kz930 opened a new pull request, #7645:
URL: https://github.com/apache/texera/pull/7645

   ### What changes were proposed in this PR?
   
   Two configurations ended the run with an error from inside scikit-learn or 
from code generation, naming neither the column nor the field to change.
   
   The text column now states what it takes. `Count Vectorizer` tokenizes 
documents, so the column is a string, and it is required exactly when that 
switch is on: with the switch off nothing reads it, and with the switch on a 
blank one reached code generation as a null and became `#EXCEPTION DURING CODE 
GENERATION`. Both are schema constraints, the second in the conditional form 
Aggregate already uses, so the panel refuses the configuration while it is 
being written. Conditional rather than a plain `required`, so a freshly dropped 
operator, whose vectorizer is off, is not flagged for a field it has no use for.
   
   The feature set drops what it cannot fit rather than ending the run. These 
operators take every column but the target, so a text column beside the 
numbers, one the user never meant as a feature, raised `ValueError: could not 
convert string to float`, and a timestamp raised `DTypePromotionError`. Nothing 
in the configuration could exclude it, and the message named neither the column 
nor a way out. Booleans are kept, fitting as 0/1. What was left out is printed, 
so the choice is visible rather than silent, and this follows the rest of the 
codebase, where twenty-four visualization operators drop missing values before 
plotting.
   
   The drop is skipped under the text pipeline, where X is one string column by 
construction and filtering would empty it.
   
   The constraints sit on the shared base, so they reach all fifty-one 
operators of the Sklearn and Sklearn Training groups. The required marker for 
the text column needs #7642; without it the configuration is still refused, 
only unmarked.
   
   ### Any related issues, documentation, discussions?
   
   Closes #7643. The marker for the new conditional required comes from #7642.
   
   ### How was this PR tested?
   
   `SklearnClassifierOpDescCodegenSpec` and `SklearnTrainingOpDescCodegenSpec` 
already pinned the generated feature-selection line and were updated to the new 
one, including that the text pipeline does not carry it. 
`WorkflowOperator/test` passes: 2387 tests.
   
   ### Was this PR authored or co-authored using generative AI tooling?
   
   Generated-by: Claude Code (Claude Opus 5)
   


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