Mongodb Indexes: Creating, Finding & Dropping Top Index Types

Indexes provide users with an efficient way of querying data. When querying data without indexes, the query will have to search for all the records within a database to find data that match the query.

In MongoDB, querying without indexes is called a collection scan. A collection scan will:

• Result in various performance bottlenecks
• Significantly slow down your application

Fortunately, using indexes fixes both these issues. By limiting the number of documents to be queried, you’ll increases the overall performance of the application.

In this tutorial, I’ll walk you through different types of indexes and show you how to create and manage indexes in MongoDB.

(This article is part of our MongoDB Guide. Use the right-hand menu to navigate.)

What are indexes in MongoDB?

Indexes are special data structures that store a small part of the Collection’s data in a way that can be queried easily.

In simplest terms, indexes store the values of the indexed fields outside the table or collection and keep track of their location in the disk. These values are used to order the indexed fields. This ordering helps to perform equality matches and range-based query operations efficiently. In MongoDB, indexes are defined in the collection level and indexes on any field or subfield of the documents in a collection are supported.

For this tutorial, we’ll use the following data set to demonstrate the indexing functionality of MongoDB.

use students
db.createCollection("studentgrades")
db.studentgrades.insertMany(
    [
        {name: "Barry", subject: "Maths", },
        {name: "Kent", subject: "Physics", },
        {name: "Harry", subject: "Maths", , notes: "Exceptional Performance"},
        {name: "Alex", subject: "Literature", },
        {name: "Tom", subject: "History", , notes: "Adequate"}
    ]
)
db.studentgrades.find({},{_id:0})

Result

Creating indexes

When creating documents in a collection, MongoDB creates a unique index using the _id field. MongoDB refers to this as the Default _id Index. This default index cannot be dropped from the collection.

When querying the test data set, you can see the _id field which will be utilized as the default index:

db.studentgrades.find().pretty()

Result:

Now let’s create an index. To do that, you can use the createIndex method using the following syntax:

db.<collection>.createIndex(<Key and Index Type>, <Options>)

When creating an index, you need to define the field to be indexed and the direction of the key (1 or -1) to indicate ascending or descending order.

Another thing to keep in mind is the index names. By default, MongoDB will generate index names by concatenating the indexed keys with the direction of each key in the index using an underscore as the separator. For example: {name: 1} will be created as name_1.

The best option is to use the name option to define a custom index name when creating an index. Indexes cannot be renamed after creation. (The only way to rename an index is to first drop that index, which we show below, and recreate it using the desired name.)

Let’s create an index using the name field in the studentgrades collection and name it as student name index.

db.studentgrades.createIndex(
{name: 1},
{name: "student name index"}
)

Result: