Description:
When You working with MongoDB, retrieving related data from multiple collections it is a common requirement, similar to performing SQL JOIN operations. MongoDB provides a powerful aggregation framework that allows you to join data from different collections seamlessly using the $lookup stage.
In this article, we will walk you through a step-by-step guide on how to fetch and combine data from two collections. We’ll start by setting up sample collections such as users and orders, then construct an aggregation pipeline to match and merge related documents. Using the $lookup, $unwind, and $project stages, we’ll create structured, relational-like results directly in MongoDB.
By the end of this guide, you'll understand how to:
- Use the
$lookupstage for joining collections
- Customize the output fields
- Handle unmatched data scenarios
- Optimize your aggregation queries for better performance
📂 1. Understanding MongoDB Aggregate and Lookup Basics:
- What is aggregation in MongoDB?
- How does
$lookupsimulate a JOIN operation?
- Why aggregation is important for combining multiple datasets.
🛠️ 2. Practical Example: Joining Two Collections:
- This will embed matching orders into each user document under
userOrder.
🚀 3. Tips for Optimizing Aggregate Queries:
- Use indexing on join fields for faster lookup
- Limit fields with
$projectto reduce payload size
- Handle null or empty arrays when no matches are found
- Split complex pipelines into multiple stages for clarity
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