MongoDB Aggregation

MongoDB’s aggregation framework processes data through a pipeline of stages to perform complex transformations, filtering, grouping, and computations. Below is a concise overview of aggregation with examples using the MongoDB Node.js driver, assuming a users collection with documents like { name: “Alice”, age: 25, city: “New York”, salary: 50000 }.

Aggregation Pipeline

A pipeline consists of stages, each transforming the input documents and passing the result to the next stage. Common stages include $match, $group, $sort, $project, $unwind, and $lookup.

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• Performance: Use $match early to reduce documents. Indexes improve efficiency.
• Accumulators: $sum, $avg, $push, $addToSet, etc., work in $group.
• Syntax: Each stage is an object in an array. Pipelines execute sequentially.
• Output: Use .toArray() to get results or iterate with cursors for large datasets.
• Debugging: Test pipelines stage-by-stage to verify intermediate outputs.