100% Free MongoDB C100DEV Practice Test Questions

Question 1

You manage a MongoDB collection called inventory that stores documents for a store's inventory. Each document has the fields item, category, and quantity. You want to ensure that an item is always present in the collection, even if it needs to be inserted. Specifically, if the item "notebook" in the "Stationery" category does not exist, it should be inserted with a quantity of 50. If it does exist, its quantity should be updated to 50. You plan to use the following command:

db.inventory.updateOne(

{ "item": "notebook", "category": "Stationery" },

{ $set: { "quantity": 50 } },

{ upsert: true }

)

What will happen after executing this command if there is no "notebook" item in the "Stationery" category in the inventory collection?

A : A new document will be inserted with only quantity: 50, as other fields (item and category) are not mentioned in the $set operator.

B : Nothing will happen because the $set operator only updates existing documents and cannot insert new ones.

C : A new document will be inserted with quantity: 50, but the item field will be set to null.

D : A new document will be inserted with item: "notebook", category: "Stationery", and quantity: 50.

Answer: D

Question 2

Given the following orders collection in MongoDB:

[

{

"_id": 1,

"customer": "John",

"orderDetails": [

{ "productId": "P1", "quantity": 2, "unitPrice": 50 },

{ "productId": "P2", "quantity": 1, "unitPrice": 30 }

]

},

{

"_id": 2,

"customer": "Sara",

"orderDetails": [

{ "productId": "P1", "quantity": 3, "unitPrice": 50 },

{ "productId": "P3", "quantity": 2, "unitPrice": 20 }

]

},

{

"_id": 3,

"customer": "Peter",

"orderDetails": [

{ "productId": "P2", "quantity": 2, "unitPrice": 30 },

{ "productId": "P4", "quantity": 1, "unitPrice": 100 }

]

}

]

Which MongoDB query will find all orders that contain a product with the productId of "P1" and a quantity greater than 1?

A : db.orders.find( { orderDetails: { $elemMatch: { productId: "P1", quantity: { $gt: 1 } } } } )

B : db.orders.find( { "orderDetails.productId": "P1", "orderDetails.quantity": { $gt: 1 } } )

C : db.orders.find( { orderDetails: { $elemMatch: { productId: "P1", quantity: { $gte: 1 } } } } )

D : db.orders.find( { "orderDetails.productId": "P1", "orderDetails.quantity": { $eq: 2 } } )

Answer: A

Question 3

As a MongoDB Developer, you are tasked with the deletion of specific documents in a collection named users. The documents to be deleted are those that meet the following criteria: the age field is less than 18 and the status field is "inactive". After the deletion, you need to know the count of the deleted documents. Which of the following commands would correctly perform this operation?

A :

B :

C :

D :

E :

Answer: A

Question 4

A collection called players contains the following documents:

[

{ _id: 1, user: 'Tom', scores: [ 23, 56, 3, 52, 62 ], bonus: 5 },

{ _id: 2, user: 'Jane', scores: [ 42, 50, 10 ], bonus: 3 }

]

You want to add additional fields to each document:

-> total_score (sum of the scores Array)

-> avg_score (average score in scores Array)

-> total_score_with_bonus (total_score + bonus)

Expected output:

[

{

_id: 1,

user: 'Tom',

scores: [ 23, 56, 3, 52, 62 ],

bonus: 5,

total_score: 196,

avg_score: 39.2,

total_score_with_bonus: 201

},

{

_id: 2,

user: 'Jane',

scores: [ 42, 50, 10 ],

bonus: 3,

total_score: 102,

avg_score: 34,

total_score_with_bonus: 105

}

]

Which query do you need to use?

A : db.players.aggregate([{ $addFields: { total_score: { $sum: '$scores' }, avg_score: { $avg: '$scores' } }}, { $addFields: { total_score_with_bonus: { $add: ['$total_score', '$bonus'] } }}])

B : db.players.aggregate([{ $addFields: { total_score: { $sum: '$scores' }, avg_score: { $avg: '$scores' }, total_score_with_bonus: { $add: ['$total_score', '$bonus'] } }}])

C : db.players.aggregate([{ $add: { total_score: { $sum: '$scores' }, avg_score: { $avg: '$scores' } }}, { $add: { total_score_with_bonus: { $add: ['$total_score', '$bonus'] } }}])

Answer: A

Question 5

In your database there is a collection named sales with the following document structure:

{

_id: ObjectId("5bd761dcae323e45a93ccfe8"),

saleDate: ISODate("2015-03-23T21:06:49.506Z"),

items: [

{

tags: [ 'office', 'stationary' ],

price: Decimal128("40.01"),

quantity: 2

},

{

tags: [ 'office', 'writing', 'school' ],

price: Decimal128("35.29"),

quantity: 2

},

{

tags: [ 'writing', 'school', 'stationary' ],

price: Decimal128("56.12"),

quantity: 5

}

],

storeLocation: 'Denver',

customer: { gender: 'M', age: 42, email: '[email protected]', satisfaction: 4 },

purchaseMethod: 'Online'

}

{

_id: ObjectId("5bd761dcae323e45a93ccfe9"),

saleDate: ISODate("2015-08-25T10:01:02.918Z"),

items: [

{

tags: [ 'school', 'general', 'organization' ],

price: Decimal128("28.31"),

quantity: 9

},

{

tags: [ 'school', 'travel', 'kids' ],

price: Decimal128("83.28"),

quantity: 2

}

],

storeLocation: 'Seattle',

customer: { gender: 'M', age: 50, email: '[email protected]', satisfaction: 5 },

couponUsed: false,

purchaseMethod: 'Phone'

}

How can you extract all documents from this collection where the first tag in the tags field (Array) is 'office' in at least one item?

A : db.sales.find( { 'items.tags$0': 'office' } )

B : db.sales.find( { 'items.tags.0': 'office' } )

C : db.sales.find( { 'items.tags': 'office' } )

D : db.sales.find( { 'items.tags.[0]': 'office' } )

Answer: B

Free Practice MongoDB C100DEV Exam Questions 2026