MongoDB Aggregation Interview Questions 2026, 28 Pipeline Q&A with Queries

The aggregation pipeline is where MongoDB interviews separate users from experts. Candidates report that one well-posed pipeline question, "compute revenue per customer with their latest order", filters who has actually done analytics on MongoDB. This guide compiles 28 questions from candidate-reported rounds and public preparation resources, each with a runnable pipeline and the optimization the interviewer is probing.

The model: documents flow stage to stage like a Unix pipe. Each stage transforms the stream. Order stages to filter early and compute late.

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Core Stages (Q1 to Q12)

Q1. What is the aggregation pipeline?

Q2. What does $match do and why place it first?

db.orders.aggregate([{ $match: { status: 'paid', amount: { $gt: 100 } } }]);

Q3. What does $group do?

db.orders.aggregate([
  { $group: { _id: '$userId', total: { $sum: '$amount' }, count: { $sum: 1 } } }
]);

Q4. What are the common accumulator operators?

Q5. What does $project do?

{ $project: { name: 1, year: { $year: '$createdAt' }, _id: 0 } }

Q6. What does $sort do and how do you optimize it?

Q7. What is $limit and $skip?

Q8. What does $unwind do?

db.orders.aggregate([{ $unwind: '$items' }, { $group: { _id: '$items.sku', qty: { $sum: '$items.qty' } } }]);

Q9. What does $lookup do?

{ $lookup: { from: 'users', localField: 'userId', foreignField: '_id', as: 'user' } }

Q10. How do you flatten a $lookup result?

Q11. What does $addFields do?

Q12. What is $count?

Intermediate Pipelines (Q13 to Q22)

Q13. How do you compute revenue per customer with their name?

db.orders.aggregate([
  { $match: { status: 'paid' } },
  { $group: { _id: '$userId', revenue: { $sum: '$amount' } } },
  { $lookup: { from: 'users', localField: '_id', foreignField: '_id', as: 'user' } },
  { $unwind: '$user' },
  { $project: { _id: 0, name: '$user.name', revenue: 1 } },
  { $sort: { revenue: -1 } }
]);

Candidate-reported as a near-canonical aggregation question. The interviewer watches stage order: filter, group, join, flatten, shape, sort.

Q14. How do you get the latest order per user?

db.orders.aggregate([
  { $sort: { userId: 1, createdAt: -1 } },
  { $group: { _id: '$userId', latest: { $first: '$$ROOT' } } }
]);

$first after a sort captures the newest. $$ROOT refers to the whole document.

Q15. What is $facet and when do you use it?

{ $facet: { byStatus: [{ $group: { _id: '$status', n: { $sum: 1 } } }], total: [{ $count: 'all' }] } }

Q16. What is $bucket and $bucketAuto?

Q17. How do conditional expressions work in aggregation?

{ $project: { tier: { $cond: [{ $gt: ['$amount', 1000] }, 'gold', 'standard'] } } }

Q18. How do you handle dates in aggregation?

{ $group: { _id: { $dateToString: { format: '%Y-%m', date: '$createdAt' } }, total: { $sum: '$amount' } } }

Q19. What are aggregation window functions?

Q20. How do you deduplicate documents in a pipeline?

{ $group: { _id: '$email', doc: { $first: '$$ROOT' } } },
{ $replaceRoot: { newRoot: '$doc' } }

Q21. What does $replaceRoot do?

Q22. How do you write results to a collection?

Performance and Scenarios (Q23 to Q28)

Q23. What is the memory limit for a stage and how do you handle it?

Q24. How do you make an aggregation use an index?

Q25. Why is $lookup sometimes slow and how do you speed it up?

Q26. Scenario: a dashboard query times out. How do you optimize the pipeline?

Q27. How do you debug a wrong aggregation result?

Q28. When should you precompute aggregations instead of running them live?

Aggregation Mock Test, 2026 Edition

5 original questions calibrated to the 2026 MongoDB batch by Aditya Sharma, from candidate-reported patterns.

Question 1

To count documents per group you use:

a) $count inside $group b) $sum: 1 in $group c) $size d) $limit

Solution: { $sum: 1 } counts documents per bucket. Answer: (b)

Question 2

$match should be placed:

a) last b) as early as possible to shrink the set and use indexes c) after $group d) anywhere

Solution: Early filtering reduces work and enables index use. Answer: (b)

Question 3

$unwind on an array field:

a) deletes the array b) outputs one document per array element c) sorts the array d) sums it

Solution: It deconstructs the array into separate documents. Answer: (b)

Question 4

The default per-stage memory limit is:

a) 16 MB b) 100 MB c) unlimited d) 1 GB

Solution: 100 MB per stage unless allowDiskUse is set. Answer: (b)

Question 5

To run several aggregations on the same input in one query, use:

a) $group b) $facet c) $project d) $merge

Solution: $facet runs parallel sub-pipelines. Answer: (b)

FAQ, MongoDB Aggregation Questions

Q: How many aggregation questions appear in a round? Candidates report one to three, usually one substantial pipeline you write live.

Q: Do freshers get aggregation questions? Lightly, basic $match plus $group. Deeper $lookup, $facet, and window functions skew mid to senior.

Q: Is aggregation faster than application-side processing? Usually yes, the database is closer to the data, but only with proper indexes and early filtering. Confirm operator behavior on the official MongoDB docs.

Q: What is the most-missed aggregation mistake? Forgetting that $unwind multiplies documents and inflates later sums, per candidate-reported feedback.

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