Free MongoDB C100DEV Exam Questions

Question 1

Suppose you have a restaurants collection with the following document structure:

{

_id: ObjectId("5eb3d668b31de5d588f42931"),

address: {

building: '6409',

coord: [ -74.00528899999999, 40.628886 ],

street: '11 Avenue',

zipcode: '11219'

},

borough: 'Brooklyn',

cuisine: 'American',

grades: [

{

date: ISODate("2014-07-18T00:00:00.000Z"),

grade: 'A',

score: 12

},

{

date: ISODate("2013-07-30T00:00:00.000Z"),

grade: 'A',

score: 12

},

{

date: ISODate("2013-02-13T00:00:00.000Z"),

grade: 'A',

score: 11

},

{ date: ISODate("2012-08-16T00:00:00.000Z"),

grade: 'A',

score: 2 },

{

date: ISODate("2011-08-17T00:00:00.000Z"),

grade: 'A',

score: 11

}

],

name: 'Regina Caterers',

restaurant_id: '40356649'

}

You don't have any indexes so far. What will the query plan look like for the following query?

db.restaurants.find( { "cuisine": "American" } )

A : IXSCAN

B : SORT

C : FETCH

D : COLLSCAN

Answer: D

Question 2

What command can you use to create a capped collection named latest_news that will be limited to 3 documents and 10,000 bytes?

A : db.createCollection('latest_news', {'size': 10000, 'max': 3})

B : db.createCollection('latest_news', {'capped': true, 'size': 10000, 'max': 3})

C : db.createCollection('latest_news', 'capped': true, 'size': 10000, 'max': 3)

D : db.createCollection('latest_news', {'capped': true, 'max': 3})

Answer: B

Question 3

You are developing a MongoDB application where write performance is a critical requirement. Given a scenario where your application primarily performs insert operations and rarely performs updates or deletes, which of the following MongoDB features would best optimize this heavy-write workload?

A : Change Streams

B : Capped Collections

C : Aggregation Pipeline

D : Sharding

Answer: D

Question 4

You have two collections in your MongoDB database: students and grades. The students collection contains the following document:

{

"_id": ObjectId("64d5b0e5c9d95a76ac3ebed2"),

"student_id": 1,

"name": "Alice"

}

The grades collection contains the following documents:

{

"_id": ObjectId("64d5b0e5c9d95a76ac3ebed3"),

"student_id": 2,

"course": "Math",

"grade": "A"

},

{

"_id": ObjectId("64d5b0e5c9d95a76ac3ebed4"),

"student_id": 2,

"course": "Science",

"grade": "B"

}

You run the following aggregation query to retrieve students along with their grades:

db.students.aggregate([

{

$lookup: {

from: "grades",

localField: "student_id",

foreignField: "student_id",

as: "grades_details"

}

])

What will be the structure of the documents returned by this aggregation query for the student with student_id: 1?

A : { "_id": ObjectId("64d5b0e5c9d95a76ac3ebed2"), "student_id": 1, "name": "Alice", "grades_details": null}

B : { "_id": ObjectId("64d5b0e5c9d95a76ac3ebed2"), "student_id": 1, "name": "Alice", "grades_details": []}

C : { "_id": ObjectId("64d5b0e5c9d95a76ac3ebed2"), "student_id": 1, "name": "Alice", "grades_details": [ { "course": "Math", "grade": "A" } ]}

D : { "_id": ObjectId("64d5b0e5c9d95a76ac3ebed2"), "student_id": 1, "name": "Alice", "grades_details": [ { "course": "Math", "grade": "A" }, { "course": "Science", "grade": "B" } ]}

Answer: B

Question 5

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