How does indexing work in a database?

Suppose you spend hours flipping pages searching for a word in a 1,000-page book without an index. Now scale that to millions of database rows. Indexing solves this problem by creating shortcuts that make data retrieval lightning-fast. Indexing is a method used in databases to speed up data searching and retrieval. It acts like an index in a book, helping to quickly locate the information you need.

Introduction to indexing

Indexing is a process that organizes data in a way that makes it faster to search. Without an index, the database has to go through every row to find what you’re looking for, which can take a lot of time if there are many rows.

Indexes are like shortcuts. They let the database find the required data without checking every single row.

Indexing database
Indexing database

How do database indexes work?

When you create an index, the database builds a smaller, sorted data structure based on the values in a specific column or columns. This index is separate from the main table and helps the database locate data quickly.

How it works

  1. When you search for a value, the database looks at the index instead of scanning the entire table.

  2. The index tells the database exactly where to find the data in the table.

Example

Suppose we have a table with 1 million employee records, and we want to find all employees with the last name “Smith.”

  1. Without an index:

    1. The database must look at every row in the table, one by one, to check if the last name is “Smith.”

    2. This is like reading every page of a 1,000-page book to find a word. It’s slow and time-consuming, especially with a large table.

  2. With an index:

    1. Suppose you have an index on the last_name column. This index is like an alphabetically arranged list of names in the table.

    2. When the database searches for “Smith,” it goes to the index, finds “Smith” in the sorted list, and directly retrieves the matching rows from the main table.

    3. This is like using a book’s index to jump directly to the page where the word appears. It’s much faster and more efficient.

Now that we understand how indexing speeds up data retrieval, let’s explore the different types of indexes and when to use them.

Different types of database indexes

1. Single-column index

It is created for a single column to speed up searches on that column.

CREATE INDEX idx_last_name ON employees(last_name);

2. Composite index

It is created on multiple columns and is useful for queries that use more than one column for filtering.

CREATE INDEX idx_full_name ON employees(first_name, last_name);

3. Unique index

It ensures that all values in a column are unique. This is often used for primary keys.

CREATE UNIQUE INDEX idx_employee_id ON employees(employee_id);

4. Full-text index

It is used for searching large text data like descriptions or documents.

CREATE FULLTEXT INDEX idx_description ON products(description);

5. Clustered index

It rearranges the actual table data based on the index. A table can have only one clustered index.

6. Non-clustered index

It stores pointers to the data instead of rearranging the table.

While indexes significantly speed up read operations, they can slow down INSERT, UPDATE, and DELETE operations. This is because the index structure must be updated whenever data is modified, adding overhead to these actions.

Why do we need indexing?

Indexing is important because it makes databases faster and more efficient.

  • Faster searches: Indexes let the database find data without scanning the whole table.

  • Easier sorting: Speeds up queries that use ORDER BY or GROUP BY.

  • Supports constraints: Enforces rules like unique values for primary keys.

  • Speeds up joins: Indexes improve performance when combining data from multiple tables.

Different indexing strategies

1. Choose important columns

Index columns that are used in filters, sorting, or joins. Avoid indexing columns that repeat the same value, like “sex,” “status,” or “region.”

2. Don’t overdo indexing

Adding too many indexes can slow down actions like adding or updating data.

3. Use covering indexes

A covering index includes all the columns needed in a query, so the database doesn’t need to check the table.

4. Maintain indexes regularly

Indexes can get fragmented over time. Rebuilding them ensures they work efficiently.

5. Use partial indexes

Create indexes for only a part of the data that meets certain conditions, like indexing only active users.

6. Monitor performance

Always check how indexes affect your database’s performance and remove unused indexes.

Key takeaways:
Indexing is like creating shortcuts for your database, making it faster to search and retrieve data.

  • There are different types of indexes, like single-column, composite, and full-text, for different needs.

  • While indexes speed up reading data, they can slow down writing data, so use them wisely.

  • Regularly maintain indexes to keep your database fast and efficient.

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1

What is the primary purpose of an index in a database?

A)

To store additional data in the database

B)

To enforce data integrity rules

C)

To speed up data retrieval operations

Question 1 of 30 attempted

Frequently asked questions

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How do you explain indexing?

Indexing in SQL is like creating a shortcut to find data quickly in a database. It organizes the data in a structured way, like the index at the back of a book. Instead of scanning the entire database, the index helps the database locate the needed rows directly, making queries faster and more efficient.

How is the index working in SQL?

When an index is created on a column, the database creates a smaller, sorted data structure based on that column’s values. This index contains pointers that link to the actual rows in the table. When you search for a value, the database checks the index first to quickly find the data’s location instead of scanning the entire table.

How do indexes speed up queries?

Indexes speed up queries by reducing the number of rows the database needs to scan. Instead of searching through all rows, the database uses the index to directly locate the required data. For example, searching for a specific value in a table with millions of rows becomes much faster with an index because it narrows down the search scope to relevant rows only.

How does SQL decide which index to use?

SQL decides which index to use based on the query. It analyzes the query’s conditions, such as WHERE, ORDER BY, and JOIN clauses, and determines the most suitable index. SQL uses a query optimizer to evaluate factors like the size of the table, the number of indexed columns, and the expected rows returned to select the index that offers the best performance for the query.

What is the difference between clustered and non-clustered index?

A clustered index sorts and stores the data rows in the table based on the indexed column. Think of it like organizing books on a shelf alphabetically. A non-clustered index, on the other hand, acts like a table of contents—it points to the location of data but doesn’t rearrange it.

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