comphead commented on code in PR #4833:
URL: https://github.com/apache/datafusion-comet/pull/4833#discussion_r3530199790


##########
docs/source/contributor-guide/roadmap.md:
##########
@@ -24,15 +24,22 @@ helpful to have a roadmap for some of the major items that 
require coordination
 
 ## Window Expressions
 
-Native window execution is currently disabled by default due to known 
correctness issues ([#2721], [#2841]).
-In addition, dedicated window functions such as `rank`, `dense_rank`, 
`row_number`, `lag`, `lead`, `ntile`,
-`cume_dist`, `percent_rank`, and `nth_value` are not yet implemented and fall 
back to Spark ([#2705]). The
-goal is to enable windowed aggregates by default ([#4007]) and add the missing 
dedicated window functions.
-
-[#2705]: https://github.com/apache/datafusion-comet/issues/2705
-[#2721]: https://github.com/apache/datafusion-comet/issues/2721
-[#2841]: https://github.com/apache/datafusion-comet/issues/2841
-[#4007]: https://github.com/apache/datafusion-comet/issues/4007
+Native window execution runs by default (`spark.comet.exec.window.enabled`). 
The ranking functions (`rank`,
+`dense_rank`, `row_number`, `percent_rank`, `cume_dist`, `ntile`), value 
functions (`lag`, `lead`, `nth_value`,
+`first_value`, `last_value`), and the `count`, `min`, `max`, `sum`, and `avg` 
aggregates are accelerated.
+Remaining work is to close the gaps that still fall back to Spark: statistical 
aggregates (`stddev`, variance,

Review Comment:
   ```suggestion
   Remaining work is to close the gaps that still fall back to Spark: 
statistical aggregates (`stddev`, `variance`,
   ```



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