test(workflow-operator): add unit test coverage for Sklearn training NB & tree descriptors

[aglinxinyuan]

What changes were proposed in this PR?

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

Spec	Source class
SklearnTrainingBernoulliNaiveBayesOpDescSpec	SklearnTrainingBernoulliNaiveBayesOpDesc
SklearnTrainingComplementNaiveBayesOpDescSpec	SklearnTrainingComplementNaiveBayesOpDesc
SklearnTrainingGaussianNaiveBayesOpDescSpec	SklearnTrainingGaussianNaiveBayesOpDesc
SklearnTrainingMultinomialNaiveBayesOpDescSpec	SklearnTrainingMultinomialNaiveBayesOpDesc
SklearnTrainingDecisionTreeOpDescSpec	SklearnTrainingDecisionTreeOpDesc
SklearnTrainingExtraTreeOpDescSpec	SklearnTrainingExtraTreeOpDesc
SklearnTrainingExtraTreesOpDescSpec	SklearnTrainingExtraTreesOpDesc
SklearnTrainingRandomForestOpDescSpec	SklearnTrainingRandomForestOpDesc

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.*" — 40 tests, all green
• sbt "WorkflowOperator/Test/scalafmtCheck" and sbt "WorkflowOperator/scalafixAll --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])

[github-actions]

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[Copilot]

Pull request overview

Adds ScalaTest unit coverage for the previously-untested Sklearn training operator descriptors in common/workflow-operator, pinning their shared SklearnTrainingOpDesc contract without modifying production code.

Changes:

• Added 8 descriptor-spec test files covering operatorInfo, config defaults, output schema, generated Python code snippets, and polymorphic JSON round-tripping.
• Standardized assertions to match the existing Sklearn descriptor-spec pattern already used in org.apache.texera.amber.operator.sklearn.* tests.

Reviewed changes

Copilot reviewed 8 out of 8 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/SklearnTrainingBernoulliNaiveBayesOpDescSpec.scala	Adds contract tests for BernoulliNB training descriptor.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingComplementNaiveBayesOpDescSpec.scala	Adds contract tests for ComplementNB training descriptor.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingGaussianNaiveBayesOpDescSpec.scala	Adds contract tests for GaussianNB training descriptor.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingMultinomialNaiveBayesOpDescSpec.scala	Adds contract tests for MultinomialNB training descriptor.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingDecisionTreeOpDescSpec.scala	Adds contract tests for DecisionTreeClassifier training descriptor.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingExtraTreeOpDescSpec.scala	Adds contract tests for ExtraTreeClassifier training descriptor.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingExtraTreesOpDescSpec.scala	Adds contract tests for ExtraTreesClassifier training descriptor.
common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/sklearn/training/SklearnTrainingRandomForestOpDescSpec.scala	Adds contract tests for RandomForestClassifier training descriptor.

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[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 54.93%. Comparing base (2ebfc28) to head (5f6e1f8).
⚠️ Report is 2 commits behind head on main.
✅ All tests successful. No failed tests found.

Additional details and impacted files

@@             Coverage Diff              @@
##               main    #5954      +/-   ##
============================================
+ Coverage     54.91%   54.93%   +0.02%     
- Complexity     2956     2960       +4     
============================================
  Files          1117     1117              
  Lines         43133    43133              
  Branches       4648     4648              
============================================
+ Hits          23685    23694       +9     
+ Misses        18054    18048       -6     
+ Partials       1394     1391       -3     

Flag	Coverage Δ		*Carryforward flag
access-control-service	70.00% <ø> (ø)
agent-service	34.36% <ø> (ø)		Carriedforward from 2ebfc28
amber	57.07% <ø> (+0.05%)	⬆️
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

🟢 0 better · 🔴 3 worse · ⚪ 12 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	419	0.256	22,770/30,543/30,543 us	🔴 +9.3% / 🔴 +105.2%
⚪	bs=100 sw=10 sl=64	856	0.522	114,067/142,266/142,266 us	⚪ within ±5% / 🔴 +33.9%
⚪	bs=1000 sw=10 sl=64	958	0.585	1,046,739/1,073,850/1,073,850 us	⚪ within ±5% / 🔴 +7.8%

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	419 tuples/sec	446 tuples/sec	781.13 tuples/sec	-6.1%	-46.4%
bs=10 sw=10 sl=64	MB/s	0.256 MB/s	0.272 MB/s	0.477 MB/s	-5.9%	-46.3%
bs=10 sw=10 sl=64	p50	22,770 us	20,824 us	12,542 us	+9.3%	+81.6%
bs=10 sw=10 sl=64	p95	30,543 us	30,674 us	14,886 us	-0.4%	+105.2%
bs=10 sw=10 sl=64	p99	30,543 us	30,674 us	17,580 us	-0.4%	+73.7%
bs=100 sw=10 sl=64	throughput	856 tuples/sec	852 tuples/sec	999.37 tuples/sec	+0.5%	-14.3%
bs=100 sw=10 sl=64	MB/s	0.522 MB/s	0.52 MB/s	0.61 MB/s	+0.4%	-14.4%
bs=100 sw=10 sl=64	p50	114,067 us	115,893 us	99,687 us	-1.6%	+14.4%
bs=100 sw=10 sl=64	p95	142,266 us	143,085 us	106,271 us	-0.6%	+33.9%
bs=100 sw=10 sl=64	p99	142,266 us	143,085 us	115,445 us	-0.6%	+23.2%
bs=1000 sw=10 sl=64	throughput	958 tuples/sec	975 tuples/sec	1,036 tuples/sec	-1.7%	-7.5%
bs=1000 sw=10 sl=64	MB/s	0.585 MB/s	0.595 MB/s	0.632 MB/s	-1.7%	-7.5%
bs=1000 sw=10 sl=64	p50	1,046,739 us	1,017,296 us	970,675 us	+2.9%	+7.8%
bs=1000 sw=10 sl=64	p95	1,073,850 us	1,068,932 us	1,011,928 us	+0.5%	+6.1%
bs=1000 sw=10 sl=64	p99	1,073,850 us	1,068,932 us	1,045,045 us	+0.5%	+2.8%

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
0,10,10,64,20,476.85,200,128000,419,0.256,22770.33,30542.57,30542.57
1,100,10,64,20,2337.37,2000,1280000,856,0.522,114067.17,142265.90,142265.90
2,1000,10,64,20,20868.46,20000,12800000,958,0.585,1046739.23,1073850.44,1073850.44