peterxcli commented on PR #4901:
URL: 
https://github.com/apache/datafusion-comet/pull/4901#issuecomment-5447394053

   Thanks for the review! Point by point:
   
   1. **Map ordering** — fixed; moved `DivideDTInterval` after `Days`.
   
   2. **Wide decimals** — the dispatcher handles all decimal precisions: 
`CometBatchKernelCodegen.isSupportedDataType` accepts any `DecimalType`, and 
inputs with precision > 18 read through a `BigDecimal` path on `DecimalVector` 
(precision ≤ 18 uses an unscaled-long fast path). No fallback, so no 
`expressions.md` caveat needed. I've added `DECIMAL(38, 18)` and `DECIMAL(38, 
0)` divisors to the fixture — both as columns (to exercise the wide-decimal 
Arrow read path) and as literals — and it passes under 
`checkSparkAnswerAndOperator`, which fails on any fallback. 
(`multiply_dt_interval.sql` has the same `DECIMAL(10, 2)` cap; happy to extend 
it in a follow-up.)
   
   3. **Spark versions** — `CometSqlFileTestSuite` runs in the `[expressions]` 
CI job on all five profiles (Spark 3.4/JDK 11/Scala 2.12, 3.5/JDK 17/Scala 
2.13, 4.0/JDK 21, 4.1/JDK 17, 4.2/JDK 17), so this fixture is exercised per 
Spark version before merge. Also, the dispatcher's `DurationVector` support 
isn't introduced here — it landed with `multiply_dt_interval` (#4900) and #4976 
and is already covered per-version on main; this PR's diff is just the serde 
registration, fixture, and docs. I additionally ran the fixture locally against 
the default Spark 4.1 profile.
   
   4. **Performance** — no standalone speedup claim: the dispatcher runs 
Spark's own generated code per batch, so the expression itself is at parity. 
The win is that the enclosing operator stays native instead of forcing a 
columnar→row transition and operator fallback. I've updated the PR description 
to say so explicitly.
   


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