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https://issues.apache.org/jira/browse/GROOVY-12457?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18133306#comment-18133306
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ASF GitHub Bot commented on GROOVY-12457:
-----------------------------------------

daniellansun commented on PR #2986:
URL: https://github.com/apache/groovy/pull/2986#issuecomment-6457494125

   Thank you for the careful re-read — these are very helpful catches.
   
   I will address them on this PR as follows:
   
   1. **`grepParallel`** — fix both issues here: null-check only `self` so `[1, 
null, 2].grepParallel(null)` matches sequential `grep(null)`, and treat 
`isCase` results with Groovy truth (`castToBoolean`) so custom filters align 
with sequential `grep`.
   
   2. **`maxParallel` and nulls** — match sequential `max(Comparator)` (skip 
nulls; `[null, null]` without calling the comparator). I will keep 
`minParallel` matching sequential `min` as it already does, and make the 
asymmetry explicit in comments/docs so it does not diverge silently.
   
   3. **Per-element `Pool.withCurrent`** — given the light-callback cost you 
measured, I will move to a worker thread factory that carries the owning 
`Pool`, with `Pool.current()` falling back to the current worker’s pool, so 
nested calls stay on the pool without rebinding every element. I will include a 
JMH (or equivalent) number for a light workload with that approach.
   
   4. **Interrupt semantics** — add a short note to 
`core-parallel-collections.adoc` about executor-path interruption on 
short-circuit / sibling failure (and that it can close an 
`InterruptibleChannel`).
   
   5. **`groupInOrder`** — switch to `LinkedHashMap` so keys follow first-seen 
order like sequential `groupBy`.
   
   **Housekeeping:** I will update the JIRA description to match the current 
design (no compensation). On whether this should go to 6.0.x (and the 
null-handling release-notes entries), I will confirm shortly and follow up here.
   
   Thanks again for the detailed notes.




> Blocking parallel-collection callbacks can fail to run a queued sibling task
> ----------------------------------------------------------------------------
>
>                 Key: GROOVY-12457
>                 URL: https://issues.apache.org/jira/browse/GROOVY-12457
>             Project: Groovy
>          Issue Type: Bug
>            Reporter: Daniel Sun
>            Priority: Major
>
> h2. Context
> {{{}eachParallel{}}}, {{{}collectParallel{}}}, and the other parallel 
> collection methods run their callback on a {{{}ForkJoinPool{}}}: the pool 
> bound by {{{}ParallelScope.withPool{}}}, or {{ForkJoinPool.commonPool()}} 
> when no pool is bound. {{@Parallel}} {{for-in}} loops are rewritten to call 
> {{{}eachParallel{}}}. The methods arrived with GROOVY-11952 
> ([GEP-18|https://groovy.apache.org/wiki/GEP-18.html]).
> A pool of size {{n}} is the intended way to run {{n}} callbacks that block at 
> the same time.
> h2. Problem
> This rendezvous fails intermittently, including when the pool size equals the 
> number of parties:
> {code:groovy}
> import groovy.concurrent.ParallelScope
> import java.util.concurrent.CyclicBarrier
> import java.util.concurrent.TimeUnit
> int parties = 2
> ParallelScope.withPool(parties) { scope ->
>     def barrier = new CyclicBarrier(parties)
>     (1..parties).eachParallel {
>         barrier.await(5, TimeUnit.SECONDS)
>     }
> }
> {code}
> {{CyclicBarrier.await}} throws {{TimeoutException}} because the second 
> element never starts. The failure is reported as a nested 
> {{{}UndeclaredThrowableException{}}}:
> ||Layer||What the caller sees||
> |Closure|{{TimeoutException}} from {{CyclicBarrier.await}}|
> |{{Consumer}} proxy|{{{}UndeclaredThrowableException{}}}, because {{accept}} 
> does not declare checked exceptions|
> |{{ForkJoinTask.getThrowableException}}|A second 
> {{{}UndeclaredThrowableException{}}}, rebuilt on the joining thread|
> The same shape fails for {{@Parallel}} {{{}for (item in 1..n){}}}. It shows 
> up more often once the pool's workers have already run and parked. A freshly 
> created pool can fail as well.
> h2. Cause
> {{parallelStream()}} forks the sibling leaf onto the current worker's queue, 
> then runs one leaf on that same worker. {{CyclicBarrier.await}} is not a 
> {{{}ForkJoinPool.ManagedBlocker{}}}, so the pool does not release or replace 
> the blocked worker. If the other worker has already scanned and parked, the 
> fork signal is not always delivered again. The sibling stays on the queue 
> until the barrier times out.
> Sizing the pool to exactly {{n}} threads does not close the race. The idle 
> thread is there; it is parked.
> h2. Change
> The proposed change runs the user callback inside 
> {{ForkJoinPool.managedBlock}} when the current worker still has queued tasks. 
> That releases a parked worker, or creates a spare, before the callback can 
> block. A leaf whose queue is empty is unchanged.
>  * JDK 20 and later read {{{}ForkJoinWorkerThread.getQueuedTaskCount(){}}}.
>  * JDK 17 does not have that method, so the check uses the pool-wide 
> queued-task estimate.
> The wrapper covers every parallel-collection callback, including 
> {{eachWithIndexParallel}} and the {{eachParallel}} call emitted for 
> {{{}@Parallel{}}}.
> Compensation runs only when a sibling is already queued. A callback that 
> blocks before any sibling has been forked can still stall, and so can a pool 
> that refuses another thread. Work that spends most of its time waiting still 
> fits {{Pool.io()}} or {{Pool.virtual()}} better than a fixed 
> {{{}ForkJoinPool{}}}.
> h2. Tests
>  * {{ParallelCollectionTest}} and {{ParallelAnnotationTest}} repeat the 
> two-party barrier on one pool, so later rounds run against workers parked by 
> the first round. The barrier must trip.
>  * The thread-count assertion allows a spare ({{{}size() >= parties{}}}), 
> because {{managedBlock}} may add one while a worker is blocked.
>  * The full two test classes passed on JDK 25. The three barrier tests also 
> passed on JDK 17, which exercises the queue-length fallback.



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