Github user jnh5y commented on a diff in the pull request:
https://github.com/apache/spark/pull/16329#discussion_r93262242
--- Diff: docs/sql-programming-guide.md ---
@@ -382,6 +382,52 @@ For example:
</div>
+## Aggregations
+
+The [built-in DataFrames
functions](api/scala/index.html#org.apache.spark.sql.functions$) mentioned
+before provide such common aggregations as `count()`, `countDistinct()`,
`avg()`, `max()`, `min()`, etc.
+While those functions are designed for DataFrames, Spark SQL also has
type-safe versions for some of them in
+[Scala](api/scala/index.html#org.apache.spark.sql.expressions.scalalang.typed$)
and
+[Java](api/java/org/apache/spark/sql/expressions/javalang/typed.html) to
work with strongly typed Datasets.
+Moreover, users are not limited to the predefined aggregate functions and
can create their own.
--- End diff --
I think it'd be worth showing an Spark SQL example using the
included/pre-defined functions. Since your example implements 'avg', maybe use
'min' / 'max'?
Alternatively, the example could be added to the SQL statements in the main
driver for the UserDefinedAggregateFunction implementations.
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