Cache invalidation strategies in Redis - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Cache Expiration

Which cache invalidation strategy automatically removes cached data after a set time period?

A Cache-aside pattern

B Write-through caching

C Manual cache clearing

D Time-to-live (TTL) expiration

💡 Hint

Think about a timer that deletes cache entries after some seconds.

TTL expiration sets a timer on cached data so it is removed automatically after that time.

❓ query_result

intermediate

Result of Cache Miss in Cache-Aside Pattern

In the cache-aside pattern, what happens when a requested key is not found in Redis cache?

A The application fetches data from the database and updates the cache

B Redis returns an error immediately

C Redis automatically loads data from the database

D The cache is cleared entirely

💡 Hint

Consider who is responsible for loading data when cache misses occur.

In cache-aside, the application loads data from the database on a cache miss and then updates the cache.

📝 Syntax

advanced

Correct Redis Command for Cache Invalidation

Which Redis command correctly deletes a cached key named 'user:123' to invalidate it?

A DEL user:123

B REMOVE user:123

C DELETE user:123

D CLEAR user:123

💡 Hint

Check Redis documentation for the command that deletes keys.

The DEL command deletes one or more keys from Redis.

❓ optimization

advanced

Optimizing Cache Invalidation for High Write Traffic

Which strategy best reduces cache stampede when many clients try to update the same cache key simultaneously?

A Disable caching for that key

B Set a very short TTL to expire cache quickly

C Use distributed locks to allow only one client to update cache

D Use write-through caching without locks

💡 Hint

Think about controlling who updates the cache to avoid overload.

Distributed locks ensure only one client updates the cache, preventing many simultaneous updates (cache stampede).

🔧 Debug

expert

Identifying the Cause of Stale Cache Data

A Redis cache is returning outdated data even after the database has been updated. Which is the most likely cause?

A The database update failed silently

B The cache key was never invalidated or updated after database change

C Redis server is down and serving old data

D The cache TTL is set to zero

💡 Hint

Consider what happens if cache is not refreshed after data changes.

If the cache key is not invalidated or updated after the database changes, the cache will serve stale data.

Practice

1. What is the main purpose of cache invalidation in Redis?

easy

A. To keep cached data fresh and accurate

B. To increase the size of the cache

C. To slow down data retrieval

D. To permanently store data without changes

Solution

1. Step 1: Understand cache invalidation

   Cache invalidation means removing or updating cached data to avoid stale information.

2. Step 2: Identify the main goal

   The goal is to keep the cached data fresh and accurate so users get the latest information.

3. Final Answer:

   To keep cached data fresh and accurate -> Option A

4. Quick Check:

   Cache invalidation = fresh data [OK]

Hint: Cache invalidation means keeping data fresh [OK]

Common Mistakes:

• Thinking cache invalidation increases cache size
• Believing it slows down data retrieval
• Assuming cache data never changes

2. Which Redis command is used to manually delete a cached key for invalidation?

easy

A. EXPIRE

B. GET

C. SETEX

D. DEL

Solution

1. Step 1: Identify commands for cache invalidation

   Manual invalidation requires deleting keys, so the command must remove keys.

2. Step 2: Match command to action

   DEL command deletes keys immediately, while EXPIRE sets a timeout, SETEX sets value with expiration, GET retrieves value.

3. Final Answer:

   DEL -> Option D

4. Quick Check:

   Delete key = DEL command [OK]

Hint: DEL deletes keys instantly for invalidation [OK]

Common Mistakes:

• Confusing EXPIRE with immediate deletion
• Using GET which only reads data
• Thinking SETEX deletes keys

3. Consider this Redis usage:
SET user:1 "Alice" EX 10
What happens after 10 seconds?

medium

A. The key user:1 remains forever

B. The key user:1 is deleted automatically

C. The key user:1 value changes to null

D. The key user:1 expires but stays in memory

Solution

1. Step 1: Understand the EX option in SET

   EX 10 means the key expires after 10 seconds automatically.

2. Step 2: Identify what happens on expiration

   When a key expires, Redis deletes it from memory automatically.

3. Final Answer:

   The key user:1 is deleted automatically -> Option B

4. Quick Check:

   EX sets expiration = auto delete [OK]

Hint: EX sets auto-delete time for keys [OK]

Common Mistakes:

• Thinking key stays forever after expiration
• Believing value changes to null instead of deletion
• Assuming expired keys remain in memory

4. You wrote this Redis command to expire a key:
EXPIRE user:2 0
What is the problem with this command?

medium

A. It sets expiration to zero seconds, effectively deleting the key

B. It deletes the key immediately

C. It sets the key to never expire

D. It causes a syntax error

Solution

1. Step 1: Understand EXPIRE with zero seconds

   EXPIRE key 0 removes any existing expiration timeout (equivalent to PERSIST command).

2. Step 2: Identify the problem

   The intent was to expire the key, but this sets it to never expire instead.

3. Final Answer:

   It sets the key to never expire -> Option C

4. Quick Check:

   EXPIRE 0 = remove expiration [OK]

Hint: EXPIRE 0 removes expiration (never expire) [OK]

Common Mistakes:

• Thinking it deletes the key immediately
• Believing it causes a syntax error
• Assuming zero seconds expires immediately

5. You want to keep cached product data fresh but avoid deleting keys too often. Which strategy best balances speed and data correctness in Redis?

hard

A. Use a long expiration time and rely on manual invalidation when data changes

B. Never expire keys and update them only manually

C. Delete keys immediately after every read

D. Set a short expiration time and manually delete keys on updates

Solution

1. Step 1: Understand trade-offs of expiration and manual deletion

   Short expiration causes frequent reloads; manual deletion alone risks stale data.

2. Step 2: Choose balanced approach

   Long expiration reduces reloads, manual invalidation on updates keeps data correct without overhead.

3. Final Answer:

   Use a long expiration time and rely on manual invalidation when data changes -> Option A

4. Quick Check:

   Balance speed and correctness = long expiry + manual invalidation [OK]

Hint: Long expiry plus manual delete balances freshness and speed [OK]

Common Mistakes:

• Choosing very short expiration causing overhead
• Never expiring keys causing stale data
• Deleting keys after every read causing slow performance