In this section, we'll see how fine-tuned syntax and best practices can significantly impact query performance.

A. Syntax Refinements and Best Practices

• Clarity and Readability:
  Write SQL statements that are not only correct but also easy to read and maintain. For instance:

  SELECT employee_id, first_name, last_name 
  FROM employees 
  WHERE department_id = 10;
        

  Instead of:

  SELECT e_id, fname, lname 
  FROM employees 
  WHERE d_id = 10;
        

• Appropriate Use of Aliases:
  Use column and table aliases to improve readability, especially in complex queries:

  SELECT e.employee_id, e.first_name, e.last_name, d.department_name
  FROM employees AS e
  JOIN departments AS d ON e.department_id = d.department_id;
  

• Consistent Formatting:
  Adopt a consistent formatting style for indentation, capitalization of SQL keywords, and alias naming. This not only aids review by others but can also reduce errors when modifying queries.

• Parameterization:
  Use parameterized queries to avoid SQL injection and to allow query caching by the database engine.

B. Subqueries vs. JOINs: When to Use Each

• Subqueries:
  Subqueries can be used in SELECT, FROM, or WHERE clauses. They are useful when you need to first compute a result before performing a join or filter operation. For example:

  SELECT employee_id, first_name, last_name
  FROM employees
  WHERE department_id IN (SELECT department_id FROM departments WHERE location_id = 1700);
  

  Use Cases and Considerations:

  • When the subquery returns a single or a small dataset.
  • When logical separation improves clarity, but know that some complex subqueries might be less performant than a well-indexed JOIN.

• JOINs:
  JOINs are generally more performant as they allow the use of indexes and are generally optimized by the DBMS. For example, instead of using a subquery:

  SELECT e.employee_id, e.first_name, e.last_name
  FROM employees AS e
  JOIN departments AS d ON e.department_id = d.department_id
  WHERE d.location_id = 1700;
  

  Use Cases and Considerations:

  • When merging rows from two or more tables efficiently is required.
  • When relational integrity must be enforced by retrieving data from multiple tables.

C. Query Rewriting Techniques for Performance Gains

• Avoid SELECT *:
  Only retrieve the columns you need. This minimizes I/O and reduces memory consumption.

  -- Problematic approach:
  SELECT * FROM orders;
  
  -- Optimized approach:
  SELECT order_id, order_date, customer_id FROM orders;
  

• Filtering Early:
  Use filters (WHERE clauses) as early as possible in your queries to reduce the number of rows processed:

  SELECT order_id, order_date
  FROM orders
  WHERE order_date >= '2023-01-01';
  

• Index Usage:
  Ensure that indexed columns appear in JOIN conditions and WHERE filters to take advantage of faster data access.

• Using Derived Tables and Common Table Expressions (CTEs): Recursive Queries and Modular Query Design

  • Introduction to CTEs:
    CTEs improve the readability and maintainability of SQL queries. They provide a way to define temporary result sets that can be referenced within a SELECT, INSERT, UPDATE, or DELETE statement.

  • Non-Recursive CTE Example:

    WITH TopOrders AS (
        SELECT order_id, amount
        FROM orders
        WHERE amount > 1000
    )
    SELECT * FROM TopOrders;
    

  • Recursive CTE Example:
    Recursive queries are particularly useful for hierarchical data (e.g., organizational charts, bill of materials).

    WITH EmployeeHierarchy AS (
        SELECT employee_id, manager_id, first_name, last_name, 0 AS level
        FROM employees
        WHERE manager_id IS NULL
        
        UNION ALL
        
        SELECT e.employee_id, e.manager_id, e.first_name, e.last_name, eh.level + 1
        FROM employees e
        JOIN EmployeeHierarchy eh ON e.manager_id = eh.employee_id
    )
    SELECT * FROM EmployeeHierarchy;
    

  • Modular Query Design:
    CTEs enable decomposition of complex queries into smaller, logical units that can be developed, tested, and optimized individually.