Cache invalidation strategies in Redis

Introduction

Cache invalidation strategies help keep stored data fresh and accurate by removing or updating old information in the cache.

When data changes in the main database and the cache needs to reflect those changes.

When cached data becomes outdated after a certain time and should be refreshed.

When you want to avoid serving wrong or stale information to users.

When you want to improve performance by controlling how often cache updates happen.

When you want to balance between fast access and data accuracy.

Syntax

Redis

No single Redis command for cache invalidation; strategies use commands like DEL, EXPIRE, or Lua scripts.

Cache invalidation is a strategy, not a single command.

Redis commands like DEL remove keys, EXPIRE sets time limits on keys.

Examples

Deletes the cached data immediately to invalidate it.

Redis

DEL cache_key

Sets the cache to expire after 3600 seconds (1 hour), automatically invalidating it.

Redis

EXPIRE cache_key 3600

Sets a cache key with a value that expires after 60000 milliseconds (1 minute).

Redis

SET cache_key value PX 60000

Advanced method to safely invalidate cache based on custom logic.

Redis

Using a Lua script to check and delete stale cache atomically

Sample Program

This example sets a cache key with a 10-second expiry, retrieves it, deletes it manually, then tries to get it again to show it is gone.

Redis

SET user:123 "John Doe" EX 10
GET user:123
DEL user:123
GET user:123

Important Notes

Always choose the invalidation strategy that fits your app's speed and accuracy needs.

Time-based expiration (TTL) is simple but may serve stale data until expiry.

Manual deletion ensures immediate invalidation but requires extra logic.

Summary

Cache invalidation keeps cached data fresh and accurate.

Common methods include manual deletion and time-based expiration.

Choosing the right strategy balances speed and data correctness.

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