Free MongoDB C100DEV Exam Questions

Question 1

What is the best practice in using the $match operator?

A : It doesn't matter when we apply $match stage.

B : MongoDB does not have a $match stage.

C : The later in the pipeline, the better.

D : The earlier in the pipeline, the better. Not only because we will be using expression filters which reduce the number of documents to be processed, but also because we can use indexes.

Answer: D

Question 2

Consider a MongoDB collection named products which has documents in the following format:

{

"_id" : ObjectId("5f5b0d2f3e3dfbcc11c84444"),

"name" : "Smartphone",

"brand" : "Apple",

"category" : "Electronics",

"price" : 1000,

"discount" : 0.1

}

What is the correct syntax to update the "price" field of all documents in the products collection by multiplying it with (1 - discount) using the $set operator and the $multiply operator?

A : db.products.update( {}, { $set: { price: { $multiply: ["$price", { $subtract: [1, "$discount"] }] } } })

B : db.products.updateMany( {}, { $set: { price: { $multiply: ["$price", 1 - $discount] } } })

C : db.products.update( {}, { $set: { price: { $multiply: ["$price", 1 - $discount] } } })

D : db.products.updateMany( {}, { $set: { price: { $multiply: ["$price", { $subtract: [1, "$discount"] }] } } })

Answer: D

Question 3

You are a MongoDB Associate Developer and need to demonstrate how to load the Atlas Sample Dataset into your MongoDB Atlas cluster. Your manager has asked you to guide a junior developer through this process to ensure they can independently load the dataset. What steps should the junior developer follow to successfully load the Atlas Sample Dataset?

A : In MongoDB Atlas, navigate to the "Clusters" tab, click on the "Load Sample Dataset" button, and wait for the dataset to be fully loaded.

B : In MongoDB Compass, connect to your cluster, go to the "Import Data" tab, and import the sample dataset by uploading the sample-dataset.json file.

C : Use the MongoDB Atlas API to send a POST request to the /loadSampleDataset endpoint, specifying your cluster ID in the request body.

D : Open the MongoDB Shell, connect to your cluster, and run the command mongoimport --db sample --collection datasets --file sample-dataset.json.

Answer: A

Question 4

You manage a MongoDB collection called inventory that stores documents for a store's inventory. Each document has the fields item, category, and quantity. You want to ensure that an item is always present in the collection, even if it needs to be inserted. Specifically, if the item "notebook" in the "Stationery" category does not exist, it should be inserted with a quantity of 50. If it does exist, its quantity should be updated to 50. You plan to use the following command:

db.inventory.updateOne(

{ "item": "notebook", "category": "Stationery" },

{ $set: { "quantity": 50 } },

{ upsert: true }

)

What will happen after executing this command if there is no "notebook" item in the "Stationery" category in the inventory collection?

A : A new document will be inserted with only quantity: 50, as other fields (item and category) are not mentioned in the $set operator.

B : Nothing will happen because the $set operator only updates existing documents and cannot insert new ones.

C : A new document will be inserted with quantity: 50, but the item field will be set to null.

D : A new document will be inserted with item: "notebook", category: "Stationery", and quantity: 50.

Answer: D

Question 5

You have a MongoDB collection named employees that contains documents with fields name, department, and salary. You want to update the salary of all employees in the "Marketing" department to $75,000. The original collection looks like this:

[

{ "_id": 1, "name": "Alice", "department": "Marketing", "salary": 60000 },

{ "_id": 2, "name": "Bob", "department": "Sales", "salary": 55000 },

{ "_id": 3, "name": "Charlie", "department": "Marketing", "salary": 62000 },

{ "_id": 4, "name": "David", "department": "Engineering", "salary": 70000 }

]

You run the following MongoDB update operation:

db.employees.updateMany(

{ "department": "Marketing" },

{ $set: { "salary": 75000 } }

)

What will the collection look like after this update operation?

A : [ { "_id": 1, "name": "Alice", "department": "Marketing", "salary": 60000 }, { "_id": 2, "name": "Bob", "department": "Sales", "salary": 55000 }, { "_id": 3, "name": "Charlie", "department": "Marketing", "salary": 75000 }, { "_id": 4, "name": "David", "department": "Engineering", "salary": 70000 }]

B : [ { "_id": 1, "name": "Alice", "department": "Marketing", "salary": 62000 }, { "_id": 2, "name": "Bob", "department": "Sales", "salary": 55000 }, { "_id": 3, "name": "Charlie", "department": "Marketing", "salary": 62000 }, { "_id": 4, "name": "David", "department": "Engineering", "salary": 70000 }]

C : [ { "_id": 1, "name": "Alice", "department": "Marketing", "salary": 75000 }, { "_id": 2, "name": "Bob", "department": "Sales", "salary": 55000 }, { "_id": 3, "name": "Charlie", "department": "Marketing", "salary": 75000 }, { "_id": 4, "name": "David", "department": "Engineering", "salary": 70000 }]

D : [ { "_id": 1, "name": "Alice", "department": "Marketing", "salary": 60000 }, { "_id": 2, "name": "Bob", "department": "Sales", "salary": 75000 }, { "_id": 3, "name": "Charlie", "department": "Marketing", "salary": 75000 }, { "_id": 4, "name": "David", "department": "Engineering", "salary": 70000 }]

Answer: C