huaxingao commented on a change in pull request #28290:
URL: https://github.com/apache/spark/pull/28290#discussion_r412681949
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File path: docs/sql-getting-started.md
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@@ -347,7 +347,8 @@ For example:
</div>
## Scalar Functions
-(to be filled soon)
+
+Scalar functions are functions that return a single value per row, as opposed
to aggregation functions, which return a value for a group of rows. Spark SQL
supports a variety of built-in scalar functions such as [Array
Functions](sql-ref-functions-builtin.html#array-functions), [Map
Functions](sql-ref-functions-builtin.html#map-functions), [Date and Timestamp
Functions](sql-ref-functions-builtin.html#date-and-timestamp-functions), etc.
It also supports [User Defined Scalar
Functions](sql-ref-functions-udf-scalar.html).
Review comment:
I used Scalar function instead of built-in function (because the next
paragraph is for aggregations). I don't want to talk about window function
because I think window function is still sort of aggregation, even thought it
returns result for each row.
I can't link it to builtin function because builtin function contains
aggregation function, so I link to each group of the builtin scalar functions.
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