chore(workflow-operator): remove the unused ProgressiveUtils

[aglinxinyuan]

What changes were proposed in this PR?

Deletes ProgressiveUtils and its spec — the insert/retract flag helper for the old progressive-sink path, whose consumers were removed long ago. Pure deletion, no behaviour change: −282 lines.

All four public methods (addInsertionFlag, addRetractionFlag, isInsertion, getTupleFlagAndValue) have no caller outside the object's own spec. The marker attribute the helper is built around, __internal_is_insertion, appears nowhere else in the repository — no operator, no storage reader, no frontend code, no test fixture. Nothing produces or consumes tuples carrying that flag, so the helper is unreachable even indirectly.

Reviewer note: it acquired unit tests during the 2026 coverage work, which is why it currently looks live. The spec covers this object and nothing else, so it goes with it.

Any related issues, documentation, discussions?

Closes #7616

How was this PR tested?

Existing tests only — this PR adds none, since it removes code and the spec that covered it.

Locally, from the repo root with Java 17:

• sbt "WorkflowExecutionService/Test/compile" — success (main and test sources).

Verification, re-runnable by a reviewer:

git grep -n ProgressiveUtils           # only the two deleted files
git grep -n __internal_is_insertion    # only the two deleted files

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

Generated-by: Claude Code (Claude Opus 5)

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Automated Reviewer Suggestions

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

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[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 87.87%. Comparing base (dd7d813) to head (1cb553c).
⚠️ Report is 6 commits behind head on main.
✅ All tests successful. No failed tests found.

Additional details and impacted files

@@             Coverage Diff              @@
##               main    #7619      +/-   ##
============================================
- Coverage     88.96%   87.87%   -1.09%     
- Complexity     4338     4340       +2     
============================================
  Files          1178     1175       -3     
  Lines         46835    46728     -107     
  Branches       5226     5191      -35     
============================================
- Hits          41667    41063     -604     
- Misses         3422     3911     +489     
- Partials       1746     1754       +8     

Flag	Coverage Δ		*Carryforward flag
access-control-service	70.00% <ø> (ø)
agent-service	89.01% <ø> (-9.61%)	⬇️	Carriedforward from a7f4386
amber	84.89% <ø> (+<0.01%)	⬆️
computing-unit-managing-service	60.38% <ø> (ø)
config-service	77.31% <ø> (ø)
file-service	68.90% <ø> (ø)
frontend	89.52% <ø> (-1.06%)	⬇️	Carriedforward from a7f4386
notebook-migration-service	78.89% <ø> (ø)
pyamber	97.50% <ø> (-0.02%)	⬇️	Carriedforward from a7f4386
workflow-compiling-service	57.89% <ø> (ø)

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

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⚠️ Benchmark changes need a look

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

Compared against main dd7d813 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	375	0.229	25,301/37,649/37,649 us	🔴 +8.6% / 🔴 +130.8%
🔴	bs=100 sw=10 sl=64	764	0.467	128,495/175,173/175,173 us	🔴 +10.8% / 🔴 +61.9%
🔴	bs=1000 sw=10 sl=64	900	0.549	1,115,187/1,210,366/1,210,366 us	🔴 +5.9% / 🔴 +16.1%

Baseline details

Latest main dd7d813 from same runner

config	metric	PR	latest main	7d avg	Δ latest	Δ 7d
bs=10 sw=10 sl=64	throughput	375 tuples/sec	395 tuples/sec	775.33 tuples/sec	-5.1%	-51.6%
bs=10 sw=10 sl=64	MB/s	0.229 MB/s	0.241 MB/s	0.473 MB/s	-5.0%	-51.6%
bs=10 sw=10 sl=64	p50	25,301 us	23,290 us	12,743 us	+8.6%	+98.6%
bs=10 sw=10 sl=64	p95	37,649 us	35,996 us	16,310 us	+4.6%	+130.8%
bs=10 sw=10 sl=64	p99	37,649 us	35,996 us	18,926 us	+4.6%	+98.9%
bs=100 sw=10 sl=64	throughput	764 tuples/sec	813 tuples/sec	1,001 tuples/sec	-6.0%	-23.7%
bs=100 sw=10 sl=64	MB/s	0.467 MB/s	0.496 MB/s	0.611 MB/s	-5.8%	-23.5%
bs=100 sw=10 sl=64	p50	128,495 us	120,713 us	101,399 us	+6.4%	+26.7%
bs=100 sw=10 sl=64	p95	175,173 us	158,058 us	108,206 us	+10.8%	+61.9%
bs=100 sw=10 sl=64	p99	175,173 us	158,058 us	118,195 us	+10.8%	+48.2%
bs=1000 sw=10 sl=64	throughput	900 tuples/sec	906 tuples/sec	1,026 tuples/sec	-0.7%	-12.3%
bs=1000 sw=10 sl=64	MB/s	0.549 MB/s	0.553 MB/s	0.626 MB/s	-0.7%	-12.4%
bs=1000 sw=10 sl=64	p50	1,115,187 us	1,096,765 us	996,304 us	+1.7%	+11.9%
bs=1000 sw=10 sl=64	p95	1,210,366 us	1,142,562 us	1,042,531 us	+5.9%	+16.1%
bs=1000 sw=10 sl=64	p99	1,210,366 us	1,142,562 us	1,074,934 us	+5.9%	+12.6%

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
0,10,10,64,20,533.50,200,128000,375,0.229,25300.52,37648.54,37648.54
1,100,10,64,20,2616.35,2000,1280000,764,0.467,128494.87,175172.66,175172.66
2,1000,10,64,20,22225.50,20000,12800000,900,0.549,1115187.31,1210365.85,1210365.85