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maropu committed Apr 13, 2020
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24 changes: 6 additions & 18 deletions docs/_data/menu-sql.yaml
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- text: Functions
url: sql-ref-functions.html
subitems:
- text: Build-in Functions
url: sql-ref-functions-builtin.html
subitems:
- text: Build-in Aggregate Functions
url: sql-ref-functions-builtin-aggregate.html
- text: Build-in Array Functions
url: sql-ref-functions-builtin-array.html
- text: Build-in Date Time Functions
url: sql-ref-functions-builtin-date-time.html
- text: UDFs (User-Defined Functions)
url: sql-ref-functions-udf.html
subitems:
- text: Scalar UDFs (User-Defined Functions)
url: sql-ref-functions-udf-scalar.html
- text: UDAFs (User-Defined Aggregate Functions)
url: sql-ref-functions-udf-aggregate.html
- text: Integration with Hive UDFs/UDAFs/UDTFs
url: sql-ref-functions-udf-hive.html
- text: Scalar UDFs (User-Defined Functions)
url: sql-ref-functions-udf-scalar.html
- text: UDAFs (User-Defined Aggregate Functions)
url: sql-ref-functions-udf-aggregate.html
- text: Integration with Hive UDFs/UDAFs/UDTFs
url: sql-ref-functions-udf-hive.html
- text: Datetime Pattern
url: sql-ref-datetime-pattern.html
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11 changes: 10 additions & 1 deletion docs/sql-ref-functions.md
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limitations under the License.
---

Spark SQL defines commonly used functions as built-in functions. It also provides User-Defined Functions (UDFs) to allow users to define their own functions when the system’s built-in functions are not enough to perform the desired task.
Spark SQL provides two function features to meet a wide range of user needs: built-in functions and user-defined functions (UDFs).
Built-in functions are commonly used routines that Spark SQL predefines and a complete list of the functions can be found in the [Built-in Functions](api/sql/) API document. UDFs allow users to define their own functions when the system’s built-in functions are not enough to perform the desired task.

### UDFs (User-Defined Functions)

User-Defined Functions (UDFs) are a feature of Spark SQL that allows users to define their own functions when the system's built-in functions are not enough to perform the desired task. To use UDFs in Spark SQL, users must first define the function, then register the function with Spark, and finally call the registered function. The User-Defined Functions can act on a single row or act on multiple rows at once. Spark SQL also supports integration of existing Hive implementations of UDFs, UDAFs and UDTFs.

* [Scalar User-Defined Functions (UDFs)](sql-ref-functions-udf-scalar.html)
* [User-Defined Aggregate Functions (UDAFs)](sql-ref-functions-udf-aggregate.html)
* [Integration with Hive UDFs/UDAFs/UDTFs](sql-ref-functions-udf-hive.html)

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