test(workflow-operator): add unit test coverage for Sklearn training ensemble & linear descriptors

[aglinxinyuan]

What changes were proposed in this PR?

Pin behavior of nine previously-untested Sklearn training operator descriptors in common/workflow-operator. No production-code changes.

Spec	Source class
SklearnTrainingAdaptiveBoostingOpDescSpec	SklearnTrainingAdaptiveBoostingOpDesc
SklearnTrainingBaggingOpDescSpec	SklearnTrainingBaggingOpDesc
SklearnTrainingGradientBoostingOpDescSpec	SklearnTrainingGradientBoostingOpDesc
SklearnTrainingLogisticRegressionOpDescSpec	SklearnTrainingLogisticRegressionOpDesc
SklearnTrainingLogisticRegressionCVOpDescSpec	SklearnTrainingLogisticRegressionCVOpDesc
SklearnTrainingPerceptronOpDescSpec	SklearnTrainingPerceptronOpDesc
SklearnTrainingPassiveAggressiveOpDescSpec	SklearnTrainingPassiveAggressiveOpDesc
SklearnTrainingSDGOpDescSpec	SklearnTrainingSDGOpDesc
SklearnTrainingLinearRegressionOpDescSpec	SklearnTrainingLinearRegressionOpDesc

Behavior pinned (shared SklearnTrainingOpDesc contract)

Surface	Contract
operatorInfo	exact model name (Training: <model>) + Sklearn <name> Operator description; Sklearn Training group; single training input port; one blocking output
field defaults	countVectorizer/tfidfTransformer false; target/text null
getOutputSchemas	model_name (STRING) + model (BINARY) keyed by the declared output port
generatePythonCode	imports the matching sklearn estimator and builds the make_pipeline(...).fit(X, Y) training model
Round-trip	config fields preserved through the polymorphic LogicalOp base, with the correct operatorType discriminator

Any related issues, documentation, discussions?

Part of the ongoing workflow-operator unit-test coverage effort (the training-side counterpart to the Sklearn classifier coverage in #5925/#5939/#5940/#5941/#5945/#5946/#5951).

How was this PR tested?

• sbt "WorkflowOperator/testOnly org.apache.texera.amber.operator.sklearn.training.*" — 45 tests, all green
• sbt "WorkflowOperator/Test/scalafmtCheck" and sbt "WorkflowOperator/scalafixAll --check" — clean
• CI to confirm

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

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[Copilot]

Pull request overview

This PR adds ScalaTest unit specs under common/workflow-operator to pin the current behavior of nine previously-untested Sklearn training operator descriptors (operator metadata, default config values, output schema shape, Python codegen basics, and JSON polymorphic round-trip via LogicalOp).

Changes:

• Add 9 new AnyFlatSpec test classes covering SklearnTraining*OpDesc descriptors in the Sklearn training family.
• Assert consistent operatorInfo contract (group, ports, blocking output) and config defaults (countVectorizer/tfidfTransformer false; target/text null).
• Validate output schema fields (model_name STRING, model BINARY), basic codegen import expectations, and operatorType discriminator round-tripping.

Reviewed changes

Copilot reviewed 9 out of 9 changed files in this pull request and generated no comments.

Show a summary per file

File	Description
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingAdaptiveBoostingOpDescSpec.scala	Adds unit coverage for AdaBoost training descriptor contract/codegen/round-trip.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingBaggingOpDescSpec.scala	Adds unit coverage for Bagging training descriptor contract/codegen/round-trip.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingGradientBoostingOpDescSpec.scala	Adds unit coverage for Gradient Boosting training descriptor contract/codegen/round-trip.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingLinearRegressionOpDescSpec.scala	Adds unit coverage for Linear Regression training descriptor contract/codegen/round-trip.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingLogisticRegressionCVOpDescSpec.scala	Adds unit coverage for LogisticRegressionCV training descriptor contract/codegen/round-trip.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingLogisticRegressionOpDescSpec.scala	Adds unit coverage for Logistic Regression training descriptor contract/codegen/round-trip.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingPassiveAggressiveOpDescSpec.scala	Adds unit coverage for Passive Aggressive training descriptor contract/codegen/round-trip.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingPerceptronOpDescSpec.scala	Adds unit coverage for Perceptron training descriptor contract/codegen/round-trip.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingSDGOpDescSpec.scala	Adds unit coverage for SGD training descriptor contract/codegen/round-trip (using existing SDG naming in codebase).

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[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 54.91%. Comparing base (2ebfc28) to head (02aa8da).
⚠️ Report is 2 commits behind head on main.
✅ All tests successful. No failed tests found.

Additional details and impacted files

@@            Coverage Diff            @@
##               main    #5955   +/-   ##
=========================================
  Coverage     54.91%   54.91%           
  Complexity     2956     2956           
=========================================
  Files          1117     1117           
  Lines         43133    43133           
  Branches       4648     4648           
=========================================
+ Hits          23685    23686    +1     
+ Misses        18054    18051    -3     
- Partials       1394     1396    +2     

Flag	Coverage Δ		*Carryforward flag
access-control-service	70.00% <ø> (ø)
agent-service	34.36% <ø> (ø)		Carriedforward from 2ebfc28
amber	57.02% <ø> (+<0.01%)	⬆️
computing-unit-managing-service	0.00% <ø> (ø)
config-service	51.56% <ø> (ø)
file-service	59.02% <ø> (ø)
frontend	48.67% <ø> (ø)		Carriedforward from 2ebfc28
notebook-migration-service	78.57% <ø> (ø)
pyamber	90.20% <ø> (ø)		Carriedforward from 2ebfc28
python	90.76% <ø> (ø)		Carriedforward from 2ebfc28
workflow-compiling-service	55.14% <ø> (ø)

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

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[github-actions]

⚠️ Benchmark changes need a look

🟢 2 better · 🔴 5 worse · ⚪ 8 noise (<±5%) · 0 without baseline

Compared against main 2ebfc28 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	364	0.222	26,473/37,622/37,622 us	🔴 +11.6% / 🔴 +152.7%
🟢	bs=100 sw=10 sl=64	802	0.489	124,621/140,467/140,467 us	🟢 -6.1% / 🔴 +32.2%
⚪	bs=1000 sw=10 sl=64	916	0.559	1,090,698/1,118,560/1,118,560 us	⚪ within ±5% / 🔴 +12.4%

Baseline details

Latest main 2ebfc28 from same runner

config	metric	PR	latest main	7d avg	Δ latest	Δ 7d
bs=10 sw=10 sl=64	throughput	364 tuples/sec	396 tuples/sec	781.13 tuples/sec	-8.1%	-53.4%
bs=10 sw=10 sl=64	MB/s	0.222 MB/s	0.242 MB/s	0.477 MB/s	-8.3%	-53.4%
bs=10 sw=10 sl=64	p50	26,473 us	24,766 us	12,542 us	+6.9%	+111.1%
bs=10 sw=10 sl=64	p95	37,622 us	33,719 us	14,886 us	+11.6%	+152.7%
bs=10 sw=10 sl=64	p99	37,622 us	33,719 us	17,580 us	+11.6%	+114.0%
bs=100 sw=10 sl=64	throughput	802 tuples/sec	820 tuples/sec	999.37 tuples/sec	-2.2%	-19.7%
bs=100 sw=10 sl=64	MB/s	0.489 MB/s	0.501 MB/s	0.61 MB/s	-2.4%	-19.8%
bs=100 sw=10 sl=64	p50	124,621 us	121,333 us	99,687 us	+2.7%	+25.0%
bs=100 sw=10 sl=64	p95	140,467 us	149,535 us	106,271 us	-6.1%	+32.2%
bs=100 sw=10 sl=64	p99	140,467 us	149,535 us	115,445 us	-6.1%	+21.7%
bs=1000 sw=10 sl=64	throughput	916 tuples/sec	926 tuples/sec	1,036 tuples/sec	-1.1%	-11.6%
bs=1000 sw=10 sl=64	MB/s	0.559 MB/s	0.565 MB/s	0.632 MB/s	-1.1%	-11.6%
bs=1000 sw=10 sl=64	p50	1,090,698 us	1,082,440 us	970,675 us	+0.8%	+12.4%
bs=1000 sw=10 sl=64	p95	1,118,560 us	1,103,515 us	1,011,928 us	+1.4%	+10.5%
bs=1000 sw=10 sl=64	p99	1,118,560 us	1,103,515 us	1,045,045 us	+1.4%	+7.0%

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
0,10,10,64,20,548.96,200,128000,364,0.222,26473.10,37622.43,37622.43
1,100,10,64,20,2494.46,2000,1280000,802,0.489,124621.34,140467.21,140467.21
2,1000,10,64,20,21838.09,20000,12800000,916,0.559,1090698.21,1118560.47,1118560.47