Free MongoDB C100DEV Exam Questions

Question 1

We have the following indexes:

{ name: 1, founded_year: 1 }

{ tag_list: 1, is_active: 1 }

And the following documents:

{

_id: ObjectId("52cdef7c4bab8bd675297daa"),

name: "Sparter",

founded_year: 2007,

tag_list: ["gaming", "game", "wow"],

is_active: true

},

{

_id: ObjectId("52cdef7c4bab8bd675297da3"),

name: "Yahoo!",

founded_year: 1994,

tag_list: ["search", "webmail"],

is_active: true

}

Select the true statement.

A : There would be a total of 2 index keys created across all of these documents and indexes.

B : There would be a total of 7 index keys created across all of these documents and indexes.

C : There would be a total of 4 index keys created across all of these documents and indexes.

D : The number of index keys cannot be determined from the given data.

Answer: B

Question 2

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

{

'_id': ObjectId("572bb8222b288919b68abf6d"),

'trip_duration': 858,

'start_station id': 532,

'end_station_id': 401,

'bike_id': 17057,

'start_station_loc': { type: 'Point', coordinates: [ -73.960876, 40.710451 ] },

'end_station_loc': { type: 'Point', coordinates: [ -73.98997825, 40.72019576 ] },

'start_time': ISODate("2016-01-01T00:09:31.000Z"),

'stop_time': ISODate("2016-01-01T00:23:49.000Z")

}

How can you extract all trips from this collection ended at stations that are to the west of the -73.5 longitude coordinate?

A : db.trips.find( { 'end_station_loc.coordinates.0': { $gt: -73.5 } } )

B : db.trips.find( { 'coordinates': { $lt: -73.5 } } )

C : db.trips.find( { 'end_station_loc.coordinates.0': { $lt: -73.5 } } )

D : db.trips.find( { 'end_station_loc.coordinates.1': { $lt: -73.5 } } )

Answer: C

Question 3

In the context of MongoDB development, you are creating a new service that is expected to handle high load. You've decided to leverage the MongoDB drivers' connection pooling capability. What best describes connection pooling and its advantages?

A : Connection pooling ensures secure data transfer between the client and the server by encrypting all connections in the pool.

B : Connection pooling allows a client to connect to a database only when a data transfer operation occurs, reducing the memory requirements.

C : Connection pooling involves maintaining a "pool" of open database connections, which can be reused for multiple requests, improving performance.

D : Connection pooling refers to the storage of multiple connection strings for redundancy, increasing system reliability.

Answer: C

Question 4

What is the correct syntax to insert multiple documents into a MongoDB collection named orders and return the _id values for all inserted documents?

A :

B :

C :

D :

Answer: B

Question 5

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