>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 <yuj...@gmail.com> Sent: Monday, 2 June 2025 17:05 To: Viktor Klang <viktor.kl...@oracle.com> Cc: core-libs-dev@openjdk.org <core-libs-dev@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.kl...@oracle.com<mailto:viktor.kl...@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 <yuj...@gmail.com<mailto:yuj...@gmail.com>> Sent: Monday, 2 June 2025 16:29 To: Viktor Klang <viktor.kl...@oracle.com<mailto:viktor.kl...@oracle.com>>; core-libs-dev@openjdk.org<mailto:core-libs-dev@openjdk.org> <core-libs-dev@openjdk.org<mailto:core-libs-dev@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 <yuj...@gmail.com<mailto:yuj...@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.kl...@oracle.com<mailto:viktor.kl...@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-r...@openjdk.org<mailto:core-libs-dev-r...@openjdk.org>> on behalf of Jige Yu <yuj...@gmail.com<mailto:yuj...@gmail.com>> Sent: Sunday, 1 June 2025 21:08 To: core-libs-dev@openjdk.org<mailto:core-libs-dev@openjdk.org> <core-libs-dev@openjdk.org<mailto:core-libs-dev@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,
