Assign typical operational tasks to the Mongo Developer.

• A.read data
• B.create user, create index
• C.write data, read data

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Suppose you have a following index for football_palyers collection: { "last_name": 1, "details.country": 1, "details.club": 1, "age": 1 } Determine which queries are able to successfully use a given index for both filtering and sorting.

• A.db.football_players.find( { "last_name": "Lewandowski" } ).sort( { "details.country": 1, "details.club": 1 } )
• B.db.football_players.find( { "last_name": { "$gte": "L" } } ).sort( { "details.club": -1 } )
• C.db.football_players.find( { "last_name": "Lewandowski", "details.country": { "$gt": "D" } } ).sort( { "details.country": 1 } )

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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( { "title": "James Bond" } ).sort( { "imdb.rating": 1, "imdb.votes": 1 } )

• A.Yes
• B.No

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You are working in a team on a certain application in the gaming sector. Queries similar to the following are quite often executed by your application. db.gamers.find( { level: 10, is_active: true } ) How can you speed up the execution of similar queries? Choose the best option.

• A.Create the given index:
• B.db.gamers.createIndex( { level: 1 } )
• C.Create the given index:
• D.db.gamers.createIndex( { level: 1, is_active: 1 } )
• E.Create the given index:
• F.db.gamers.createIndex( { is_active: 1 } )
• G.There is no way to speed up this query.

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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" ] } How many index entries will be created?

• A.0
• B.1
• C.4
• D.2
• E.3

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