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FIT3182 Big data management and processing - MUM S1 2026
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Following is the structure of the restaurant collection:
{
"address": {
"building": "1007",
"coord": [ 144.946457, -37.840935 ],
"street": "Monash University Bakery",
"zipcode": "3800"
},
"suburb": "Clayton",
"cuisine": "Bakery",
"grades": [
{ "date": { "$date": 1241804700000 }, "grade": "C", "score": 1 },
{ "date": { "$date": 1224857600000 }, "grade": "A", "score": 5 },
{ "date": { "$date": 1261985600000 }, "grade": "B", "score": 9 },
{ "date": { "$date": 1201003200000 }, "grade": "A", "score": 8 },
{ "date": { "$date": 1137705200000 }, "grade": "B", "score": 13 }
],
"name": "Monash Bakery Shop",
"restaurant_id": "317455"
}
Write a MongoDB query to find the restaurants that achieved a score, more than 80 but less than 100
A mongoDB collection has the following structure:
{"sid": 128,"name": { "first": "Drew", "last": "Barrymore"},"course": "MasterAI","result": [ { "unit_code": "FIT3182", "unit_name": "Data processing for big data", "synopsis":"This unit pertains to managing big data.", "semester": 2, "year": [2023], "mark": 80 }],"yearOfUni": 3}Which of the following query finds out the number of students in each unit.Billy wrote the following query but forgot to document it. What does the following query do?
db.climate.aggregate ([{"$unwind": "$Fire"}, {"$sort":{"Fire.Surface Temp(C)":-1}}, {"$limit": 3}, {"$project":{"Fire.Surface Temp(C)":1}}])
You are designing a user database. Each user can have up to 3 addresses (e.g., home, work, mailing), and your application very frequently needs to retrieve a user profile along with all their addresses. What is the most efficient way to model this in MongoDB?
Which of the following is NOT correct regarding removing data in MongoDB?
Please enter the code seen on your table (e.g., M###)