[External] : Re: Should mapConcurrent() respect time order instead of input order?
Jige Yu
yujige at gmail.com
Wed Jun 4 14:20:41 UTC 2025
Hi Viktor,
Thank you for sharing that the general feedback on mapConcurrent() has been
positive and for the insights into the ongoing enhancements, especially
around interruption handling and work-in-progress tracking.
To clarify my own position, I am also extremely enthusiastic about the
mapConcurrent() API overall. It offers an elegant and straightforward way
to manage homogenous, I/O-intensive concurrent tasks within a structured
concurrency model, which is a significant improvement and a much-needed
addition. My feedback on ordering is aimed at maximizing its potential.
I'd like to elaborate on a few specific scenarios and expectations that
inform my perspective on the ordering:
1.
*Temptation for Race Semantics:* The beauty of mapConcurrent()
integrating with the Stream API means developers will naturally be drawn to
use it for race-like scenarios. Operations like findFirst() or limit(N)
to get the first few completed results are very intuitive combinations. For
example:
Java
// Hypothetical use case: find the fastest responding service
Optional<Result> fastestResult = serviceUrls.stream()
.gather(Gatherers.mapConcurrent(MAX_CONCURRENCY, url -> fetch(url)))
.findFirst();
2.
*Surprise for Race Semantics Users:* Following from the above, it could
be surprising for developers when they realize that the inherent input
ordering of mapConcurrent() means it's not optimized for these race
scenarios. The expectation would be that findFirst() returns as soon as
*any* task completes, but ordering can delay this if an earlier task (in
input order) is slower.
3.
*Ordering Assumption in Concurrency:* My experience is that ordering is
not typically a default assumption when dealing with operations explicitly
marked as "parallel" or "concurrent." For instance, Stream.forEach() on
a parallel stream does not guarantee encounter order, presumably for
performance reasons – a similar trade-off to what's being discussed for
mapConcurrent(). Developers often consult documentation for ordering
guarantees in concurrent contexts rather than assuming them.
4.
*Expectation of "True" Concurrency:* When I see an API like
mapConcurrent(maxConcurrency,
mapper), my mental model is that if maxConcurrency permits, new tasks
should be initiated as soon as a slot is free. For example, with
maxConcurrency=2:
- Task 1 starts.
- Task 2 starts.
- If Task 2 finishes while Task 1 is still running, I would expect
Task 3 to run concurrently alongside task 1, because the max
concurrency is
2, not 1. The current ordered behavior, where Task 3 might have
to wait for
Task 1 to complete before its result can be processed (even if Task 3
itself could have started and finished), can feel a bit
counterintuitive to
the notion of maximizing concurrency up to the specified limit. It almost
feels like not a "max concurrency", but "max buffer size".
These points are offered to highlight potential areas where the current
default could lead to subtle surprises or suboptimal performance for useful
concurrent patterns.
Thanks again for the open discussion and for your work on these valuable
additions to the JDK.
Best regards,
On Tue, Jun 3, 2025 at 2:13 AM Viktor Klang <viktor.klang at oracle.com> wrote:
> The general feedback received thus far has been primarily positive. There
> have been a few behavior-related enhancements over the previews to better
> handle interruption (there's still room to improve there, as per our
> concurrent conversation) as well as some improvements to work-in-progress
> tracking.
>
> It will be interesting to see which Gatherer-based operations will be
> devised by Java developers in the future.
>
> Cheers,
> √
>
>
> *Viktor Klang*
> Software Architect, Java Platform Group
> Oracle
> ------------------------------
> *From:* Jige Yu <yujige at gmail.com>
> *Sent:* Monday, 2 June 2025 18:54
> *To:* Viktor Klang <viktor.klang at oracle.com>
> *Cc:* core-libs-dev at openjdk.org <core-libs-dev at openjdk.org>
> *Subject:* Re: [External] : Re: Should mapConcurrent() respect time order
> instead of input order?
>
>
> Hi Viktor,
>
> Thanks for your reply and for sharing your experience regarding user
> preferences. I appreciate that perspective.
>
> You're right, if an unordered version of mapConcurrent proves to be
> widely beneficial and is implemented and adopted by the community, it could
> certainly make a strong case for future inclusion in the JDK.
>
> I wanted to clarify a nuance regarding user preference that I might not
> have articulated clearly before. If the question is simply "ordered or
> unordered?", in isolation, I can see why many, myself included, might lean
> towards "ordered" as a general preference.
>
> However, the decision becomes more complex when the associated trade-offs
> are considered. If the question were phrased more like, "Do you prefer an
> ordered mapConcurrent by default, even if it entails potential
> performance overhead and limitations for certain use cases like race()
> operations, versus an unordered version that offers higher throughput and
> broader applicability in such scenarios?" my (and perhaps others') answer
> might differ. The perceived cost versus benefit of ordering changes
> significantly when these factors are explicit.
>
> My initial suggestion stemmed from the belief that the performance and
> flexibility gains of an unordered approach for I/O-bound tasks would, in
> many practical situations, outweigh the convenience of default ordering,
> especially since ordering can be reintroduced relatively easily, and
> explicitly, when needed.
>
> Thanks again for the discussion.
>
> Best regards,
>
> On Mon, Jun 2, 2025 at 8:51 AM Viktor Klang <viktor.klang at oracle.com>
> wrote:
>
> >My perspective is that strict adherence to input order for
> mapConcurrent() might not be the most common or beneficial default
> behavior for users.
>
> If there is indeed a *majority* who would benefit from an unordered
> version of mapConcurrent (my experience is that the majority prefer
> ordered) then, since it is possible to implement such a Gatherer outside of
> the JDK, this is something which will be constructed, widely used, and
> someone will then propose to add something similar to the JDK.
>
> >While re-implementing the gatherer is a possibility, the existing
> implementation is non-trivial, and creating a custom, robust alternative
> represents a significant undertaking.
>
> The existing version needs to maintain order, which adds to the complexity
> of the implementation. Implementing an unordered version would likely look
> different.
> I'd definitely encourage taking the opportunity to attempt to implement it.
>
> Cheers,
> √
>
>
> *Viktor Klang*
> Software Architect, Java Platform Group
> Oracle
>
> ------------------------------
> *From:* Jige Yu <yujige at gmail.com>
> *Sent:* Monday, 2 June 2025 17:05
> *To:* Viktor Klang <viktor.klang at oracle.com>
> *Cc:* core-libs-dev at openjdk.org <core-libs-dev at openjdk.org>
> *Subject:* Re: [External] : Re: Should mapConcurrent() respect time order
> instead of input order?
>
>
> Thank you for your response and for considering my feedback on the
> mapConcurrent() gatherer. I understand and respect that the final
> decision rests with the JDK maintainers.
>
> I would like to offer a couple of further points for consideration. My
> perspective is that strict adherence to input order for mapConcurrent() might
> not be the most common or beneficial default behavior for users. I'd be
> very interested to see any research or data that suggests otherwise, as
> that would certainly inform my understanding.
>
> From my experience, a more common need is for higher throughput in
> I/O-intensive operations. The ability to support use cases like race()—where
> the first successfully completed operation determines the outcome—also
> seems like a valuable capability that is currently infeasible due to the
> ordering constraint.
>
> As I see it, if a developer specifically requires the input order to be
> preserved, this can be achieved with relative ease by applying a subsequent
> sorting operation. For instance:
>
> .gather(mapConcurrent(...))
> .sorted(Comparator.comparing(Result::getInputSequenceId))
>
> The primary challenge in these scenarios is typically the efficient
> fan-out and execution of concurrent tasks, not the subsequent sorting of
> results.
>
> Conversely, as you've noted, there isn't a straightforward way to modify
> the current default ordered behavior to achieve the higher throughput or
> race() semantics that an unordered approach would naturally provide.
>
> While re-implementing the gatherer is a possibility, the existing
> implementation is non-trivial, and creating a custom, robust alternative
> represents a significant undertaking. My hope was that an unordered option
> could be a valuable addition to the standard library, benefiting a wider
> range of developers.
>
> Thank you again for your time and consideration.
>
>
> On Mon, Jun 2, 2025 at 7:48 AM Viktor Klang <viktor.klang at oracle.com>
> wrote:
>
> >Even if it by default preserves input order, when I explicitly called
> stream.unordered(), could mapConcurrent() respect that and in return
> achieve higher throughput with support for race?
>
> The Gatherer doesn't know whether the Stream is unordered or ordered. The
> operation should be semantically equivalent anyway.
>
> Cheers,
> √
>
>
> *Viktor Klang*
> Software Architect, Java Platform Group
> Oracle
> ------------------------------
> *From:* Jige Yu <yujige at gmail.com>
> *Sent:* Monday, 2 June 2025 16:29
> *To:* Viktor Klang <viktor.klang at oracle.com>; core-libs-dev at openjdk.org <
> core-libs-dev at openjdk.org>
> *Subject:* [External] : Re: Should mapConcurrent() respect time order
> instead of input order?
>
> Sorry. Forgot to copy to the mailing list.
>
> On Mon, Jun 2, 2025 at 7:27 AM Jige Yu <yujige at gmail.com> wrote:
>
> Thanks Viktor!
>
> I was thinking from my own experience that I wouldn't have automatically
> assumed that a concurrent fanout library would by default preserve input
> order.
>
> And I think wanting high throughput with real-life utilities like race
> would be more commonly useful.
>
> But I could be wrong.
>
> Regardless, mapConcurrent() can do both, no?
>
> Even if it by default preserves input order, when I explicitly called
> stream.unordered(), could mapConcurrent() respect that and in return
> achieve higher throughput with support for race?
>
>
>
> On Mon, Jun 2, 2025 at 2:33 AM Viktor Klang <viktor.klang at oracle.com>
> wrote:
>
> Hi!
>
> In a similar vein to the built-in Collectors,
> the built-in Gatherers provide solutions to common stream-related
> problems, but also, they also serve as "inspiration" for developers for
> what is possible to implement using Gatherers.
>
> If someone, for performance reasons, and with a use-case which does not
> require encounter-order, want to take advantage of that combination of
> circumstances, it is definitely possible to implement your own Gatherer
> which has that behavior.
>
> Cheers,
> √
>
>
> *Viktor Klang*
> Software Architect, Java Platform Group
> Oracle
> ------------------------------
> *From:* core-libs-dev <core-libs-dev-retn at openjdk.org> on behalf of Jige
> Yu <yujige at gmail.com>
> *Sent:* Sunday, 1 June 2025 21:08
> *To:* core-libs-dev at openjdk.org <core-libs-dev at openjdk.org>
> *Subject:* Should mapConcurrent() respect time order instead of input
> order?
>
> It seems like for most people, input order isn't that important for
> concurrent work, and concurrent results being in non-deterministic order is
> often expected.
>
> If mapConcurrent() just respect output encounter order:
>
> It'll be able to achieve *higher throughput* if an early task is slow,
> For example, with concurrency=2, and if the first task takes 10 minutes to
> run, mapConcurrent() would only be able to process 2 tasks within the first
> 10 minutes; whereas with encounter order, the first task being slow doesn't
> block the 3rd - 100th elements from being processed and output.
>
> mapConcurrent() can be used to implement useful concurrent semantics, for
> example to *support race* semantics. Imagine if I need to send request to
> 10 candidate backends and take whichever that succeeds first, I'd be able
> to do:
>
> backends.stream()
> .gather(mapConcurrent(
> backend -> {
> try {
> return backend.fetchOrder();
> } catch (RpcException e) {
> return null; // failed to fetch but not fatal
> }
> })
> .filter(Objects::notNull)
> .findFirst(); // first success then cancel the rest
>
> Cheers,
>
>
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