_enqueue_notifications`, and exists to handle cases like a
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user was newly mentioned after the message is edited (since that
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should trigger email/push notifications, even if the original
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message didn't have one).
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* We use a similar technique to what's described in the local echo
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section for doing client-side rerendering to update the message feed.
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* In the default configuration, Zulip stores the message edit history
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(which is useful for forensics but also exposed in the UI), in the
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`message.edit_history` attribute.
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* We support topic editing, including bulk-updates moving several
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messages between topics.
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### Inline URL previews
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Zulip's inline URL previews feature (`zerver/lib/url_preview/`) uses
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variant of the message editing/local echo behavior. The reason is
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that for inline URL previews, the backend needs to fetch the content
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from the target URL, and for slow websites, this could result in a
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significant delay in rendering the message and delivering it to other
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users.
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* For this case, Zulip's backend markdown processor will render the
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message without including the URL embeds/previews, but it will add a
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deferred work item into the `embed_links` queue.
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* The [queue processor](../subsystems/queuing.md) for the
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`embed_links` queue will fetch the URLs, and then if they return
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results, rerun the markdown processor and notify clients of the
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updated message `rendered_content`.
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* We reuse the `update_message` framework (used for
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Zulip's message editing feature) in order to avoid needing custom code
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to implement the notification-and-rerender part of this implementation.
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## Soft deactivation
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This section details a somewhat subtle issue: How Zulip uses a
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user-invisible technique called "soft deactivation" to handle
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scalability to communities with many thousands of inactive users.
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For background, Zulip’s threading model requires tracking which
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individual messages each user has received and read (in other chat
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products, the system either doesn’t track what the user has read at
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all, or just needs to store a pointer for “how far the user has read”
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in each room, channel, or stream).
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We track these data in the backend in the `UserMessage` table, storing
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rows `(message_id, user_id, flags)`, where `flags` is 32 bits of space
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for boolean data like whether the user has read or starred the
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message. All the key queries needed for accessing message history,
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full-text search, and other key features can be done efficiently with
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the database indexes on this table (with joins to the `Message` table
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containing the actual message content where required).
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The downside of this design is that when a new message is sent to a
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stream with `N` recipients, we need to write `N` rows to the
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`UserMessage` table to record those users receiving those messages.
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Each row is just 3 integers in size, but even with modern databases
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and SSDs, writing thousands of rows to a database starts to take a few
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seconds.
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This isn’t a problem for most Zulip servers, but is a major problem
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for communities like chat.zulip.org, where might be 10,000s of
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inactive users who only stopped by briefly to check out the product or
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ask a single question, but are subscribed to whatever the default
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streams in the organization are.
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The total amount of work being done here was acceptable (a few seconds
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of total CPU work per message to large public streams), but the
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latency was unacceptable: The server backend was introducing a latency
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of about 1 second per 2000 users subscribed to receive the message.
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While these delays may not be immediately obvious to users (Zulip,
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like many other chat applications,
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[local echoes](../subsystems/markdown.md) messages that a user sends
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as soon as the user hits “send”), latency beyond a second or two
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significantly impacts the feeling of interactivity in a chat
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experience (i.e. it feels like everyone takes a long time to reply to
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even simple questions).
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A key insight for addressing this problem is that there isn’t much of
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a use case for long chat discussions among 1000s of users who are all
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continuously online and actively participating. Streams with a very
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large number of active users are likely to only be used for occasional
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announcements, where some latency before everyone sees the message is
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fine. Even in giant organizations, almost all messages are sent to
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smaller streams with dozens or hundreds of active users, representing
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some organizational unit within the community or company.
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However, large, active streams are common in open source projects,
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standards bodies, professional development groups, and other large
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communities with the rough structure of the Zulip development
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community. These communities usually have thousands of user accounts
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subscribed to all the default streams, even if they only have dozens
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or hundreds of those users active in any given month. Many of the
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other accounts may be from people who signed up just to check the
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community out, or who signed up to ask a few questions and may never
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be seen again.
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The key technical insight is that if we can make the latency scale
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with the number of users who actually participate in the community,
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not the total size of the community, then our database write limited
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send latency of 1 second per 2000 users is totally fine. But we need
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to do this in a way that doesn’t create problems if any of the
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thousands of “inactive” users come back (or one of the active users
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sends a private message to one of the inactive users), since it’s
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impossible for the software to know which users are eventually coming
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back or will eventually be interacted with by an existing user.
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We solved this problem with a solution we call “soft deactivation”;
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users that are soft-deactivated consume less resources from Zulip in a
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way that is designed to be invisible both to other users and to the
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user themself. If a user hasn’t logged into a given Zulip
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organization for a few weeks, they are tagged as soft-deactivated.
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The way this works internally is:
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* We (usually) skip creating UserMessage rows for soft-deactivated
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users when a message is sent to a stream where they are subscribed.
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* If/when the user ever returns to Zulip, we can at that time
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reconstruct the UserMessage rows that they missed, and create the rows
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at that time (or, to avoid a latency spike if/when the user returns to
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Zulip, this work can be done in a nightly cron job). We can construct
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those rows later because we already have the data for when the user
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might have been subscribed or unsubscribed from streams by other
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users, and, importantly, we also know that the user didn’t interact
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with the UI since the message was sent (and thus we can safely assume
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that the messages has not been marked a read by the user). This is
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done in the `add_missing_messages` function, which is the core of the
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soft-deactivation implementation.
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* The “usually” above is because there are a few flags that result
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from content in the message (e.g., a message that mentions a user
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results in a “mentioned” flag in the UserMessage row), that we need to
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keep track of. Since parsing a message can be expensive (>10ms of
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work, depending on message content), it would be too inefficient to
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need to re-parse every message when a soft-deactivated user comes back
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to Zulip. Conveniently, those messages are rare, and so we can just
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create UserMessage rows which would have “interesting” flags at the
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time they were sent without any material performance impact. And then
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`add_missing_messages` skips any messages that already have a
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`UserMessage` row for that user when doing its backfill.
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The end result is the best of both worlds:
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* Nobody's view of the world is different because the user was
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soft-deactivated (resulting in no visible user-experience impact), at
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least if one is running the cron job. If one does not run the cron
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job, then users returning after being away for a very long time will
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potentially have a (very) slow loading experience as potentially
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100,000s of UserMessage rows might need to be reconstructed at once.
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* On the latency-sensitive message sending and fanout code path, the
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server only needs to do work for users who are currently interacting
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with Zulip.
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Empirically, we've found this technique completely resolved the "send
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latency" scaling problem. The latency of sending a message to a stream
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now scales only with the number of active subscribers, so one can send
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a message to a stream with 5K subscribers of which 500 are active, and
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it’ll arrive in the couple hundred milliseconds one would expect if
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the extra 4500 inactive subscribers didn’t exist.
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There are a few details that require special care with this system:
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* Email and mobile push notifications. We need to make sure these are
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still correctly delivered to soft-deactivated users; making this
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work required careful work for those code paths that assumed a
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`UserMessage` row would always exist for a message that triggers a
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notification to a given user.
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* Digest emails, which use the `UserMessage` table extensively to
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determine what has happened in streams the user can see. We can use
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the user's subscriptions to construct what messages they should have
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access to for this feature.
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