Question 1

Consider a collection named orders with the following documents:

{

"_id" : ObjectId("5f0a7e80d8c9c7b5a48c49e1"),

"order_id" : 101,

"customer_name" : "John Doe",

"order_date" : ISODate("2022-01-01T00:00:00.000Z"),

"items" : [

{

"product_name" : "Apple",

"quantity" : 2,

"price" : 0.99

},

{

"product_name" : "Banana",

"quantity" : 5,

"price" : 0.5

}

]

}

{

"_id" : ObjectId("5f0a7e80d8c9c7b5a48c49e2"),

"order_id" : 102,

"customer_name" : "Jane Doe",

"order_date" : ISODate("2022-01-02T00:00:00.000Z"),

"items" : [

{

"product_name" : "Orange",

"quantity" : 3,

"price" : 0.79

},

{

"product_name" : "Mango",

"quantity" : 2,

"price" : 1.99

}

]

}

{

"_id" : ObjectId("5f0a7e80d8c9c7b5a48c49e3"),

"order_id" : 103,

"customer_name" : "Bob Smith",

"order_date" : ISODate("2022-01-03T00:00:00.000Z"),

"items" : [

{

"product_name" : "Peach",

"quantity" : 4,

"price" : 1.49

},

{

"product_name" : "Pear",

"quantity" : 1,

"price" : 2.99

}

]

}

What is the query to retrieve the total sales for each customer in the orders collection?

Options :

A :

db.orders.aggregate([
   {
      $group: {
         _id: "$customer_name",
         total_sales: { $sum: { $multiply: ["$items.quantity", "$items.price"] } }
      }
   }
])

B :

db.orders.aggregate([
   {
      $unwind: "$items"
   },
   {
      $group: {
         _id: "$customer_name",
         total_sales: { $sum: { $multiply: ["$items.quantity", "$items.price"] } }
      }
   }
])

C :

db.orders.aggregate([
   {
      $unwind: "$items"
   },
   {
      $group: {
         total_sales: { $sum: { $multiply: ["$items.quantity", "$items.price"] } }
      }
   }
])

D :

db.orders.aggregate([
   {
      $unwind: "$items"
   },
   {
      $group: {
         _id: "$customer_name",
         total_sales: { $sum: { $multiply: ["quantity", "price"] } }
      }
   }
])

Answer: B

Question 2

Which of the following stages do you need to use to randomly select 10 documents from a specific collection?

Options :

A : { $rand: { size: 10 } }

B : { $sample: { get: 10 } }

C : { $sampleRate: { size: 10 } }

D : { $sample: { size: 10 } }

Answer: D

Question 3

Where is the MongoDB configuration file usually located?

Options :

A :

B :

C :

D :

E :

Answer: B

Question 4

Consider a tasks collection that holds task records. The document structure is as follows:

{

"_id": ObjectId("64b64c58ed01c0a5e72dbf5f"),

"task": "Review PR",

"status": "pending",

"assignedTo": "alice"

}

Two operations are performed concurrently:

Operation A:

db.tasks.findAndModify({

query: { task: "Review PR", status: "pending" },

remove: true

});

Operation B:

db.tasks.findAndModify({

query: { task: "Review PR", status: "pending" },

update: { $set: { status: "completed" } },

new: true

});

Operation B starts slightly after Operation A but before Operation A completes. What will be the final state of the tasks collection after both operations have been executed?

Options :

A : The document will be removed from the collection.

B : The document-s status will be updated to "completed".

C : A new document with the status "completed" will be inserted.

D : The document-s status will remain "pending".

Answer: A

Question 5

Consider a MongoDB database containing a collection of documents representing online orders for an e-commerce website. The documents have the following structure:

{

"_id": ObjectId("5f95a1d11a12b400001b75c0"),

"order_number": "ORD-001",

"order_date": ISODate("2022-01-01T00:00:00.000Z"),

"customer": {

"name": "John Doe",

"email": "[email protected]"

},

"items": [

{ "product_name": "Smartphone", "quantity": 2, "price": 800 },

{ "product_name": "Laptop", "quantity": 1, "price": 1500 }

],

"shipping_address": {

"street": "123 Main St",

"city": "New York",

"state": "NY",

"zipcode": "10001"

},

"total_amount": 3000

}

Select an aggregation pipeline that returns the total sales amount by state and month, for orders placed in the year 2022. The result should have the following format:

Options :

A :

[
   {
      "$match": {
         "order_date": {
            "$gte": ISODate("2022-01-01T00:00:00.000Z"),
            "$lt": ISODate("2023-01-01T00:00:00.000Z")
         }
      }
   },
   {
      "$group": {
         "_id": { "state": "$shipping_address.state", "month": { "$month": "$order_date" } },
         "sales_amount": { "$sum": "$total_amount" }
      }
   },
   {
      "$project": {
         "state": "$_id.state",
         "month": "$_id.month",
         "sales_amount": "$sales_amount",
         "_id": 0
      }
   }
]

B :

[
   {
      "$group": {
         "_id": { "state": "$shipping_address.state", "month": { "$month": "$order_date" } },
         "sales_amount": { "$sum": "$total_amount" }
      }
   },
   {
      "$project": {
         "state": "$_id.state",
         "month": "$_id.month",
         "sales_amount": "$sales_amount",
         "_id": 0
      }
   }
]

C :

[
   {
      "$match": {
         "order_date": {
            "$gte": ISODate("2022-01-01T00:00:00.000Z"),
            "$lt": ISODate("2023-01-01T00:00:00.000Z")
         }
      }
   },
   {
      "$group": {
         "sales_amount": { "$sum": "$total_amount" }
      }
   },
   {
      "$project": {
         "state": "$_id.state",
         "month": "$_id.month",
         "sales_amount": "$sales_amount",
         "_id": 0
      }
   }
]

D :

[
   {
      "$match": {
         "order_date": {
            "$gte": ISODate("2022-01-01T00:00:00.000Z"),
            "$lt": ISODate("2023-01-01T00:00:00.000Z")
         }
      }
   },
   {
      "$project": {
         "state": "$_id.state",
         "month": "$_id.month",
         "sales_amount": "$sales_amount",
         "_id": 0
      }
   }
]

Answer: A

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