[aglinxinyuan]

What changes were proposed in this PR?

Removes the unused @value.setter on AtomicInteger in amber/src/main/python/core/util/atomic.py:48-52. Callers across the engine mutate the atomic value strictly via atomic methods (inc, dec, get_and_inc, get_and_dec, get_and_set) and read via the property getter (.value), leaving the setter unused. The corresponding unit test in test_atomic.py is updated to verify value is a read-only property (AttributeError on assignment).

+3/-11 lines. Pure deletion of dead setter and regression test update.

Any related issues, documentation, discussions?

Closes #9188.

How was this PR tested?

• python -m py_compile amber/src/main/python/core/util/atomic.py
• python -m pytest amber/src/test/python/core/util/test_atomic.py (11 passed)
• Verified 0 callers repo-wide:
  git grep -nw "AtomicInteger" | grep -v test shows only .inc(), .dec(), .get_and_inc(), .get_and_dec(), .get_and_set(), .value (getter).

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

Generated-by: Antigravity (Claude Opus 5.5)

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[github-actions]

Automated Reviewer Suggestions

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

• Contributors with relevant context: @nathant27, @mengw15
  You can notify them by mentioning @nathant27, @mengw15 in a comment.

[kunwp1]

LGTM!

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 91.96%. Comparing base (6659eec) to head (0448e95).
✅ All tests successful. No failed tests found.

Additional details and impacted files

@@             Coverage Diff              @@
##               main    #9189      +/-   ##
============================================
- Coverage     91.98%   91.96%   -0.02%     
+ Complexity     5084     5083       -1     
============================================
  Files          1281     1281              
  Lines         55812    55712     -100     
  Branches       7076     7067       -9     
============================================
- Hits          51337    51238      -99     
+ Misses         2734     2731       -3     
- Partials       1741     1743       +2     

Flag	Coverage Δ		*Carryforward flag
access-control-service	77.44% <ø> (ø)		Carriedforward from 0f1df22
agent-service	99.16% <ø> (ø)		Carriedforward from 0f1df22
amber	86.36% <ø> (-0.08%)	⬇️	Carriedforward from 0f1df22
computing-unit-managing-service	63.52% <ø> (ø)		Carriedforward from 0f1df22
config-service	87.50% <ø> (ø)		Carriedforward from 0f1df22
file-service	82.29% <ø> (ø)		Carriedforward from 0f1df22
frontend	96.53% <ø> (-0.01%)	⬇️	Carriedforward from 0f1df22
notebook-migration-service	83.77% <ø> (ø)		Carriedforward from 0f1df22
pyamber	98.54% <ø> (+0.06%)	⬆️
workflow-compiling-service	74.25% <ø> (ø)		Carriedforward from 0f1df22

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

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[github-actions]

⚠️ Benchmark changes need a look

🟢 0 better · 🔴 6 worse · ⚪ 9 noise (<±5%) · 0 without baseline

Compared against main 6659eec 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	559	0.341	17,758/21,994/21,994 us	🔴 +10.7% / 🔴 +61.6%
🔴	bs=100 sw=10 sl=64	1,195	0.73	83,079/97,495/97,495 us	🔴 +11.6% / 🟢 -12.3%
⚪	bs=1000 sw=10 sl=64	1,404	0.857	707,731/771,993/771,993 us	⚪ within ±5% / 🟢 -15.9%

Baseline details

Latest main 6659eec from same runner

config	metric	PR	latest main	7d avg	Δ latest	Δ 7d
bs=10 sw=10 sl=64	throughput	559 tuples/sec	620 tuples/sec	941.58 tuples/sec	-9.8%	-40.6%
bs=10 sw=10 sl=64	MB/s	0.341 MB/s	0.378 MB/s	0.575 MB/s	-9.8%	-40.7%
bs=10 sw=10 sl=64	p50	17,758 us	16,041 us	10,991 us	+10.7%	+61.6%
bs=10 sw=10 sl=64	p95	21,994 us	22,842 us	13,776 us	-3.7%	+59.7%
bs=10 sw=10 sl=64	p99	21,994 us	22,842 us	16,872 us	-3.7%	+30.4%
bs=100 sw=10 sl=64	throughput	1,195 tuples/sec	1,313 tuples/sec	1,264 tuples/sec	-9.0%	-5.5%
bs=100 sw=10 sl=64	MB/s	0.73 MB/s	0.801 MB/s	0.772 MB/s	-8.9%	-5.4%
bs=100 sw=10 sl=64	p50	83,079 us	74,449 us	86,073 us	+11.6%	-3.5%
bs=100 sw=10 sl=64	p95	97,495 us	99,073 us	93,135 us	-1.6%	+4.7%
bs=100 sw=10 sl=64	p99	97,495 us	99,073 us	111,124 us	-1.6%	-12.3%
bs=1000 sw=10 sl=64	throughput	1,404 tuples/sec	1,423 tuples/sec	1,304 tuples/sec	-1.3%	+7.6%
bs=1000 sw=10 sl=64	MB/s	0.857 MB/s	0.869 MB/s	0.796 MB/s	-1.4%	+7.7%
bs=1000 sw=10 sl=64	p50	707,731 us	705,462 us	841,986 us	+0.3%	-15.9%
bs=1000 sw=10 sl=64	p95	771,993 us	736,705 us	881,107 us	+4.8%	-12.4%
bs=1000 sw=10 sl=64	p99	771,993 us	736,705 us	918,208 us	+4.8%	-15.9%

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
0,10,10,64,20,357.95,200,128000,559,0.341,17758.24,21994.45,21994.45
1,100,10,64,20,1673.23,2000,1280000,1195,0.730,83078.88,97495.42,97495.42
2,1000,10,64,20,14247.39,20000,12800000,1404,0.857,707731.23,771993.16,771993.16