Cache invalidation strategies in Redis - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is cache invalidation in Redis?

Cache invalidation is the process of removing or updating cached data in Redis to ensure that the cache does not serve stale or outdated information.

beginner

Explain the Time-to-Live (TTL) strategy for cache invalidation.

TTL sets an expiration time on cached data in Redis. When the time expires, Redis automatically removes the cached item, ensuring data is refreshed after a set period.

intermediate

What is the Write-Through cache invalidation strategy?

In Write-Through, data is written to both the cache and the database at the same time. This keeps cache and database synchronized, reducing stale data risk.

advanced

Describe the Write-Back cache invalidation strategy.

Write-Back delays writing data to the database until the cache entry is evicted or updated. This improves performance but risks data loss if cache fails before writing back.

intermediate

What is the Explicit Invalidation strategy?

Explicit Invalidation means manually removing or updating cache entries when the underlying data changes, ensuring the cache always reflects the latest data.

Which Redis feature automatically removes cached data after a set time?

A Write-Back

B Write-Through

C Explicit Invalidation

D Time-to-Live (TTL)

TTL sets an expiration time on cached data, after which Redis deletes it automatically.

In which strategy is data written to cache and database simultaneously?

A Write-Through

B Write-Back

C Explicit Invalidation

D TTL

Write-Through writes data to both cache and database at the same time to keep them synchronized.

Which cache invalidation strategy risks data loss if the cache fails before writing back?

A Write-Through

B Write-Back

C TTL

D Explicit Invalidation

Write-Back delays writing to the database, so data can be lost if cache fails before syncing.

What does Explicit Invalidation require?

A Manual removal or update of cache entries

B Writing data only to database

C Writing data only to cache

D Automatic expiration

Explicit Invalidation means manually removing or updating cache entries when data changes.

Which strategy is best for ensuring cache never serves stale data without manual intervention?

A Explicit Invalidation

B Write-Back

C TTL

D Write-Through

TTL automatically expires cache entries after a set time, preventing stale data without manual steps.

Describe the main cache invalidation strategies used in Redis and when you might use each.

Think about how and when cache data gets updated or removed.

Explain the risks and benefits of Write-Back cache invalidation compared to Write-Through.

Consider speed versus data safety.

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