[Full-Version] 2025 New PrepAwayExam C100DEV PDF Recently Updated Questions [Q34-Q49]

Rate this post

[Full-Version] 2025 New PrepAwayExam C100DEV PDF Recently Updated Questions

C100DEV Exam with Guarantee Updated 253 Questions

MongoDB C100DEV Exam consists of multiple-choice questions and practical exercises that test developers’ skills and knowledge. C100DEV exam is divided into two parts: the first part covers a range of topics related to MongoDB, such as data modeling, query language, and indexing. The second part is a practical exercise where developers are required to build a MongoDB application based on a given set of requirements.

MongoDB C100DEV Certification Exam is an online, proctored exam that consists of 60 multiple-choice questions. C100DEV exam duration is 90 minutes, and candidates must score at least 75% to pass the exam. C100DEV exam fee is $150, and the certification is valid for two years. MongoDB Certified Developer Associate Exam certification provides developers with a competitive edge in the job market and enhances their career growth by validating their skills and knowledge in MongoDB application development.

Q34. 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_location’: { type: ‘Point’, coordinates: [ -73.960876, 40.710451 ] }, ‘end_station_location’: { 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?

db.trips.find( { ‘coordinates’: { $lt: -73.5 } } )

db.trips.find( { ‘end_station_location.coordinates.0’: { $gt: -73.5 } } )

db.trips.find( { ‘end_station_location.coordinates.0’: { $lt: -73.5 } } )

db.trips.find( { ‘end_station_location.coordinates.1’: { $lt: -73.5 } } )

https://docs.mongodb.com/manual/reference/operator/query/lt/

Q35. Select properly used $out operator.

db.collection.aggregate([ { stage1 }, { stage2 }, …, { stageN }, { $out: “new_collection” } ])

db.collection.aggregate([ { stage1 }, { $out: “new_collection” }, { stage2 }, …, { stageN } ])

db.collection.aggregate([ { $out: “new_collection” }, { stage1 }, { stage2 }, …, { $stageN } ])

https://docs.mongodb.com/manual/reference/operator/aggregation/out/

Q36. Select all true statements about MongoDB documents.

MongoDB documents must have the same fields in the collection.

MongoDB documents are stored as BSON documents.

MongoDB documents have a flexible schema.

MongoDB documents are stored as JSON documents.

https://docs.mongodb.com/manual/core/document/

Q37. Select all true statements about differences between using aggregate() and find() methods?

find() allows us to compute and reshape data in the cursor.

Any aggregation pipeline can be translated into a find() query.

Any find() query can be translated into an aggregation pipeline.

aggregate() allows us to compute and reshape data in the cursor (like $group, $min and other stages).

https://docs.mongodb.com/manual/reference/method/db.collection.find/ https://docs.mongodb.com/manual/reference/method/db.collection.aggregate/

Q38. You have to create a simple configuration file for mongod instance. Here are the requirements of your mongod instance: * run on port 27100 * authentication is enabled Which of the following configuration file meet these requirements?

net:
port: 27000
processManagement:
fork: true

net:
port: 27100
security:
authorization: disabled

net:
port: 27100
security:
authorization: enabled

https://docs.mongodb.com/manual/reference/configuration-options/

Q39. Suppose you have a reviews collection in your database and you want to optimize the following query: db.reviews.find( { “votes”: { “$gt”: 100 }, “rating”: 4.5 } ).sort( { “date”: 1 } ) Which index on this collection will be the most performant for the above query? Keep in mind the equality, sort, range rule.

{ votes: 1, rating: 1, date: 1 }

{ rating: 1, votes: 1, date: 1 }

{ date: 1, rating: 1, votes: 1 }

{ rating: 1, date: 1, votes: 1 }

{ votes: 1, date: 1, rating: 1 }

{ date: 1, votes: 1, rating: 1 }

The most efficient index for the given query should follow the equality, sort, range rule which is in this case: { rating: 1, date: 1, votes: 1 } https://docs.mongodb.com/manual/indexes/

Q40. Suppose you are connected to mongod instance that is already running on port 27000 as admin user. You have to export reviews collection from the restaurants database to JSON file named reviews.json. Which command should you use?

mongoexport –db restaurants –collection reviews -o reviews.json

mongodump –db restaurants –collection reviews -o reviews.json

mongoexport –db restaurants –collection reviews -o export.json

https://docs.mongodb.com/database-tools/mongoexport/

Q41. Suppose you are connected to mongod instance that is already running on port 27000 as admin user. You have to create a new user for an application that has the readWrite role. Use the db.createUser() command to create a user for a CRUD application. The requirements for this user are: -> role: readWrite on esmartdata database -> username: esmart -> password: esmart123 Which command should you use?

db.createUser({ user: ‘esmart’, pwd: ‘esmart123’, roles: [{role: ‘read’, db: ‘esmartdata’}] })

db.createUser({ user: ‘esmart’, pwd: ‘esmart123’, roles: [{role: ‘readWrite’, db: ”}] })

db.createUser({ user: ‘esmart’, pwd: ‘esmart123’, roles: [{role: ‘readWrite’, db: ‘esmartdata’}] })

db.createUser({ user: ‘esmart’, pwd: ‘esmart123’, roles: [{role: ‘read+write’, db: ‘esmartdata’}] })

https://docs.mongodb.com/manual/reference/method/db.createUser/

Q42. Suppose you added the following index to a products collection: { product_category: 1 } Which of the following operations can potentially decrease performance?

db.products.insertOne( { product_category: ‘clothes’ } )

db.products.find( { product_category: ‘clothes’ } )

db.products.updateOne( { product_category: ‘shoes’ }, { $set: company: ‘Nike’ } )

The updateOne and insertOne operations are correct because adding indexes affects write performance.

Q43. 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 } } We need to extract all movies from this collection where genres does not include ‘Romance’. Which query should we use?

db.movies.find( { genres: { $nin: [‘Romance’] } } )

db.movies.find( { genres: { $or: [‘Romance’] } } )

db.movies.find( { genres: { $and: [‘Romance’] } } )

db.movies.find( { genres: { $in: [‘Romance’] } } )

https://docs.mongodb.com/manual/reference/operator/query/nin/

Q44. 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” } )

COLLSCAN

IXSCAN

https://docs.mongodb.com/manual/indexes/

Q45. There is a collection named products in MongoDB database. Your coworker wants to know how many products are in this collection (number of documents in the collection) from the United States. Which query should you use?

db.products.find( { country: “USA” } ).count()

db.products.find( country = “USA” ).count()

db.products.find( country == “USA” ).count()

db.products.find( { country: “USA” } )

https://docs.mongodb.com/manual/reference/method/db.collection.find/

Q46. Given the following MongoDB URI: mongodb+srv://datascientist34:[email protected]/admin Which of the following statements are true? (select 2)

There are 178 nodes in the xtr replica set.

The password used for authentication is xtr-178

The password used for authentication is ta33w9rd

The user datascientist34 is trying to authenticate on database admin.

Explanation: https://docs.mongodb.com/manual/reference/connection-string/

Q47. Which cursor method should you use to get information about the query plan?

cursor.hint()

cursor.explain()

cursor.map()

https://docs.mongodb.com/manual/reference/method/cursor.explain/

Q48. Suppose you have a developers collection with the following document structure: { _id: 1, fname: ‘Bob’, lname: ‘Smith’, tech_stack: [ ‘git’, ‘c++’, ‘sqlite’, ‘linux’ ] } Select a query that can be executed without errors.

db.developers.updateOne( { _id: 1 }, { $set: { _id: 3 } } )

db.developers.updateOne( { _id: 1 }, { $set: { fname: ‘John’ } } )

db.developers.updateOne( { _id: 1 }, { $unset: { _id: ” } } )

db.developers.updateOne( { _id: 1 }, { $set: { _id: 3, fname: ‘Bob’ } } )

https://docs.mongodb.com/manual/reference/method/db.collection.updateOne/

Q49. Suppose you have an accounts collection in your database. Only the following documents are stored in this collection: { _id: ObjectId(“61af47c6e29861661d063714”), account_id: 1010, type: ‘investment’, limit: 2000000 }, { _id: ObjectId(“61af47c6e29861661d063715”), account_id: 4336, type: ‘derivatives’, limit: 100000 }, { _id: ObjectId(“61af47c6e29861661d063716”), account_id: 4336, type: ‘commodity’, limit: 1000 }, { _id: ObjectId(“61af47c6e29861661d067825”), account_id: 7355, type: ‘commodity’, limit: 500000 }, { _id: ObjectId(“61b1bde1ceb6f770f56b0cd9”), account_id: 4915, type: ‘investment’, limit: 2000000 } How many documents will be returned in response to the following aggregation pipeline? [{ $group: { _id: “$type”, number_of_accounts: { $sum: 1 } }}, { $match: { number_of_accounts: { $gt: 1 } }}]