Creating Indexes in PostgreSQL: Understanding CREATE TABLE and Separate Statements

• CREATE TABLE: This command defines the structure of a table, specifying columns, data types, and constraints like primary keys.
• Indexes: These are additional structures that improve query performance by allowing faster data retrieval based on specific columns.

There are two key points to remember:

CREATE TABLE products (
  id SERIAL PRIMARY KEY,
  name VARCHAR(255) NOT NULL,
  price DECIMAL(10,2) NOT NULL
);

In this example, defining id as the primary key automatically creates an index on that column.

Creating a Separate Index:

CREATE TABLE customers (
  customer_id INT PRIMARY KEY,
  name VARCHAR(255) NOT NULL,
  email VARCHAR(255) UNIQUE NOT NULL
);

CREATE INDEX idx_customer_email ON customers (email);

This example creates a table with a primary key and a unique email constraint. Then, a separate CREATE INDEX statement creates an index named idx_customer_email on the email column.

Specifying Sort Order and Handling NULL Values:

CREATE INDEX idx_products_name_desc ON products (name DESC NULLS LAST);

1. Using CREATE TABLE with a FOREIGN KEY referencing an existing indexed table:

• This approach leverages existing indexes. Define a FOREIGN KEY constraint in your table that references a column in another table with an existing index.
• When querying your table using the foreign key column, the optimizer might utilize the existing index on the referenced table to speed up the search.

Example:

CREATE TABLE orders (
  order_id SERIAL PRIMARY KEY,
  customer_id INT NOT NULL,
  FOREIGN KEY (customer_id) REFERENCES customers(customer_id)
);

-- Assuming an index already exists on customers.customer_id

1. Post-deployment Indexing based on Query Analysis:

• Analyze your application's query patterns after deployment. Tools like EXPLAIN and pg_stat_statements can reveal frequently used WHERE clauses that might benefit from indexing.
• Based on this analysis, create targeted indexes using separate CREATE INDEX statements.

Benefits:

• This method avoids unnecessary indexes that might not be used in practice.
• It tailors indexes to specific query patterns, potentially offering better performance gains.

1. Using materialized views (advanced):

• Materialized views are pre-computed results of a complex query stored as a separate table.
• If your queries involve joins or aggregations, a materialized view with proper indexes can significantly improve performance.