What is an Index in PostgreSQL?

In relational databases, PostgreSQL is recognized as one of the most reliable database management systems which is used for many web applications, mobile, and analytics applications. Indexing is one of the most important aspects that has a lot to do with the efficiency of the database.

In this article, we focus on indexes in PostgreSQL, explain their significance, examine their types, learn how to create them and discuss ways of optimization.

What is an Index?

PostgreSQL index is a data structure linked to a table that contains the database. This structure increases the performance of the retrieval of rows based on columns or expressions. It functions like a menu, delivering the needed data without the need to search the entire table row by row.

Think of an index as a detailed table of contents in a book, enabling you to quickly locate relevant information instead of flipping through every page.

Syntax to create an index:

CREATE INDEX index_name ON table_name;

Example of Index in PostgreSQL

Let’s create an example table, insert some data into it, and then create some indexes.

Create a table

CREATE TABLE books (
    id SERIAL PRIMARY KEY,
    title VARCHAR(100) NOT NULL,
    author VARCHAR(100) NOT NULL,
    publication_year INT
);

Insert some data into it.

INSERT INTO books (title, author, publication_year) VALUES
    ('To Kill a Mockingbird', 'Harper Lee', 1960),
    ('1984', 'George Orwell', 1949),
    ('Pride and Prejudice', 'Jane Austen', 1813);

Check whether the table is successfully created or not by executing the below command:

SELECT * FROM books;

Output:

Books Table

Create an index on the author column:

CREATE INDEX idx_author ON books (author);

After executing this statement, PostgreSQL will set up an index called “idx_author” on the author field of the books table. This index will be useful for queries containing filtering and searching functions on records based on the author column.

EXPLAIN statement:

In PostgreSQL, the EXPLAIN statement is used to obtain the execution plan for a query without it being executed. It offers an insight into how PostgreSQL formulates the query, like which indexes to use, how to access the data, and any other operation it performs.

We can use the EXPLAIN command to see the query plan, as we can see in the below command:

EXPLAIN SELECT * FROM books WHERE author = 'Harper Lee';

EXPLAIN: This command is used to generate the execution plan for the following query.
SELECT * FROM books WHERE author = ‘Harper Lee’: This is the query you want to analyze. It takes all columns (*) from the books table where the author = ‘Harper Lee‘.

Output:

Query Plan

Types of Indexes

PostgreSQL supports various types of indexes, each tailored to specific use cases:

B-Tree Index

This is the default index type in PostgreSQL and is well-suited for most scenarios. It organizes data in a balanced tree structure, facilitating efficient range queries and equality checks. In particular, the PostgreSQL query planner will consider using a B-tree index whenever an indexed column is involved in a comparison using one of these operators:

<   <=   =   >=   >

Hash Index

Ideal for exact match queries, hash indexes employ a hash function to map keys to index entries. While they offer fast retrieval for equality conditions, they may not perform well with range queries or sorting.

This supports indexed queries using these operators:

GiST (Generalized Search Tree) Index

GiST indexes are versatile and support a wide range of data types and search operations. They are particularly useful for spatial and full-text search queries.

This supports indexed queries using these operators:

<<   &<   &>   >>   <<|   &<|   |&>   |>>   @>   <@   ~=   &&

GIN (Generalized Inverted Index) Index

GIN indexes are designed for handling complex data types such as arrays and full-text searches. They are optimized for fast search operations but may incur higher storage overhead compared to other index types.

This supports indexed queries using these operators:

<@   @>   =   &&

BRIN (Block Range Index) Index

BRIN indexes are suitable for large tables with ordered data. They divide the table into blocks and store summarized information for each block, making them efficient for range queries on sorted data.

This supports indexed queries using these operators:

<   <=   =   >=   >

Optimizing Index Usage

While indexes significantly improve query performance, they require careful management to ensure optimal utilization:

Regular Maintenance: Periodically analyze and reindex indexes to optimize their performance, especially in environments with frequent data modifications.
Index Selection: Select index types and column sets cautiously according to the query patterns and their workload features. Try different indexing schemes to learn the most effective one quickly.
Query Optimization: Make use of PostgreSQL’s query planner and execution analyzer tools so that you can identify inefficient runs and thereby optimize them better for index utilization.

Conclusion

PostgreSQL indexes are like super tools for searching and sorting data to increase the speed of retrieval and processing of queries. The importance of knowing the different types of indexes, the process of creating them, and the optimal strategies for the use of indexes lies in the hands of database administrators and developers. This will ultimately help in developing PostgreSQL-based applications that not only will be efficient but scalable as well. Index management, including proper index performance optimizations and monitoring procedures, is crucial for getting the best index results and making optimal PostgreSQL database performance.

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Databases

PostgreSQL