address feedback

Author: andygrove

common/src/main/scala/org/apache/comet/CometConf.scala

@@ -400,6 +400,9 @@ object CometConf extends ShimCometConf {
           "which can improve performance for wide tables while still providing " +
           "reasonable distribution.")
       .intConf
+      .checkValue(
+        v => v >= 0,
+        "The maximum number of columns to hash for round robin partitioning must be non-negative.")
       .createWithDefault(0)
 
   val COMET_EXEC_SHUFFLE_COMPRESSION_CODEC: ConfigEntry[String] =

docs/source/user-guide/latest/compatibility.md

@@ -87,7 +87,8 @@ impossible to match Spark's exact partition assignments.
 Instead of true round-robin assignment, Comet implements round-robin as hash partitioning on ALL columns. This
 achieves the same semantic goals:
 
-- **Even distribution**: Rows are distributed evenly across partitions
+- **Even distribution**: Rows are distributed evenly across partitions (as long as the hash varies sufficiently -
+  in some cases there could be skew)
 - **Deterministic**: Same input always produces the same partition assignments (important for fault tolerance)
 - **No semantic grouping**: Unlike hash partitioning on specific columns, this doesn't group related rows together