Rows vs documents thinking in MongoDB - Practice Questions

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding document structure vs row structure

In MongoDB, which statement best describes how data is stored compared to a traditional SQL row?

A Data is stored as flexible documents that can contain nested arrays and objects, unlike fixed columns in SQL rows.

B Data is stored strictly in tables with fixed columns and rows, similar to SQL databases.

C Each document in MongoDB must have the same fields and data types, just like SQL rows.

D MongoDB stores data only as key-value pairs without any nested structure.

💡 Hint

Think about how JSON-like documents allow more flexible data than rows.

MongoDB stores data as documents that can have nested objects and arrays, allowing flexible schemas. SQL rows have fixed columns.

❓ query_result

intermediate

Query result shape in MongoDB vs SQL

Given a MongoDB collection 'users' with documents containing nested 'address' objects, what will this query return? `db.users.find({"address.city": "Seattle"})`

MongoDB

db.users.find({"address.city": "Seattle"})

A Only the 'address' subdocuments where city is 'Seattle', excluding other user data.

B All user documents where the nested 'address' object has a 'city' field equal to 'Seattle'.

C An error because nested fields cannot be queried in MongoDB.

D All users regardless of city because nested queries are ignored.

💡 Hint

MongoDB allows querying nested fields using dot notation.

The query returns full user documents where the nested 'address.city' equals 'Seattle'.

📝 Syntax

advanced

Correct MongoDB query to update nested document field

Which of the following MongoDB update queries correctly sets the 'address.zip' field to '98101' for user with _id 123?

A db.users.updateOne({_id: 123}, {$update: {"address.zip": "98101"}})

B db.users.updateOne({_id: 123}, {$set: {address: {zip: "98101"}}})

C db.users.updateOne({_id: 123}, {$set: {"address.zip": "98101"}})

D db.users.update({_id: 123}, {$set: {zip: "98101"}})

💡 Hint

Use dot notation inside $set to update nested fields.

Option C uses correct syntax with $set and dot notation to update nested field 'address.zip'.

❓ optimization

advanced

Optimizing queries on nested document fields

You have a large MongoDB collection with documents containing nested 'profile.age' fields. Which indexing strategy will best optimize queries filtering by 'profile.age'?

A Create a single-field index on 'profile.age'.

B Create a compound index on 'profile' and 'age' separately.

C Create a text index on the entire document.

D No index is needed because nested fields cannot be indexed.

💡 Hint

Indexes on nested fields use dot notation.

MongoDB supports indexes on nested fields using dot notation, so indexing 'profile.age' improves query speed.

🔧 Debug

expert

Diagnosing unexpected query results with nested documents

A developer runs this query on a MongoDB collection: `db.orders.find({"customer.address.city": "Boston"})` But it returns no results, even though some documents have 'customer' with nested 'address.city' equal to 'Boston'. What is the most likely cause?

A MongoDB does not support querying nested fields with dot notation.

B The field name 'city' is case-sensitive and should be 'City' instead.

C The query syntax is invalid because quotes are missing around the field name.

D The 'customer' field is an array of objects, so dot notation does not match nested fields inside arrays without $elemMatch.

💡 Hint

Consider how nested arrays affect dot notation queries.

If 'customer' is an array, dot notation alone won't match nested fields inside array elements. Use $elemMatch to query inside arrays.