Free MongoDB C100DEV Exam Questions

Question 1

What is the best practice in using the $match operator?

A : It doesn't matter when we apply $match stage.

B : MongoDB does not have a $match stage.

C : The later in the pipeline, the better.

D : The earlier in the pipeline, the better. Not only because we will be using expression filters which reduce the number of documents to be processed, but also because we can use indexes.

Answer: D

Question 2

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 3

We have a movies collection with the following document structure:

{

_id: ObjectId("573a1390f29313caabcd6223"),

genres: [ 'Comedy', 'Drama', 'Family' ],

title: 'The Poor Little Rich Girl',

released: ISODate("1917-03-05T00:00:00.000Z"),

year: 1917,

imdb: { rating: 6.9, votes: 884, id: 8443 }

},

{

_id: ObjectId("573a13e3f29313caabdc08a4"),

genres: [ 'Horror', 'Thriller' ],

title: 'Mary Loss of Soul',

year: 2014,

imdb: { rating: '', votes: '', id: 2904798 }

}

We need to use Aggregation Framework to calculate the following aggregates:

average imdb rating

minimum imdb rating

maximum imdb rating

Expected output:

[

{

_id: null,

avg_rating: 6.6934040649367255,

min_rating: 1.6,

max_rating: 9.6

}

]

Please note that some documents have "" (empty string) for the field "imdb.rating". Exclude these documents before aggregation.

Which pipeline should you use?

A : [{ $match: { "imdb.rating": { $ne: "" } }}, { $group: { _id: null, avg_rating: { $avg: "imdb.rating" }, min_rating: { $min: "imdb.rating" }, max_rating: { $max: "imdb.rating" } }}]

B : [{ $group: { _id: null, avg_rating: { $avg: "$imdb.rating" }, min_rating: { $min: "$imdb.rating" }, max_rating: { $max: "$imdb.rating" } }}]

C : [{ $match: { "imdb.rating": { $ne: "" } }}, { $group: { _id: null, avg_rating: { $avg: "$imdb.rating" }, min_rating: { $min: "$imdb.rating" }, max_rating: { $max: "$imdb.rating" } }}]

D : [{ $match: { "imdb.rating": { $ne: "" } }}, { $group: { _id: null, avg_rating: { avg: "$imdb.rating" }, min_rating: { min: "$imdb.rating" }, max_rating: { max: "$imdb.rating" } }}]

Answer: C

Question 4

Consider a collection named students with the following document:

{

"_id" : ObjectId("5f0a7e80d8c9c7b5a48c49e1"),

"name" : "Alice",

"age" : 21,

"courses" : [

{

"name" : "Math",

"grade" : 89

},

{

"name" : "Science",

"grade" : 92

}

]

}

What is the query to update the grade of the "Math" course for the student with "_id" equal to ObjectId("5f0a7e80d8c9c7b5a48c49e1") to 95?

A : db.students.updateOne( { "courses.name": "Math" }, { $set: { "courses.$.grade": 95 } })

B : db.students.updateOne( { _id: ObjectId("5f0a7e80d8c9c7b5a48c49e1") }, { $set: { "courses.$.grade": 95 } })

C : db.students.updateOne( { _id: ObjectId("5f0a7e80d8c9c7b5a48c49e1"), "courses.name": "Math" }, { $set: { "courses.$.grade": 95 } })

D : db.students.updateOne( { _id: ObjectId("5f0a7e80d8c9c7b5a48c49e1"), "courses.name": "Math" }, { $set: { "grade": 95 } })

Answer: C

Question 5

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