[Full-Version] 2023 New C100DEV Actual Exam Dumps, MongoDB Practice Test [Q14-Q36]

18 Aug, 2023 By admin C100DEV, MongoDB 0 Comments

[Full-Version] 2023 New C100DEV Actual Exam Dumps, MongoDB Practice Test [Q14-Q36]

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[Full-Version] 2023 New C100DEV Actual Exam Dumps, MongoDB Practice Test

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The MongoDB C100DEV exam is available worldwide, and it is administered through the MongoDB certification portal. There is a fee to take the exam, but it is a worthwhile investment for individuals who are looking to advance their careers in the technology field. MongoDB Certified Developer Associate Exam certification is valid for two years, after which, the candidate must retake the exam or complete a continuing education requirement to renew the certification. Certification is a great way to show potential employers that the developer has the skills and knowledge needed to work with MongoDB effectively.

Q14. What is a document in MongoDB?

It’s an ordered collection of keys (fields) with assigned values. The keys in each document are strings of characters. Documents in MongoDB cannot contain duplicate keys.

It’s a text file containing the configuration of the MongoDB instance.

It’s a table that contains information about all collections in the database.

Q15. Suppose you have a sales collection with the following document structure: { _id: ObjectId(“5bd761dcae323e45a93ccfe8”), saleDate: ISODate(“2015-03-23T21:06:49.506Z”), items: [ { name: ‘printer paper’, tags: [ ‘office’, ‘stationary’ ], price: Decimal128(“40.01”), quantity: 2 } { name: ‘pens’, tags: [ ‘writing’, ‘office’, ‘school’, ‘stationary’ ], price: Decimal128(“56.12”), quantity: 5 }, { name: ‘notepad’, tags: [ ‘office’, ‘writing’, ‘school’ ], price: Decimal128(“18.47”), quantity: 2 } ], storeLocation: ‘Denver’, couponUsed: true, purchaseMethod: ‘Online’ } Which operator should you use to extract all sales documents that have ‘notepad’ name in items field?

$in

$elemMatch

$nin

$match

$all

Q16. The following capped collection is given: db.createCollection(‘latest_news’, {‘capped’: true, ‘size’: 10000, ‘max’: 3}) [ { _id: ObjectId(“61e8007c9b3067e362440a88”), title: ‘COVID records broken again as weekend brings nearly 40K new cases’ }, { _id: ObjectId(“61e800989b3067e362440a89”), title: ‘Bitcoin, Ethereum, Dogecoin Face Fresh Round Of Regulatory Scrutiny’ }, { _id: ObjectId(“61e800d19b3067e362440a8a”), title: ‘Where Six Meme Stock Investors Are Now’ } ] What the latest_news collection will look like after the following operation?

db.latest_news.insertOne({title: ‘TikTok owner ByteDance dissolves its investment arm’}) [ { _id: ObjectId(“61e800989b3067e362440a89”), title: ‘Bitcoin, Ethereum, Dogecoin Face Fresh Round Of Regulatory Scrutiny’ }, { _id: ObjectId(“61e800d19b3067e362440a8a”), title: ‘Where Six Meme Stock Investors Are Now’ }, { _id: ObjectId(“61e801439b3067e362440a8b”), title: ‘TikTok owner ByteDance dissolves its investment arm’ } ]

[ { _id: ObjectId(“61e8007c9b3067e362440a88”), title: ‘COVID records broken again as weekend brings nearly 40K new cases’ }, { _id: ObjectId(“61e800989b3067e362440a89”), title: ‘Bitcoin, Ethereum, Dogecoin Face Fresh Round Of Regulatory Scrutiny’ }, { _id: ObjectId(“61e800d19b3067e362440a8a”), title: ‘Where Six Meme Stock Investors Are Now’ }, { _id: ObjectId(“61e801439b3067e362440a8b”), title: ‘TikTok owner ByteDance dissolves its investment arm’ } ]

Q17. Which of the following rules (when ordering) should be followed when building query indexes?

equality, range, sort

equality, sort, range

range, sort, equality

Q18. Suppose you have a mobile_games collection with the following document structure:
{ game: “Fishing Clash”, company: “Ten Square Games”, platforms: [‘Android’, ‘IOS’], …
release_USA: ISODate(“2017-04-09T01:00:00+01:00”),
release_France: ISODate(“2017-04-09T01:00:00+01:00”),
release_Italy: ISODate(“2017-08-17T01:00:00+01:00”), … }
You want to redesign your document structure as below:
{ game: “Fishing Clash”, company: “Ten Square Games”, platforms: [‘Android’, ‘IOS’],
releases: [ { location: “USA”, date: ISODate(“2017-04-09T01:00:00+01:00”) },
{ location: “France”, date: ISODate(“2017-04-09T01:00:00+01:00”) },
{ location: “Italy”, date: ISODate(“2017-08-17T01:00:00+01:00”) }, ], }
Which pattern solution will you use to solve this problem?

The Schema Versioning Pattern.

The Attribute Pattern.

The Bucket Pattern.

The Subset Pattern.

The Extended Reference Pattern.

Q19. 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 includes both ‘Crime’ and ‘Mystery’. Which query should we use?

db.movies.find( { genres: { $any: [“Crime”, “Mystery”] } } )

db.movies.find( { genres: { $all: [“Crime”, “Mystery”] } } )

db.movies.find( { genres: { $nin: [“Crime”, “Mystery”] } } )

db.movies.find( { genres: { $in: [“Crime”, “Mystery”] } } )

Q20. You have to launch a replica set with three members. For the first node you have the following mongo1.conf configuration file: storage: dbPath: /var/mongodb/db/1 net: bindIp: localhost port: 27000 security: authorization: enabled systemLog: destination: file path: /var/mongodb/logs/mongod1.log logAppend: true processManagement: fork: true Update this configuration file so that this mongod instance: -> authenticates internally using the keyfile /var/mongodb/pki/keyfile -> belongs to the replica set repl-set-1 Which of the following configuration file should you choose?

storage:
dbPath: /var/mongodb/db/1
fork: true
replication:
replSetName: repl-set-1

storage:
dbPath: /var/mongodb/db/1
net:
bindIp: localhost
port: 27000
security:
authorization: enabled

systemLog:
destination: file
path: /var/mongodb/logs/mongod1.log
logAppend: true
processManagement:
fork: true
repl:
replSetName: repl-set-1

Q21. Which of the following roles provides minimal privileges needed for backing up data in MongoDB?

backup

restore

update

Q22. 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).

Q23. Which of the following documents are valid JSON format? (select 2)

{_id: 1, name: “Riviera Caterer”, cuisine: “American”}

<“_id”: 1, “name”: “Riviera Caterer”, “cuisine”: “American”>

[“_id”: 1, “name”: “Riviera Caterer”, “cuisine”: “American”]

{“_id”: 1, “name”: “Riviera Caterer”, “cuisine”: “American”}

{“_id”: 1, “address”: {“street”: “Stillwell Avenue”, “zipcode”: “11224”}}

Q24. 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 movies that do not contain the Comedy and Romance genres?

db.movies.find( { genres: { $or: [“Comedy”, “Romance”] } } )

db.movies.find( { genres: { $in: [“Comedy”, “Romance”] } } )

db.movies.find( { genres: { $nin: [“Comedy”, “Romance”] } } )

Q25. Which of the following scenarios is best suited for applying the Attribute Pattern?

You need to apply document validation before inserting/modifying.

Some fields share a similar characteristics, and you want to search across those fields.

The documents in the collection are quite large.

Q26. You have the following replica set configuration: conf = { “_id”: “replset”, “version”: 1, “protocolVersion”: 1, “members”: [ { “_id”: 0, “host”: “192.168.120.24:27017”, “priority”: 2, “votes”: 1 }, { “_id”: 1, “host”: “192.168.120.24:27018”, “priority”: 1, “votes”: 1 }, { “_id”: 1, “host”: “192.168.120.24:27019”, “priority”: 1, “votes”: 1 } ] } Select all true statements about this configuration.

This configuration is incorrect. Host information must be unique for each member in a replica set.

This configuration is correct.

This configuration is incorrect. _id field must be unique for each member in a replica set.

This configuration is incorrect. You can only specify a priority of 0 or 1.

Q27. Why is high cardinality important when choosing a shard key?

Because documents with the same shard key will be placed in the same chunk. This can result in a very big chunk.

It’s not important. Low cardinality is just as good as high cardinality.

Q28. Which of the following commands are valid to start a mongod?

mongod –dbpath /data/db –fork

mongod -f /etc/mongod.conf

mongod –logpath /var/log/mongo/mongod.log –dbpath /data/db –fork

mongod –log /var/log/mongo/mongod.log –db /data/db –fork

Q29. Where is collection metadata stored in a sharded cluster?

In a random shard.

On the configuration servers.

In the primary shard.

Q30. Suppose you have a mobile_games collection with the following document structure to redesign: { game: “Fishing Clash”, company: “Ten Square Games”, platforms: [‘Android’, ‘IOS’], … release_USA: ISODate(“2017-04-09T01:00:00+01:00”), release_France: ISODate(“2017-04-09T01:00:00+01:00”), release_Italy: ISODate(“2017-08-17T01:00:00+01:00”), … } Which pattern solution is best suited for this situation?

The Subset Pattern.

There is no need to redesign the document structure.

The Bucket Pattern.

The Extended Reference Pattern.

The Attribute Pattern.

Q31. 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’ } )

Q32. Suppose you have a sales collection with the following document structure: { _id: ObjectId(“5bd761dcae323e45a93ccfe8”), saleDate: ISODate(“2015-03-23T21:06:49.506Z”), items: [ { name: ‘printer paper’, tags: [ ‘office’, ‘stationary’ ], price: Decimal128(“40.01”), quantity: 2 } { name: ‘pens’, tags: [ ‘writing’, ‘office’, ‘school’, ‘stationary’ ], price: Decimal128(“56.12”), quantity: 5 }, { name: ‘notepad’, tags: [ ‘office’, ‘writing’, ‘school’ ], price: Decimal128(“18.47”), quantity: 2 } ], storeLocation: ‘Denver’, couponUsed: true, purchaseMethod: ‘Online’ } Which of the following queries will return all document sales with ‘printer paper’ sold?

db.sales.find( { items: { $match: { name: ‘printer paper’ } } } )

db.sales.find( { items: { $elemMatch: { name: ‘printer paper’ } } } )

db.sales.find( { items: { elemMatch: { name: ‘printer paper’ } } } )

Q33. We can use REGEX in our queries in MongoDB – JavaScript regular expression syntax.

False

True

Q34. 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 use Aggregation Framework to fetch all movies from this collection where ‘Drama’ is not in genres list and the minimum ‘imdb.votes’ is at least 100. Additionally, in the projection stage, we want to leave only the following fields: -> title -> genres -> imdb.votes We also want to sort the result set by decreasing imdb votes and limit the number of documents retuned to 5. Example output: [ { imdb: { votes: 1294646 }, genres: [ ‘Action’, ‘Mystery’, ‘Sci-Fi’ ], title: ‘Inception’ }, { imdb: { votes: 1109724 }, genres: [ ‘Adventure’, ‘Fantasy’ ], title: ‘The Lord of the Rings: The Fellowship of the Ring’ }, { imdb: { votes: 1081144 }, genres: [ ‘Adventure’, ‘Fantasy’ ], title: ‘The Lord of the Rings: The Return of the King’ }, { imdb: { votes: 1080566 }, genres: [ ‘Action’, ‘Sci-Fi’ ], title: ‘The Matrix’ }, { imdb: { votes: 1004805 }, genres: [ ‘Action’, ‘Thriller’ ], title: ‘The Dark Knight Rises’ } ] Which pipeline should you use?

[{ $match: { genres: { $nin: [‘Drama’] }, ‘imdb.votes’: { $gte: 100 } } }, { $project: { _id: 0, title: 1, genres: 1, ‘imdb.votes’: 1 } }, { $sort: { ‘imdb.votes’: -1 } }, { $limit: 5 }]

[{ $match: { genres: { $in: [‘Drama’] }, ‘imdb.votes’: { $gte: 100 } } }, { $project: { _id: 0, title: 1, genres: 1, ‘imdb.votes’: 1 } }, { $sort: { ‘imdb.votes’: -1 } }, { $limit: 5 }]

[{ $match: { genres: { $nin: [‘Drama’] }, ‘imdb.votes’: { $gte: 100 } } }, { $project: { _id: 0, title: 1, genres: 1, ‘imdb.votes’: 1 } }, { $sort: { ‘imdb.votes’: -1 } }]

Q35. Select true statements about the naming convention of collections in MongoDB.

Empty string ” cannot be a collection name.

Collection names should not contain $ sign.

Don’t create collections that start with system.

Q36. 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 }

MongoDB C100DEV (MongoDB Certified Developer Associate) Exam is a certification program designed to validate the skills and knowledge of developers who use MongoDB in their applications. C100DEV exam is aimed at individuals who have a good understanding of the MongoDB database system and have experience designing and building applications using MongoDB. MongoDB Certified Developer Associate Exam certification program is designed to demonstrate that a developer has the skills necessary to develop, deploy, and maintain MongoDB-based applications.

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[Full-Version] 2023 New C100DEV Actual Exam Dumps, MongoDB Practice Test [Q14-Q36]

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