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Posted to notifications@texera.apache.org by "aglinxinyuan (via GitHub)" <gi...@apache.org> on 2026/06/24 04:07:48 UTC
[PR] test(workflow-operator): add unit test coverage for Sklearn Naive Bayes descriptors [texera]
aglinxinyuan opened a new pull request, #5925:
URL: https://github.com/apache/texera/pull/5925
### What changes were proposed in this PR?
Pin behavior of the four previously-untested Sklearn Naive Bayes classifier descriptors in `common/workflow-operator`. No production-code changes.
| Spec | Source class | Tests |
| --- | --- | --- |
| `SklearnBernoulliNaiveBayesOpDescSpec` | `SklearnBernoulliNaiveBayesOpDesc` | 5 |
| `SklearnComplementNaiveBayesOpDescSpec` | `SklearnComplementNaiveBayesOpDesc` | 5 |
| `SklearnGaussianNaiveBayesOpDescSpec` | `SklearnGaussianNaiveBayesOpDesc` | 5 |
| `SklearnMultinomialNaiveBayesOpDescSpec` | `SklearnMultinomialNaiveBayesOpDesc` | 5 |
**Behavior pinned**
| Surface | Contract |
| --- | --- |
| `operatorInfo` | exact model name + `Sklearn <name> Operator` description; Sklearn group; training/testing input ports + 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 and instantiates the matching sklearn estimator (e.g. `BernoulliNB`) via `make_pipeline` |
| 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.
### How was this PR tested?
- `sbt "WorkflowOperator/testOnly *SklearnBernoulliNaiveBayesOpDescSpec *SklearnComplementNaiveBayesOpDescSpec *SklearnGaussianNaiveBayesOpDescSpec *SklearnMultinomialNaiveBayesOpDescSpec"` — 20 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])
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Re: [PR] test(workflow-operator): add unit test coverage for Sklearn Naive Bayes descriptors [texera]
Posted by "github-actions[bot] (via GitHub)" <gi...@apache.org>.
github-actions[bot] commented on PR #5925:
URL: https://github.com/apache/texera/pull/5925#issuecomment-4785780666
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### Automated Reviewer Suggestions
Based on the `git blame` history of the changed files, we recommend the following reviewers:
- No candidates found from `git blame` history.
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Re: [PR] test(workflow-operator): add unit test coverage for Sklearn Naive Bayes descriptors [texera]
Posted by "codecov-commenter (via GitHub)" <gi...@apache.org>.
codecov-commenter commented on PR #5925:
URL: https://github.com/apache/texera/pull/5925#issuecomment-4785792485
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:white_check_mark: All modified and coverable lines are covered by tests.
:white_check_mark: Project coverage is 54.60%. Comparing base ([`1c580e5`](https://app.codecov.io/gh/apache/texera/commit/1c580e59eb69bc45205298606c3980c67a05803f?dropdown=coverage&el=desc&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=apache)) to head ([`7a72636`](https://app.codecov.io/gh/apache/texera/commit/7a726365d80acda81a16daaa6084f7a58863e321?dropdown=coverage&el=desc&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=apache)).
<details><summary>Additional details and impacted files</summary>
```diff
@@ Coverage Diff @@
## main #5925 +/- ##
=========================================
Coverage 54.60% 54.60%
Complexity 2927 2927
=========================================
Files 1109 1109
Lines 42828 42828
Branches 4608 4608
=========================================
Hits 23385 23385
Misses 18081 18081
Partials 1362 1362
```
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Re: [PR] test(workflow-operator): add unit test coverage for Sklearn Naive Bayes descriptors [texera]
Posted by "aglinxinyuan (via GitHub)" <gi...@apache.org>.
aglinxinyuan merged PR #5925:
URL: https://github.com/apache/texera/pull/5925
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Re: [PR] test(workflow-operator): add unit test coverage for Sklearn Naive Bayes descriptors [texera]
Posted by "github-actions[bot] (via GitHub)" <gi...@apache.org>.
github-actions[bot] commented on PR #5925:
URL: https://github.com/apache/texera/pull/5925#issuecomment-4785806973
<!-- texera-benchmarks-comment -->
## ⚠️ Benchmark changes need a look
🟢 4 better · 🔴 1 worse · ⚪ 10 noise (<±5%) · 0 without baseline
> Compared against main `1c580e5` 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](https://apache.github.io/texera/dev/bench/) · [Run](https://github.com/apache/texera/actions/runs/28074458614)
| | config | throughput | MB/s | latency | max Δ latest / 7d |
|---|---|---:|---:|---:|---:|
| 🔴 | bs=10 sw=10 sl=64 | 389 | 0.238 | 25,780/33,058/33,058 us | 🔴 +10.0% / 🔴 +8.4% |
| 🟢 | bs=100 sw=10 sl=64 | 833 | 0.508 | 116,571/139,934/139,934 us | 🟢 -11.4% / 🔴 -6.7% |
| ⚪ | bs=1000 sw=10 sl=64 | 935 | 0.57 | 1,069,345/1,118,882/1,118,882 us | ⚪ within ±5% / 🔴 -10.3% |
<details><summary>Baseline details</summary>
Latest main `1c580e5` from same runner
| config | metric | PR | latest main | 7d avg | Δ latest | Δ 7d |
|---|---|---:|---:|---:|---:|---:|
| bs=10 sw=10 sl=64 | throughput | 389 tuples/sec | 395 tuples/sec | 410.82 tuples/sec | -1.5% | -5.3% |
| bs=10 sw=10 sl=64 | MB/s | 0.238 MB/s | 0.241 MB/s | 0.251 MB/s | -1.2% | -5.1% |
| bs=10 sw=10 sl=64 | p50 | 25,780 us | 23,427 us | 23,785 us | +10.0% | +8.4% |
| bs=10 sw=10 sl=64 | p95 | 33,058 us | 36,524 us | 34,980 us | -9.5% | -5.5% |
| bs=10 sw=10 sl=64 | p99 | 33,058 us | 36,524 us | 34,980 us | -9.5% | -5.5% |
| bs=100 sw=10 sl=64 | throughput | 833 tuples/sec | 819 tuples/sec | 891.94 tuples/sec | +1.7% | -6.6% |
| bs=100 sw=10 sl=64 | MB/s | 0.508 MB/s | 0.5 MB/s | 0.544 MB/s | +1.6% | -6.7% |
| bs=100 sw=10 sl=64 | p50 | 116,571 us | 119,613 us | 112,277 us | -2.5% | +3.8% |
| bs=100 sw=10 sl=64 | p95 | 139,934 us | 158,005 us | 139,802 us | -11.4% | +0.1% |
| bs=100 sw=10 sl=64 | p99 | 139,934 us | 158,005 us | 139,802 us | -11.4% | +0.1% |
| bs=1000 sw=10 sl=64 | throughput | 935 tuples/sec | 920 tuples/sec | 1,041 tuples/sec | +1.6% | -10.2% |
| bs=1000 sw=10 sl=64 | MB/s | 0.57 MB/s | 0.561 MB/s | 0.635 MB/s | +1.6% | -10.3% |
| bs=1000 sw=10 sl=64 | p50 | 1,069,345 us | 1,084,616 us | 972,714 us | -1.4% | +9.9% |
| bs=1000 sw=10 sl=64 | p95 | 1,118,882 us | 1,133,084 us | 1,023,057 us | -1.3% | +9.4% |
| bs=1000 sw=10 sl=64 | p99 | 1,118,882 us | 1,133,084 us | 1,023,057 us | -1.3% | +9.4% |
</details>
<details><summary>Raw CSV</summary>
```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
0,10,10,64,20,513.76,200,128000,389,0.238,25779.92,33057.68,33057.68
1,100,10,64,20,2400.65,2000,1280000,833,0.508,116571.14,139933.82,139933.82
2,1000,10,64,20,21400.53,20000,12800000,935,0.570,1069345.18,1118882.16,1118882.16
```
</details>
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