Why expressions matter in pipelines in MongoDB - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to add a new field 'total' that sums 'price' and 'tax' in each document.

MongoDB

db.sales.aggregate([{ $addFields: { total: { $[1]: ["$price", "$tax"] } } }])

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

Aadd

Bsum

Cmultiply

Dconcat

Attempts:

3 left

💡 Hint

Common Mistakes

Using $sum instead of $add inside $addFields

Using $multiply which multiplies values

Using $concat which joins strings

The $add expression adds numbers in MongoDB pipelines. Here, it sums 'price' and 'tax'.

2fill in blank

medium

Complete the code to filter documents where 'score' is greater than 80 using $match and $expr.

MongoDB

db.students.aggregate([{ $match: { $expr: { $[1]: ["$score", 80] } } }])

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

Aeq

Bgt

Clt

Dne

Attempts:

3 left

💡 Hint

Common Mistakes

Using $eq which checks equality

Using $lt which checks less than

Using $ne which checks not equal

The $gt expression checks if the first value is greater than the second.

3fill in blank

hard

Fix the error in the pipeline to correctly compute the average of 'marks' array using $avg.

MongoDB

db.exams.aggregate([{ $project: { average: { $[1]: "$marks" } } }])

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

Asum

Bmin

Cmax

Davg

Attempts:

3 left

💡 Hint

Common Mistakes

Using $sum which adds values

Using $max or $min which find extremes

The $avg expression calculates the average of values in an array.

4fill in blank

hard

Fill both blanks to create a pipeline that filters documents where 'age' is less than 30 and then projects only 'name' and 'age'.

MongoDB

db.people.aggregate([{ $match: { $expr: { $[1]: ["$age", 30] } } }, { $project: { [2]: 1, age: 1 } }])

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

Alt

Bgt

Cname

Dscore

Attempts:

3 left

💡 Hint

Common Mistakes

Using $gt instead of $lt

Projecting wrong fields like 'score'

$lt filters ages less than 30. Projecting 'name' and 'age' shows only these fields.

5fill in blank

hard

Fill all three blanks to create a pipeline that adds a field 'discountedPrice' by subtracting 'discount' from 'price', then filters where 'discountedPrice' is greater than 100.

MongoDB

db.products.aggregate([{ $addFields: { discountedPrice: { $[1]: ["$price", "$discount"] } } }, { $match: { $expr: { $[2]: ["$discountedPrice", [3]] } } }])

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

Asubtract

Bgt

C100

Dadd

Attempts:

3 left

💡 Hint

Common Mistakes

Using $add instead of $subtract

Using $lt instead of $gt

Filtering with wrong value

$subtract calculates discounted price. $gt filters prices greater than 100.