C100DEV Practice Exams and Training Solutions for Certifications [Q19-Q33]

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C100DEV Practice Exams and Training Solutions for Certifications

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Q19. 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

Q20. Select all true statements about the differences between mongoexport and mongodump.

mongoexport outputs BSON file, but mongodump outputs JSON file.

mongoexport outputs JSON file, but mongodump outputs BSON file.

mongodump can create a data file and a metadata file, but mongoexport just creates a data file.

By default, mongodump sends output to stdout, but mongoexport writes to a file.

mongodump is typically faster than mongoexport

Q21. Select all true statements regarding to the role of fields and values in a MongoDB document. (select 2)

A field is a unique identifier for a specific data point.

You can have duplicate field names within the same level of a single document.

Values don’t need to be attached to fields and can be standalone data points.

Each field has a value associated with it.

Q22. Select all true statements about setting up a replica set in MongoDB.

All nodes in a replica set must be running on the same port.

rs.initiate() should only be run on one node in the replica set.

When connecting to a replica set, the mongo shell will redirect to the connection to the primary node.

Q23. Is MongoDB a NoSQL database?

Yes

Q24. 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 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. Example output: [ { imdb: { votes: 1521105 }, genres: [ ‘Crime’, ‘Drama’ ], title: ‘The Shawshank Redemption’ }, { imdb: { votes: 1513145 }, genres: [ ‘Crime’, ‘Drama’ ], title: ‘The Shawshank Redemption’ }, { imdb: { votes: 1495351 }, genres: [ ‘Action’, ‘Crime’, ‘Drama’ ], title: ‘The Dark Knight’ }, … Which pipeline should you use?

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

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

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

Q25. You have the following index in a movies collection: { “title”: 1, “imdb.rating”: -1, “imdb.votes”: -1, “type”: 1 } Can the following query use the given index for both filtering and sorting?
db.movies.find( { “imdb.rating”: 8, “title”: “James Bond” } ).sort( { “imdb.votes”: -1 } )

Yes

Q26. We have the following index in a movies collection: { title: 1, genres: 1 } We want to insert the following document: { “title”: “The Immigrant”, “year”: 1917, “genres”: [ “Short”, “Comedy”, “Drama” ] } Select proper index entries.

“The Immigrant”, “Short”

“The Immigrant”, “Comedy”

“The Immigrant”, “Drama”

“Short”, “The Immigrant”

“Comedy”, “The Immigrant”

“Drama”, “The Immigrant”

“The Immigrant”, “Short”, “Comedy”, “Drama”

Q27. Select all options where you should use sharding.

Your server disks are full, but you can scale up.

You have over 6TB per server and operating costs are increasing dramatically.

Your organization outgrows the most powerful servers available, which limits your vertical scaling capabilities.

Every time you start a new project with MongoDB.

Q28. How to shutdown the server? (Mongo shell)

use admin

db.shutdown()

use admin

db.shutdownServer()

use admin

db.disconnect()

Q29. What is data modeling in MongoDB world?

A way to organize fields in a document to support your application performance and querying capabilities.

A way to build your application based on how your data is stored.

A way to show your database with graphs.

A way to decide whether to store your data in the cloud or locally.

Q30. 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’}] })

Q31. Which of the following commands will successfully insert exactly two new documents into an empty companies collection?

db.companies.insertMany([ {“_id”: 1, “name”: “Facebook”}, {“_id”: 1, “name”: “Twitter”}, {“_id”: 2, “name”: “Tesla”} ], {“ordered”: false})

db.companies.insertMany([ {“_id”: 1, “name”: “Facebook”}, {“_id”: 1, “name”: “Twitter”}, {“_id”: 2, “name”: “Tesla”} ])

db.companies.insertMany([ {“_id”: 1, “name”: “Facebook”}, {“_id”: 2, “name”: “Twitter”} ])

db.companies.insertMany([ {“_id”: 1, “name”: “Facebook”}, {“_id”: 2, “name”: “Twitter”}, {“_id”: 2, “name”: “Tesla”} ])

db.companies.insertMany([ {“name”: “Facebook”}, {“name”: “Twitter”} ])

Q32. 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?

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

[{ $group: { _id: “$products”, total: { $sum: 1 } } }, { $sort: { total: -1 } }]

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

Q33. Select all true statement regarding to the MongoDB (BSON, JSON). (select 3)

MongoDB stores data in BSON, and we can view it in JSON.

MongoDB stores data in JSON, and we can view it in BSON.

BSON supports as many data types as JSON.

BSON supports more data types than JSON.

BSON is faster to parse and lighter to store than JSON.