feat(csv-scan): keep a numeric column's type when one of its cells is blank

[kz930]

What changes were proposed in this PR?

Schema inference and execution disagreed about what a blank cell is, and the schema side was the one that lost information. Inference set nullValue("") on its parser, so a blank read as an empty string: tryParseDouble("") fails, tryParseBoolean("") fails, and inferField lands on tryParseString(). One empty cell was enough to type a whole numeric column as STRING. Execution builds its parser without nullValue, so the same blank read as null there, which is what AttributeTypeUtils.parseField is written to pass through.

The effect reaches well past the scan. Every downstream operator that does arithmetic on such a column then receives strings and fails on rows whose values are perfectly good numbers, not on the blank one. Hugging Face Iris Logistic Regression on a three-row file fails at the first row, where numpy is handed array([['2.6', '0.75']], dtype='<U32').

Dropping the setting leaves both sides reading a blank as null, and tryParseDouble(null) already answers DOUBLE, so the column keeps the type its values give it.

One corner changes with it: a column that is blank in every sampled row now infers as INTEGER rather than STRING. Its values are null either way, so this renames the empty rather than reinterpreting anything.

Any related issues, documentation, discussions?

Closes #7550

How was this PR tested?

CSVScanSourceOpDescSpec gains a case that writes a two-column file whose numeric column is blank on one row and asserts the inferred type is DOUBLE. It fails on the previous behavior, 16 passed / 1 failed before the change and 17 / 0 after. Since this touches inference every scan goes through, the whole module was run as well: 2187 passed, 0 failed.

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

Generated-by: Claude Code (Claude Opus 5)

[github-actions]

Backport auto-label report

This fix: PR was checked against each actively-supported release branch. release/* labels drive the post-merge backport, so add or remove one to change where this fix lands.

Release branch	Analysis
✅ release/v1.2	Change detected on this branch — label added; this fix is queued to backport here. Requested review from @xuang7.

Auto-label run.

[github-actions]

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.

[github-actions]

⚠️ Benchmark changes need a look

🟢 6 better · 🔴 3 worse · ⚪ 6 noise (<±5%) · 0 without baseline

Compared against main e878df3 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	402	0.245	23,705/32,572/32,572 us	🔴 +11.4% / 🔴 +103.7%
🟢	bs=100 sw=10 sl=64	912	0.556	108,227/131,485/131,485 us	🟢 -6.7% / 🔴 +21.7%
🟢	bs=1000 sw=10 sl=64	1,076	0.656	927,480/972,320/972,320 us	🟢 -5.6% / 🟢 -9.0%

Baseline details

Latest main e878df3 from same runner

config	metric	PR	latest main	7d avg	Δ latest	Δ 7d
bs=10 sw=10 sl=64	throughput	402 tuples/sec	424 tuples/sec	784.3 tuples/sec	-5.2%	-48.7%
bs=10 sw=10 sl=64	MB/s	0.245 MB/s	0.259 MB/s	0.479 MB/s	-5.4%	-48.8%
bs=10 sw=10 sl=64	p50	23,705 us	21,276 us	12,590 us	+11.4%	+88.3%
bs=10 sw=10 sl=64	p95	32,572 us	36,545 us	15,991 us	-10.9%	+103.7%
bs=10 sw=10 sl=64	p99	32,572 us	36,545 us	18,694 us	-10.9%	+74.2%
bs=100 sw=10 sl=64	throughput	912 tuples/sec	946 tuples/sec	1,002 tuples/sec	-3.6%	-9.0%
bs=100 sw=10 sl=64	MB/s	0.556 MB/s	0.578 MB/s	0.612 MB/s	-3.8%	-9.1%
bs=100 sw=10 sl=64	p50	108,227 us	103,584 us	101,285 us	+4.5%	+6.9%
bs=100 sw=10 sl=64	p95	131,485 us	140,904 us	108,068 us	-6.7%	+21.7%
bs=100 sw=10 sl=64	p99	131,485 us	140,904 us	118,235 us	-6.7%	+11.2%
bs=1000 sw=10 sl=64	throughput	1,076 tuples/sec	1,075 tuples/sec	1,030 tuples/sec	+0.1%	+4.5%
bs=1000 sw=10 sl=64	MB/s	0.656 MB/s	0.656 MB/s	0.629 MB/s	0.0%	+4.4%
bs=1000 sw=10 sl=64	p50	927,480 us	918,309 us	991,882 us	+1.0%	-6.5%
bs=1000 sw=10 sl=64	p95	972,320 us	1,029,692 us	1,038,496 us	-5.6%	-6.4%
bs=1000 sw=10 sl=64	p99	972,320 us	1,029,692 us	1,068,265 us	-5.6%	-9.0%

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
0,10,10,64,20,497.25,200,128000,402,0.245,23704.76,32571.79,32571.79
1,100,10,64,20,2194.03,2000,1280000,912,0.556,108226.81,131485.04,131485.04
2,1000,10,64,20,18594.59,20000,12800000,1076,0.656,927479.97,972319.66,972319.66

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 87.87%. Comparing base (e878df3) to head (9f49d90).

Additional details and impacted files

@@             Coverage Diff              @@
##               main    #7568      +/-   ##
============================================
- Coverage     87.88%   87.87%   -0.02%     
+ Complexity     4276     4273       -3     
============================================
  Files          1176     1176              
  Lines         47018    47017       -1     
  Branches       5245     5245              
============================================
- Hits          41323    41317       -6     
- Misses         3972     3974       +2     
- Partials       1723     1726       +3     

Flag	Coverage Δ		*Carryforward flag
access-control-service	70.00% <ø> (ø)
agent-service	98.62% <ø> (ø)		Carriedforward from e878df3
amber	82.85% <ø> (-0.03%)	⬇️
computing-unit-managing-service	60.38% <ø> (ø)
config-service	65.97% <ø> (ø)
file-service	69.05% <ø> (ø)
frontend	89.94% <ø> (ø)		Carriedforward from e878df3
notebook-migration-service	78.89% <ø> (ø)
pyamber	97.52% <ø> (ø)		Carriedforward from e878df3
workflow-compiling-service	26.31% <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.

[kz930]

@aglinxinyuan May you take a look at this?