viirya commented on code in PR #1210:
URL: https://github.com/apache/datafusion-comet/pull/1210#discussion_r1902636032


##########
docs/source/user-guide/tuning.md:
##########
@@ -23,11 +23,52 @@ Comet provides some tuning options to help you get the best 
performance from you
 
 ## Memory Tuning
 
-Comet shares an off-heap memory pool between Spark and Comet. This requires 
setting `spark.memory.offHeap.enabled=true`.
-If this setting is not enabled, Comet will not accelerate queries and will 
fall back to Spark.
+### Unified Memory Management with Off-Heap Memory
+
+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`.
+
+### Dedicated Comet Memory Pools
+
+If the `spark.memory.offHeap.enabled` setting is not enabled then Comet will 
use its own dedicated memory pools that
+are not shared with Spark. This requires additional configuration settings to 
be specified to set the size and type of
+memory pool to use.
+
+The size of the pool can be set explicitly with `spark.comet.memoryOverhead`. 
If this setting is not specified then
+the memory overhead will be calculated by multiplying the executor memory by 
`spark.comet.memory.overhead.factor`
+(defaults to `0.2`).
+
+The type of pool can be specified with `spark.comet.exec.memoryPool`. The 
default setting is `greedy_task_shared`.
+
+The valid pool types are:
+
+- `greedy`
+- `greedy_global`
+- `greedy_task_shared`
+- `fair_spill`
+- `fair_spill_global`
+- `fair_spill_task_shared`
+
+Pool types ending with `_global` use a single global memory pool between all 
tasks.

Review Comment:
   ```suggestion
   Pool types ending with `_global` use a single global memory pool between all 
tasks on same executor.
   ```



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