Index usage verification in MongoDB - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

Check index usage with explain()

Given a MongoDB collection users with an index on age, what does the explain() output show when running db.users.find({age: 30}).explain()?

MongoDB

db.users.find({age: 30}).explain()

A The output shows an error because <code>explain()</code> cannot be used with <code>find()</code>.

B The output is empty because no documents match <code>age: 30</code>.

C The output shows <code>stage: "COLLSCAN"</code> indicating a full collection scan was done.

D The output shows <code>stage: "IXSCAN"</code> indicating the index on <code>age</code> was used.

💡 Hint

Look for the stage field in the winningPlan part of the explain output.

When an index is used, the explain output includes stage: "IXSCAN" which means an index scan was performed instead of scanning the whole collection.

❓ query_result

intermediate

Effect of missing index on query plan

If a MongoDB collection orders has no index on customerId, what will db.orders.find({customerId: 123}).explain() show?

MongoDB

db.orders.find({customerId: 123}).explain()

A The explain output shows <code>stage: "COLLSCAN"</code> indicating a full collection scan.

B The explain output shows <code>stage: "IXSCAN"</code> even without an index.

C The explain output shows <code>stage: "FETCH"</code> without scanning.

D The query will fail with an error about missing index.

💡 Hint

Without an index, MongoDB must scan all documents to find matches.

If no index exists on the queried field, MongoDB performs a collection scan, shown as stage: "COLLSCAN" in explain output.

📝 Syntax

advanced

Identify correct syntax to create a compound index

Which option correctly creates a compound index on category ascending and price descending in MongoDB?

A db.products.createIndex({category => 1, price => -1})

B db.products.createIndex([category: 1, price: -1])

C db.products.createIndex({category: 1, price: -1})

D db.products.createIndex({category: "asc", price: "desc"})

💡 Hint

Use an object with field names as keys and 1 or -1 for ascending or descending.

The correct syntax uses an object with keys as field names and values 1 for ascending or -1 for descending order.

❓ optimization

advanced

Optimize query with index for range and equality

Given a collection sales with an index on {region: 1, date: 1}, which query will use the index efficiently?

A db.sales.find({region: "West", date: {$gte: ISODate("2023-01-01")}})

B db.sales.find({date: {$gte: ISODate("2023-01-01")}, region: "West"})

C db.sales.find({region: {$gte: "West"}, date: ISODate("2023-01-01")})

D db.sales.find({region: "West"})

💡 Hint

The index fields order matters: equality on first field then range on second uses index best.

The index on {region: 1, date: 1} is best used when the query specifies equality on region and a range on date. Option A does this correctly.

🧠 Conceptual

expert

Understanding index intersection

If a MongoDB collection has separate indexes on status and priority, which query can benefit from index intersection?

A db.tasks.find({status: "open"})

B db.tasks.find({status: "open", priority: "high"})

C db.tasks.find({priority: "high"})

D db.tasks.find({status: "open", priority: {$gt: 5}})

💡 Hint

Index intersection combines multiple single-field indexes to answer queries with multiple conditions.

When a query filters on multiple fields each having separate indexes, MongoDB can combine those indexes using index intersection to improve performance. Option B filters on both status and priority.