Computed pattern for pre-aggregation in MongoDB - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to add a new field 'totalSales' that sums the 'amount' field in each document.

MongoDB

db.sales.aggregate([{ $addFields: { totalSales: { $[1]: "$amount" } } }])

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

Amin

Bavg

Cmax

Dsum

Attempts:

3 left

💡 Hint

Common Mistakes

Using $avg instead of $sum will calculate average, not total.

Using $max or $min will not sum values.

The $sum operator calculates the total sum of the specified field values.

2fill in blank

medium

Complete the code to group documents by 'category' and calculate the total sales per category.

MongoDB

db.sales.aggregate([{ $group: { _id: "$category", total: { $[1]: "$amount" } } }])

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

Aavg

Bcount

Csum

Dmax

Attempts:

3 left

💡 Hint

Common Mistakes

Using $count inside $group is invalid for summing values.

Using $avg will calculate average, not total.

The $group stage groups documents by the specified field, and $sum calculates the total amount per group.

3fill in blank

hard

Fix the error in the aggregation pipeline to correctly compute the average 'score' per 'player'.

MongoDB

db.games.aggregate([{ $group: { _id: "$player", avgScore: { $[1]: "$score" } } }])

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

Aavg

Bsum

Cmax

Dmin

Attempts:

3 left

💡 Hint

Common Mistakes

Using $sum will give total, not average.

Using $max or $min will give wrong results.

The $avg operator calculates the average value of the specified field.

4fill in blank

hard

Fill both blanks to create a pre-aggregation that groups by 'region' and counts the number of sales.

MongoDB

db.sales.aggregate([{ $group: { _id: "$ [1] ", count: { $[2]: 1 } } }])

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

Aregion

Bsum

Ccount

Dcategory

Attempts:

3 left

💡 Hint

Common Mistakes

Using $count inside $group is invalid.

Grouping by wrong field will give wrong groups.

Grouping by region groups sales by that field. Using $sum: 1 counts each document.

5fill in blank

hard

Fill all three blanks to create a pre-aggregation pipeline that groups by 'product', calculates total 'quantity', and filters groups with total quantity greater than 100.

MongoDB

db.sales.aggregate([ { $group: { _id: "$ [1] ", totalQty: { $[2]: "$quantity" } } }, { $match: { totalQty: { $[3]: 100 } } } ])

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

Aproduct

Bsum

Cgt

Dcategory

Attempts:

3 left

💡 Hint

Common Mistakes

Using $avg instead of $sum will calculate average, not total.

Using $lt instead of $gt will filter wrong groups.

Group by product, sum quantity with $sum, then filter with $gt (greater than) 100.