Best Practices for Writing SQL Queries: Expert Tips for Clean, Efficient, and Fast Code

SQL (Structured Query Language) is the backbone of database management and querying. Whether you’re just starting with SQL or you’re an experienced developer, writing efficient and optimized SQL queries is crucial to ensure smooth database performance. Poorly written SQL queries can lead to slower processing times, inefficient resource usage, and even errors in data retrieval.

In this blog post, we’ll dive into the best practices for writing SQL queries that are not only effective but also easy to maintain. We’ll cover key tips, common mistakes to avoid, and practical examples to help you write better, faster, and cleaner SQL code.

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1. Filter Early, Aggregate Late

Why Filtering Early Helps

One of the most important principles in writing efficient SQL queries is applying filtering conditions as early as possible. This principle is important because filtering rows before performing any aggregation reduces the number of rows that need to be processed, which improves query performance. SQL queries can often be quite resource-intensive, and applying conditions like WHERE clauses early ensures the database engine has to work with a smaller, more manageable dataset before performing computationally expensive operations like aggregation.

When to Aggregate

Once you’ve filtered out the data you don’t need, you should proceed to perform any necessary aggregations (e.g., using SUM(), AVG(), COUNT()) in the HAVING or SELECT clauses.

Example:

-- Good Practice: Filter early, then aggregate
SELECT department, COUNT(*) AS employee_count
FROM employees
WHERE status = 'Active'  -- Apply filter early
GROUP BY department;

In this example, we first filter out employees who are not active and only then calculate the count for each department. This reduces the rows that the COUNT function must process, making the query faster.

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2. Use Table Aliases When Joining Multiple Tables

What Are Table Aliases?

When joining multiple tables in SQL, using table aliases can significantly improve the readability of your query. An alias is essentially a shorthand name that makes it easier to reference tables and columns, especially when the query involves multiple tables. This is particularly useful in complex queries that join many tables or when the table names are long.

Why Table Aliases Improve Readability

Using table aliases can make your SQL code easier to follow. It avoids repetitive table names and allows you to clearly distinguish between columns that belong to different tables.

Example:

-- Using aliases for better readability
SELECT e.name, d.department_name
FROM employees AS e
JOIN departments AS d ON e.department_id = d.id;

In this example:

• employees AS e gives the employees table the alias e.
• departments AS d gives the departments table the alias d.

With these aliases, the query is much easier to read, especially when dealing with long column names or more complex joins.

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3. Never Use SELECT *: Specify Columns Explicitly

Why Avoid SELECT *?

It’s tempting to use SELECT * to select all columns from a table, especially when you’re just starting with SQL or writing quick queries. However, this practice can hurt performance, especially when dealing with large datasets. SELECT * retrieves all columns from the specified table(s), which may not be necessary for your application, resulting in wasted resources.

Specify Only the Columns You Need

By explicitly specifying only the columns you need, you improve both the readability of your query and its performance. This minimizes the data the database must retrieve and transmit, making your queries more efficient.

Example:

-- Bad Practice
SELECT * FROM employees;  -- Retrieves all columns

-- Good Practice
SELECT name, department FROM employees;  -- Retrieves only necessary columns

By listing specific columns (name, department) in the SELECT clause, you reduce the data returned by the query, which improves performance and makes the query easier to understand.

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4. Add Useful Comments Where Necessary

When to Comment

While comments can be very useful for explaining complex logic or reasoning behind certain query design choices, over-commenting or commenting trivial operations can clutter your SQL code. Good practice is to add comments only when the logic of a section of code might not be immediately clear, or if there is a specific reason you chose a certain approach over another.

Best Practice for Commenting

When you write complex SQL queries, it’s helpful to add comments at the beginning of major blocks of logic. Be sure to avoid over-commenting, which could make the code harder to read.

Example:

-- This query counts the number of active employees in each department
SELECT department, COUNT(*) AS active_employees
FROM employees
WHERE status = 'Active'
GROUP BY department;

In this example, the comment explains what the query does, making it easier for someone else (or yourself in the future) to quickly understand the query’s purpose.

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5. Use Joins Instead of Correlated Subqueries

Why Joins Are Better

Correlated subqueries are often less efficient because they are executed for each row in the outer query. This results in redundant operations, which can degrade performance, especially when working with large datasets. In contrast, using explicit JOIN operations typically leads to more efficient queries.

Preferred Approach: Joins

Using JOIN operations not only simplifies your query but also optimizes performance, as the database engine can handle joins more efficiently than correlated subqueries.

Example:

-- Bad Practice: Correlated subquery
SELECT e.name, e.department
FROM employees e
WHERE e.salary > (SELECT AVG(salary) FROM employees);

-- Good Practice: Using JOIN
SELECT e.name, e.department
FROM employees e
JOIN (SELECT AVG(salary) AS avg_salary FROM employees) avg
ON e.salary > avg.avg_salary;

In this case, using a JOIN with a subquery in the FROM clause can be more efficient than using a correlated subquery in the WHERE clause.

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6. Create Common Table Expressions (CTEs) Instead of Multiple Subqueries

What Are CTEs?

Common Table Expressions (CTEs) are temporary result sets that you can refer to within the scope of a SELECT, INSERT, UPDATE, or DELETE statement. CTEs are a great way to simplify your SQL queries by breaking them into smaller, more manageable parts, especially when dealing with complex or nested subqueries.

Why Use CTEs?

CTEs improve the readability and maintainability of your code. They allow you to define a temporary result set once and reference it multiple times in your query. This can help avoid repetitive code and make your query easier to understand.

Example:

-- Bad Practice: Multiple subqueries
SELECT department, COUNT(*) 
FROM (SELECT * FROM employees WHERE status = 'Active') AS active_employees
GROUP BY department;

-- Good Practice: Using CTEs
WITH active_employees AS (
    SELECT * FROM employees WHERE status = 'Active'
)
SELECT department, COUNT(*) 
FROM active_employees
GROUP BY department;

In the second query, we define a CTE called active_employees that holds the subset of employees with an active status. This makes the query cleaner and easier to maintain.

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7. Use JOIN Keywords Instead of Putting Join Conditions in WHERE

Why This Is Important

While it’s technically possible to write a join condition in the WHERE clause, it’s generally a better practice to use the JOIN keyword to explicitly indicate the relationship between tables. This not only makes your code more readable but also reduces the risk of writing incorrect joins.

Example:

-- Bad Practice: Using WHERE for joins
SELECT e.name, d.department_name
FROM employees e, departments d
WHERE e.department_id = d.id;

-- Good Practice: Using JOIN keyword
SELECT e.name, d.department_name
FROM employees e
JOIN departments d ON e.department_id = d.id;

In this example, using the JOIN keyword makes the relationship between the employees and departments tables clear and explicit, improving the query’s readability and maintainability.

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8. Never Use ORDER BY in Subqueries

Why Avoid ORDER BY in Subqueries?

Adding an ORDER BY clause inside a subquery can degrade query performance because it forces the database engine to sort the data before executing the outer query. This is usually unnecessary, and in fact, many database systems don’t even allow ORDER BY in subqueries.

When to Use ORDER BY

If sorting is required, it’s best to apply the ORDER BY clause only in the outer query, where you want the final result to be ordered.

Example:

-- Bad Practice: Ordering in subquery
SELECT * FROM (
    SELECT * FROM employees ORDER BY name
) AS sorted_employees;

-- Good Practice: Ordering in outer query
SELECT * FROM employees ORDER BY name;

By placing the ORDER BY in the outer query, the database engine can sort the results of the final query without having to process unnecessary sorting within the subquery.

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9. Use UNION ALL Instead of UNION When Duplicates Are Not a Concern

Why UNION ALL is Faster

The UNION operator removes duplicate rows by default, which requires extra processing. If you’re certain that the data you’re combining won’t contain duplicates, using UNION ALL is a faster option because it simply appends the result sets without checking for duplicates.

Example:

-- Bad Practice: Using UNION (removes duplicates)
SELECT name FROM employees
UNION
SELECT name FROM contractors;

-- Good Practice: Using UNION ALL (no duplicates removed)
SELECT name FROM employees
UNION ALL
SELECT name FROM contractors;

By using UNION ALL, the query performs faster because it avoids the overhead of duplicate elimination.

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Conclusion: Key Takeaways for Writing Efficient SQL Queries

By following these best practices for writing SQL queries, you’ll not only improve your query performance but also make your code more readable, maintainable, and efficient. Here’s a quick recap:

• Filter early, aggregate late

to improve performance.

• Use table aliases for better readability, especially when joining tables.
• Never use SELECT *—only select the columns you need.
• Comment your queries where necessary for clarity.
• Use joins instead of correlated subqueries to enhance performance.
• Leverage CTEs for simplifying complex queries.
• Use explicit JOIN keywords rather than placing conditions in the WHERE clause.
• Avoid ORDER BY in subqueries.
• Use UNION ALL when duplicates don’t matter to speed up your query.

By adopting these strategies, you’ll write better SQL queries that are faster, cleaner, and more efficient.