This proposal seeks to define an approach to user-controlled cancellation of asynchronous operations through the adoption of a set of native platform objects.
Stage: 1
Champion: Ron Buckton (@rbuckton), Brian Terlson (@bterlson), Domenic Denicola (@domenic), Yehuda Katz (@wycats)
For more information see the TC39 proposal process.
NOTE: TC39 has decided to investigate a cancellation mechanism in the core library. As such, Cancellation has moved to Stage 1, but not in the form of the previous Stage 0 proposal. Instead, TC39 believes this is a space that requires further investigation and discussion. The previous Stage 0 proposal can be found here.
- Ron Buckton (@rbuckton)
- A clear and consistent approach to cancelling asynchronous operations:
- Asynchronous functions or iterators
- Fetching remote resources (HTTP, I/O, etc.)
- Interacting with background tasks (Web Workers, forked processes, etc.)
- Long-running operations (animations, etc.)
- A general-purpose coordination mechanism with many use cases:
- Synchronous observation (e.g. in a game loop)
- Asynchronous observation (e.g. aborting an XMLHttpRequest, stopping an animation)
- Easy to use in async functions.
- A common API that is reusable in multiple host environments (Browser, NodeJS, IoT/embedded, etc.).
- Cancellation in Managed Threads in the .NET Framework
The following are some architectural observations provided by Dean Tribble on the es-discuss mailing list:
Cancel requests, not results
Promises are like object references for async; any particular promise might be returned or passed to more than one client. Usually, programmers would be surprised if a returned or passed in reference just got ripped out from under them by another client. this is especially obvious when considering a library that gets a promise passed into it. Using "cancel" on the promise is like having delete on object references; it's dangerous to use, and unreliable to have used by others.Cancellation is heterogeneous
It can be misleading to think about canceling a single activity. In most systems, when cancellation happens, many unrelated tasks may need to be cancelled for the same reason. For example, if a user hits a stop button on a large incremental query after they see the first few results, what should happen?
- the async fetch of more query results should be terminated and the connection closed
- background computation to process the remote results into renderable form should be stopped
- rendering of not-yet rendered content should be stopped. this might include retrieval of secondary content for the items no longer of interest (e.g., album covers for the songs found by a complicated content search)
- the animation of "loading more" should be stopped, and should be replaced with "user cancelled"
- etc.
Some of these are different levels of abstraction, and for any non-trivial application, there isn't a single piece of code that can know to terminate all these activities. This kind of system also requires that cancellation support is consistent across many very different types of components. But if each activity takes a cancellationToken, in the above example, they just get passed the one that would be cancelled if the user hits stop and the right thing happens.
Cancellation should be smart
Libraries can and should be smart about how they cancel. In the case of an async query, once the result of a query from the server has come back, it may make sense to finish parsing and caching it rather than just reflexively discarding it. In the case of a brokerage system, for example, the round trip to the servers to get recent data is the expensive part. Once that's been kicked off and a result is coming back, having it available in a local cache in case the user asks again is efficient. If the application spawned another worker, it may be more efficient to let the worker complete (so that you can reuse it) rather than abruptly terminate it (requiring discarding of the running worker and cached state).Cancellation is a race
In an async system, new activities may be getting continuously scheduled by asks that are themselves scheduled but not currently running. The act of cancelling needs to run in this environment. When cancel starts, you can think of it as a signal racing out to catch up with all the computations launched to achieve the now-cancelled objective. Some of those may choose to complete (see the caching example above). Some may potentially keep launching more work before that work itself gets signaled (yeah it's a bug but people write buggy code). In an async system, cancellation is not prompt. Thus, it's infeasible to ask "has cancellation finished?" because that's not a well defined state. Indeed, there can be code scheduled that should and does not get cancelled (e.g., the result processor for a pub/sub system), but that schedules work that will be cancelled (parse the publication of an update to the now-cancelled query).Cancellation is "don't care"
Because smart cancellation sometimes doesn't stop anything and in an async environment, cancellation is racing with progress, it is at most "best efforts". When a set of computations are cancelled, the party canceling the activities is saying "I no longer care whether this completes". That is importantly different from saying "I want to prevent this from completing". The former is broadly usable resource reduction. The latter is only usefully achieved in systems with expensive engineering around atomicity and transactions. It was amazing how much simpler cancellation logic becomes when it's "don't care".Cancellation requires separation of concerns
In the pattern where more than one thing gets cancelled, the source of the cancellation is rarely one of the things to be cancelled. It would be a surprise if a library called for a cancellable activity (load this image) cancelled an unrelated server query just because they cared about the same cancellation event. I find it interesting that the separation between cancellation token and cancellation source mirrors that separation between a promise and it's resolver.Cancellation recovery is transient
As a task progresses, the cleanup action may change. In the example above, if the data table requests more results upon scrolling, it's cancellation behavior when there's an outstanding query for more data is likely to be quite different than when it's got everything it needs displayed for the current page. That's the reason why the "register" method returns a capability to unregister the action.
The following is a high-level list of tasks to progress through each stage of the TC39 proposal process:
- Identified a "champion" who will advance the addition.
- Prose outlining the problem or need and the general shape of a solution.
- Illustrative examples of usage.
- High-level [API][API].
- Initial specification text.
- Optional. Transpiler support (for syntax) or Polyfill (for API).
- Complete specification text.
- Designated reviewers have signed off on the current spec text.
- The ECMAScript editor has signed off on the current spec text.
- Test262 acceptance tests have been written for mainline usage scenarios and merged.
- Two compatible implementations which pass the acceptance tests: [1], [2].
- A pull request has been sent to tc39/ecma262 with the integrated spec text.
- The ECMAScript editor has signed off on the pull request.