Parameterized queries play a very critical role in the database-driven applications by proving a way to pass the parameters (values) into SQL statements.
In this tutorial, we will learn how to create and work with parameterized queries in the SQL ecosystem. It is good to keep in mind that the format and syntax of parameterized queries can vary depending on the database engine.
What Is a Parameterized Query?
In SQL, a parameterized query, also known as prepared statement or parameterized statement, is an SQL query that contains the placeholder values which can adjust dynamically and can be replaced during the query execution.
In most cases, the placeholders in a parameterized query are represented by question marks (?) or named parameters.
Syntax:
The syntax for parameterized queries may vary slightly depending on the database engine. However, here is a general syntax that can represent the parameterized queries:
SELECT column1, column2, ...
FROM table
WHERE condition = ?;
-- For SQL Server
SELECT column1, column2, ...
FROM table
WHERE condition = @parameter_name;
In the example query:
- The “?” or “parameter_name” refers to the placeholders which contains the dynamic values.
- The “column1, column2” represents the columns that we wish to retrieve.
- The table refers to the table that we wish to query.
- The condition is a filter condition that specifies which rows we wish to retrieve.
Example: Retrieve the Customer Information
Let us look at some examples that can help to demonstrate how to use and work with parameterized queries in a real database.
For this example, we will use the Pakila sample database provided in PostgreSQL.
Suppose we want to retrieve the customer information based on their customer ID. We can run a query as follows:
FROM customer
WHERE customer_id = ?;
The given query retrieves the customer’s ID, first name, last name, and email based on the provided customer ID.
Conclusion
In this post, we learned how to use and work with SQL parameterized queries which is a crucial tool for building a dynamic and database-driven application.