$facet for multiple pipelines in MongoDB - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to use $facet to run multiple pipelines in one aggregation.

MongoDB

db.collection.aggregate([{ $facet: { results: [[1]] } }])

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A{ $limit: 5 }

B{ $match: { status: 'A' } }

C{ $sort: { score: -1 } }

D{ $group: { _id: '$status' } }

Attempts:

3 left

💡 Hint

Common Mistakes

Using a single stage object instead of an array.

Not wrapping the pipeline stages in an array.

The $facet stage requires an array of pipeline stages. Here, we start with a $match stage inside the 'results' pipeline.

2fill in blank

medium

Complete the code to add a second pipeline named 'counts' inside $facet.

MongoDB

db.collection.aggregate([{ $facet: { results: [{ $match: { status: 'A' } }], counts: [[1]] } }])

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A{ $sort: { total: -1 } }

B{ $group: { _id: null } }

C{ $limit: 10 }

D{ $count: 'total' }

Attempts:

3 left

💡 Hint

Common Mistakes

Using $group without specifying an accumulator.

Using $sort or $limit instead of $count.

The $count stage counts the number of documents passing through the pipeline and outputs a document with the count.

3fill in blank

hard

Fix the error in the $facet stage by completing the missing pipeline for 'averageScore'.

MongoDB

db.collection.aggregate([{ $facet: { averageScore: [[1]] } }])

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A{ $group: { _id: null, avgScore: { $avg: '$score' } } }

B{ $match: { score: { $exists: true } } }

C{ $sort: { score: 1 } }

D{ $limit: 1 }

Attempts:

3 left

💡 Hint

Common Mistakes

Using $match instead of $group for aggregation.

Not specifying the _id field in $group.

The $group stage with $avg accumulator calculates the average score across documents.

4fill in blank

hard

Fill both blanks to create two pipelines inside $facet: one for filtering active users and one for counting them.

MongoDB

db.users.aggregate([{ $facet: { activeUsers: [[1]], activeCount: [[2]] } }])

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A{ $match: { active: true } }

B{ $count: 'count' }

C{ $group: { _id: '$active' } }

D{ $sort: { name: 1 } }

Attempts:

3 left

💡 Hint

Common Mistakes

Using $group instead of $count for counting.

Not filtering active users before counting.

The first pipeline filters active users with $match. The second pipeline counts them with $count.

5fill in blank

hard

Fill all three blanks to create pipelines inside $facet: one to sort by age, one to group by city, and one to count total documents.

MongoDB

db.people.aggregate([{ $facet: { sortedByAge: [[1]], groupedByCity: [[2]], totalCount: [[3]] } }])

Drag options to blanks, or click blank then click option'

A{ $sort: { age: 1 } }

B{ $group: { _id: '$city' } }

C{ $count: 'total' }

D{ $match: { age: { $gt: 18 } } }

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up $group and $count stages.

Not using $sort correctly for ordering.

The first pipeline sorts documents by age ascending. The second groups documents by city. The third counts total documents.