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Indexing

In MongoDB, indexing plays a crucial role in enhancing the performance of search operations in the database. Indexes are special data structures that store a small portion of the database's data set in an easy-to-traverse form. The index stores the value of a specific field or set of fields, ordered by the value of the field. In this tutorial, we'll look at what indexing is, why it's necessary, and how to use it in MongoDB.

What is Indexing?​

Imagine you're reading a book and looking for a specific topic. You could go through every single page until you find what you're looking for, but that would be time-consuming. Instead, you would probably use the book's index, which lists topics alphabetically and provides the page numbers where those topics can be found.

Similarly, an index in MongoDB is a special data structure that holds data in an easy-to-read format. This makes the search operation in MongoDB much faster. Without indexing, MongoDB must perform a collection scan, i.e., scan every document in a collection, to select those documents that match the query statement.

Why is Indexing Important?​

Indexing significantly enhances MongoDB's performance. Without it, MongoDB would need to scan every document in a database to find the required data. This can be extremely inefficient, particularly for large databases. Indexing solves this problem by providing a more efficient path to the data.

How to Create Indexes in MongoDB?​

To create an index in MongoDB, you use the createIndex() method. This method requires two parameters:

  1. Field or fields to index.
  2. The type of index.

Here's a basic example:

db.collection.createIndex( { <field1>: <type>, <field2>: <type2>, ... } )

The <type> can be 1 for ascending order, -1 for descending order.

For instance, if you have a users collection and you want to create an ascending index on the username field, you'd do the following:

db.users.createIndex( { "username": 1 } )

Types of Indexes in MongoDB​

MongoDB provides several types of indexes that serve different purposes. Some of them include:

  • Single Field: MongoDb supports user-defined indexes on a single field of a document.

  • Compound Index: MongoDB also supports user-defined indexes on multiple fields, i.e., compound indexes.

  • Multikey Index: MongoDB uses multikey indexes to index the content stored in arrays.

  • Text Indexes: Text indexes are used to search for string content in data.

  • 2dsphere Indexes: 2dsphere indexes are used to search for data in a geospatial format.

  • Hashed Indexes: Hashed indexes are used to support hash based sharding.

Conclusion​

Indexing is a powerful feature in MongoDB that can greatly improve the performance of read operations. By creating indexes, MongoDB can limit the number of documents it must inspect when querying data. As a result, your applications can have increased performance and responsiveness. However, remember that indexes come with a cost of write and storage overhead so it's important to find a balance between speeding up read operations and slowing down write operations.