What are the best practices for MongoDB aggregation?

What are the best practices for MongoDB aggregation?

When using MongoDB aggregation, consider these best practices: 1. Use the $match stage early to filter data. 2. Limit the number of documents processed by using $project to include only necessary fields. 3. Use indexes to improve performance. 4. Avoid using $group on large datasets without filtering first.

Can you explain why using $match early is important?

Using $match early in the pipeline reduces the number of documents that subsequent stages need to process, which can significantly improve performance.

What is the impact of using $project?

The $project stage allows you to reshape documents by including or excluding fields, which can reduce the amount of data passed through the pipeline and improve efficiency.

Are there any common mistakes to avoid?

Yes, common mistakes include not using indexes, overusing $group without filtering, and neglecting to limit the fields in $project.