最新のC100DEV問題集で試験を準備する

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MongoDB Certified Developer Associate 認定 C100DEV 試験問題：

1. How many indexes will the following command create?
db.products.createIndex( { product_name: 1, product_category: -1 } )

A) 2
B) 1
C) 0
D) 3

2. 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 } }, { _id: ObjectId("573a13e3f29313caabdc08a4"), genres: [ 'Horror', 'Thriller' ], title: 'Mary Loss of Soul', year: 2014, imdb: { rating: '', votes: '', id: 2904798 } } We need to use Aggregation Framework to calculate the following aggregates: -> average imdb rating -> minimum imdb rating -> maximum imdb rating Expected output: [ { _id: null, avg_rating: 6.6934040649367255, min_rating: 1.6, max_rating: 9.6 } ] Please note that some documents have "" (empty string) for the field "imdb.rating". Exclude these documents before aggregation. Which pipeline should you use?

A) [{ $match: { "imdb.rating": { $ne: "" } } }, { $group: { _id: null, avg_rating: { $avg: "$imdb.rating" }, min_rating: { $min: "$imdb.rating" }, max_rating: { $max: "$imdb.rating" } } }]
B) [{ $match: { "imdb.rating": { $ne: "" } } }, { $group: { _id: null, avg_rating: { $avg: "imdb.rating" }, min_rating: { $min: "imdb.rating" }, max_rating: { $max: "imdb.rating" } } }]
C) [{ $match: { "imdb.rating": { $ne: "" } } }, { $group: { _id: null, avg_rating: { avg: "$imdb.rating" }, min_rating: { min: "$imdb.rating" }, max_rating: { max: "$imdb.rating" } } }]
D) [{ $group: { _id: null, avg_rating: { $avg: "$imdb.rating" }, min_rating: { $min: "$imdb.rating" }, max_rating: { $max: "$imdb.rating" } } }]

3. What command can you use to create a capped collection named latest_news that will be limited to 3 documents and 10,000 bytes?

A) db.createCollection('latest_news', {'capped': true, 'max': 3})
B) db.createCollection('latest_news', {'capped': true, 'size': 10000, 'max': 3})
C) db.createCollection('latest_news', {'size': 10000, 'max': 3})

4. You have the following index in a products collection: { product_category: 1, product_name: 1, origin_country: -1 } Which of the following queries can use this index? Check all that apply.

A) db.products.find({ product_name: 'AIR MAX 90', origin_country: 'Bangladesh' })
B) db.products.find({ origin_country: 'Bangladesh', product_name: 'AIR MAX 90', product_category: 'shoes' })
C) db.products.find({ product_name: 'AIR MAX 90', product_category: 'shoes', origin_country: 'Bangladesh' })
D) db.products.find({ product_category: 'shoes', product_name: 'AIR MAX 90', origin_country: 'Bangladesh' })

5. Why adding indexes may lead to slower write operations?

A) Because we also need to update the index.
B) Because we have less and less disk space.

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