How can I optimize my MongoDB aggregation pipeline in Node.js?

How can I optimize my MongoDB aggregation pipeline in Node.js?

To optimize your MongoDB aggregation pipeline, consider using the following strategies: 1. Use $match early to filter documents. 2. Limit the number of documents processed with $limit. 3. Use indexes to speed up queries. 4. Avoid using $unwind if possible, as it can be resource-intensive.

What are some common pitfalls to avoid when using aggregation pipelines?

Common pitfalls include: 1. Not using indexes effectively, which can slow down performance. 2. Overusing $lookup, which can lead to performance issues if not managed properly. 3. Failing to limit the number of documents processed, which can increase memory usage.

Can you give an example of an optimized aggregation pipeline?

Sure! Here's an example:

db.collection.aggregate([
  { $match: { status: 'active' } },
  { $group: { _id: '$category', total: { $sum: '$amount' } } },
  { $sort: { total: -1 } },
  { $limit: 10 }
]);

This pipeline filters active documents first, groups by category, sorts the totals, and limits the results.

How can I measure the performance of my aggregation pipeline?

You can measure performance using the explain() method in MongoDB. It provides insights into how the query is executed, including execution time and stages involved. This helps identify bottlenecks in your pipeline.