test(workflow-operator): add unit test coverage for operator metadata types (OperatorInfo, PortDescription, PortDescriptor)

[aglinxinyuan]

What changes were proposed in this PR?

Pin behavior of three core operator-metadata types in common/workflow-operator/ — the data/trait types every LogicalOp relies on for port wiring and metadata. No production-code changes.

Spec	Source class	Tests
OperatorInfoSpec	OperatorInfo (case class)	4
PortDescriptionSpec	PortDescription (case class)	5
PortDescriptorSpec	PortDescriptor (trait)	2

Behavior pinned

Surface	Contract
OperatorInfo fields	constructor field exposure; the four boolean flags default to false and round-trip true when set; value equality
OperatorInfo.forVisualization	inputPorts == List(InputPort(disallowMultiLinks = true)), outputPorts == List(OutputPort(mode = SINGLE_SNAPSHOT))
PortDescription	field exposure; dependencies defaults List.empty + accepts explicit deps; value equality + copy; @JsonIgnoreProperties("allowMultiInputs") backward-compat marker (verified via reflection)
PortDescriptor (trait)	inputPorts/outputPorts default to null (not empty) and are reassignable

Note for reviewers: scoped to the pure case-class/trait types only. The OperatorMetadataGenerator object in the same file is deliberately not tested — it eagerly reflects over the entire LogicalOp registry at init (instantiating every descriptor), which is not pure-unit-testable.

Any related issues, documentation, discussions?

Closes #5829.

How was this PR tested?

• sbt "WorkflowOperator/testOnly org.apache.texera.amber.operator.metadata.OperatorInfoSpec org.apache.texera.amber.operator.PortDescriptionSpec org.apache.texera.amber.operator.PortDescriptorSpec" — 11 tests, all green
• sbt "WorkflowOperator/Test/scalafmtCheck" and sbt "WorkflowOperator/Test/scalafix --check" — clean
• CI to confirm

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

Generated-by: Claude Code (Opus 4.8 [1M context])

[Copilot]

Pull request overview

Adds Scala unit tests in common/workflow-operator to pin the current behavior of three core operator-metadata types (OperatorInfo, PortDescription, PortDescriptor) that are widely used for operator port wiring and metadata across LogicalOp implementations. No production code changes are included.

Changes:

• Add OperatorInfoSpec to validate constructor field exposure, boolean default/override behavior, forVisualization factory contract, and case-class equality.
• Add PortDescriptionSpec to validate field exposure, dependencies default/override, copy/equality behavior, and the @JsonIgnoreProperties("allowMultiInputs") backward-compat marker.
• Add PortDescriptorSpec to validate the trait’s inputPorts/outputPorts default-to-null behavior and reassignment semantics.

Reviewed changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated no comments.

File	Description
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/PortDescriptorSpec.scala	Adds unit tests pinning PortDescriptor default null ports and reassignment behavior.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/PortDescriptionSpec.scala	Adds unit tests for PortDescription defaults, equality/copy, and Jackson backward-compat annotation presence.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/metadata/OperatorInfoSpec.scala	Adds unit tests for OperatorInfo field exposure/defaults, forVisualization contract, and value-based equality.

---

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 53.62%. Comparing base (8ca6bb2) to head (d391f8b).
⚠️ Report is 2 commits behind head on main.

Additional details and impacted files

@@             Coverage Diff              @@
##               main    #5832      +/-   ##
============================================
+ Coverage     53.56%   53.62%   +0.05%     
- Complexity     2717     2720       +3     
============================================
  Files          1099     1099              
  Lines         42541    42541              
  Branches       4577     4577              
============================================
+ Hits          22789    22814      +25     
+ Misses        18421    18392      -29     
- Partials       1331     1335       +4     

Flag	Coverage Δ		*Carryforward flag
access-control-service	70.44% <ø> (ø)
agent-service	34.36% <ø> (ø)		Carriedforward from 8ca6bb2
amber	54.61% <ø> (+0.15%)	⬆️
computing-unit-managing-service	1.65% <ø> (ø)
config-service	56.71% <ø> (ø)
file-service	57.06% <ø> (ø)
frontend	48.02% <ø> (ø)		Carriedforward from 8ca6bb2
pyamber	90.13% <ø> (ø)		Carriedforward from 8ca6bb2
python	90.80% <ø> (ø)		Carriedforward from 8ca6bb2
workflow-compiling-service	58.69% <ø> (ø)

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

☔ View full report in Codecov by Harness.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• 📦 JS Bundle Analysis: Save yourself from yourself by tracking and limiting bundle sizes in JS merges.

[github-actions]

⚠️ Benchmark changes need a look

🟢 2 better · 🔴 6 worse · ⚪ 7 noise (<±5%) · 0 without baseline

Compared against main 357fed0 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	363	0.222	27,683/34,434/34,434 us	🔴 +37.6% / 🔴 +16.4%
🔴	bs=100 sw=10 sl=64	933	0.57	107,937/144,823/144,823 us	🔴 +6.3% / ⚪ within ±5%
🟢	bs=1000 sw=10 sl=64	1,115	0.681	894,317/946,639/946,639 us	🟢 -9.1% / 🟢 -8.1%

Baseline details

Latest main 357fed0 from same runner

config	metric	PR	latest main	7d avg	Δ latest	Δ 7d
bs=10 sw=10 sl=64	throughput	363 tuples/sec	456 tuples/sec	410.82 tuples/sec	-20.4%	-11.6%
bs=10 sw=10 sl=64	MB/s	0.222 MB/s	0.278 MB/s	0.251 MB/s	-20.1%	-11.5%
bs=10 sw=10 sl=64	p50	27,683 us	20,118 us	23,785 us	+37.6%	+16.4%
bs=10 sw=10 sl=64	p95	34,434 us	34,624 us	34,980 us	-0.5%	-1.6%
bs=10 sw=10 sl=64	p99	34,434 us	34,624 us	34,980 us	-0.5%	-1.6%
bs=100 sw=10 sl=64	throughput	933 tuples/sec	939 tuples/sec	891.94 tuples/sec	-0.6%	+4.6%
bs=100 sw=10 sl=64	MB/s	0.57 MB/s	0.573 MB/s	0.544 MB/s	-0.5%	+4.7%
bs=100 sw=10 sl=64	p50	107,937 us	102,190 us	112,277 us	+5.6%	-3.9%
bs=100 sw=10 sl=64	p95	144,823 us	136,294 us	139,802 us	+6.3%	+3.6%
bs=100 sw=10 sl=64	p99	144,823 us	136,294 us	139,802 us	+6.3%	+3.6%
bs=1000 sw=10 sl=64	throughput	1,115 tuples/sec	1,085 tuples/sec	1,041 tuples/sec	+2.8%	+7.1%
bs=1000 sw=10 sl=64	MB/s	0.681 MB/s	0.662 MB/s	0.635 MB/s	+2.9%	+7.2%
bs=1000 sw=10 sl=64	p50	894,317 us	911,100 us	972,714 us	-1.8%	-8.1%
bs=1000 sw=10 sl=64	p95	946,639 us	1,041,648 us	1,023,057 us	-9.1%	-7.5%
bs=1000 sw=10 sl=64	p99	946,639 us	1,041,648 us	1,023,057 us	-9.1%	-7.5%

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
0,10,10,64,20,550.43,200,128000,363,0.222,27683.15,34434.30,34434.30
1,100,10,64,20,2142.97,2000,1280000,933,0.570,107936.70,144823.17,144823.17
2,1000,10,64,20,17937.02,20000,12800000,1115,0.681,894317.09,946638.93,946638.93

[xuang7]

LGTM!