MongoDB Aggregation Pipeline

The aggregation pipeline is MongoDB's most powerful feature for data transformation and analysis.

What is Aggregation?

A sequence of stages that process documents:

db.orders.aggregate([
 { $match: { status: 'completed' } },
 { $group: { _id: '$customer', total: { $sum: '$amount' } } },
 { $sort: { total: -1 } }
]);

Essential Stages

$match - Filter Documents

{ $match: { status: 'active', age: { $gte: 18 } } }

$project - Shape Output

{
 $project: {
 name: 1,
 fullName: { $concat: ['$firstName', ' ', '$lastName'] },
 yearJoined: { $year: '$createdAt' }
 }
}

$group - Aggregate Data

{
 $group: {
 _id: '$category',
 count: { $sum: 1 },
 avgPrice: { $avg: '$price' },
 maxPrice: { $max: '$price' },
 products: { $push: '$name' }
 }
}

$sort and $limit

{ $sort: { createdAt: -1 } },
{ $limit: 10 }

$lookup - Join Collections

{
 $lookup: {
 from: 'authors',
 localField: 'authorId',
 foreignField: '_id',
 as: 'author'
 }
}

Real-World Examples

Sales Report by Month

db.sales.aggregate([
 {
 $group: {
 _id: {
 year: { $year: '$date' },
 month: { $month: '$date' }
 },
 totalSales: { $sum: '$amount' },
 orderCount: { $sum: 1 }
 }
 },
 { $sort: { '_id.year': -1, '_id.month': -1 } }
]);

Top Products with Details

db.orders.aggregate([
 { $unwind: '$items' },
 {
 $group: {
 _id: '$items.productId',
 totalSold: { $sum: '$items.quantity' },
 revenue: { $sum: { $multiply: ['$items.price', '$items.quantity'] } }
 }
 },
 {
 $lookup: {
 from: 'products',
 localField: '_id',
 foreignField: '_id',
 as: 'product'
 }
 },
 { $unwind: '$product' },
 { $sort: { totalSold: -1 } },
 { $limit: 10 }
]);

Performance Tips

1. Place $match early - Filter before processing
2. Use indexes - $match and $sort can use indexes
3. Limit fields with $project - Reduce memory usage
4. Use allowDiskUse - For large datasets

db.collection.aggregate(pipeline, { allowDiskUse: true });

Conclusion

Master the aggregation pipeline to unlock MongoDB's full potential for data analysis.