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Cancellation architectural observations

From: Dean Tribble <tribble@e-dean.com>
Date: Sun, 1 Mar 2015 23:06:32 -0800
Message-ID: <CAPM7YNtRODcgD0RuUdZcqOQtymV2bZRqizR87dMg9NO_RRyLqA@mail.gmail.com>
To: "public-script-coord@w3.org" <public-script-coord@w3.org>, es-discuss <es-discuss@mozilla.org>
Another thread here brought up the challenge of supporting cancellation in
an async environment. I spent some time on that particular challenge a few
years ago, and it turned out to be bigger and more interesting than it
appeared on the surface. In the another thread, Ron Buckton pointed at the
..Net approach and it's use in JavaScript:


> AsyncJS (http://github.com/rbuckton/asyncjs) uses a separate abstraction
> for cancellation based on the .NET
> CancellationTokenSource/CancellationToken types. You can find more
> information about this abstraction in the MSDN documentation here:
> https://msdn.microsoft.com/en-us/library/dd997364(v=vs.110).aspx
>

It's great that asyncjs already has started using it. I was surprised at
how well the cancellationToken approach worked in both small applications
and when extended to a very large async system. I'll summarize some of the
architectural observations, especially from extending it to async:

*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.


I don't want to derail the other threads on the topic, but thought it
useful to start articulating some of the architectural background for a
consistent async cancellation architecture.
Received on Monday, 2 March 2015 09:32:51 UTC

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