Free MongoDB C100DEV Exam Questions

Question 1

Where is the MongoDB configuration file usually located?

A :

B :

C :

D :

E :

Answer: B

Question 2

Given a movies collection where each document has the following structure:

{

_id: ObjectId('573a1390f29313caabcd60e4'),

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

title: 'The Immigrant',

year: 1917,

imdb: { rating: 7.8, votes: 4680, id: 8133 },

countries: [ 'USA' ]

}

Which of the following queries will find all the movies that have more votes than the year in which they were released?

A : db.movies.find({ $expr: { $gt: ["imdb.votes", "year"] } } )

B : db.movies.find({ $expr: { $lt: ["$imdb.votes", "$year"] } } )

C : db.movies.find({ $gt: ["$imdb.votes", "$year"] } )

D : db.movies.find({ $expr: { $gt: ["$imdb.votes", "$year"] } } )

Answer: D

Question 3

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

{

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

"product_name": "Smartphone",

"brand": "Apple",

"price": 800,

"categories": [ "Electronics", "Smartphones" ],

"reviews": [

{ "username": "user1", "rating": 4, "comment": "Great product!" },

{ "username": "user2", "rating": 5, "comment": "Excellent!" },

{ "username": "user3", "rating": 3, "comment": "Good but overpriced." }

]

}

Select the MongoDB aggregation pipeline that returns the average rating of all products grouped by brand. The result should include only brands with an average rating greater than or equal to 4. The output should have the following format:

A : [ { "$unwind": "$reviews" }, { "$group": { "_id": "$brand", "avg_rating": { "$avg": "$reviews.rating" } } }, { "$match": { "avg_rating": { "$gte": 4 } } }]

B : [ { "$group": { "_id": "$brand", "avg_rating": { "$avg": "$reviews.rating" } } }, { "$match": { "avg_rating": { "$gte": 4 } } }, { "$project": { "brand": "$_id", "avg_rating": "$avg_rating", "_id": 0 } }]

C : [ { "$unwind": "$reviews" }, { "$group": { "_id": "$brand", "avg_rating": { "$avg": "$reviews.rating" } } }, { "$project": { "brand": "$_id", "avg_rating": "$avg_rating", "_id": 0 } }]

D : [ { "$unwind": "$reviews" }, { "$group": { "_id": "$brand", "avg_rating": { "$avg": "$reviews.rating" } } }, { "$match": { "avg_rating": { "$gte": 4 } } }, { "$project": { "brand": "$_id", "avg_rating": "$avg_rating", "_id": 0 } }]

Answer: D

Question 4

You are a MongoDB Associate Developer and need to demonstrate how to load the Atlas Sample Dataset into your MongoDB Atlas cluster. Your manager has asked you to guide a junior developer through this process to ensure they can independently load the dataset. What steps should the junior developer follow to successfully load the Atlas Sample Dataset?

A : In MongoDB Atlas, navigate to the "Clusters" tab, click on the "Load Sample Dataset" button, and wait for the dataset to be fully loaded.

B : In MongoDB Compass, connect to your cluster, go to the "Import Data" tab, and import the sample dataset by uploading the sample-dataset.json file.

C : Use the MongoDB Atlas API to send a POST request to the /loadSampleDataset endpoint, specifying your cluster ID in the request body.

D : Open the MongoDB Shell, connect to your cluster, and run the command mongoimport --db sample --collection datasets --file sample-dataset.json.

Answer: A

Question 5

We have an accounts collection with the following document structure:

{

_id: ObjectId("5ca4bbc7a2dd94ee5816239d"),

account_id: 864905,

limit: 10000,

products: [ 'Commodity', 'InvestmentStock' ]

},

{

_id: ObjectId("5ca4bbc7a2dd94ee5816239e"),

account_id: 299072,

limit: 10000,

products: [ 'InvestmentFund', 'InvestmentStock' ]

},

{

_id: ObjectId("5ca4bbc7a2dd94ee5816239f"),

account_id: 137994,

limit: 10000,

products: [ 'CurrencyService', 'InvestmentStock' ]

}

We need to use Aggregation Framework to find the distribution of products field. Sort the result set by decreasing total number of products.

Expected output:

[

{ _id: 'InvestmentStock', total: 1746 },

{ _id: 'CurrencyService', total: 742 },

{ _id: 'Brokerage', total: 741 },

{ _id: 'InvestmentFund', total: 728 },

{ _id: 'Commodity', total: 720 },

{ _id: 'Derivatives', total: 706 }

]

Which pipeline should you use?

A : [{ $group: { _id: "$products", total: { $sum: 1 } }}]

B : [{ $unwind: { path: "$products" }}, { $group: { _id: "$products", total: { $sum: 1 } }}, { $sort: { total: -1 }}]

C : [{ $unwind: { path: "products" }}, { $group: { _id: "products", total: { $sum: 1 } }}, { $sort: { total: -1 }}]

D : [{ $group: { _id: "$products", total: { $sum: 1 } }}, { $sort: { total: -1 }}]

Answer: B