andygrove commented on code in PR #5496:
URL: https://github.com/apache/datafusion-comet/pull/5496#discussion_r4303802947


##########
docs/source/user-guide/latest/tuning/transitions.md:
##########
@@ -38,3 +38,25 @@ columns and nested fields. If profiling shows these 
conversions dominating a que
 exceeds the threshold to Spark row-based execution — Comet removes the stage's 
native operators rather than running a
 mix of native and fallback operators joined by repeated conversions — which 
can be cheaper than paying the
 expensive conversions again and again.
+
+## Experimental: Direct Columnar-to-Row Conversion
+
+When the JVM columnar-to-row operator is in use 
(`spark.comet.exec.columnarToRow.native.enabled=false`),
+setting `spark.comet.exec.columnarToRow.direct.enabled=true` enables an 
experimental converter that writes
+values straight from Arrow buffers into Spark's row format without allocating 
an object per value. This is
+most beneficial for decimal-heavy schemas, where the default conversion 
allocates a `Decimal` object per

Review Comment:
   Thanks, this is covered now. The section says that schemas with strings and 
no expensive decimals can get slower, quotes the 12.1 vs 9.4 ns/row numbers, 
and tells readers to measure a representative workload before enabling the 
flag. Resolving.



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