feat(pyamber): preserve minus-one shuffle hashes

[carloea2]

What changes were proposed in this PR?

Hash shuffle now uses the tuple's raw Java-compatible hash method directly, avoiding Python's reserved -1 to -2 normalization before receiver selection.

Any related issues, documentation, discussions?

Closes #8253

How was this PR tested?

python -c "import sys,pytest; sys.path[:0]=[r'C:\Users\carlo\texera\texera-worktrees\investigate-bug63\amber\src\main\python',r'C:\Users\carlo\texera\texera\amber\src\main\python']; raise SystemExit(pytest.main(['amber/src/test/python/core/architecture/sendsemantics/test_partitioners.py','-q','-p','no:cacheprovider']))"
36 passed

ruff check amber/src/main/python amber/src/test/python
All checks passed

ruff format --check amber/src/main/python amber/src/test/python
213 files already formatted

Direct reproduction after the fix:

raw_java_hash=-1 builtin_hash=-2 receiver=B

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

Generated-by: Codex

[github-actions]

Automated Reviewer Suggestions

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

• Contributors with relevant context: @Ma77Ball, @Yicong-Huang
  You can notify them by mentioning @Ma77Ball, @Yicong-Huang 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/v1.3	Not labeled automatically — none of the files this PR modifies exist on this branch (amber/src/main/python/core/architecture/sendsemantics/hash_based_shuffle_partitioner.py, amber/src/test/python/core/architecture/sendsemantics/test_partitioners.py). The fix may target code that isn't on this release, or the files were moved/renamed after the branch was cut. Please check and add release/v1.3 by hand if this fix should be backported here.
✅ release/v1.2	Already labeled — this fix is queued to backport here.

Auto-label run.

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 93.90%. Comparing base (50321e4) to head (02bcf80).
⚠️ Report is 11 commits behind head on main.

Additional details and impacted files

@@             Coverage Diff              @@
##               main    #8254      +/-   ##
============================================
- Coverage     93.93%   93.90%   -0.04%     
+ Complexity     4762     4761       -1     
============================================
  Files          1191     1191              
  Lines         48308    49051     +743     
  Branches       5377     5377              
============================================
+ Hits          45380    46059     +679     
- Misses         1494     1557      +63     
- Partials       1434     1435       +1     

Flag	Coverage Δ		*Carryforward flag
access-control-service	81.00% <ø> (ø)		Carriedforward from 50321e4
agent-service	99.32% <ø> (ø)		Carriedforward from 50321e4
amber	90.02% <ø> (-0.02%)	⬇️	Carriedforward from 50321e4
computing-unit-managing-service	73.67% <ø> (ø)		Carriedforward from 50321e4
config-service	86.86% <ø> (ø)		Carriedforward from 50321e4
file-service	87.91% <ø> (ø)		Carriedforward from 50321e4
frontend	96.41% <ø> (ø)		Carriedforward from 50321e4
notebook-migration-service	79.31% <ø> (ø)		Carriedforward from 50321e4
pyamber	97.87% <100.00%> (-1.01%)	⬇️
workflow-compiling-service	77.19% <ø> (ø)		Carriedforward from 50321e4

*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 · 🔴 5 worse · ⚪ 10 noise (<±5%) · 0 without baseline

Compared against main 50321e4 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	548	0.335	17,599/22,605/22,605 us	🔴 +20.5% / 🔴 +45.1%
🔴	bs=100 sw=10 sl=64	1,216	0.742	80,009/110,340/110,340 us	🔴 +20.3% / 🟢 +20.6%
⚪	bs=1000 sw=10 sl=64	1,415	0.864	713,312/746,101/746,101 us	⚪ within ±5% / 🟢 +35.8%

Baseline details

Latest main 50321e4 from same runner

config	metric	PR	latest main	7d avg	Δ latest	Δ 7d
bs=10 sw=10 sl=64	throughput	548 tuples/sec	626 tuples/sec	787.98 tuples/sec	-12.5%	-30.5%
bs=10 sw=10 sl=64	MB/s	0.335 MB/s	0.382 MB/s	0.481 MB/s	-12.3%	-30.3%
bs=10 sw=10 sl=64	p50	17,599 us	14,609 us	12,593 us	+20.5%	+39.8%
bs=10 sw=10 sl=64	p95	22,605 us	22,524 us	15,579 us	+0.4%	+45.1%
bs=10 sw=10 sl=64	p99	22,605 us	22,524 us	18,786 us	+0.4%	+20.3%
bs=100 sw=10 sl=64	throughput	1,216 tuples/sec	1,227 tuples/sec	1,008 tuples/sec	-0.9%	+20.6%
bs=100 sw=10 sl=64	MB/s	0.742 MB/s	0.749 MB/s	0.615 MB/s	-0.9%	+20.6%
bs=100 sw=10 sl=64	p50	80,009 us	80,311 us	100,701 us	-0.4%	-20.5%
bs=100 sw=10 sl=64	p95	110,340 us	91,695 us	107,244 us	+20.3%	+2.9%
bs=100 sw=10 sl=64	p99	110,340 us	91,695 us	116,122 us	+20.3%	-5.0%
bs=1000 sw=10 sl=64	throughput	1,415 tuples/sec	1,428 tuples/sec	1,042 tuples/sec	-0.9%	+35.8%
bs=1000 sw=10 sl=64	MB/s	0.864 MB/s	0.872 MB/s	0.636 MB/s	-0.9%	+35.8%
bs=1000 sw=10 sl=64	p50	713,312 us	701,051 us	981,959 us	+1.7%	-27.4%
bs=1000 sw=10 sl=64	p95	746,101 us	735,365 us	1,023,080 us	+1.5%	-27.1%
bs=1000 sw=10 sl=64	p99	746,101 us	735,365 us	1,051,697 us	+1.5%	-29.1%

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
0,10,10,64,20,364.88,200,128000,548,0.335,17599.13,22604.67,22604.67
1,100,10,64,20,1644.71,2000,1280000,1216,0.742,80009.35,110339.80,110339.80
2,1000,10,64,20,14133.68,20000,12800000,1415,0.864,713311.75,746101.03,746101.03

[Yicong-Huang]

I am converting this PR to a draft: please follow our PR template and mark it ready for review.

[carloea2]

The description now follows the current template, and this is ready for review.