aggregate

APPLIES TO: MongoDB vCore

The aggregate command is used to process data records and return computed results. It performs operations on the data, such as filtering, grouping, and sorting, and can transform the data in various ways. The aggregate command is highly versatile and is commonly used for data analysis and reporting.

db.collection.aggregate(pipeline, options)

• pipeline: An array of aggregation stages that process and transform the data.
• options: Optional. Specifies more options for the aggregation, such as explain, allowDiskUse, and cursor.

This example demonstrates how to calculate the total sales for each category in the stores collection.

db.stores.aggregate([
  {
    $unwind: "$sales.salesByCategory"
  },
  {
    $group: {
      _id: "$sales.salesByCategory.categoryName",
      totalSales: { $sum: "$sales.salesByCategory.totalSales" }
    }
  }
])

[mongos] StoreData> db.stores.aggregate([
...   {
...     $unwind: "$sales.salesByCategory"
...   },
...   {
...     $group: {
...       _id: "$sales.salesByCategory.categoryName",
...       totalSales: { $sum: "$sales.salesByCategory.totalSales" }
...     }
...   }
... ])

[
  { _id: 'Christmas Trees', totalSales: 3147281 },
  { _id: 'Nuts', totalSales: 3002332 },
  { _id: 'Camping Tables', totalSales: 4431667 }
]
 

This example shows how to filter stores where the number of full-time staff is greater than 10.

db.stores.aggregate([
  {
    $match: {
      "staff.totalStaff.fullTime": { $gt: 10 }
    }
  }
])

[mongos] StoreData> db.stores.aggregate([
...   {
...     $match: {
...       "staff.totalStaff.fullTime": { $gt: 10 }
...     }
...   }
... ])

[
  {
    _id: '7954bd5c-9ac2-4c10-bb7a-2b79bd0963c5',
    name: "Lenore's DJ Equipment Store",
    location: { lat: -9.9399, lon: -0.334 },
    staff: { totalStaff: { fullTime: 18, partTime: 7 } },
    sales: {
      totalSales: 35911,
      salesByCategory: [ { categoryName: 'DJ Headphones', totalSales: 35911 } ]
    },
    promotionEvents: [
      {
        discounts: [
          { categoryName: 'DJ Turntables', discountPercentage: 18 },
          { categoryName: 'DJ Mixers', discountPercentage: 15 }
        ]
      }
    ],
    tag: [ '#SeasonalSale', '#FreeShipping', '#MembershipDeals' ]
  }
]

This example lists all promotion events where any discount is greater than 15%.

db.stores.aggregate([
  {
    $unwind: "$promotionEvents"
  },
  {
    $unwind: "$promotionEvents.discounts"
  },
  {
    $match: {
      "promotionEvents.discounts.discountPercentage": { $gt: 15 }
    }
  },
  {
    $group: {
      _id: "$promotionEvents.eventName",
      discounts: { $push: "$promotionEvents.discounts" }
    }
  }
])

[mongos] StoreData> db.stores.aggregate([
...   {
...     $unwind: "$promotionEvents"
...   },
...   {
...     $unwind: "$promotionEvents.discounts"
...   },
...   {
...     $match: {
...       "promotionEvents.discounts.discountPercentage": { $gt: 20 }
...     }
...   },
...   {
...     $group: {
...       _id: "$promotionEvents.eventName",
...       discounts: { $push: "$promotionEvents.discounts" }
...     }
...   }
... ])
[
  {
    [
      { categoryName: 'Basketball Gear', discountPercentage: 23 },
      { categoryName: 'Wool Carpets', discountPercentage: 22 },
      {
        categoryName: 'Portable Bluetooth Speakers',
        discountPercentage: 24
      }
    ]
  }
]

• Review options for Migrating from MongoDB to Azure Cosmos DB for MongoDB (vCore)
• Read more about Feature compatibility with MongoDB