Free MongoDB C100DEV Exam Questions

Question 1

You have a MongoDB collection named employees that contains documents with fields name, department, and salary. You want to update the salary of all employees in the "Marketing" department to $75,000. The original collection looks like this:

[

{ "_id": 1, "name": "Alice", "department": "Marketing", "salary": 60000 },

{ "_id": 2, "name": "Bob", "department": "Sales", "salary": 55000 },

{ "_id": 3, "name": "Charlie", "department": "Marketing", "salary": 62000 },

{ "_id": 4, "name": "David", "department": "Engineering", "salary": 70000 }

]

You run the following MongoDB update operation:

db.employees.updateMany(

{ "department": "Marketing" },

{ $set: { "salary": 75000 } }

)

What will the collection look like after this update operation?

A : [ { "_id": 1, "name": "Alice", "department": "Marketing", "salary": 60000 }, { "_id": 2, "name": "Bob", "department": "Sales", "salary": 55000 }, { "_id": 3, "name": "Charlie", "department": "Marketing", "salary": 75000 }, { "_id": 4, "name": "David", "department": "Engineering", "salary": 70000 }]

B : [ { "_id": 1, "name": "Alice", "department": "Marketing", "salary": 62000 }, { "_id": 2, "name": "Bob", "department": "Sales", "salary": 55000 }, { "_id": 3, "name": "Charlie", "department": "Marketing", "salary": 62000 }, { "_id": 4, "name": "David", "department": "Engineering", "salary": 70000 }]

C : [ { "_id": 1, "name": "Alice", "department": "Marketing", "salary": 75000 }, { "_id": 2, "name": "Bob", "department": "Sales", "salary": 55000 }, { "_id": 3, "name": "Charlie", "department": "Marketing", "salary": 75000 }, { "_id": 4, "name": "David", "department": "Engineering", "salary": 70000 }]

D : [ { "_id": 1, "name": "Alice", "department": "Marketing", "salary": 60000 }, { "_id": 2, "name": "Bob", "department": "Sales", "salary": 75000 }, { "_id": 3, "name": "Charlie", "department": "Marketing", "salary": 75000 }, { "_id": 4, "name": "David", "department": "Engineering", "salary": 70000 }]

Answer: C

Question 2

Which of the following statements correctly describes the relationship between BSON and JSON in MongoDB?

A : BSON and JSON are exactly the same data format, and the terms can be used interchangeably.

B : MongoDB uses JSON for data storage, and BSON is only used for querying data.

C : BSON is a binary representation of JSON-like documents, with additional data types not found in JSON.

D : BSON is a subset of JSON and only includes a portion of JSON's data types.

Answer: C

Question 3

Consider the following scenario: You have a MongoDB collection named users that stores user information. Each document in the collection has the following structure:

{

"_id": ObjectId("609fe4b5728ad805aef1a88d"),

"name": "John Doe",

"age": 30,

"email": "johndoe@example.com",

"address": {

"street": "123 Main St",

"city": "New York",

"state": "NY",

"zipcode": "10001"

}

You need to retrieve all the documents from the users collection and convert them to an array format. Which of the following MongoDB queries should you use for this task?

A : db.users.find().convertToArray()

B : db.users.find().toArray()

C : db.users.toArray()

D : db.users.aggregate({ $toArray: "users" })

Answer: B

Question 4

What is the difference between a sparse index and a non-sparse index in MongoDB?

A : A sparse index only indexes documents that contain the indexed field, while a non-sparse index indexes all documents in the collection, including those that do not contain the indexed field.

B : A sparse index indexes all documents in the collection, including those that contain the indexed field, while a non-sparse index only indexes documents that do not contain the indexed field.

C : A sparse index only indexes documents that do not contain the indexed field, while a non-sparse index indexes all documents in the collection, including those that contain the indexed field.

D : A sparse index indexes all documents in the collection, including those that do not contain the indexed field, while a non-sparse index only indexes documents that contain the indexed field.

Answer: A

Question 5

Consider a tasks collection that holds task records. The document structure is as follows:

{

"_id": ObjectId("64b64c58ed01c0a5e72dbf5f"),

"task": "Review PR",

"status": "pending",

"assignedTo": "alice"

}

Two operations are performed concurrently:

Operation A:

db.tasks.findAndModify({

query: { task: "Review PR", status: "pending" },

remove: true

});

Operation B:

db.tasks.findAndModify({

query: { task: "Review PR", status: "pending" },

update: { $set: { status: "completed" } },

new: true

});

Operation B starts slightly after Operation A but before Operation A completes. What will be the final state of the tasks collection after both operations have been executed?

A : The document will be removed from the collection.

B : The document's status will be updated to "completed".

C : A new document with the status "completed" will be inserted.

D : The document's status will remain "pending".

Answer: A