Free MongoDB C100DEV Exam Questions

Question 1

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 2

Which of the following statements are true regarding the MongoDB Aggregation Framework and pipelines? (Select two)

A : Aggregation pipelines can include stages like $match, $group, $project, and $sort.

B : Aggregation pipelines allow you to modify the structure of the original collection.

C : Aggregation pipelines support SQL-like joins between multiple collections.

D : The $limit stage is used to skip a specified number of documents in the aggregation pipeline.

E : The $unwind stage is used to deconstruct an array field from the input documents, creating a new document for each element of the array.

Answer: A,E

Question 3

You are managing a MongoDB collection named orders, where each document represents an order. The documents contain the following fields:order_id (String): The unique identifier for the order.customer_name (String): The name of the customer who placed the order.total_amount (Number): The total amount of the order.status (String): The status of the order, which can be "pending," "shipped," or "delivered."items (Array of Strings): A list of items included in the order.You want to find all orders that meet the following criteria:The order has a total amount greater than $1000.The order status is either "pending" or "shipped."The order contains either "laptop" or "smartphone" in the list of items.Which of the following queries would return the correct documents?

A :

B :

C :

D :

Answer: D

Question 4

Suppose you have a reviews collection with the following index:

{ stars: 1, votes: 1 }

Which of the following queries would be a covered query?

A : db.reviews.find( { votes: { $gte: 100 } }, { _id: 0, votes: 1, stars: 1 })

B : db.reviews.find( { votes: { $gte: 100 } }, { _id: 0, votes: 1 })

C : db.reviews.find( { votes: { $gte: 100 }, stars: 4.5 }, { _id: 0 })

D : db.reviews.find( { stars: { $gt: 4.5 } }, { _id: 0, votes: 1 })

Answer: D

Question 5

Consider a MongoDB database containing a collection of documents representing online orders for an e-commerce website. The documents have the following structure:

{

"_id": ObjectId("5f95a1d11a12b400001b75c0"),

"order_number": "ORD-001",

"order_date": ISODate("2022-01-01T00:00:00.000Z"),

"customer": {

"name": "John Doe",

"email": "johndoe@example.com"

},

"items": [

{ "product_name": "Smartphone", "quantity": 2, "price": 800 },

{ "product_name": "Laptop", "quantity": 1, "price": 1500 }

],

"shipping_address": {

"street": "123 Main St",

"city": "New York",

"state": "NY",

"zipcode": "10001"

},

"total_amount": 3000

}

Select an aggregation pipeline that returns the total sales amount by state and month, for orders placed in the year 2022. The result should have the following format:

A : [ { "$match": { "order_date": { "$gte": ISODate("2022-01-01T00:00:00.000Z"), "$lt": ISODate("2023-01-01T00:00:00.000Z") } } }, { "$group": { "_id": { "state": "$shipping_address.state", "month": { "$month": "$order_date" } }, "sales_amount": { "$sum": "$total_amount" } } }, { "$project": { "state": "$_id.state", "month": "$_id.month", "sales_amount": "$sales_amount", "_id": 0 } }]

B : [ { "$group": { "_id": { "state": "$shipping_address.state", "month": { "$month": "$order_date" } }, "sales_amount": { "$sum": "$total_amount" } } }, { "$project": { "state": "$_id.state", "month": "$_id.month", "sales_amount": "$sales_amount", "_id": 0 } }]

C : [ { "$match": { "order_date": { "$gte": ISODate("2022-01-01T00:00:00.000Z"), "$lt": ISODate("2023-01-01T00:00:00.000Z") } } }, { "$group": { "sales_amount": { "$sum": "$total_amount" } } }, { "$project": { "state": "$_id.state", "month": "$_id.month", "sales_amount": "$sales_amount", "_id": 0 } }]

D : [ { "$match": { "order_date": { "$gte": ISODate("2022-01-01T00:00:00.000Z"), "$lt": ISODate("2023-01-01T00:00:00.000Z") } } }, { "$project": { "state": "$_id.state", "month": "$_id.month", "sales_amount": "$sales_amount", "_id": 0 } }]

Answer: A