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]

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[github-actions]

⚠️ Benchmark changes need a look

🟢 4 better · 🔴 3 worse · ⚪ 8 noise (<±5%) · 0 without baseline

Compared against main 324278e 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	531	0.324	18,012/27,103/27,103 us	🟢 -6.8% / 🔴 +65.8%
🔴	bs=100 sw=10 sl=64	1,098	0.67	89,673/102,715/102,715 us	🟢 -20.8% / 🟢 -11.8%
🔴	bs=1000 sw=10 sl=64	1,270	0.775	779,973/875,982/875,982 us	🔴 +5.6% / 🟢 +23.3%

Baseline details

Latest main 324278e from same runner

config	metric	PR	latest main	7d avg	Δ latest	Δ 7d
bs=10 sw=10 sl=64	throughput	531 tuples/sec	557 tuples/sec	774.89 tuples/sec	-4.7%	-31.5%
bs=10 sw=10 sl=64	MB/s	0.324 MB/s	0.34 MB/s	0.473 MB/s	-4.7%	-31.5%
bs=10 sw=10 sl=64	p50	18,012 us	18,017 us	12,738 us	-0.0%	+41.4%
bs=10 sw=10 sl=64	p95	27,103 us	29,069 us	16,348 us	-6.8%	+65.8%
bs=10 sw=10 sl=64	p99	27,103 us	29,069 us	18,848 us	-6.8%	+43.8%
bs=100 sw=10 sl=64	throughput	1,098 tuples/sec	1,114 tuples/sec	1,005 tuples/sec	-1.4%	+9.3%
bs=100 sw=10 sl=64	MB/s	0.67 MB/s	0.68 MB/s	0.613 MB/s	-1.5%	+9.3%
bs=100 sw=10 sl=64	p50	89,673 us	85,057 us	100,970 us	+5.4%	-11.2%
bs=100 sw=10 sl=64	p95	102,715 us	129,610 us	107,605 us	-20.8%	-4.5%
bs=100 sw=10 sl=64	p99	102,715 us	129,610 us	116,429 us	-20.8%	-11.8%
bs=1000 sw=10 sl=64	throughput	1,270 tuples/sec	1,300 tuples/sec	1,030 tuples/sec	-2.3%	+23.3%
bs=1000 sw=10 sl=64	MB/s	0.775 MB/s	0.794 MB/s	0.629 MB/s	-2.4%	+23.2%
bs=1000 sw=10 sl=64	p50	779,973 us	768,157 us	991,433 us	+1.5%	-21.3%
bs=1000 sw=10 sl=64	p95	875,982 us	829,181 us	1,036,668 us	+5.6%	-15.5%
bs=1000 sw=10 sl=64	p99	875,982 us	829,181 us	1,070,470 us	+5.6%	-18.2%

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
0,10,10,64,20,376.40,200,128000,531,0.324,18012.06,27102.55,27102.55
1,100,10,64,20,1821.38,2000,1280000,1098,0.670,89672.63,102714.92,102714.92
2,1000,10,64,20,15742.36,20000,12800000,1270,0.775,779972.68,875982.32,875982.32

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 90.13%. Comparing base (324278e) to head (24f2b96).
✅ All tests successful. No failed tests found.

Additional details and impacted files

@@             Coverage Diff              @@
##               main    #7568      +/-   ##
============================================
- Coverage     90.14%   90.13%   -0.02%     
+ Complexity     4417     4413       -4     
============================================
  Files          1174     1174              
  Lines         46964    46963       -1     
  Branches       5262     5262              
============================================
- Hits          42334    42328       -6     
- Misses         2876     2877       +1     
- Partials       1754     1758       +4     

Flag	Coverage Δ		*Carryforward flag
access-control-service	70.00% <ø> (ø)
agent-service	98.62% <ø> (ø)		Carriedforward from d420e20
amber	86.71% <ø> (-0.03%)	⬇️
computing-unit-managing-service	72.46% <ø> (ø)
config-service	77.31% <ø> (ø)
file-service	68.90% <ø> (ø)
frontend	91.44% <ø> (ø)		Carriedforward from d420e20
notebook-migration-service	78.89% <ø> (ø)
pyamber	97.57% <ø> (ø)		Carriedforward from d420e20
workflow-compiling-service	57.89% <ø> (ø)

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

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[kz930]

@aglinxinyuan May you take a look at this?