Given the following example document from an artists collection: { _id: 5, last_name: 'Maurer', first_name: 'Alfred', year_born: 1868, year_died: 1932, nationality: 'USA' } and the following index: db.artists.createIndex( { "last_name": 1, "nationality": 1 } ) How MongoDB will handle the query below?
db.artists.find( { "last_name": /^B./, "nationality": 'France' } )

• A. None of these.
• B. As a collection scan.
• C. As an index scan.

Select all true statements regarding to transactions in MongoDB.

• A. We cannot read/write to collections in the config, admin, or local databases.
• B. Transactions are associated with a session.
• C. The collections used in a transaction can be in different databases.

Suppose we have database with the following collections: db.users.insertMany([ { _id: 1, user_name: 'karo243', account_id: 1010 }, { _id: 2, user_name: 'jano23', account_id: 3213 }, { _id: 3, user_name: 'fac_data', account_id: 4336 } ]) db.accounts.insertMany([ { account_id: 1010, type: 'investment', limit: 1000000 }, { account_id: 4336, type: 'derivatives', limit: 100000 } ]) We want to perform so-called left join. To the users collection join account details from accounts collection based on account_id field. See below. Expected output: [ { _id: 1, user_name: 'karo243', account_id: 1010, account_details: [ { _id: ObjectId("61af47c6e29861661d063714"), account_id: 1010, type: 'investment', limit: 1000000 } ] }, { _id: 2, user_name: 'jano23', account_id: 3213, account_details: [] }, { _id: 3, user_name: 'fac_data', account_id: 4336, account_details: [ { _id: ObjectId("61af47c6e29861661d063715"), account_id: 4336, type: 'derivatives', limit: 100000 } ] } ]
Which query do you need to use?

• A. db.accounts.aggregate([ { $lookup: { from: 'accounts', localField: 'account_id', foreignField: 'account_id', as: 'account_details' } } ])
• B. db.users.aggregate([ { $lookup: { from: 'accounts', localField: 'account_id', foreignField: 'account_id' } } ])
• C. db.users.aggregate([ { $lookup: { from: 'accounts', localField: 'account_id', foreignField: 'account_id', as: 'account_details' } } ])
• D. db.users.aggregate([ { $lookup: { from: 'accounts', as: 'account_details' } } ])

Complete the sentence below.

• A. have an field_id index.
• B. have an _id index.
• C. By default, all MongoDB user-created collections...
• D. have no index.

Suppose we have a shipwrecks collection with the following document structure: { _id: ObjectId("578f6fa2df35c7fbdbaed8ce"), feature_type: 'Wrecks - Visible', watlev: 'always dry', coordinates: [ -79.9469681, 9.3729954 ] } Your application will often query based on the coordinates field. How to create a 2dsphere geospatial index for the coordinates field?

• A. db.shipwrecks.createIndex({'coordinates': 'text'})
• B. db.shipwrecks.createIndex({'coordinates': '1'})
• C. db.shipwrecks.createIndex({'coordinates': '2d'})
• D. db.shipwrecks.createIndex({'coordinates': '2dsphere'})