In the context of DBMS, aggregation refers to the process of combining multiple rows of data into a single result. It is typically used in conjunction with aggregate functions to perform calculations on groups of data.
Aggregate functions, such as SUM, AVG, COUNT, MAX, and MIN, operate on a set of values and return a single result. When combined with the GROUP BY clause, these functions allow you to group rows based on one or more columns and calculate aggregate values for each group.
Here’s an example to illustrate aggregation in DBMS:
Consider a table called “Sales” with the following columns: “Product”, “Region”, and “SalesAmount”.
| Product | Region | SalesAmount | |----------|---------|-------------| | A | East | 100 | | B | West | 200 | | A | East | 150 | | B | East | 50 | | A | West | 300 |
If you want to calculate the total sales amount for each product, you can use the SUM function with the GROUP BY clause:
SELECT Product, SUM(SalesAmount) AS TotalSales FROM Sales GROUP BY Product;
The result will be:
| Product | TotalSales | |----------|------------| | A | 550 | | B | 250 |
In this example, the rows are grouped by the “Product” column, and the SUM function calculates the total sales amount for each group.
Aggregation is useful for generating summary reports, analyzing data, and obtaining insights from large datasets. It allows you to perform calculations on groups of data without the need for manual iteration and computation.