docs(spark): list Spark-compatible aggregates in aggregations guide

Add avg, try_sum, collect_list, and collect_set under a dedicated
Spark-Compatible Functions entry, with a note that the
datafusion.functions.spark namespace mirrors Spark semantics and may
differ from the like-named built-ins. Adds a (spark-functions) anchor
for the cross-reference.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Author: timsaucer

docs/source/user-guide/common-operations/aggregations.md

@@ -412,6 +412,16 @@ The available aggregate functions are:
     \- {py:meth}`datafusion.expr.GroupingSet.rollup`
     \- {py:meth}`datafusion.expr.GroupingSet.cube`
     \- {py:meth}`datafusion.expr.GroupingSet.grouping_sets`
+11. Spark-Compatible Functions
+    : - {py:func}`datafusion.functions.spark.avg`
+      - {py:func}`datafusion.functions.spark.try_sum`
+      - {py:func}`datafusion.functions.spark.collect_list`
+      - {py:func}`datafusion.functions.spark.collect_set`
+
+The functions in the `datafusion.functions.spark` namespace mirror Apache
+Spark semantics, which can differ from the DataFusion built-ins of the same
+name. They live in a separate namespace so you opt in explicitly. See
+{ref}`spark-functions` for the full catalog and the semantic differences.
 
 ## User-Defined Aggregate Functions
 

docs/source/user-guide/common-operations/spark-functions.md

@@ -17,6 +17,8 @@
   under the License.
 -->
 
+(spark-functions)=
+
 # Spark-Compatible Functions
 
 DataFusion ships Spark-compatible versions of a wide set of functions