Embedded documents (nested objects) in MongoDB - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

Find documents with a nested field value

Given a collection users where each document has an embedded address object with fields city and zip, which query returns all users living in the city 'Springfield'?

MongoDB

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

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

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

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

D db.users.find({city: "Springfield"})

💡 Hint

Use dot notation to query nested fields inside embedded documents.

Option C uses dot notation correctly to access the nested city field inside the address embedded document. Options B and C try to match the entire embedded document exactly, which will fail if other fields exist. Option C looks for a top-level city field, which does not exist.

❓ query_result

intermediate

Retrieve nested array elements in embedded documents

Consider a collection orders where each document has an embedded array items with objects containing product and quantity. Which query returns all orders that include an item with product equal to 'Pen'?

MongoDB

db.orders.find({"items.product": "Pen"})

A db.orders.find({product: "Pen"})

B db.orders.find({items: {product: "Pen"}})

C db.orders.find({"items": {"product": "Pen"}})

D db.orders.find({"items.product": "Pen"})

💡 Hint

Use dot notation to query fields inside objects within arrays.

Option D correctly uses dot notation to find documents where the items array contains an object with product equal to 'Pen'. Options B and C try to match the entire array or object exactly, which will fail if there are multiple items. Option D looks for a top-level product field, which does not exist.

📝 Syntax

advanced

Identify the syntax error in nested document update

Which update command correctly sets the nested field profile.contact.email to '[e-mail]' for the document with _id 1?

MongoDB

db.users.updateOne({_id: 1}, {$set: {"profile.contact.email": "[e-mail]"}})

A )}}"moc.elpmaxe@resu" :"liame.tcatnoc.eliforp"{ :tes${ ,}1 :di_{(enOetadpu.sresu.bd

B db.users.updateOne({_id: 1}, {$set: {"profile.contact.email": "[e-mail]"}})

C db.users.updateOne({_id: 1}, {$set: {profile: {contact: {email: "[e-mail]"}}}})

D db.users.updateOne({_id: 1}, {$set: {"profile": {"contact": {"email": "[e-mail]"}}}})

💡 Hint

Use quotes around the full nested field path when using dot notation in update operators.

Option B correctly uses quotes around the nested field path in dot notation. Option B is valid syntax but is duplicated here; the original Option B was invalid because keys with dots must be quoted. Options C and D replace the entire profile object, which may overwrite other fields unintentionally.

❓ optimization

advanced

Optimize query on nested fields with indexes

You have a collection products with embedded documents specs containing weight and color. Which index will best optimize queries filtering by specs.color?

A {"specs.color": 1}

B {"specs": 1}

C {"color": 1}

D {"specs.weight": 1}

💡 Hint

Indexes on nested fields use dot notation for the field name.

Option A creates an index on the nested field specs.color, which directly supports queries filtering by that field. Option A indexes the entire specs object, which is less efficient. Option A indexes a top-level color field that does not exist. Option A indexes a different nested field specs.weight.

🧠 Conceptual

expert

Understanding document size limits with embedded documents

MongoDB has a maximum document size of 16MB. Which statement about using embedded documents is true?

A Embedding large nested documents can cause the document to exceed the 16MB limit, so large data should be referenced instead.

B Embedded documents do not count towards the 16MB document size limit.

C MongoDB automatically splits large embedded documents into multiple documents to avoid size limits.

D The 16MB limit applies only to top-level fields, not to embedded documents.

💡 Hint

Consider how document size limits affect embedded data storage.

Option A is correct because the entire document, including embedded documents, counts towards the 16MB limit. Large nested data should be stored separately and referenced. Options B and D are false because embedded documents count fully towards the size limit. Option A is false because MongoDB does not split documents automatically.