Indexing Strategies for MongoDB

1. Introduction

Indexing is a crucial aspect of database performance, particularly for read-heavy applications. In this lesson, we will explore MongoDB's indexing strategies to optimize query performance.

2. What is Indexing?

An index is a data structure that improves the speed of data retrieval operations on a database at the cost of additional space and slower write operations. MongoDB supports various types of indexes to facilitate efficient querying.

3. Types of Indexes

3.1 Single Field Index

A single field index is created on a single field of a document. It is the most basic form of indexing.

3.2 Compound Index

Compound indexes are created on multiple fields of a document. They allow for efficient querying when multiple fields are used in the query.

3.3 Multikey Index

Multikey indexes are used to index array fields, allowing queries to efficiently access array elements.

3.4 Geospatial Index

Geospatial indexes support queries that include geospatial data, such as points and polygons.

3.5 Text Index

Text indexes support text search queries on string content.

4. Creating Indexes

Indexes can be created using the createIndex() method in MongoDB. Below is a basic example:

db.collection.createIndex({ fieldName: 1 }) // Ascending index
db.collection.createIndex({ fieldName: -1 }) // Descending index

5. Indexing Strategies

When designing indexes, consider the following strategies:

Use compound indexes for queries that filter by multiple fields.
Optimize for read vs. write performance based on application needs.
Analyze query patterns using the explain() method to understand how queries use indexes.
Limit the number of indexes to reduce the overhead during writes.
Use TTL indexes for automatic expiration of documents.

6. Best Practices

Always monitor index usage with MongoDB's tools. Remove unused indexes to optimize performance.

Index fields that are frequently used in queries.
Avoid indexing fields with low selectivity.
Regularly review and optimize your indexes.

7. FAQ

What is the impact of indexing on write performance?

Indexing can degrade write performance because each write operation requires updating the index, which adds overhead.

Can I create indexes on embedded documents?

Yes, you can create indexes on fields within embedded documents.

How do I analyze index performance?

You can use the db.collection.find().explain() method to see how MongoDB uses indexes for your queries.