Mongodb aggregation methods

Let’s go through each aggregation stage example again, this time with sample collections and expected outputs.

Sample Collection

Assume we have the following sample products collection:

[
  { "_id": 1, "name": "Product A", "category": "Electronics", "price": 100, "status": "active", "tags": ["new", "sale"] },
  { "_id": 2, "name": "Product B", "category": "Electronics", "price": 200, "status": "inactive", "tags": ["popular"] },
  { "_id": 3, "name": "Product C", "category": "Books", "price": 50, "status": "active", "tags": ["bestseller", "new"] },
  { "_id": 4, "name": "Product D", "category": "Books", "price": 80, "status": "active", "tags": ["new"] },
  { "_id": 5, "name": "Product E", "category": "Clothing", "price": 30, "status": "inactive", "tags": ["sale"] }
]

---

1. $match

Query: Filter documents where status is "active".

const result = await collection.aggregate([{ $match: { status: "active" } }]).toArray();

Output:

[
  { "_id": 1, "name": "Product A", "category": "Electronics", "price": 100, "status": "active", "tags": ["new", "sale"] },
  { "_id": 3, "name": "Product C", "category": "Books", "price": 50, "status": "active", "tags": ["bestseller", "new"] },
  { "_id": 4, "name": "Product D", "category": "Books", "price": 80, "status": "active", "tags": ["new"] }
]

---

2. $group

Query: Group by category and calculate the total count.

const result = await collection.aggregate([
  { $group: { _id: "$category", total: { $sum: 1 } } }
]).toArray();

Output:

[
  { "_id": "Electronics", "total": 2 },
  { "_id": "Books", "total": 2 },
  { "_id": "Clothing", "total": 1 }
]

---

3. $sort

Query: Sort by price in descending order.

const result = await collection.aggregate([{ $sort: { price: -1 } }]).toArray();

Output:

[
  { "_id": 2, "name": "Product B", "category": "Electronics", "price": 200, "status": "inactive", "tags": ["popular"] },
  { "_id": 1, "name": "Product A", "category": "Electronics", "price": 100, "status": "active", "tags": ["new", "sale"] },
  { "_id": 4, "name": "Product D", "category": "Books", "price": 80, "status": "active", "tags": ["new"] },
  { "_id": 3, "name": "Product C", "category": "Books", "price": 50, "status": "active", "tags": ["bestseller", "new"] },
  { "_id": 5, "name": "Product E", "category": "Clothing", "price": 30, "status": "inactive", "tags": ["sale"] }
]

---

4. $project

Query: Include only name and price fields.

const result = await collection.aggregate([
  { $project: { name: 1, price: 1, _id: 0 } }
]).toArray();

Output:

[
  { "name": "Product A", "price": 100 },
  { "name": "Product B", "price": 200 },
  { "name": "Product C", "price": 50 },
  { "name": "Product D", "price": 80 },
  { "name": "Product E", "price": 30 }
]

---

5. $unwind

Query: Deconstruct the tags array.

const result = await collection.aggregate([{ $unwind: "$tags" }]).toArray();

Output:

[
  { "_id": 1, "name": "Product A", "category": "Electronics", "price": 100, "status": "active", "tags": "new" },
  { "_id": 1, "name": "Product A", "category": "Electronics", "price": 100, "status": "active", "tags": "sale" },
  { "_id": 2, "name": "Product B", "category": "Electronics", "price": 200, "status": "inactive", "tags": "popular" },
  { "_id": 3, "name": "Product C", "category": "Books", "price": 50, "status": "active", "tags": "bestseller" },
  { "_id": 3, "name": "Product C", "category": "Books", "price": 50, "status": "active", "tags": "new" },
  { "_id": 4, "name": "Product D", "category": "Books", "price": 80, "status": "active", "tags": "new" },
  { "_id": 5, "name": "Product E", "category": "Clothing", "price": 30, "status": "inactive", "tags": "sale" }
]

---

6. $lookup

Query: Join with an orders collection to include order details. Assume orders collection:

[
  { "_id": 101, "productId": 1, "quantity": 2 },
  { "_id": 102, "productId": 3, "quantity": 1 }
]

const result = await collection.aggregate([
  { $lookup: {
    from: "orders",
    localField: "_id",
    foreignField: "productId",
    as: "orderDetails"
  } }
]).toArray();

Output:

[
  { "_id": 1, "name": "Product A", "orderDetails": [{ "_id": 101, "productId": 1, "quantity": 2 }] },
  { "_id": 3, "name": "Product C", "orderDetails": [{ "_id": 102, "productId": 3, "quantity": 1 }] },
  ...
]

---

7. $addFields

Query: Add a discountedPrice field (10% discount).

const result = await collection.aggregate([
  { $addFields: { discountedPrice: { $multiply: ["$price", 0.9] } } }
]).toArray();

Output:

[
  { "_id": 1, "name": "Product A", "price": 100, "discountedPrice": 90 },
  { "_id": 2, "name": "Product B", "price": 200, "discountedPrice": 180 },
  ...
]

---

8. $replaceRoot

Query: Replace root with tags.

const result = await collection.aggregate([
  { $replaceRoot: { newRoot: { tags: "$tags" } } }
]).toArray();

Output:

[
  { "tags": ["new", "sale"] },
  { "tags": ["popular"] },
  ...
]

---

9. $limit

Query: Limit to 2 documents.

const result = await collection.aggregate([{ $limit: 2 }]).toArray();

Output:

[
  { "_id": 1, "name": "Product A", "category": "Electronics", ... },
  { "_id": 2, "name": "Product B", "category": "Electronics", ... }
]

---

10. $skip

Query: Skip the first 2 documents.

const result = await collection.aggregate([{ $skip: 2 }]).toArray();

Output:

[
  { "_id": 3, "name": "Product C", "category": "Books", ... },
  ...
]