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 returns aggregated 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 the SUM()
and PARTITION BY
functions 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.
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SUM in Oracle is used to calculate the sum of non-null values, while COUNT counts the number of non-null values of all data types, including duplicate values.

The SUM() function in SQL is used to calculate the sum of numeric columns. It can calculate sums based on specified columns, filters, aliases, grouping and aggregation of multiple columns, but only handles numeric values and ignores NULL values.

The SQL SUM function calculates the sum of a set of numbers by adding them together. The operation process includes: 1. Identifying the input value; 2. Looping the input value and converting it into a number; 3. Adding each number to accumulate a sum; 4. Returning the sum result.

Aggregate functions in SQL are used to calculate and return a single value for a set of rows. Common aggregation functions include: Numeric aggregation functions: COUNT(), SUM(), AVG(), MIN(), MAX() Row set aggregation functions: GROUP_CONCAT(), FIRST(), LAST() Statistical aggregation functions: STDDEV (), VARIANCE() optional aggregate functions: COUNT(DISTINCT), TOP(N)

The COUNT function in Oracle is used to count non-null values in a specified column or expression. The syntax is COUNT(DISTINCT <column_name>) or COUNT(*), which counts the number of unique values and all non-null values respectively.

MySQL's AVG() function is used to calculate the average of numeric values. It supports multiple usages, including: Calculate the average quantity of all sold products: SELECT AVG(quantity_sold) FROM sales; Calculate the average price: AVG(price); Calculate the average sales volume: AVG(quantity_sold * price). The AVG() function ignores NULL values, use IFNULL() to calculate the average of non-null values.

Non-aggregated columns in SQL are columns that store single record values and are not processed by aggregate functions. These columns contain unique values for each record and are used to identify, categorize, or filter the data.

Grouped data can be sorted using GROUP BY and ORDER BY: 1. GROUP BY groups data; 2. ORDER BY sorts each group of data.
