fix(pyamber): add_sub_queue replaces existing sub-queue instead of using putIfAbsent semantics

[Musxeto]

What changes were proposed in this PR?

LinkedBlockingMultiQueue.add_sub_queue diverged from the upstream Java
LinkedBlockingMultiQueue 0.6.0 it ports. The Java implementation registers
sub-queues with subQueues.putIfAbsent(key, subQueue), which leaves the map
untouched when the key already exists. The Python port unconditionally
overwrote self.sub_queues[key] with a freshly constructed SubQueue before
checking whether the key was already present.

On a repeated key the method still returned the old SubQueue (matching its
docstring), but an unattached replacement (priority_group = None) had
already been installed in the map. The failure chain:

Before: add_sub_queue("k") called twice → orphan SubQueue in map (priority_group = None)
After:  put("k", item) → total_count incremented, blocked get() woken
        → get_next() walks priority_groups, finds no non-empty group, returns None
        → None.dequeue() → AttributeError while holding take_lock

The fix: early-return from add_sub_queue when the key is already registered,
leaving the map and all priority groups untouched. The SubQueue object is
now constructed only when the key is absent, matching upstream Java semantics.

Any related issues, documentation, discussions?

Closes #7810

Related to the same family of port divergences as #6903, found during review
of #6906.

How was this PR tested?

Added TestAddSubQueue to
amber/src/test/python/core/util/customized_queue/test_linked_blocking_multi_queue.py
with 5 tests written red-first (TDD):

• test_new_key_returns_none — positive path: first registration returns None
• test_repeated_key_returns_existing_sub_queue — duplicate call returns the original object
• test_repeated_key_keeps_existing_queue_in_map — map still holds the original after a second add
• test_repeated_key_priority_group_is_not_none — priority_group is not None after a duplicate add
• test_repeated_key_put_then_get_does_not_crash — exact reproduction from the issue: no AttributeError

All 47 tests (5 new + 42 pre-existing) pass with no regressions:

pytest src/test/python/core/util/customized_queue/test_linked_blocking_multi_queue.py -v
# 47 passed in 3.64s

Was this PR authored or co-authored using generative AI tooling?

Generated-by: Antigravity (Google DeepMind), powered by Claude Sonnet 4.6

[github-actions]

Automated Reviewer Suggestions

Based on the git blame history of the changed files, we recommend the following reviewers:

• Contributors with relevant context: @mengw15
  You can notify them by mentioning @mengw15 in a comment.

[github-actions]

Backport auto-label report

This fix: PR was checked against each actively-supported release branch. release/* labels drive the post-merge backport, so add or remove one to change where this fix lands.

Release branch	Analysis
✅ release/v1.2	Already labeled — this fix is queued to backport here.

Auto-label run.

[github-actions]

⚠️ Benchmark changes need a look

🟢 2 better · 🔴 2 worse · ⚪ 11 noise (<±5%) · 0 without baseline

Compared against main b7c33b0 benchmarked on this same runner, so the delta is largely free of cross-runner hardware noise. The "7d avg" column still reflects the gh-pages dashboard. Treat <±5% as noise unless repeated.

Dashboard · Run

	config	throughput	MB/s	latency	max Δ latest / 7d
🔴	bs=10 sw=10 sl=64	371	0.226	26,679/37,591/37,591 us	🔴 +20.7% / 🔴 +161.4%
🔴	bs=100 sw=10 sl=64	798	0.487	125,730/143,366/143,366 us	🟢 -14.0% / 🔴 +44.0%
⚪	bs=1000 sw=10 sl=64	927	0.566	1,083,659/1,115,887/1,115,887 us	⚪ within ±5% / 🔴 +19.2%

Baseline details

Latest main b7c33b0 from same runner

config	metric	PR	latest main	7d avg	Δ latest	Δ 7d
bs=10 sw=10 sl=64	throughput	371 tuples/sec	384 tuples/sec	833.79 tuples/sec	-3.4%	-55.5%
bs=10 sw=10 sl=64	MB/s	0.226 MB/s	0.234 MB/s	0.509 MB/s	-3.4%	-55.6%
bs=10 sw=10 sl=64	p50	26,679 us	22,112 us	11,864 us	+20.7%	+124.9%
bs=10 sw=10 sl=64	p95	37,591 us	36,531 us	14,381 us	+2.9%	+161.4%
bs=10 sw=10 sl=64	p99	37,591 us	36,531 us	18,035 us	+2.9%	+108.4%
bs=100 sw=10 sl=64	throughput	798 tuples/sec	823 tuples/sec	1,083 tuples/sec	-3.0%	-26.3%
bs=100 sw=10 sl=64	MB/s	0.487 MB/s	0.502 MB/s	0.661 MB/s	-3.0%	-26.4%
bs=100 sw=10 sl=64	p50	125,730 us	116,626 us	93,077 us	+7.8%	+35.1%
bs=100 sw=10 sl=64	p95	143,366 us	166,783 us	99,553 us	-14.0%	+44.0%
bs=100 sw=10 sl=64	p99	143,366 us	166,783 us	108,604 us	-14.0%	+32.0%
bs=1000 sw=10 sl=64	throughput	927 tuples/sec	925 tuples/sec	1,119 tuples/sec	+0.2%	-17.1%
bs=1000 sw=10 sl=64	MB/s	0.566 MB/s	0.565 MB/s	0.683 MB/s	+0.2%	-17.1%
bs=1000 sw=10 sl=64	p50	1,083,659 us	1,074,248 us	909,247 us	+0.9%	+19.2%
bs=1000 sw=10 sl=64	p95	1,115,887 us	1,128,446 us	952,561 us	-1.1%	+17.1%
bs=1000 sw=10 sl=64	p99	1,115,887 us	1,128,446 us	985,186 us	-1.1%	+13.3%

Raw CSV

config_idx,batch_size,schema_width,string_len,num_batches,total_ms,total_tuples,total_bytes,tuples_per_sec,mb_per_sec,lat_p50_us,lat_p95_us,lat_p99_us
0,10,10,64,20,539.73,200,128000,371,0.226,26678.79,37591.14,37591.14
1,100,10,64,20,2505.24,2000,1280000,798,0.487,125729.80,143366.24,143366.24
2,1000,10,64,20,21566.07,20000,12800000,927,0.566,1083658.56,1115887.48,1115887.48

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 91.88%. Comparing base (b7c33b0) to head (a11b35c).

Additional details and impacted files

@@            Coverage Diff             @@
##               main    #7850    +/-   ##
==========================================
  Coverage     91.87%   91.88%            
  Complexity     4510     4510            
==========================================
  Files          1173     1173            
  Lines         47350    48067   +717     
  Branches       5306     5306            
==========================================
+ Hits          43502    44165   +663     
- Misses         2204     2258    +54     
  Partials       1644     1644            

Flag	Coverage Δ		*Carryforward flag
access-control-service	81.00% <ø> (ø)		Carriedforward from b7c33b0
agent-service	98.62% <ø> (ø)		Carriedforward from b7c33b0
amber	88.38% <ø> (ø)		Carriedforward from b7c33b0
computing-unit-managing-service	73.67% <ø> (ø)		Carriedforward from b7c33b0
config-service	86.73% <ø> (ø)		Carriedforward from b7c33b0
file-service	75.74% <ø> (ø)		Carriedforward from b7c33b0
frontend	93.79% <ø> (ø)		Carriedforward from b7c33b0
notebook-migration-service	79.13% <ø> (ø)		Carriedforward from b7c33b0
pyamber	96.88% <100.00%> (-0.69%)	⬇️
workflow-compiling-service	77.19% <ø> (ø)		Carriedforward from b7c33b0

*This pull request uses carry forward flags. Click here to find out more.

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