Cache-aside (lazy loading) deep dive in Redis - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the Cache-aside (lazy loading) pattern?

Cache-aside is a caching strategy where the application first checks the cache for data. If the data is missing (a cache miss), it loads the data from the database, stores it in the cache, and then returns it to the user.

beginner

Why is Cache-aside called 'lazy loading'?

Because data is only loaded into the cache when it is requested and not found there. This means the cache is filled on demand, not in advance.

beginner

What happens on a cache miss in Cache-aside pattern?

The application fetches the data from the database, writes it to the cache, and then returns the data to the user.

intermediate

How does Cache-aside handle data updates?

When data is updated in the database, the cache entry is usually invalidated or updated to keep cache and database consistent.

intermediate

What is a potential downside of Cache-aside pattern?

It can cause higher latency on the first request for data (cache miss), and if many requests miss simultaneously, it can overload the database (cache stampede).

In Cache-aside pattern, where is data loaded from when a cache miss occurs?

A From the client

B From the cache

C From a backup cache

D From the database

On a cache miss, the application loads data from the database before storing it in the cache.

What does Cache-aside pattern do when data is updated in the database?

A Automatically updates the cache without intervention

B Invalidates or updates the cache entry

C Ignores the cache

D Deletes the database record

To keep cache and database consistent, the cache entry is invalidated or updated after database changes.

Why might Cache-aside pattern cause a 'cache stampede'?

A Because many requests miss the cache simultaneously and hit the database

B Because cache is preloaded with too much data

C Because cache entries never expire

D Because the cache is too large

If many requests miss the cache at once, they all query the database, causing high load called a cache stampede.

Which of these best describes the Cache-aside pattern?

A Cache is loaded before any request

B Cache is updated only after data changes

C Cache is loaded on demand when data is requested

D Cache is never used

Cache-aside loads data into cache only when requested and missing, hence 'lazy loading'.

What is the first step in Cache-aside pattern when a user requests data?

A Check cache for data

B Update cache

C Fetch data from database

D Invalidate cache

The application first checks the cache to see if data is available before querying the database.

Explain how the Cache-aside (lazy loading) pattern works step-by-step when a user requests data.

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

Describe how Cache-aside pattern handles data updates to keep cache and database consistent.

Consider what must happen after changing data in the database.

Practice

1. What is the main idea behind the Cache-aside (lazy loading) pattern in Redis?

easy

A. Preload all data into cache before any request

B. Load data into cache only when it is requested and missing

C. Update cache only after database changes without reading cache

D. Keep cache and database completely separate without syncing

Solution

1. Step 1: Understand cache-aside purpose

   Cache-aside means data is loaded into cache only when requested and not found in cache.

2. Step 2: Compare options with definition

   Load data into cache only when it is requested and missing matches this lazy loading idea; others describe different caching strategies.

3. Final Answer:

   Load data into cache only when it is requested and missing -> Option B

4. Quick Check:

   Cache-aside = lazy loading on miss [OK]

Hint: Cache-aside loads data only on cache miss [OK]

Common Mistakes:

• Thinking cache preloads all data
• Confusing cache-aside with write-through caching
• Assuming cache and DB never sync

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. EXISTS

B. GET

C. SET

D. DEL

Solution

1. Step 1: Identify command to check key presence

   Redis command EXISTS returns if a key is present in cache.

2. Step 2: Eliminate other commands

   GET retrieves value, SET writes value, DEL deletes key; only EXISTS checks presence.

3. Final Answer:

   EXISTS -> Option A

4. Quick Check:

   Check key presence = EXISTS [OK]

Hint: Use EXISTS to check cache key before GET [OK]

Common Mistakes:

• Using GET to check existence (returns nil if missing)
• Confusing SET as check command
• Using DEL which deletes keys

3. Consider this pseudo-code for cache-aside in Redis:

if not redis.exists(key):
  data = db.query(key)
  redis.set(key, data)
return redis.get(key)

What will be returned if the key is missing in cache but present in database?

medium

A. Old stale data from cache

B. Null or empty because cache was empty initially

C. An error because key does not exist in cache

D. The data fetched from database and cached

Solution

1. Step 1: Follow code logic on cache miss

   If key missing in Redis, code queries database and sets cache with fresh data.

2. Step 2: Return cached data after setting

   After setting, code returns redis.get(key) which now holds fresh data.

3. Final Answer:

   The data fetched from database and cached -> Option D

4. Quick Check:

   Cache miss triggers DB fetch and cache set [OK]

Hint: Cache miss loads DB data then returns it [OK]

Common Mistakes:

• Assuming cache returns empty if initially missing
• Expecting error on missing cache key
• Thinking cache returns stale data without update

4. You have this cache-aside code snippet:

if redis.get(key) is None:
  data = db.query(key)
  redis.set(key, data)
return redis.get(key)

But sometimes stale data is returned after DB update. What is the likely bug?

medium

A. Setting cache before querying database

B. Using redis.get instead of redis.exists to check cache

C. Not deleting or updating cache after DB changes

D. Returning data before setting cache

Solution

1. Step 1: Identify stale data cause

   Stale data means cache was not refreshed after DB update.

2. Step 2: Check cache update strategy

   Code only sets cache on miss, but does not invalidate or update cache after DB changes.

3. Final Answer:

   Not deleting or updating cache after DB changes -> Option C

4. Quick Check:

   Cache stale if not refreshed after DB update [OK]

Hint: Always invalidate cache after DB update [OK]

Common Mistakes:

• Thinking redis.get check causes stale data
• Believing cache sets before DB query fixes stale data
• Ignoring cache invalidation on DB writes

5. You want to implement cache-aside with Redis for a user profile service. The database updates user info frequently. Which approach best ensures cache consistency and performance?

hard

A. On DB update, delete cache key; on read, load from DB if cache miss

B. Always write to cache first, then update DB asynchronously

C. Preload all user profiles into cache at service start

D. Never update cache; always read directly from DB

Solution

1. Step 1: Analyze cache consistency needs

   Frequent DB updates require cache invalidation to avoid stale data.

2. Step 2: Evaluate options for cache-aside pattern

   On DB update, delete cache key; on read, load from DB if cache miss deletes cache on DB update, so next read reloads fresh data, matching cache-aside best practice.

3. Final Answer:

   On DB update, delete cache key; on read, load from DB if cache miss -> Option A

4. Quick Check:

   Invalidate cache on update, lazy load on read [OK]

Hint: Delete cache on update, lazy load on read [OK]

Common Mistakes:

• Writing cache before DB causes inconsistency
• Preloading all data wastes memory and may be stale
• Ignoring cache leads to poor performance