Views in SQL: Creating and Querying Virtual Tables

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Table of Contents

1. Introduction
2. What is a View in SQL?
3. Benefits of Using Views
4. Syntax for Creating a View
5. Querying Data from a View
6. Updating a View
7. Rules and Limitations of Updatable Views
8. Modifying an Existing View
9. Dropping a View
10. Using WITH CHECK OPTION
11. Views vs Tables
12. Views vs CTEs
13. Security and Access Control via Views
14. Performance Considerations
15. Materialized Views (vs Regular Views)
16. Real-World Example: Simplifying Joins
17. Real-World Example: Department-Level Reporting
18. Best Practices for Working with Views
19. Common Errors and Troubleshooting
20. Summary and What’s Next

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1. Introduction

SQL views are virtual tables built from queries. They allow you to simplify complex logic, encapsulate business rules, and present data in a structured way — without duplicating actual data.

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2. What is a View in SQL?

A view is a saved SQL query that acts like a virtual table. When you select from a view, it runs the underlying query and returns the result set as if you queried a real table.

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3. Benefits of Using Views

• Simplify complex queries
• Enforce business logic
• Control user access
• Reuse logic across applications
• Improve readability and maintainability

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4. Syntax for Creating a View

sqlCopyEditCREATE VIEW view_name AS
SELECT column1, column2
FROM table_name
WHERE condition;

Example:

sqlCopyEditCREATE VIEW active_customers AS
SELECT id, name, email
FROM customers
WHERE status = 'active';

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5. Querying Data from a View

sqlCopyEditSELECT * FROM active_customers;

You can use a view just like a table in SELECT, JOIN, WHERE, etc.

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6. Updating a View

sqlCopyEditCREATE OR REPLACE VIEW active_customers AS
SELECT id, name
FROM customers
WHERE is_active = 1;

Most SQL dialects support CREATE OR REPLACE to update a view’s definition.

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7. Rules and Limitations of Updatable Views

Some views allow updates (INSERT, UPDATE, DELETE) if:

• Based on a single table
• No GROUP BY, DISTINCT, or aggregate functions
• No subqueries or joins

If these rules are violated, the view becomes read-only.

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8. Modifying an Existing View

In MySQL and PostgreSQL:

sqlCopyEditCREATE OR REPLACE VIEW view_name AS
-- new query here

In SQL Server:

sqlCopyEditALTER VIEW view_name AS
-- new query here

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9. Dropping a View

sqlCopyEditDROP VIEW view_name;

This removes the virtual table from the schema (not the underlying data).

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10. Using WITH CHECK OPTION

Prevents updates through a view that would violate its conditions:

sqlCopyEditCREATE VIEW high_salary_employees AS
SELECT * FROM employees
WHERE salary > 100000
WITH CHECK OPTION;

Now, you cannot insert or update a row through this view unless it satisfies salary > 100000.

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11. Views vs Tables

Feature	Table	View (Virtual Table)
Stores data	Yes	No (except materialized views)
Modifiable	Yes	Sometimes (updatable views)
Physical storage	On disk	Not stored; computed on access
Refresh needed	No	No (unless materialized)

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12. Views vs CTEs

Feature	View	CTE (WITH)
Persistent	Yes	No (temporary for one query)
Reusable	Across queries	Only in the current query
Performance	May benefit from indexing	Typically not cached
Ideal for	Reusable logic	Temporary intermediate logic

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13. Security and Access Control via Views

Views can limit access to sensitive data:

sqlCopyEditCREATE VIEW employee_public AS
SELECT name, department
FROM employees;

You can grant access to this view without exposing the full table:

sqlCopyEditGRANT SELECT ON employee_public TO analyst_role;

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14. Performance Considerations

• Views don’t store data — each access reruns the query
• Complex views with joins and filters may slow down queries
• You can index base tables, but not views
• Consider materialized views for performance-sensitive cases

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15. Materialized Views (vs Regular Views)

Materialized views store data physically:

Feature	Regular View	Materialized View
Data stored	No	Yes
Always fresh	Yes (computed live)	No (requires manual/auto refresh)
Performance	Slower	Faster for large static datasets

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16. Real-World Example: Simplifying Joins

sqlCopyEditCREATE VIEW order_summary AS
SELECT o.id, c.name, o.total
FROM orders o
JOIN customers c ON o.customer_id = c.id;

Now query reports using:

sqlCopyEditSELECT * FROM order_summary WHERE total > 500;

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17. Real-World Example: Department-Level Reporting

sqlCopyEditCREATE VIEW department_sales AS
SELECT d.name AS department, SUM(o.total) AS total_sales
FROM orders o
JOIN employees e ON o.employee_id = e.id
JOIN departments d ON e.department_id = d.id
GROUP BY d.name;

Use for dashboards or monthly summaries.

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18. Best Practices for Working with Views

• Name views meaningfully (active_users, monthly_sales, etc.)
• Use WITH CHECK OPTION if enforcing integrity
• Avoid overly complex views with multiple nested joins
• Document views as part of schema design
• Don’t use views as a substitute for indexing or denormalization

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19. Common Errors and Troubleshooting

Issue	Solution
View not updating	Check if base table changed or not
Cannot modify data in view	Ensure it’s not based on join/grouped data
Performance is slow	Simplify view query or use materialized view
Invalid column in query	Update view definition using CREATE OR REPLACE

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20. Summary and What’s Next

Views in SQL act as virtual tables, helping you simplify complex logic, protect sensitive data, and write cleaner, reusable queries. Mastering views is essential for maintaining scalable and secure SQL systems.