December 18, 2024
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SQL Syntax: Understanding SQL Keywords and Structure

Pankaj Kumar022 mins
SQL-Syntax

Did you know that SQL powers more than 80% of all database systems out there? 🌐 With just a few simple keywords, you can unlock the secrets of structured data! 🗃️
Curious?

Let’s dive into the world of SQL syntax and unravel the magic behind these powerful queries.

Table of Contents

SQL Keywords: The Building Blocks

Definition and significance of SQL keywords

SQL keywords are reserved words in the SQL language that have a specific meaning and purpose. They help you interact with a database by forming SQL statements, which are the basic units of SQL queries.

These keywords are crucial for managing, manipulating, and retrieving data efficiently.

Examples of commonly used SQL keywords

SELECT

The SELECT keyword is used to retrieve data from one or more tables in a database. It is followed by the columns you want to retrieve.

Example:

SELECT first_name, last_name FROM employees;

FROM

The FROM keyword specifies the table(s) where you want to fetch the data. It is used along with the SELECT keyword.

Example:

SELECT first_name, last_name FROM employees;

WHERE

The WHERE keyword is used to filter records based on specified conditions. It follows the FROM keyword.

Example:

SELECT first_name, last_name FROM employees WHERE salary > 50000;

GROUP BY

The GROUP BY keyword is used to group rows with the same values in specified columns. It is often used with aggregate functions like COUNT, SUM, AVG, etc.

Example:

SELECT department, COUNT(*) as num_employees FROM employees GROUP BY department;

HAVING

The HAVING keyword is used to filter the results of a GROUP BY query based on a condition that involves an aggregate function.

Example:

SELECT department, COUNT(*) as num_employees FROM employees GROUP BY department HAVING num_employees > 10;

ORDER BY

The ORDER BY keyword is used to sort the result set based on one or more columns in ascending (ASC) or descending (DESC) order.

Example:

SELECT first_name, last_name, salary FROM employees ORDER BY salary DESC;

INSERT INTO

The INSERT INTO keyword is used to insert new records into a table. It specifies the table and the values to be inserted.

Example:

INSERT INTO employees (first_name, last_name, salary) VALUES ('John', 'Doe', 60000);

UPDATE

The UPDATE keyword is used to modify existing records in a table. It is followed by the SET keyword to specify the new values and the WHERE keyword to define the conditions.

Example:

UPDATE employees SET salary = salary * 1.1 WHERE department = 'Sales';

DELETE

The DELETE keyword is used to remove records from a table based on specified conditions.

Example:

DELETE FROM employees WHERE last_name = 'Smith';

Case sensitivity and best practices

SQL keywords are not case-sensitive; however, it’s a common best practice to write them in uppercase for better readability. Consistently formatting your SQL queries will make it easier for others to understand and maintain your code.

SQL Statements: Combining Keywords and Structure

The structure of a typical SQL statement

A SQL statement is a combination of SQL keywords, operators, and identifiers that follow specific syntax rules.

The structure of a typical SQL statement consists of a starting keyword (e.g., SELECT, INSERT, UPDATE, DELETE) followed by additional keywords and expressions that define the operation.

Basic syntax rules for writing SQL statements

  • Use SQL keywords in the correct order.
  • Separate keywords, identifiers, and operators with spaces.
  • Enclose string literals in single quotes (‘ ‘).
  • Use commas (,) to separate multiple columns or values.
  • Terminate each SQL statement with a semicolon (;).
  • Use parentheses to control the order of evaluation for expressions or to group conditions.

Common SQL statement examples

SELECT statement for data retrieval

The SELECT statement retrieves data from one or more tables based on specified conditions.

Example:

SELECT first_name, last_name, salary
FROM employees
WHERE salary > 50000
ORDER BY salary DESC;

This statement selects the first name, last name, and salary of employees with a salary greater than 50,000, ordered by salary in descending order.

INSERT statement for adding data

The INSERT statement adds new records to a table by specifying the target table and the values to be inserted.

Example:

INSERT INTO employees (first_name, last_name, department, salary)
VALUES ('Jane', 'Doe', 'Marketing', 55000);

This statement inserts a new employee record with the given values for first name, last name, department, and salary.

UPDATE statement for modifying data

The UPDATE statement modifies existing records in a table by specifying the target table, the new values, and the conditions for the update.

Example:

UPDATE employees
SET salary = salary * 1.1, job_title = 'Senior Developer'
WHERE years_of_experience >= 5 AND job_title = 'Developer';

This statement updates the salary and job title of employees with 5 or more years of experience who currently have the job title ‘Developer’.

DELETE statement for removing data

The DELETE statement removes records from a table based on specified conditions.

Example:

DELETE FROM employees
WHERE last_name = 'Smith' AND department = 'HR';

This statement deletes all records of employees with the last name ‘Smith’ who work in the HR department.

Advanced SQL Syntax and Structures

Subqueries and nested queries

Subqueries are SQL queries nested within another query, often used to filter or calculate values based on results from another query.

Example (using subquery in WHERE clause):

SELECT first_name, last_name, salary
FROM employees
WHERE salary > (SELECT AVG(salary) FROM employees);

This statement selects employees with salaries greater than the average salary of all employees.

JOIN operations

JOIN operations combine records from two or more tables based on a related column between them. There are four main types of JOIN operations:

INNER JOIN

The INNER JOIN returns only the rows from both tables that have matching values in the specified columns.

Example:

SELECT employees.first_name, employees.last_name, departments.name AS department
FROM employees
INNER JOIN departments ON employees.department_id = departments.id;

LEFT JOIN (or LEFT OUTER JOIN)

The LEFT JOIN returns all rows from the left table and the matched rows from the right table. If no match is found, NULL values are returned for right table columns.

Example:

SELECT employees.first_name, employees.last_name, departments.name AS department
FROM employees
LEFT JOIN departments ON employees.department_id = departments.id;

This statement returns the first name, last name, and department name of all employees, including those without a department.

RIGHT JOIN (or RIGHT OUTER JOIN)

The RIGHT JOIN returns all rows from the right table and the matched rows from the left table. If no match is found, NULL values are returned for left table columns.

Example:

SELECT employees.first_name, employees.last_name, departments.name AS department
FROM employees
RIGHT JOIN departments ON employees.department_id = departments.id;

This statement returns the first name, last name, and department name for all employees and all departments, including departments without any employees.

FULL JOIN (or FULL OUTER JOIN)

The FULL JOIN returns all rows when there’s a match in either the left or right table. If no match is found, NULL values are returned for the non-matching table columns.

Example:

SELECT employees.first_name, employees.last_name, departments.name AS department
FROM employees
FULL JOIN departments ON employees.department_id = departments.id;

This statement returns the first name, last name, and department name for all employees and all departments, including employees without a department and departments without employees.

UNION and UNION ALL

UNION and UNION ALL are used to combine the result sets of two or more SELECT statements into a single result set.

  • UNION removes duplicate rows from the combined result set.
  • UNION ALL retains duplicate rows in the combined result set.
SELECT first_name, last_name FROM employees WHERE department = 'Sales'
UNION
SELECT first_name, last_name FROM employees WHERE department = 'Marketing';

This statement returns a single result set with the first and last names of employees from both the Sales and Marketing departments, without duplicate rows.

Conditional expressions with CASE

The CASE expression allows you to perform conditional logic in SQL queries by returning a value based on specified conditions.

Example:

SELECT first_name, last_name, salary,
       CASE
           WHEN salary <= 50000 THEN 'Low'
           WHEN salary <= 75000 THEN 'Medium'
           ELSE 'High'
       END AS salary_range
FROM employees;

This statement returns the first name, last name, salary, and a calculated salary range (‘Low’, ‘Medium’, or ‘High’) for each employee based

SQL Functions and Stored Procedures

Overview of SQL functions

SQL functions are pre-defined operations that perform calculations or transformations on values, columns, or rows in a table. Functions can be used in various parts of an SQL query, such as the SELECT, WHERE, or HAVING clauses.

Built-in functions

Built-in functions are provided by the database system and are available for use in SQL queries. There are three main types of built-in functions:

Aggregate functions

Aggregate functions perform calculations on a group of rows and return a single summary value.

Examples:

  • COUNT: Counts the number of rows in a group.
  • SUM: Calculates the sum of values in a group.
  • AVG: Calculates the average of values in a group.
  • MIN: Finds the minimum value in a group.
  • MAX: Finds the maximum value in a group.

Example:

SELECT department, COUNT(*) as num_employees, AVG(salary) as avg_salary
FROM employees
GROUP BY department;

This statement returns the number of employees and the average salary per department.

Scalar functions

Scalar functions perform operations on single values and return a single value as a result.

Examples:

  • UPPER: Converts a string to uppercase.
  • LOWER: Converts a string to lowercase.
  • LENGTH: Returns the length of a string.
  • SUBSTRING: Extracts a substring from a string.
  • ROUND: Rounds a numeric value.

Example:

SELECT first_name, UPPER(last_name) as last_name_upper, ROUND(salary, 0) as rounded_salary
FROM employees;

This statement returns the first name, last name in uppercase, and the rounded salary of employees.

Window functions

Window functions perform calculations across a set of rows related to the current row, allowing for complex operations like ranking, cumulative sums, or moving averages.

Examples:

  • ROW_NUMBER: Assigns a unique number to each row in the result set.
  • RANK: Assigns a unique rank to each distinct value in a result set.
  • DENSE_RANK: Assigns a rank to each value in a result set, with no gaps in ranking numbers.
  • NTILE: Divides the result set into a specified number of groups.

Example:

SELECT first_name, last_name, salary,
       RANK() OVER (PARTITION BY department ORDER BY salary DESC) as rank_in_department
FROM employees;

This statement returns the first name, last name, salary, and rank of employees within their department based on salary.

User-defined functions and stored procedures

User-defined functions (UDFs) and stored procedures are custom functions or procedures written by users and stored in the database. They allow for code reuse, modularization, and better performance.

  • User-defined functions return a single value or a table of values.
  • Stored procedures perform a series of operations but do not return a value.

Example (creating a simple UDF in SQL Server):

CREATE FUNCTION dbo.FullName(@first_name NVARCHAR(50), @last_name NVARCHAR(50))
RETURNS NVARCHAR(101)
AS
BEGIN
    RETURN CONCAT(@first_name, ' ', @last_name);
END;

This user-defined function concatenates the first and last name with a space in between.

Benefits and best practices

Using SQL functions and stored procedures provides several benefits:

  • Encapsulation: Encapsulate complex logic within a single reusable entity.
  • Modularization: Break down complex queries into smaller, manageable pieces.
  • Performance: Reduce network traffic and increase performance by running operations on the server side.

Best practices include:

  • Use built-in functions whenever possible for better performance and compatibility.
  • Use descriptive names for user-defined functions and stored procedures.
  • Document the purpose and usage of custom functions and stored procedures to make them easier for others to understand and maintain.
  • Optimize your functions and stored procedures by avoiding excessive loops, using proper indexing, and minimizing the number of database calls.
  • Regularly review and update your custom functions and stored procedures to ensure they remain relevant and efficient as your database schema and requirements evolve.
  • Consider using window functions for advanced calculations and analytics instead of multiple nested subqueries or self-joins.
  • Test your user-defined functions and stored procedures thoroughly to ensure they return correct results and handle edge cases properly.

Summary

In conclusion, understanding SQL syntax, keywords, and structure is crucial for working effectively with relational databases.

Mastering the basic and advanced SQL concepts, such as JOIN operations, subqueries, aggregate and window functions, and stored procedures, enables you to write efficient and powerful queries to manage and analyze your data.

By following best practices and utilizing built-in SQL functions, you can ensure that your queries are not only performant but also maintainable and easy to understand for others.

As you continue to develop your SQL skills, you’ll find that you can unlock new insights and capabilities from your data, making you an invaluable asset in any data-driven organization.

Thank you for reading our blog, we hope you found the information provided helpful and informative. We invite you to follow and share this blog with your colleagues and friends if you found it useful.

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