What are the best practices for using aggregation pipelines in Node.js with MongoDB?

What are the best practices for using aggregation pipelines in Node.js with MongoDB?

When using aggregation pipelines in Node.js with MongoDB, consider the following best practices: 1. Use $match early to filter data. 2. Limit the number of documents processed with $limit. 3. Use $project to include only necessary fields. 4. Optimize your indexes for the fields used in the pipeline.

Can you explain why using $match early is important?

Using $match early in the pipeline is crucial because it reduces the number of documents that subsequent stages need to process. This can significantly improve performance, especially with large datasets.

What are some common mistakes to avoid with aggregation pipelines?

Common mistakes include not using indexes effectively, overusing $group which can be resource-intensive, and neglecting to limit the output size with $limit or $skip.

How can I debug aggregation pipelines in MongoDB?

You can debug aggregation pipelines by using the explain() method to analyze the execution plan, checking for performance issues, and testing each stage of the pipeline individually to ensure correctness.