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Aggregation Pipeline

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Aggregation Framework

The aggregation framework allows you to process data records and return computed results. It is similar to the GROUP BY clause in SQL but much more powerful.

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The Pipeline

Aggregations work as a pipeline. Documents pass through a series of stages, where each stage transforms the documents. 
db.orders.aggregate([
  { $match: { status: "A" } },
  { $group: { _id: "$cust_id", total: { $sum: "$amount" } } }
])

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Common Stages

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$match

Filters the documents (like find or SQL WHERE). 
{ $match: { status: "active" } }

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$group

Groups documents by a specified identifier key and applies the accumulator expression(s) to each group. 
{
  $group: {
    _id: "$category", // Group by category
    count: { $sum: 1 }, // Count items per category
    avgPrice: { $avg: "$price" } // Calculate average price
  }
}

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$project

Reshapes each document in the stream, such as by adding new fields or removing existing fields. 
{ $project: { name: 1, total: 1, _id: 0 } }

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$sort

Sorts all input documents and returns them to the pipeline in sorted order. 
{ $sort: { total: -1 } } // Descending order

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$limit & $skip

Used for pagination. 
{ $skip: 10 },
{ $limit: 5 }

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Example Pipeline

Calculate the total sales per product for the year 2023, sorted by highest sales. 
db.sales.aggregate([
  // 1. Filter for 2023
  { $match: { date: { $gte: new Date('2023-01-01'), $lt: new Date('2024-01-01') } } },
  
  // 2. Group by product and sum amount
  { $group: { _id: "$product", totalSales: { $sum: "$amount" } } },
  
  // 3. Sort by totalSales descending
  { $sort: { totalSales: -1 } }
])

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Summary

  • Aggregation Pipeline processes data in stages.
  • Use $match to filter early (for performance).
  • Use $group to calculate statistics (sum, avg, etc.).
  • Use $project to format the output.