Understanding the Difference Between Materialised Views and Physical Tables for Database Design

Understanding Materialised View vs Physical Table

When it comes to database design, choosing the right tool for the job can be a daunting task, especially when deciding between two popular options: Materialised View (MV) and physical table. In this article, we’ll delve into the world of MVs and explore their differences from traditional tables.

What are Materialised Views?

A Materialised View is a database object that stores the result of a query in a physical table, rather than just storing the query definition. This means that instead of executing a complex query every time it’s needed, the result can be retrieved directly from the materialised view, reducing the load on the database server.

When to Use Materialised Views

So, when should you use materialised views? Here are some key scenarios:

Improved Performance: MVs can significantly improve query performance by reducing the need for complex queries. This is especially useful for long-running queries or those that involve multiple joins.
Data Refreshing: As you mentioned in your question, materialised views can be refreshed to update their data periodically. However, this approach requires periodic maintenance and may not suit all use cases.
Data Analysis: Materialised views are ideal for tasks like report generation, where the same data needs to be queried frequently.

How Materialised Views Work

Now that we’ve established when materialised views should be used, let’s dive into their inner workings. Here’s a step-by-step explanation:

Query Definition: The first step in creating a materialised view is defining a query that you want the MV to execute.
Data Retrieval: When the materialised view is queried, the database server executes the original query and retrieves the necessary data from one or more underlying tables.
Cache Update: If the data hasn’t been updated recently, the materialised view will update its cache by writing the retrieved data to disk.
Query Response: Once the cache has been updated, the database server returns the result of the query, which is stored in memory (hence the name “materialised view”).

Advantages of Materialised Views

So, what are the benefits of using materialised views? Here are some key advantages:

Improved Performance: As mentioned earlier, MVs can significantly improve performance by reducing the need for complex queries.
Reduced Load on Database Server: By storing query results in a physical table, MVs reduce the load on the database server, allowing it to focus on more critical tasks.

Disadvantages of Materialised Views

While materialised views have many benefits, they also come with some drawbacks. Here are some key disadvantages:

Data Maintenance: As you mentioned in your question, one of the challenges with MVs is maintaining their data. This requires periodic updates to ensure that the MV remains accurate and up-to-date.
Limited Flexibility: Materialised views can be inflexible when it comes to changes to the underlying data or schema.

How to Create a Materialised View

Creating a materialised view is relatively straightforward. Here’s an example using PostgreSQL:

-- Create a new table to store the materialised view
CREATE TABLE mv_name (
    column1 type,
    column2 type,
    -- Other columns...
);

-- Create a materialised view based on an existing query
CREATE MATERIALIZED VIEW mv_name AS
SELECT * FROM table_name;

Using Materialised Views with PostgreSQL

PostgreSQL is one of the most popular RDBMS, and it supports materialised views natively. Here’s how you can create a materialised view using PostgreSQL:

-- Create a new table to store the materialised view
CREATE TABLE mv_name (
    column1 type,
    column2 type,
    -- Other columns...
);

-- Insert some sample data into the underlying table
INSERT INTO table_name (column1, column2)
VALUES ('value1', 'value2');

-- Create a materialised view based on an existing query
CREATE MATERIALIZED VIEW mv_name AS
SELECT * FROM table_name;

Comparison with Physical Tables

Now that we’ve covered the basics of materialised views, let’s compare them to physical tables. Here are some key differences:

Data Storage: The most obvious difference is how data is stored. Physical tables store data in a relational format, while materialised views store query results in a physical table.
Query Performance: Materialised views can significantly improve performance by reducing the need for complex queries. However, this comes at the cost of increased storage requirements and maintenance needs.
Data Maintenance: One of the key differences between materialised views and physical tables is how data is maintained. Physical tables are updated in real-time, while materialised views require periodic updates to ensure accuracy and up-to-dateness.

Best Practices for Using Materialised Views

While materialised views can be a powerful tool, they do come with some limitations and challenges. Here are some best practices for using materialised views:

Choose the Right Use Case: Don’t use materialised views unless you have a specific use case that benefits from their performance characteristics.
Consider Data Volume and Velocity: Materialised views can become bloated quickly, especially if they’re used to store large amounts of data. Make sure you have a plan for maintaining and updating the data.
Monitor Performance: Keep an eye on query performance when using materialised views. If performance starts to degrade, it may be worth re-examining your design.

Conclusion

In conclusion, materialised views can be a valuable tool in your database arsenal, offering improved performance and reduced load on the database server. However, they do come with some limitations and challenges, including increased storage requirements and maintenance needs. By understanding how materialised views work and implementing them judiciously, you can unlock their full potential and take your database to the next level.

Frequently Asked Questions

Q: How do I refresh a materialised view? A: Materialised views typically need to be refreshed periodically to update their data. This is usually done by running a periodic maintenance script or by using PostgreSQL’s REFRESH MATERIALIZED VIEW command.

Q: Can I use materialised views with complex queries? A: Yes, materialised views can handle complex queries, including joins and subqueries. However, be aware that the query performance may degrade as the complexity of the query increases.

Q: Do materialised views support indexing? A: Yes, materialised views support indexing just like physical tables. Indexing can significantly improve query performance when using materialised views.

Additional Resources

Last modified on 2025-01-07