aglinxinyuan opened a new pull request, #6884:
URL: https://github.com/apache/texera/pull/6884

   ### What changes were proposed in this PR?
   
   `LoopIntegrationSpec` costs **~4m16s of the ~6-minute `amber-integration` 
test step (~70%)** on every PR. The cost tracks worker spawns almost perfectly 
(~2s per Python worker boot + Flight handshake; 132 spawns across the suite), 
because every loop iteration respawns each worker in the re-executed regions:
   
   | Test | Time | Worker spawns (py + jvm) |
   |---|---:|---:|
   | single loop (Python-only) | 17s | 6 + 1 |
   | nested 3×3 (Python-only) | 63s | 24 + 1 |
   | single + Limit | 19s | 6 + 4 |
   | nested + Limit | 64s | 24 + 10 |
   | nested + chain (Limit→Sleep) | 72s | 24 + 19 |
   | single + chain | 21s | 6 + 7 |
   
   Two cases are **strict subsets** of the nested-chain case, which already 
covers nested routing, counter magnitude across JVM hops, the JVM→JVM state 
handoff, and both operator kinds in one workflow:
   
   - `nested + Limit` (~64s) — nested × Limit ⊂ nested × (Limit → Sleep)
   - `single + chain` (~21s) — chain ⊂ nested chain
   
   This PR removes those two, saving **~85s (~33% of the loop suite)** with no 
unique coverage lost. Retained matrix: Python-only single (base), Python-only 
nested (pins the no-JVM path), single + Limit (verbatim repro of the #6660 
bug), nested + chain (superset JVM case). The subsumption reasoning is recorded 
in the retained test's comment so the cases don't get re-added.
   
   The deeper fix (reusing workers across loop iterations instead of 
respawn-per-jump) is an engine design change and out of scope here.
   
   ### Any related issues, documentation, discussions?
   
   Follow-up to #6661 (which introduced the JVM loop-body cases). Related 
engine context: #6660.
   
   ### How was this PR tested?
   
   Test-only change (removes two e2e cases; no source touched). 
`WorkflowExecutionService/Test/compile` + `scalafmtCheckAll` + `scalafixAll 
--check` pass locally (Java 17); the remaining suite runs in the 
`amber-integration` CI job on this PR.
   
   ### Was this PR authored or co-authored using generative AI tooling?
   
   Generated-by: Claude Code (Fable 5)
   


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