Subset pattern for large documents in MongoDB - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

Find subset fields in a large document

Given a collection users where each document contains many fields, which query returns only the name and email fields for all users?

MongoDB

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

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

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

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

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

💡 Hint

Use projection to include only the fields you want and exclude _id if not needed.

Option C correctly includes only 'name' and 'email' fields and excludes '_id'. Option C includes '_id' by default. Option C excludes 'name' and 'email' which is opposite of the goal. Option C mixes inclusion and exclusion which is invalid.

🧠 Conceptual

intermediate

Why use subset pattern for large documents?

What is the main benefit of using the subset pattern when querying large documents in MongoDB?

A It automatically indexes all fields in the document.

B It increases the size of documents stored in the database.

C It duplicates data to improve query speed.

D It reduces the amount of data transferred over the network.

💡 Hint

Think about network efficiency and response size.

Using subset pattern returns only needed fields, reducing data sent over the network and improving performance. Other options are incorrect or unrelated.

📝 Syntax

advanced

Correct projection syntax for nested fields

Which query correctly returns only the name and the nested field address.city from documents in the customers collection?

MongoDB

db.customers.find({}, {name: 1, 'address.city': 1, _id: 0})

A db.customers.find({}, {name: 1, 'address.city': 1, _id: 0})

B db.customers.find({}, {name: 1, address.city: 1, _id: 0})

C db.customers.find({}, {name: 1, address: 1, city: 1, _id: 0})

D db.customers.find({}, {name: 1, address: {city: 1}, _id: 0})

💡 Hint

Use quotes for nested field names with dots.

Option A uses correct syntax with quotes around 'address.city'. Option A is invalid syntax. Option A tries to nest projection which is not supported. Option A incorrectly projects 'city' as a top-level field.

❓ optimization

advanced

Optimizing queries with subset pattern

You have a collection with large documents. You only need to display the title and summary fields in your app. Which approach optimizes query performance?

A Use projection to return only <code>title</code> and <code>summary</code> fields.

B Return full documents and filter fields in the application code.

C Create a new collection with only <code>title</code> and <code>summary</code> fields.

D Use aggregation pipeline without projection.

💡 Hint

Think about minimizing data transfer and processing.

Using projection reduces data sent and speeds up queries. Filtering in app wastes bandwidth. Creating new collection duplicates data and adds maintenance. Aggregation without projection returns full documents.

🔧 Debug

expert

Identify the error in this subset query

What error will this MongoDB query produce?

db.products.find({}, {name: 1, price: 1, quantity: 0})

A No error, returns name and price fields only

B MongoError: Cannot mix inclusion and exclusion in projection

C SyntaxError: Unexpected token in projection

D TypeError: Invalid projection format

💡 Hint

In projection, you cannot mix including and excluding fields except for _id.

MongoDB projection rules forbid mixing inclusion (1) and exclusion (0) except for _id. Here, 'quantity: 0' conflicts with 'name: 1' and 'price: 1', causing an error.

Practice

1. What is the main purpose of using the subset pattern in MongoDB when working with large documents?

easy

A. To retrieve only specific fields from documents to reduce data size

B. To delete large documents from the collection

C. To create indexes on large documents

D. To merge multiple documents into one

Solution

1. Step 1: Understand subset pattern purpose

   The subset pattern is used to get only the needed parts of large documents instead of the whole document.

2. Step 2: Identify the benefit

   This reduces the amount of data sent over the network and improves performance.

3. Final Answer:

   To retrieve only specific fields from documents to reduce data size -> Option A

4. Quick Check:

   Subset pattern = retrieve specific fields [OK]

Hint: Subset pattern means get only needed fields [OK]

Common Mistakes:

• Thinking it deletes documents
• Confusing with indexing
• Assuming it merges documents

2. Which of the following is the correct syntax to retrieve only the name and age fields from documents in a MongoDB collection named users?

easy

A. db.users.find({name: 1, age: 1})

B. db.users.find({}, {name: 1, age: 1})

C. db.users.find({name: 1, age: 1}, {})

D. db.users.find({}, {name: 0, age: 0})

Solution

1. Step 1: Understand find() parameters

   The first parameter is the query filter (empty {} means all documents), the second is the projection specifying fields to include.

2. Step 2: Identify correct projection syntax

   Using {name: 1, age: 1} includes only these fields in the result.

3. Final Answer:

   db.users.find({}, {name: 1, age: 1}) -> Option B

4. Quick Check:

   Projection with 1 includes fields [OK]

Hint: Use find({}, {field: 1}) to include fields [OK]

Common Mistakes:

• Putting projection in the first argument
• Using 0 instead of 1 to include fields
• Omitting the empty filter {}

3. Given the collection products with documents containing _id, name, price, and details fields, what will be the output of this query?

db.products.find({}, {name: 1, price: 1, _id: 0})

medium

A. Documents with only name and price fields, excluding _id

B. Documents with all fields including _id

C. Documents with only _id field

D. Syntax error due to excluding _id

Solution

1. Step 1: Analyze projection fields

   The projection includes name and price with 1, and excludes _id with 0.

2. Step 2: Understand MongoDB default behavior

   By default, _id is included unless explicitly excluded. Here it is excluded.

3. Final Answer:

   Documents with only name and price fields, excluding _id -> Option A

4. Quick Check:

   Projection includes name, price; excludes _id [OK]

Hint: Use _id:0 to exclude _id field [OK]

Common Mistakes:

• Assuming _id is always included
• Thinking projection excludes all other fields automatically
• Confusing 0 and 1 in projection

4. You wrote this query to get only the title and author fields from books collection:

db.books.find({}, {title: 1, author: 0})

Why does this query cause an error or unexpected result?

medium

A. MongoDB requires _id to be included explicitly

B. Missing filter condition in find()

C. Projection keys must be strings, not identifiers

D. Mixing inclusion and exclusion in projection causes error

Solution

1. Step 1: Check projection rules

   MongoDB does not allow mixing inclusion (1) and exclusion (0) in the same projection except for _id.

2. Step 2: Identify the problem in given projection

   Here, title is included (1) and author is excluded (0), which is invalid.

3. Final Answer:

   Mixing inclusion and exclusion in projection causes error -> Option D

4. Quick Check:

   Projection must be all include or all exclude except _id [OK]

Hint: Use only 1s or only 0s in projection except _id [OK]

Common Mistakes:

• Mixing 1 and 0 in projection fields
• Forgetting _id can be excluded separately
• Assuming filter is mandatory for projection

5. You have a large collection orders with documents containing many fields including customer, items, total, and shipping. You want to fetch only customer and the total fields but exclude _id. Which query correctly applies the subset pattern for best performance?

hard

A. db.orders.find({}, {customer: 0, total: 0, _id: 0})

B. db.orders.find({}, {customer: 1, total: 1, _id: 1})

C. db.orders.find({}, {customer: 1, total: 1, _id: 0})

D. db.orders.find({}, {customer: 1, total: 0, _id: 0})

Solution

1. Step 1: Include needed fields

   To get only customer and total, set them to 1 in projection.

2. Step 2: Exclude _id field

   Set _id to 0 to exclude it from results.

3. Step 3: Avoid mixing inclusion and exclusion

   All fields except _id must be included (1), no mixing with 0.

4. Final Answer:

   db.orders.find({}, {customer: 1, total: 1, _id: 0}) -> Option C

5. Quick Check:

   Include fields with 1, exclude _id with 0 [OK]

Hint: Include needed fields with 1, exclude _id with 0 [OK]

Common Mistakes:

• Including _id by default
• Mixing 1 and 0 in fields other than _id
• Excluding needed fields accidentally