Today’s practice involved joining two collections (users and orders) and mastering lookup, unwind, group, sort, and limit stages in aggregation pipelines!
Here’s the full practice breakdown ⤵️
🗄️ Database Structure:
Collection: users
[
{ "_id": 1, "name": "Alice", "country": "USA" },
{ "_id": 2, "name": "Bob", "country": "Canada" },
{ "_id": 3, "name": "Charlie", "country": "India" }
]
Collection: orders
[
{ "_id": 101, "userId": 1, "amount": 250 },
{ "_id": 102, "userId": 1, "amount": 300 },
{ "_id": 103, "userId": 2, "amount": 400 },
{ "_id": 104, "userId": 3, "amount": 150 },
{ "_id": 105, "userId": 3, "amount": 200 }
]
🧩 Challenge Questions and Answers:
1️⃣ Join users with their orders
[
{
$lookup: {
from: "orders",
localField: "_id",
foreignField: "userId",
as: "orders"
}
}
]
✅ Result: Each user document will now have an array of their related orders under "orders".
2️⃣ Unwind the orders
[
{
$lookup: {
from: "orders",
localField: "_id",
foreignField: "userId",
as: "orders"
}
},
{
$unwind: "$orders"
}
]
✅ Result: Each order becomes a separate document with user data attached (no longer an array).
3️⃣ Calculate total spend by each user
[
{
$lookup: {
from: "orders",
localField: "_id",
foreignField: "userId",
as: "orders"
}
},
{
$unwind: "$orders"
},
{
$group: {
_id: "$_id",
totalSpend: { $sum: "$orders.amount" },
name: { $first: "$name" }
}
}
]
✅ Result: Each user now has a totalSpend field showing how much they spent in total!
4️⃣ Calculate average spend per country
[
{
$lookup: {
from: "orders",
localField: "_id",
foreignField: "userId",
as: "orders"
}
},
{
$unwind: "$orders"
},
{
$group: {
_id: "$country",
avgSpent: { $avg: "$orders.amount" }
}
},
{
$project: {
country: "$_id",
avgSpent: 1,
_id: 0
}
}
]
✅ Result: Average order amount for each country!
5️⃣ Find the user who spent the most (Most Expensive User)
[
{
$lookup: {
from: "orders",
localField: "_id",
foreignField: "userId",
as: "orders"
}
},
{
$unwind: "$orders"
},
{
$group: {
_id: "$_id",
totalSpend: { $sum: "$orders.amount" },
name: { $first: "$name" }
}
},
{
$sort: {
totalSpend: -1
}
},
{
$limit: 1
},
{
$project: {
name: 1,
totalSpend: 1,
_id: 0
}
}
]
✅ Result: The top spender in the users list!
🎯 Key MongoDB Operators Practiced:
$lookup ➔ for joining collections
$unwind ➔ flatten arrays
$group ➔ aggregate data
$sort ➔ order results
$limit ➔ restrict number of outputs
$project ➔ customize final output
💬 Final Thoughts:
Working with lookup and aggregation pipelines makes MongoDB a very powerful tool for analytics, reporting, and complex data transformations!
🔥 Practice like this strengthens your real-world NoSQL database skills!
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