Free MongoDB C100DEV Exam Questions

Question 1

In the context of MongoDB development, you are creating a new service that is expected to handle high load. You've decided to leverage the MongoDB drivers' connection pooling capability. What best describes connection pooling and its advantages?

A : Connection pooling ensures secure data transfer between the client and the server by encrypting all connections in the pool.

B : Connection pooling allows a client to connect to a database only when a data transfer operation occurs, reducing the memory requirements.

C : Connection pooling involves maintaining a "pool" of open database connections, which can be reused for multiple requests, improving performance.

D : Connection pooling refers to the storage of multiple connection strings for redundancy, increasing system reliability.

Answer: C

Question 2

Which of the following statements are true regarding the MongoDB Aggregation Framework and pipelines? (Select two)

A : Aggregation pipelines can include stages like $match, $group, $project, and $sort.

B : Aggregation pipelines allow you to modify the structure of the original collection.

C : Aggregation pipelines support SQL-like joins between multiple collections.

D : The $limit stage is used to skip a specified number of documents in the aggregation pipeline.

E : The $unwind stage is used to deconstruct an array field from the input documents, creating a new document for each element of the array.

Answer: A,E

Question 3

As a MongoDB Developer, you are tasked with the deletion of specific documents in a collection named users. The documents to be deleted are those that meet the following criteria: the age field is less than 18 and the status field is "inactive". After the deletion, you need to know the count of the deleted documents. Which of the following commands would correctly perform this operation?

A :

B :

C :

D :

E :

Answer: A

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?

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 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?

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