Cache-aside pattern in Redis - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the Cache-aside pattern?

The Cache-aside pattern is a way to keep data in a cache and a database. When data is needed, the app first looks in the cache. If it's not there, it loads from the database and then saves it in the cache for next time.

beginner

In the Cache-aside pattern, what happens when data is not found in the cache?

The application loads the data from the database, then stores it in the cache for future requests.

beginner

Why use the Cache-aside pattern instead of always reading from the database?

Because reading from cache is much faster than reading from the database, so it improves app speed and reduces database load.

intermediate

How does the Cache-aside pattern handle data updates?

When data changes, the app updates the database first and then removes or updates the cache entry to keep data consistent.

beginner

What is a cache miss in the Cache-aside pattern?

A cache miss happens when the requested data is not found in the cache, so the app must get it from the database.

In the Cache-aside pattern, where does the application look first for data?

A Cache

B Database

C File system

D Network

The application first checks the cache to find the data quickly before going to the database.

What should the application do after a cache miss in the Cache-aside pattern?

A Load data from the database and update the cache

B Return an error

C Clear the cache

D Restart the application

After a cache miss, the app loads data from the database and stores it in the cache for future use.

How does the Cache-aside pattern help improve application performance?

A By storing data only in the database

B By increasing database writes

C By reducing database reads using fast cache access

D By disabling the cache

It reduces the number of database reads by serving data from the faster cache.

When data is updated, what must happen to keep cache and database consistent?

A Only update the database

B Only update the cache

C Do nothing

D Update the database and then invalidate or update the cache

The database is updated first, then the cache is cleared or updated to avoid stale data.

Which of these is NOT a benefit of the Cache-aside pattern?

A Faster data access

B Automatic cache refresh without app control

C Reduced database load

D Better app scalability

Cache-aside requires the app to manage cache updates; it does not refresh cache automatically.

Explain how the Cache-aside pattern works step-by-step when an application requests data.

Think about what happens when data is found or not found in cache.

Describe how data updates are handled in the Cache-aside pattern to keep cache and database consistent.

Consider the order of operations for data changes.

Practice

1. What is the main idea behind the cache-aside pattern in Redis?

easy

A. Automatically update cache whenever the database changes without application intervention

B. Load data into cache only when the application requests it and cache misses occur

C. Preload all data into cache before any application requests

D. Use cache only for temporary data that does not come from the database

Solution

1. Step 1: Understand cache-aside pattern basics

   The cache-aside pattern means the application loads data into cache only when it is needed, not before.

2. Step 2: Compare options with this concept

   Load data into cache only when the application requests it and cache misses occur matches this idea exactly, while others describe different caching strategies.

3. Final Answer:

   Load data into cache only when the application requests it and cache misses occur -> Option B

4. Quick Check:

   Cache-aside = Load on demand [OK]

Hint: Cache-aside means load cache only on demand [OK]

Common Mistakes:

• Thinking cache is preloaded with all data
• Assuming cache updates automatically without app logic
• Confusing cache-aside with write-through caching

2. Which Redis command is typically used to check if a key exists in cache before loading from the database in cache-aside pattern?

easy

A. DEL

B. GET

C. SET

D. EXISTS

Solution

1. Step 1: Identify command to check key presence

   In Redis, EXISTS checks if a key is present in cache.

2. Step 2: Match commands with their purpose

   GET retrieves value, SET stores value, DEL deletes key. Only EXISTS checks presence.

3. Final Answer:

   EXISTS -> Option D

4. Quick Check:

   Check key presence = EXISTS [OK]

Hint: Use EXISTS to check if cache key is present [OK]

Common Mistakes:

• Using GET to check existence (GET returns null if missing)
• Confusing SET with checking commands
• Using DEL which deletes keys

3. Consider this Redis cache-aside pseudocode:

if not redis.exists('user:123'):
    data = db.query('SELECT * FROM users WHERE id=123')
    redis.set('user:123', data)
else:
    data = redis.get('user:123')

What happens if the key user:123 is missing in Redis?

medium

A. Redis automatically loads data from database

B. Data is fetched from Redis but will be empty

C. Data is fetched from the database and stored in Redis cache

D. An error occurs because key does not exist

Solution

1. Step 1: Analyze the if condition for cache miss

   If user:123 does not exist in Redis, the code queries the database for data.

2. Step 2: Understand cache population after miss

   After fetching from database, it stores the data in Redis with set for future requests.

3. Final Answer:

   Data is fetched from the database and stored in Redis cache -> Option C

4. Quick Check:

   Cache miss triggers DB fetch and cache store [OK]

Hint: Cache miss means fetch DB and store in cache [OK]

Common Mistakes:

• Assuming Redis auto-loads data from DB
• Expecting error on missing key
• Thinking Redis returns empty data silently

4. You have this cache-aside code snippet in Redis:

if redis.get('product:456') is None:
    data = db.query('SELECT * FROM products WHERE id=456')
    redis.set('product:456', data)
else:
    data = redis.get('product:456')

But the cache never updates even after database changes. What is the likely problem?

medium

A. The cache is never invalidated or updated after DB changes

B. The Redis GET command is incorrect

C. The database query syntax is wrong

D. The key name 'product:456' is invalid in Redis

Solution

1. Step 1: Identify cache update mechanism

   The code only sets cache if key is missing but does not update or invalidate cache after DB changes.

2. Step 2: Understand cache staleness cause

   Without cache invalidation or update logic after DB writes, cache remains stale and does not reflect DB changes.

3. Final Answer:

   The cache is never invalidated or updated after DB changes -> Option A

4. Quick Check:

   Cache stale if no invalidation after DB update [OK]

Hint: Cache must be invalidated after DB updates [OK]

Common Mistakes:

• Assuming GET command causes update
• Blaming DB query syntax without evidence
• Thinking Redis keys are invalid without reason

5. You want to implement cache-aside pattern in Redis for a user profile service. Which approach correctly handles cache misses and updates when user data changes?

1. On read: check cache, if miss fetch DB and set cache
2. On write: update DB, then delete cache key to force reload on next read

Why is deleting the cache key after DB update preferred over updating cache directly?

hard

A. Deleting cache key avoids race conditions and stale data issues

B. Updating cache directly is impossible in Redis

C. Deleting cache key improves Redis memory usage drastically

D. Updating cache directly causes Redis to crash

Solution

1. Step 1: Understand cache update strategies

   Deleting cache key after DB update forces next read to reload fresh data, avoiding stale cache.

2. Step 2: Recognize race condition prevention

   Direct cache update risks race conditions if multiple writes/read happen concurrently; deleting key is safer.

3. Final Answer:

   Deleting cache key avoids race conditions and stale data issues -> Option A

4. Quick Check:

   Delete cache key after DB write to avoid stale data [OK]

Hint: Delete cache key after DB update to avoid stale data [OK]

Common Mistakes:

• Thinking Redis cannot update cache values
• Believing direct cache update is always better
• Assuming deleting cache key crashes Redis