Types of Materialized views

Materialized views in a database system are precomputed and stored results of queries, which can help improve query performance, particularly for complex or time-consuming queries. The different types of materialized views are designed to serve specific optimization purposes. Here's a detailed explanation of each type, along with examples.

1. Simple Materialized View

A Simple Materialized View is a precomputed result of a query that typically pulls data directly from one table without any complex calculations, joins, or aggregations.

Example: Suppose you have a table employees that contains employee details, and you frequently need to fetch a list of employees from a specific department.

CREATE MATERIALIZED VIEW mv_employees_department AS
SELECT * FROM employees WHERE department = 'Sales';

In this case, the materialized view mv_employees_department stores the results of the query that retrieves all employees in the "Sales" department. This can be particularly useful if you frequently need this data, as it avoids recalculating the result each time.

2. Aggregate Materialized View

An Aggregate Materialized View precomputes aggregated values like sums, averages, counts, or other aggregate functions on large datasets, which speeds up queries that require these calculations.

Example: Consider a sales table where you have transaction data. You often need to calculate the total sales per store.

CREATE MATERIALIZED VIEW mv_total_sales AS
SELECT store_id, SUM(sales_amount) AS total_sales
FROM sales
GROUP BY store_id;

In this case, the materialized view mv_total_sales stores the precomputed total sales per store. This way, queries asking for the total sales of a store can simply access the materialized view rather than recalculating the sum of sales_amount every time.

3. Join Materialized View

A Join Materialized View stores the result of a join between multiple tables. It is particularly useful when you frequently run complex queries that require joining large tables.

Example: Imagine you have two tables: orders and customers, and you often need to get the order details along with the customer name.

CREATE MATERIALIZED VIEW mv_order_details AS
SELECT o.order_id, o.order_date, c.customer_name, o.order_total
FROM orders o
JOIN customers c ON o.customer_id = c.customer_id;

Here, the materialized view mv_order_details precomputes the results of joining the orders and customers tables, allowing you to quickly retrieve order details without repeatedly performing the join operation.

4. Refreshable Materialized View

A Refreshable Materialized View allows you to refresh the stored data either manually or automatically. This ensures that the materialized view reflects the latest changes in the underlying base tables. There are two main types of refresh strategies:

Complete Refresh: The entire materialized view is recomputed from scratch.

Incremental (Fast) Refresh: Only the changes since the last refresh are applied, making the refresh process faster.

Example: Let’s say you have a materialized view for sales totals, but you want to refresh it every day at midnight to keep it up to date with new sales data.

CREATE MATERIALIZED VIEW mv_sales_summary 
REFRESH FAST
AS
SELECT store_id, SUM(sales_amount) AS daily_sales
FROM sales
GROUP BY store_id;

You can set up an automatic refresh using scheduling tools or triggers to refresh this view nightly to capture the most up-to-date information.

5. Partitioned Materialized View

A Partitioned Materialized View is a type of materialized view where the data is divided into smaller, more manageable segments called partitions. This can optimize performance on large datasets by enabling faster refresh and query access to specific parts of the data.

Example: Suppose you have a sales table with millions of records. You could partition the materialized view by month.

CREATE MATERIALIZED VIEW mv_monthly_sales PARTITION BY RANGE (sale_date) AS
SELECT sale_date, SUM(sales_amount)
FROM sales
GROUP BY sale_date;

With partitioning, the materialized view is divided into smaller parts (e.g., by month or year), making it easier to manage and improving query performance on specific ranges of data (e.g., querying sales from a particular month).

6. Hybrid Materialized View

A Hybrid Materialized View combines the features of multiple types of materialized views, such as aggregation and joins. It can be used to optimize queries that require both precomputed aggregates and data from multiple tables.

Example: If you need a materialized view that stores both aggregate sales data and customer information, you might combine an aggregation and a join in a single view:

CREATE MATERIALIZED VIEW mv_customer_sales_summary AS
SELECT c.customer_name, SUM(s.sales_amount) AS total_sales
FROM customers c
JOIN sales s ON c.customer_id = s.customer_id
GROUP BY c.customer_name;

This view combines the aggregation of sales and the join between the customers and sales tables. It optimizes the performance of queries asking for aggregated sales by customer.

Summary of Key Points:

Simple Materialized View: Direct results of a query on one table.
Aggregate Materialized View: Precomputes aggregated values (e.g., SUM, COUNT).
Join Materialized View: Precomputes the result of joins between multiple tables.
Refreshable Materialized View: Allows refreshing the data, either automatically or manually.
Partitioned Materialized View: Divides the data into smaller partitions to improve performance.
Hybrid Materialized View: Combines multiple optimizations like aggregation and joins.
Formal Materialized View: Strictly defined schema for consistent, structured results.

Materialized views, depending on their type and use case, can significantly improve performance, particularly for frequently executed complex queries.