Selection Operation with Indexes
Conditions
Various conditions can be used with the help of ‘WHERE‘ clause:
- The WHERE clause is used to filter data in a database table. It allows you to specify conditions that each row must meet to be included in the result. These conditions can be comparisons, such as equal to (=), not equal to (!=), less than (<), greater than (>), and many others. You can also use logical operators like AND, OR, and NOT to combine multiple conditions. The database engine checks every row against these conditions. It then returns only the rows that satisfy all the specified criteria.
Syntax:
SELECT CustomerName, Age, CustomerID FROM Customer
WHERE Age>22;
- output:
- Similarly, there are many other operators which can you use, like
Selection Operation in Query Processing in DBMS
Regarding query processing, the term “selection” operation denotes fetching particular rows from a database table that fulfill some given condition or conditions. Why is this important? Because databases manage vast volumes of information, users must be able to narrow down their searches based on different parameters. The next few lines explain how selection works during query processing.
Databases are like huge libraries where information is stored in tables. The “selection” operation is like finding the books you need from all the shelves. It helps you pick out specific rows or records from a table that match certain rules or conditions you set. For example, if you want to find all the books written by a particular author, you would use the selection operation to look through the “Author” column and gather only those rows where the author’s name matches what you searched for. This operation is super important because it allows you to extract just the data you need from the vast amounts of information stored in databases. It’s often combined with other operations like choosing specific columns (projection), combining data from multiple tables (join), and calculating things like sums or averages (aggregation) to create complex database queries.