Why advanced indexing matters in MongoDB - Challenge Your Understanding

Challenge - 5 Problems

❓ query_result

intermediate

Find documents using a compound index

Given a MongoDB collection users with a compound index on { age: 1, city: 1 }, what is the output of this query?

db.users.find({ age: 30, city: "New York" }).explain("executionStats")

Which option correctly describes the query plan's index usage?

A The query scans the entire collection because the index is not used for equality matches.

B The query uses only the index on age and ignores the city field.

C The query uses the compound index to efficiently find documents matching both age and city.

D The query uses a text index instead of the compound index.

💡 Hint

Think about how compound indexes work with multiple fields in the query.

A compound index on { age: 1, city: 1 } allows efficient queries that specify both fields. The query uses the index to quickly find matching documents without scanning the whole collection.

🧠 Conceptual

intermediate

Why use multikey indexes?

In MongoDB, which situation requires a multikey index to improve query performance?

A When indexing a field with only numeric values.

B When indexing a single string field with unique values.

C When indexing a field that is always null.

D When indexing a field that contains an array of values.

💡 Hint

Think about how MongoDB indexes array fields.

Multikey indexes are used when a field contains arrays. MongoDB indexes each element of the array separately to allow efficient queries on array contents.

📝 Syntax

advanced

Identify the correct syntax for creating a partial index

Which option shows the correct MongoDB command to create a partial index on the orders collection for documents where status is "pending"?

A db.orders.createIndex({ orderDate: 1 }, { partialFilterExpression: { status: "pending" } })

B db.orders.createIndex({ orderDate: 1 }, { partialFilterExpression: { status: { $eq: "pending" } } })

C db.orders.createIndex({ orderDate: 1 }, { filter: { status: "pending" } })

D db.orders.createIndex({ orderDate: 1 }, { partialFilter: { status: "pending" } })

💡 Hint

Check the exact option name and syntax for partialFilterExpression.

The correct syntax uses the option name 'partialFilterExpression' with a valid query expression like { status: { $eq: "pending" } }.

❓ optimization

advanced

Choosing the best index for a frequent query

You have a collection products with fields category, price, and stock. The most frequent query is:

db.products.find({ category: "electronics", price: { $lt: 500 } })

Which index will optimize this query best?

A A compound index on { category: 1, price: 1 }

B A single field index on category only

C A single field index on price only

D A compound index on { price: 1, stock: 1 }

💡 Hint

Think about which fields appear in the query filter and their order in the index.

A compound index on { category: 1, price: 1 } supports queries filtering by category and price efficiently. The order matters: category first, then price.

🔧 Debug

expert

Why does this index not improve query performance?

A developer created this index:

db.sales.createIndex({ date: 1, total: 1 })

But the query

db.sales.find({ total: { $gt: 100 } })

still performs a collection scan. Why?

A Because the query does not specify the first field of the compound index (date), the index cannot be used.

B Because the index fields are in ascending order and the query needs descending order.

C Because the query uses a range operator on total, which is the second field, so the index is ignored.

D Because the index was created incorrectly and needs a unique constraint.

💡 Hint

Remember how MongoDB uses the prefix of compound indexes.

MongoDB can only use a compound index if the query filters on the first field in the index. Since the query filters only on total (the second field), the index is not used.