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Day 3 of 5
⏱ ~60 minutes
MongoDB in 5 Days — Day 3

Aggregation Pipelines

Transform and analyze data with $match, $group, $sort, $lookup, and $project stages.

Aggregation Pipeline Concept

The aggregation pipeline is like a series of Unix pipes. Each stage transforms the documents and passes results to the next stage.

Pipeline stages
db.orders.aggregate([
  // Stage 1: filter documents
  { $match: { status: 'completed' } },

  // Stage 2: group and calculate
  { $group: {
    _id: '$category',
    totalRevenue: { $sum: '$amount' },
    orderCount: { $count: {} },
    avgOrder: { $avg: '$amount' }
  }},

  // Stage 3: sort results
  { $sort: { totalRevenue: -1 } },

  // Stage 4: limit
  { $limit: 10 },

  // Stage 5: reshape output
  { $project: {
    _id: 0,
    category: '$_id',
    totalRevenue: 1,
    orderCount: 1,
    avgOrder: { $round: ['$avgOrder', 2] }
  }}
])
$lookup: Joins
// Join users to their orders
db.orders.aggregate([
  { $lookup: {
    from: 'users',
    localField: 'userId',
    foreignField: '_id',
    as: 'user'
  }},
  { $unwind: '$user' },  // flatten the user array
  { $project: {
    orderId: '$_id',
    amount: 1,
    userName: '$user.name',
    userEmail: '$user.email'
  }}
])
📝 Day 3 Exercise
Build a Sales Report
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Day 3 Summary

  • Aggregation pipelines are stages: $match → $group → $sort → $project.
  • $group with $sum, $avg, $count, $min, $max for analytics.
  • $lookup joins collections. Follow with $unwind to flatten the joined array.
  • Put $match first so subsequent stages process fewer documents.
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