Aggregation Pipeline

The aggregation pipeline processes documents through stages.

Each stage transforms or filters the data and passes results to the next stage.

Simple example

Find total orders per user:

db.orders.aggregate([
  { $match: { status: 'paid' } },
  {
    $group: {
      _id: '$userId',
      totalAmount: { $sum: '$amount' },
      orderCount: { $sum: 1 }
    }
  },
  { $sort: { totalAmount: -1 } }
])

Common stages

Stage	Use
`$match`	filter documents
`$project`	select or reshape fields
`$group`	group and aggregate
`$sort`	sort results
`$limit`	limit result count
`$lookup`	join with another collection
`$unwind`	expand array items

Why aggregation matters

Aggregation is used for:

reports,
dashboards,
analytics,
summaries,
grouped totals,
joins through $lookup.

Common mistake

Put $match early when possible.

Filtering early reduces how many documents later stages process.

Interview answer

MongoDB aggregation pipeline processes documents through stages such as $match, $group, $project, $sort, and $lookup. It is used for transformations, summaries, reports, and analytics. A good pipeline filters early and only processes the data needed.