Response caching strategies in GraphQL - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

What is the main benefit of using response caching in GraphQL?

Response caching stores the results of GraphQL queries. What is the primary benefit of this?

A It increases the size of the database by storing duplicate data.

B It reduces the number of times the server must process the same query, improving performance.

C It forces clients to always fetch fresh data from the server.

D It disables query batching to improve security.

💡 Hint

Think about how caching helps with repeated requests.

Response caching saves the results of queries so the server can quickly return data without reprocessing the same query multiple times, which improves performance.

❓ query_result

intermediate

Which caching strategy returns cached data only if the query and variables match exactly?

Given these caching strategies, which one returns cached data only when the query and variables are exactly the same?

A Cache by query name only, ignoring variables.

B Cache by response size.

C Cache by query string and variables (strict matching).

D Cache by user session ID only.

💡 Hint

Consider what strict matching means for caching.

Strict matching caches responses only when both the query and variables match exactly, ensuring correct data is returned for each unique request.

📝 Syntax

advanced

Identify the correct GraphQL cache-control directive syntax to set max-age to 60 seconds.

Which of the following cache-control directives correctly sets the max-age to 60 seconds in a GraphQL schema?

A @cacheControl(maxAge: 60)

B @cacheControl(max_age=60)

C @cacheControl(max-age: 60)

D @cacheControl(maxAge=60)

💡 Hint

Look for correct argument naming and syntax in GraphQL directives.

The correct syntax uses camelCase for argument names and colon to assign values in GraphQL directives.

❓ optimization

advanced

Which approach best optimizes caching for frequently changing user-specific data?

You have user-specific data that changes often. Which caching strategy optimizes performance without serving stale data?

A Use short max-age with cache key including user ID and invalidate cache on updates.

B Use long max-age ignoring user ID in cache key.

C Disable caching completely for user-specific data.

D Cache only the query name without variables.

💡 Hint

Think about balancing freshness and performance for user data.

Short max-age with user-specific cache keys and invalidation ensures fresh data while still benefiting from caching.

🔧 Debug

expert

Why does this GraphQL response caching setup cause stale data to be served?

Consider a GraphQL server that caches responses globally without considering authentication tokens. What is the likely problem?

A The cache key includes authentication tokens, causing cache misses.

B The server crashes due to missing authentication headers.

C Caching is disabled automatically for authenticated queries.

D Cached responses are shared across users, causing one user to see another's data.

💡 Hint

Think about what happens if cache keys do not differentiate users.

If cache keys do not include user authentication info, cached data can be served to the wrong user, causing stale or incorrect data exposure.