andygrove commented on code in PR #1525:
URL: https://github.com/apache/datafusion-comet/pull/1525#discussion_r2003529179


##########
docs/source/user-guide/tuning.md:
##########
@@ -17,18 +17,96 @@ specific language governing permissions and limitations
 under the License.
 -->
 
-# Tuning Guide
+# Comet Tuning Guide
 
 Comet provides some tuning options to help you get the best performance from 
your queries.
 
 ## Memory Tuning
 
-### Unified Memory Management with Off-Heap Memory
+It is necessary to specify how much memory Comet can use in addition to memory 
already allocated to Spark. In some
+cases, it may be possible to reduce the amount of memory allocated to Spark so 
that overall memory allocation is
+the same or lower than the original configuration. In other cases, enabling 
Comet may require allocating more memory
+than before. See the [Determining How Much Memory to Allocate] section for 
more details.
 
-The recommended way to share memory between Spark and Comet is to set 
`spark.memory.offHeap.enabled=true`. This allows
-Comet to share an off-heap memory pool with Spark. The size of the pool is 
specified by `spark.memory.offHeap.size`. For more details about Spark off-heap 
memory mode, please refer to Spark documentation: 
https://spark.apache.org/docs/latest/configuration.html.
+[Determining How Much Memory to Allocate]: 
#determining-how-much-memory-to-allocate
 
-The type of pool can be specified with `spark.comet.exec.memoryPool`.
+Comet supports Spark's on-heap (the default) and off-heap mode for allocating 
memory. However, we strongly recommend
+using off-heap mode. Comet has some limitations when running in on-heap mode, 
such as requiring more memory overall,
+and requiring shuffle memory to be separately configured.
+
+### Configuring Comet Memory in Off-Heap Mode
+
+The recommended way to allocate memory for Comet is to set 
`spark.memory.offHeap.enabled=true`. This allows
+Comet to share an off-heap memory pool with Spark, reducing the overall memory 
overhead. The size of the pool is
+specified by `spark.memory.offHeap.size`. For more details about Spark 
off-heap memory mode, please refer to
+Spark documentation: https://spark.apache.org/docs/latest/configuration.html.

Review Comment:
   I filed https://github.com/apache/datafusion-comet/issues/1557



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