Match, group, project and sort

Use $match to filter, $group to combine records, $project to shape fields and $sort to order results. After grouping, refer to the new group fields rather than the old document shape.

The MongoDB Aggregation Framework allows you to process and transform large volumes of documents in stages. Think of it as a data pipeline where each stage performs a specific task such as filtering, grouping, transforming, or sorting the data.

The most commonly used stages are:

• $match – Filter documents (like WHERE in SQL)
• $group – Group and aggregate values (like GROUP BY)
• $project – Include, exclude, or transform fields
• $sort – Sort documents in ascending or descending order

Before working through the examples, make sure you can connect with mongosh and select your database. Use a practice database for writes and deletions.

Let’s assume you have a collection called orders with documents like this:

    db.orders.insertMany([
      { item: "pen", category: "stationery", price: 10, quantity: 3, store: "A" },
      { item: "notebook", category: "stationery", price: 50, quantity: 2, store: "A" },
      { item: "eraser", category: "stationery", price: 5, quantity: 5, store: "B" },
      { item: "apple", category: "grocery", price: 20, quantity: 10, store: "B" },
      { item: "banana", category: "grocery", price: 15, quantity: 8, store: "A" }
    ]);

$match – Filter Documents

$match is used to filter documents based on conditions. It’s similar to WHERE in SQL.

    db.orders.aggregate([
      { $match: { category: "stationery" } }
    ]);

    [
      { item: "pen", category: "stationery", price: 10, quantity: 3, store: "A" },
      { item: "notebook", category: "stationery", price: 50, quantity: 2, store: "A" },
      { item: "eraser", category: "stationery", price: 5, quantity: 5, store: "B" }
    ]

Explanation: This filters only the documents where category is "stationery".

Question:

Can you combine multiple conditions in $match like price > 10 and category = "stationery"?

Answer: Yes, by using operators like $gt, $and, etc.

    db.orders.aggregate([
      { $match: { category: "stationery", price: { $gt: 10 } } }
    ]);

Example data reference: the following setup creates the records used below. If you already inserted them earlier in this lesson, do not insert them again.

    db.orders.insertMany([
      { item: "pen", category: "stationery", price: 10, quantity: 3, store: "A" },
      { item: "notebook", category: "stationery", price: 50, quantity: 2, store: "A" },
      { item: "eraser", category: "stationery", price: 5, quantity: 5, store: "B" },
      { item: "apple", category: "grocery", price: 20, quantity: 10, store: "B" },
      { item: "banana", category: "grocery", price: 15, quantity: 8, store: "A" }
    ]);

$group helps us to group documents and perform operations like sum, avg, count, etc.

Example: Calculate total quantity sold per category

    db.orders.aggregate([
      { $group: { _id: "$category", totalQuantity: { $sum: "$quantity" } } }
    ]);

    [
      { _id: "stationery", totalQuantity: 10 },
      { _id: "grocery", totalQuantity: 18 }
    ]

Explanation: We grouped by category and summed the quantity field for each category.

Question:

What if you want to group by store and get the total revenue (price × quantity) from each store?

Answer: You’ll need to first calculate revenue, and then group. Let’s use $project to create a new field.

Example data reference: the following setup creates the records used below. If you already inserted them earlier in this lesson, do not insert them again.

    db.orders.insertMany([
      { item: "pen", category: "stationery", price: 10, quantity: 3, store: "A" },
      { item: "notebook", category: "stationery", price: 50, quantity: 2, store: "A" },
      { item: "eraser", category: "stationery", price: 5, quantity: 5, store: "B" },
      { item: "apple", category: "grocery", price: 20, quantity: 10, store: "B" },
      { item: "banana", category: "grocery", price: 15, quantity: 8, store: "A" }
    ]);

$project is used to reshape documents — you can include/exclude fields or create new ones.

Example: Create a new field revenue = price * quantity

    db.orders.aggregate([
      {
        $project: {
          item: 1,
          store: 1,
          revenue: { $multiply: ["$price", "$quantity"] }
        }
      }
    ]);

    [
      { item: "pen", store: "A", revenue: 30 },
      { item: "notebook", store: "A", revenue: 100 },
      { item: "eraser", store: "B", revenue: 25 },
      { item: "apple", store: "B", revenue: 200 },
      { item: "banana", store: "A", revenue: 120 }
    ]

Explanation: $multiply is used to calculate revenue by multiplying price and quantity.

Now combine $project and $group

Let’s find total revenue per store.

    db.orders.aggregate([
      {
        $project: {
          store: 1,
          revenue: { $multiply: ["$price", "$quantity"] }
        }
      },
      {
        $group: {
          _id: "$store",
          totalRevenue: { $sum: "$revenue" }
        }
      }
    ]);

    [
      { _id: "A", totalRevenue: 250 },
      { _id: "B", totalRevenue: 225 }
    ]

Example data reference: the following setup creates the records used below. If you already inserted them earlier in this lesson, do not insert them again.

    db.orders.insertMany([
      { item: "pen", category: "stationery", price: 10, quantity: 3, store: "A" },
      { item: "notebook", category: "stationery", price: 50, quantity: 2, store: "A" },
      { item: "eraser", category: "stationery", price: 5, quantity: 5, store: "B" },
      { item: "apple", category: "grocery", price: 20, quantity: 10, store: "B" },
      { item: "banana", category: "grocery", price: 15, quantity: 8, store: "A" }
    ]);

Use $sort to arrange documents in ascending (1) or descending (-1) order.

Example: Sort stores by total revenue (highest first)

    db.orders.aggregate([
      {
        $project: {
          store: 1,
          revenue: { $multiply: ["$price", "$quantity"] }
        }
      },
      {
        $group: {
          _id: "$store",
          totalRevenue: { $sum: "$revenue" }
        }
      },
      { $sort: { totalRevenue: -1 } }
    ]);

    [
      { _id: "A", totalRevenue: 250 },
      { _id: "B", totalRevenue: 225 }
    ]

Use $match to filter, $group to combine records, $project to shape fields and $sort to order results. After grouping, refer to the new group fields rather than the old document shape.

Summary

• $match filters documents
• $project transforms or adds new fields
• $group aggregates data
• $sort arranges data in a specific order

These four stages form the backbone of MongoDB's data processing capabilities. Practice chaining them to build powerful queries for real-world use cases.

Next: Dive deeper into aggregation pipelines and explore advanced operators like $unwind and $lookup.

• Review document filters