Lesson 56/100

Tutorials MongoDB Tutorial

$unwind

$unwind: free step-by-step lesson with examples, common mistakes, and interview tips — part of MongoDB Tutorial on Toolliyo Academy.

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MongoDB Tutorial · Lesson 56 of 100

$unwind

Foundations & CRUD ✓Queries & Schema ✓Aggregation & ScaleAtlas & Projects

Aggregation & Scale · 3 — Pipelines · ~10 min · MongoDB — Aggregation Pipelines

What is this?

$unwind deconstructs an array field so each element becomes its own document. It is how you turn line items into rows for reporting.

Why should you care?

To sum revenue by SKU you need one row per item, not one row per order. $unwind makes that possible.

See it live — copy this example

Open mongosh or MongoDB Compass, select database nosqlverse, then run the example. Change one field and run again.

db.orders.insertOne({
  orderId: "O1",
  items: [
    { sku: "A", price: 100, qty: 2 },
    { sku: "B", price: 50, qty: 1 }
  ]
})
db.orders.aggregate([
  { $unwind: "$items" },
  { $project: {
      orderId: 1,
      sku: "$items.sku",
      lineTotal: { $multiply: ["$items.price", "$items.qty"] }
  }}
])

Run Example »

Edit the code below and click Run to see the result in Toolliyo’s live editor.

Code
Result

What happened?

  • One order becomes two documents after $unwind.
  • Each has one items element.
  • lineTotal multiplies price and qty per line.
  • Perfect input for a later $group by sku.

Practice next

  1. Run the unwind pipeline.
  2. Add $group by sku summing lineTotal.
  3. Try preserveNullAndEmptyArrays option for empty items.
  4. Unwind tags on posts and $group to count tag popularity.
  5. Chain $sort by lineTotal.

Remember

$unwind flattens arrays to rows. Essential before per-element math. Can explode document counts.

SKU contribution report

Finance unwinds order items to see which SKUs drove festival revenue.

Outcome: Clear ranking of top-selling SKUs.

Interview prep for this lesson

Practice these questions aloud after reading—each links to a full structured answer.

Junior Detailed
Explain SQL queries in the context of MongoDB.
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. How to structure your answer (60–90 seconds) Define SQL queries in plain languag…
Mid Detailed
What are common mistakes teams make with Schema design when using MongoDB?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. How to structure your answer (60–90 seconds) Define Schema design in plain langu…
Senior Detailed
How would you debug a production issue related to Transactions in a MongoDB application?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. How to structure your answer (60–90 seconds) Define Transactions in plain langua…
Mid Detailed
Compare two approaches to Indexing—when would you choose each?
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. How to structure your answer (60–90 seconds) Define Indexing in plain language f…
Junior Detailed
Describe a real-world scenario where Normalization mattered in a MongoDB project.
Short answer: Interviewers want a crisp definition, a practical example from your projects, and awareness of trade-offs—not textbook dumps. How to structure your answer (60–90 seconds) Define Normalization in plain langu…
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MongoDB Tutorial
Course syllabus

MongoDB Tutorial

MongoDB — Foundations
MongoDB — CRUD Operations
MongoDB — Query Operators
MongoDB — Schema Design
MongoDB — Indexing & Performance
MongoDB — Aggregation Pipelines
MongoDB — Replication & Sharding
MongoDB — Atlas & Security
MongoDB — Modern Features
MongoDB — Real-World Projects
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