ErikBPF commented on PR #5786:
URL: 
https://github.com/apache/datafusion-comet/pull/5786#issuecomment-5647662940

   Thanks for the detailed review and reproductions. Addressed the requests in 
b696cc319 and rebased onto main, preserving the updated reader metrics and 
Variant handling.
   
   - Restrict duplicate validation to required top-level columns, recursively 
checking each selected subtree. Field-ID reads retain conservative whole-schema 
validation; empty projections skip all roots. Metadata-cache hits remain 
validated.
   - Added raw root-duplicate coverage plus unrelated-column, case-insensitive, 
repeated-read, pruning, count-only, and renamed field-ID cases. Added Rust 
LIST/MAP/separate-group coverage and removed the redundant batch-size dimension.
   - Updated the compatibility documentation and opened #5884 for 
Spark-compatible duplicate resolution. Independent Spark 4.1.3 vectorized 
testing found reader-dependent nested behavior; the follow-up includes that 
reproduction rather than assuming universal last-wins semantics.
   
   Validation: reproduced both valid-projection failures before the fix. 
Afterward, the full Spark 4.1 native-reader suite passed 70 tests (one existing 
NullType cancellation), and all 8 focused cases passed on Spark 3.5. Rust 
Parquet tests: 188 passed, one existing ignored benchmark. Native build, 
whole-reactor packaging, all-target workspace Clippy with warnings denied, 
semantic/syntactic Scalafix, Spotless, formatting, and whitespace checks passed.
   


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