Categories of SQL Functions
Last Updated :
28 Aug, 2024
SQL functions are powerful tools that help streamline queries, perform operations, and manipulate data efficiently. They are essential for handling various tasks within SQL queries and database management.
Functions in SQL can be broadly categorized into predefined (built-in) functions and user-defined functions. In this article, We will learn about the Categories of SQL Functions in detail with examples and so on.
Categories of Functions
Some of these categories of SQL functions are explained below.
- Single_row_function
- Aggregate_function
- Analytic_function
- Model_function
- User_defined_function
- Scalar functions
Single Row Function
Single-row functions are those functions that return a single result row for each row of the queried table or view. This function exists in Select lists, WHERE clause, START WITH, CONNECT BY clause, and HAVING clause.
- Numeric_functions
- Character_function
- Data_mining_function
- Datetime_functions
- Conversion_function
- Collection_function
- XML_function
1. Aggregate Function
While using Aggregate function it will returns single row result based on group of rows, instead of single rows.Aggregate function appears in Select lists and ORDER BY and HAVING clause.They are usually used with GROUP BY clause and SELECT Statements.
If we use GROUP BY clause, then Oracle applies aggregate function in the select list to all the rows in the queried table or view.
All the Aggregate functions except GROUPING and COUNT(*) ignores null values. You can also use NVL function in the argument to an aggregate function to substitute a value in place of null.
You can also nest aggregate functions.
For example:-
SELECT AVG(MAX(salary)
FROM employees
GROUP BY department_id
AVG(MAX(salary))
----------------
10925
Most frequently used Aggregate functions are AVG, COUNT, DENSE_RANK, MAX, MIN, RANK, SUM.
2. Analytic Function
Analytic function calculate aggregate value based on group of rows.Difference between Analytic function and Aggregate function is they return multiple rows for each group. The group of rows is termed as window and it is defined by analytic_clause.
Analytic function are the last set of operations performed in a query except the final ORDER BY clause.
- Analytic_clause
- Query_partition_clause
- Order_by_clause
- Windowing_clause
3. Model Function
Within SELECT statements, Model Functions can be used with model_clause.
Model Functions are:
- CV
- Iteration_Number
- Pesentnnv
- Presentv
- Previous
4. User Defined Function
You can use User defined functions in PL/SQL or Java to provide functionality that is not available in SQL or SQL built in functions. SQL functions and User defined functions can be appear anywhere, that is, wherever an expression occur.
For example, It can be used in:
- Select list of SELECT statement.
- Condition of WHERE clause.
- CONNECT BY, ORDER BY, START WITH and GROUP BY
- The VALUES clause of INSERT statement.
- The SET clause of UPDATE statement.
Basically we use CREATE Function to create User defined functions in SQL.
5. Scalar Function
You can use scalar functions in SQL to return a single value, based on the input value.
Input: SELECT UCASE(geeksforgeeks) ;
Output: GEEKSFORGEEKS
Most frequently used Scalar functions are UCASE() to convert a field to upper case, LCASE() to convert a field to lower case, LEN() to find the length of a text field, ROUND() to round the number of decimals specified, NOW() to find the current system date and time.
Conclusion
SQL functions, whether predefined or user-defined, play a crucial role in data manipulation and query optimization. Predefined functions provide a robust set of tools for common operations, while user-defined functions offer the flexibility to address specific needs and complex logic.
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