Projection for reducing data transfer in MongoDB - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

Projection to include specific fields

Given a MongoDB collection users with documents containing name, age, and email, what will be the output of this query?

db.users.find({}, {name: 1, email: 1, _id: 0})

Assume the collection has:

{"name": "Alice", "age": 30, "email": "[e-mail]"}

{"name": "Bob", "age": 25, "email": "[e-mail]"}

MongoDB

db.users.find({}, {name: 1, email: 1, _id: 0})

A [{"name": "Alice", "email": "[e-mail]"}, {"name": "Bob", "email": "[e-mail]"}]

B [{"name": "Alice", "age": 30, "email": "[e-mail]"}, {"name": "Bob", "age": 25, "email": "[e-mail]"}]

C [{"age": 30, "email": "[e-mail]"}, {"age": 25, "email": "[e-mail]"}]

D [{"name": "Alice"}, {"name": "Bob"}]

💡 Hint

Projection includes only the fields set to 1 and excludes _id when set to 0.

The projection specifies to include only 'name' and 'email' fields and exclude '_id'. So the output documents contain only those fields.

❓ query_result

intermediate

Projection excluding fields

What will be the result of this MongoDB query?

db.products.find({}, {description: 0, _id: 0})

Given documents:

{"name": "Pen", "price": 1.5, "description": "Blue ink pen"}

{"name": "Notebook", "price": 3.0, "description": "200 pages"}

MongoDB

db.products.find({}, {description: 0, _id: 0})

A [{"price": 1.5}, {"price": 3.0}]

B [{"name": "Pen", "price": 1.5, "description": "Blue ink pen"}, {"name": "Notebook", "price": 3.0, "description": "200 pages"}]

C [{"name": "Pen", "price": 1.5}, {"name": "Notebook", "price": 3.0}]

D [{"name": "Pen"}, {"name": "Notebook"}]

💡 Hint

Setting a field to 0 excludes it from the result.

The projection excludes 'description' and '_id', so only 'name' and 'price' remain in the output.

📝 Syntax

advanced

Identify the invalid projection syntax

Which of the following MongoDB queries has invalid projection syntax and will cause an error?

A db.orders.find({}, {item: true, quantity: true})

B db.orders.find({}, {item: 1, quantity: 1, _id: 0})

C db.orders.find({}, {item: 1, quantity: 0})

D db.orders.find({}, {item: 1, quantity: 1, _id: 1, price: 0})

💡 Hint

You cannot mix inclusion (1) and exclusion (0) in the same projection except for _id.

Option D mixes inclusion (item, quantity, _id) and exclusion (price), which is invalid and causes an error.

❓ optimization

advanced

Optimizing data transfer with projection

You have a large collection logs with documents containing many fields. You only need the timestamp and level fields for your report. Which query best reduces data transfer?

A db.logs.find({}, {timestamp: 1, level: 1, _id: 0})

B db.logs.find({}, {timestamp: 1, level: 1})

C db.logs.find({}, {})

D db.logs.find({}, {timestamp: 0, level: 0})

💡 Hint

Exclude _id if you don't need it to reduce data size further.

Option A includes only needed fields and excludes _id, minimizing data sent over the network.

🧠 Conceptual

expert

Understanding projection behavior with nested fields

Consider documents in employees collection with nested address field:

{"name": "John", "address": {"city": "NY", "zip": "10001"}, "age": 28}

What will be the output of this query?

db.employees.find({}, {"address.city": 1, _id: 0})

MongoDB

db.employees.find({}, {"address.city": 1, _id: 0})

A [{"address": {"city": "NY", "zip": "10001"}}]

B [{"address": {"city": "NY"}}]

C [{"address.city": "NY"}]

D [{"name": "John", "address": {"city": "NY"}}]

💡 Hint

Projection on nested fields returns the parent object with only the specified nested fields.

The query returns the 'address' object but only with the 'city' field included, excluding other fields and _id.