feat(workflow-operator): name the missing ground-truth column in Sklearn Prediction's error by kz930 · Pull Request #8918 · apache/texera

kz930 · 2026-10-08T03:08:09Z

What changes were proposed in this PR?

When Sklearn Prediction's "Ground Truth Attribute Name to Ignore" names a column that is not in the data input, compilation failed with java.util.NoSuchElementException: None.get, which does not tell the user what is wrong. It now fails with "Ground Truth column '' is not in the input table", the same wording MachineLearningScorer uses for its columns.

Any related issues, documentation, discussions?

Closes #8864

How was this PR tested?

Updated the existing test in SklearnPredictionOpDescSpec to check the new message. sbt "WorkflowOperator/testOnly *SklearnPredictionOpDescSpec" passes, and so do scalafmt and scalafix.

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

Generated-by: Claude Code (Claude Opus 5.5)

🤖 Generated with Claude Code

…arn Prediction's error A ground-truth name that is not in the data input failed compilation with None.get. Say which column is missing instead, in the wording MachineLearningScorer already uses. Closes apache#8864 Co-Authored-By: Claude Opus 5.5 <[email protected]>

github-actions · 2026-10-08T03:13:52Z

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

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codecov-commenter · 2026-10-08T03:24:54Z

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 92.30%. Comparing base (7426431) to head (cd90841).
✅ All tests successful. No failed tests found.

Additional details and impacted files

@@             Coverage Diff              @@
##               main    #8918      +/-   ##
============================================
- Coverage     92.30%   92.30%   -0.01%     
  Complexity     5046     5046              
============================================
  Files          1260     1259       -1     
  Lines         53887    53824      -63     
  Branches       6711     6703       -8     
============================================
- Hits          49743    49682      -61     
+ Misses         2486     2485       -1     
+ Partials       1658     1657       -1

Flag	Coverage Δ		*Carryforward flag
access-control-service	`77.38% <ø> (ø)`
agent-service	`99.16% <ø> (ø)`		Carriedforward from 65a748a
amber	`87.32% <100.00%> (+<0.01%)`	⬆️
computing-unit-managing-service	`60.48% <ø> (ø)`
config-service	`87.37% <ø> (ø)`
file-service	`82.00% <ø> (ø)`
frontend	`96.55% <ø> (ø)`		Carriedforward from 65a748a
notebook-migration-service	`83.73% <ø> (ø)`
pyamber	`98.54% <ø> (+<0.01%)`	⬆️	Carriedforward from 65a748a
workflow-compiling-service	`72.43% <ø> (ø)`

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

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github-actions · 2026-10-08T03:30:03Z

⚠️ Benchmark changes need a look

🟢 0 better · 🔴 10 worse · ⚪ 5 noise (<±5%) · 0 without baseline

Compared against main 7426431 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	404	0.246	24,045/33,080/33,080 us	🔴 -8.2% / 🔴 +126.5%
🔴	bs=100 sw=10 sl=64	931	0.568	106,771/122,720/122,720 us	🔴 +8.3% / 🔴 +22.5%
🔴	bs=1000 sw=10 sl=64	1,076	0.657	918,864/1,039,275/1,039,275 us	🔴 +8.0% / 🔴 +12.4%

Baseline details

Latest main 7426431 from same runner

config	metric	PR	latest main	7d avg	Δ latest	Δ 7d
bs=10 sw=10 sl=64	throughput	404 tuples/sec	439 tuples/sec	912.36 tuples/sec	-8.0%	-55.7%
bs=10 sw=10 sl=64	MB/s	0.246 MB/s	0.268 MB/s	0.557 MB/s	-8.2%	-55.8%
bs=10 sw=10 sl=64	p50	24,045 us	22,705 us	11,391 us	+5.9%	+111.1%
bs=10 sw=10 sl=64	p95	33,080 us	32,658 us	14,608 us	+1.3%	+126.5%
bs=10 sw=10 sl=64	p99	33,080 us	32,658 us	17,250 us	+1.3%	+91.8%
bs=100 sw=10 sl=64	throughput	931 tuples/sec	988 tuples/sec	1,161 tuples/sec	-5.8%	-19.8%
bs=100 sw=10 sl=64	MB/s	0.568 MB/s	0.603 MB/s	0.709 MB/s	-5.8%	-19.9%
bs=100 sw=10 sl=64	p50	106,771 us	101,358 us	91,471 us	+5.3%	+16.7%
bs=100 sw=10 sl=64	p95	122,720 us	113,323 us	100,192 us	+8.3%	+22.5%
bs=100 sw=10 sl=64	p99	122,720 us	113,323 us	119,565 us	+8.3%	+2.6%
bs=1000 sw=10 sl=64	throughput	1,076 tuples/sec	1,094 tuples/sec	1,226 tuples/sec	-1.6%	-12.2%
bs=1000 sw=10 sl=64	MB/s	0.657 MB/s	0.668 MB/s	0.748 MB/s	-1.6%	-12.2%
bs=1000 sw=10 sl=64	p50	918,864 us	920,734 us	887,282 us	-0.2%	+3.6%
bs=1000 sw=10 sl=64	p95	1,039,275 us	962,200 us	924,352 us	+8.0%	+12.4%
bs=1000 sw=10 sl=64	p99	1,039,275 us	962,200 us	951,858 us	+8.0%	+9.2%

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
0,10,10,64,20,495.54,200,128000,404,0.246,24044.93,33080.15,33080.15
1,100,10,64,20,2147.34,2000,1280000,931,0.568,106770.55,122719.88,122719.88
2,1000,10,64,20,18591.45,20000,12800000,1076,0.657,918864.07,1039274.84,1039274.84

carloea2

One regression reproduced on this head with a passing exact-case control.

…klearn Prediction Schema lookups ignore case, but the generated drop() does not, so a case-only match passed validation and then raised KeyError at runtime. Co-Authored-By: Claude Opus 5.5 <[email protected]>

carloea2

The case-only mismatch is now rejected before Python execution. All 17 SklearnPredictionOpDescSpec tests pass locally, including the exact-case control. The remaining macOS CI failure is in LoopIntegrationSpec; CI still needs to pass before merge.

Co-Authored-By: Claude Opus 5.5 <[email protected]>

kz930 · 2026-10-12T22:07:41Z

The remaining failure is LoopIntegrationSpec on macOS, the engine race in #8937 that also fails on main. I'll re-run CI once #8938 merges.

… into kary-integration

aglinxinyuan

LGTM!

@carloea2

…way the engine does (apache#9035) ### What changes were proposed in this PR? The engine looks a column up through `Schema`, which ignores case. So a setting that names `Name` reads the column `name`, and the workflow runs in Texera. The exported script indexed the pandas frame with the name as written and stopped with a `KeyError`. `StandaloneCodeGenerator` gains `columnAsStored`, which resolves a setting's column name against the input schema and returns the table's spelling. A name the schema does not hold comes back unchanged, so the script still fails where the run would. Seven operators read their column through it: Projection, Filter, Keyword Search, Regular Expression, Substring Search, Dictionary Matcher and Unnest String. Projection still names each output column by its alias, which falls back to the name as the setting writes it. That matches `ProjectionOpExec`. Type Casting is the exception. Its schema propagation and its executor both match the column by its exact name, so in the engine a unit whose column differs in case casts nothing and the column passes through unchanged. The export now skips that unit too, instead of raising a `KeyError`. Operators that run as Python in the engine already compare names exactly on both sides, so they are left alone. ### Any related issues, documentation, discussions? Closes apache#9004. @carloea2 found the mismatch while reviewing apache#8918. apache#8980 rewrites Filter's export and looks up the declared type by the column's name. Whichever of the two merges second should look that type up under the resolved name as well. ### How was this PR tested? Each of the eight operators' `OpDescSpec` gains a test with a setting in a different case from the table. It asserts that the generated code reads the table's spelling. For Type Casting, the test also checks that the engine's output schema leaves that column's type unchanged, and that the export skips the unit. All of `WorkflowOperator/test` passes. Merged with the other open export PRs, the verification suite still passes all 150 cases (3 ignored, as before). ### Was this PR authored or co-authored using generative AI tooling? Generated-by: Claude Code (Claude Opus 5.5) 🤖 Generated with [Claude Code](https://claude.com/claude-code) --------- Co-authored-by: Claude Opus 5.5 <[email protected]>

github-actions Bot assigned kz930 Oct 8, 2026

github-actions Bot added feature common labels Oct 8, 2026

carloea2 suggested changes Oct 8, 2026

View reviewed changes

Comment thread ...erator/src/main/scala/org/apache/texera/amber/operator/sklearn/SklearnPredictionOpDesc.scala Resolved

feat(workflow-operator): keep the exact-case ground-truth lookup in S…

0cf15b1

…klearn Prediction Schema lookups ignore case, but the generated drop() does not, so a case-only match passed validation and then raised KeyError at runtime. Co-Authored-By: Claude Opus 5.5 <[email protected]>

carloea2 approved these changes Oct 12, 2026

View reviewed changes

ci: re-run CI after the flaky LoopIntegrationSpec failure

8ce0457

Co-Authored-By: Claude Opus 5.5 <[email protected]>

Merge upstream/main into feat/sklearn-prediction-missing-ground-truth

cd90841

kz930 added a commit to kz930/texera that referenced this pull request Oct 19, 2026

Merge myfork/feat/sklearn-prediction-missing-ground-truth (apache#8918)…

ffa2299

… into kary-integration

kz930 mentioned this pull request Oct 20, 2026

feat(workflow-operator): read a column named in a different case the way the engine does #9035

Merged

aglinxinyuan approved these changes Oct 24, 2026

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aglinxinyuan enabled auto-merge October 24, 2026 05:39

aglinxinyuan added this pull request to the merge queue Oct 24, 2026

Merged via the queue into apache:main with commit 5a44b5b Oct 24, 2026
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feat(workflow-operator): name the missing ground-truth column in Sklearn Prediction's error - #8918

feat(workflow-operator): name the missing ground-truth column in Sklearn Prediction's error#8918
aglinxinyuan merged 4 commits into
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kz930:feat/sklearn-prediction-missing-ground-truth

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kz930 commented Oct 8, 2026

What changes were proposed in this PR?

Any related issues, documentation, discussions?

How was this PR tested?

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

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