Why caching patterns matter in Redis - Challenge Your Understanding

Challenge - 5 Problems

❓ query_result

intermediate

What happens when you cache data without expiration?

Consider a Redis cache where keys are set without expiration time. What is the likely outcome after continuous data updates?

Redis

SET user:123 "John Doe"
# No expiration set

A The cache will automatically clear old keys to save space.

B The cache will grow indefinitely, possibly causing memory issues.

C Redis will throw an error when memory is full.

D The cached data will expire after 24 hours by default.

💡 Hint

Think about what happens if keys never expire and new data keeps adding.

Without expiration, cached keys remain forever, causing memory to fill up over time.

🧠 Conceptual

intermediate

Why use cache aside pattern?

Which benefit best explains why the cache aside pattern is used in caching?

A It allows the application to control when to load data into the cache, reducing stale data.

B It ensures the cache is always updated automatically without application logic.

C It forces Redis to handle all database writes directly.

D It disables caching for write-heavy applications.

💡 Hint

Think about who controls the cache loading in cache aside.

Cache aside lets the application decide when to load or refresh cache, helping keep data fresh.

📝 Syntax

advanced

Which Redis command sets a key with expiration in one step?

Choose the Redis command that sets a key "session:1" with value "active" and expires after 60 seconds.

A SET session:1 active EX 60

B EXPIRE session:1 60 SET active

C SET session:1 active PX 60000

D SETEX session:1 60 active

💡 Hint

Look for the command that combines setting and expiration in one.

SETEX sets a key with a value and expiration time in seconds in one command.

❓ optimization

advanced

How to avoid cache stampede in Redis?

When many clients request the same missing cache key simultaneously, what is a good strategy to prevent all from querying the database at once?

A Use a distributed lock to allow only one client to load data and others wait.

B Increase Redis memory to handle more keys.

C Disable caching for hot keys to avoid stale data.

D Set very short expiration times to refresh cache frequently.

💡 Hint

Think about controlling who loads data when cache is missing.

Using a lock ensures only one client loads data, preventing many database hits at once.

🔧 Debug

expert

Why does this Redis cache update fail to reflect new data?

Given this sequence:
1. Cache key "product:10" set with old data.
2. Database updated with new product info.
3. Cache key deleted.
4. Application reads cache key "product:10" expecting new data.
Why might the application still see old data?

A Redis does not support deleting keys, so cache remains unchanged.

B The cache was deleted before the database update, so stale data was re-cached.

C The cache deletion and database update were not atomic, causing race condition.

D The application is reading from the database, not the cache.

💡 Hint

Consider timing between cache deletion and database update.

If cache deletion and database update are separate steps, another read may re-cache old data before update completes.