What are the analytical functions in sql

Analytical functions in SQL are used to analyze data collections and provide aggregation and cumulative results, including: Aggregation functions: Calculate the sum, count, maximum, minimum, and average of a data set or grouped data. Window functions: Calculate values between the current row and related rows (windows), such as row number, rank and leading value. Sorting function: Sort data, such as by department or date.

Analytical functions in SQL

Analytical functions are a special type of function used to analyze data collections And returnsaggregated results or cumulative results. They are widely used in data analysis and reporting to help users extract valuable insights from data.

Main types:

• Aggregation functions:Calculate the value of the entire data set or grouped data, such as SUM, COUNT, MAX, MIN and AVG.
• Window functions:Calculate the value between the current row and the related row (window), such as ROW_NUMBER(), RANK() and LEAD().
• Sort function:Sort data, such as ORDER BY, PARTITION BY and ROW_NUMBEROVER().

Purpose:

• Calculate cumulative sum, moving average and other time series analysis
• Rank, group and sum data Aggregation
• Create complex reports that show trends and patterns
• Extract advanced insights such as peer comparisons and predictive analytics

Example:

The following example calculates the total sales for each department using theSUM()andPARTITION BYfunctions in SQL:

SELECT department, SUM(sales) FROM sales GROUP BY department;

Note:

• Analytical functions differ from traditional scalar functions in that they return the result of an entire row or set.
• Different database management systems (DBMS) may support different sets of analytic functions.
• When using analysis functions, you should pay attention to the window frame and sorting rules to ensure the accuracy of the results.

The above is the detailed content of What are the analytical functions in sql. For more information, please follow other related articles on the PHP Chinese website!