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Become MongoDB Certified with updated C100DEV exam questions and correct answers
Consider a MongoDB database managing e-commerce product data. The database has a collection named products with documents containing the fields product_id, category, price, and reviews. Each reviews field is an array of subdocuments with fields user_id, rating, and comment. You are tasked with optimizing a query that retrieves all products within a specific category that have an average rating higher than 4. The query is frequently used, and performance is critical. Which indexing strategy would best optimize this query?
How can you insert a new document into a MongoDB collection named customers?
Suppose you have a restaurants collection with the following document structure:
{
_id: ObjectId("5eb3d668b31de5d588f42931"),
address: {
building: '6409',
coord: [ -74.00528899999999, 40.628886 ],
street: '11 Avenue',
zipcode: '11219'
},
borough: 'Brooklyn',
cuisine: 'American',
grades: [
{
date: ISODate("2014-07-18T00:00:00.000Z"),
grade: 'A',
score: 12
},
{
date: ISODate("2013-07-30T00:00:00.000Z"),
grade: 'A',
score: 12
},
{
date: ISODate("2013-02-13T00:00:00.000Z"),
grade: 'A',
score: 11
},
{ date: ISODate("2012-08-16T00:00:00.000Z"),
grade: 'A',
score: 2 },
{
date: ISODate("2011-08-17T00:00:00.000Z"),
grade: 'A',
score: 11
}
],
name: 'Regina Caterers',
restaurant_id: '40356649'
}
You don't have any indexes so far. What will the query plan look like for the following query?
db.restaurants.find( { "cuisine": "American" } )
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