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

Recall & Review

beginner

What is the Cache-aside pattern?

The Cache-aside pattern is a design where the application first checks the cache for data. If the data is missing, it loads from the database, then stores it in the cache for future requests.

beginner

In the Cache-aside pattern, who is responsible for loading data into the cache?

The application is responsible for loading data into the cache when it finds a cache miss. It fetches data from the database and then updates the cache.

intermediate

What happens when data is updated in the Cache-aside pattern?

When data is updated, the application updates the database first and then invalidates or updates the cache to keep data consistent.

intermediate

Why is the Cache-aside pattern considered scalable?

Because it reduces database load by serving repeated requests from the cache, and the cache can be scaled independently to handle more reads.

intermediate

Name one drawback of the Cache-aside pattern.

One drawback is the potential for stale data if the cache is not properly invalidated after database updates.

In the Cache-aside pattern, what does the application do on a cache miss?

A Fetch data from the database and update the cache

B Return an error to the user

C Only update the cache without fetching data

D Ignore the request

On a cache miss, the application fetches data from the database and then updates the cache for future requests.

Who manages cache invalidation in the Cache-aside pattern?

A The cache system automatically

B The database

C The application

D The user

The application is responsible for invalidating or updating the cache after data changes.

Which of these is a benefit of the Cache-aside pattern?

A Always consistent data without any stale reads

B Cache automatically updates itself without application logic

C No need to update the cache after database writes

D Reduced database load by caching frequently accessed data

The Cache-aside pattern reduces database load by caching data that is frequently read.

What is a common risk when using the Cache-aside pattern?

A Data in cache can become stale if not invalidated properly

B Cache never gets used

C Database is bypassed completely

D Cache updates happen automatically without control

If the cache is not invalidated after database updates, stale data can be served.

Which scenario best fits the Cache-aside pattern?

A When data changes every second

B When data is mostly read and rarely updated

C When cache is the only data source

D When no database is used

Cache-aside works best when data is read often but updated infrequently.

Explain how the Cache-aside pattern works from a user request to data retrieval.

Think about the steps the application takes when data is requested.

Describe how data consistency is maintained in the Cache-aside pattern when data is updated.

Focus on the order of operations during data write.

Practice

1. What is the main purpose of the cache-aside pattern in system design?

easy

A. To load data into cache only when it is requested

B. To preload all data into cache before any request

C. To write data directly to cache without database interaction

D. To keep cache and database completely separate without synchronization

Solution

1. Step 1: Understand cache-aside pattern behavior

   The cache-aside pattern loads data into cache only when the application requests it and the data is not already cached.

2. Step 2: Compare options with this behavior

   To load data into cache only when it is requested correctly states this lazy loading approach. Other options describe preloading or unsynchronized caching, which are incorrect.

3. Final Answer:

   To load data into cache only when it is requested -> Option A

4. Quick Check:

   Cache-aside = lazy loading on demand [OK]

Hint: Cache-aside loads data only when requested [OK]

Common Mistakes:

• Thinking cache preloads all data
• Assuming cache updates happen before DB writes
• Believing cache and DB are unsynchronized

2. Which of the following is the correct sequence of operations in the cache-aside pattern when reading data?

easy

A. Read from database -> Update cache -> Return data

B. Read from cache -> If miss, read from database -> Update cache

C. Update cache -> Read from cache -> Read from database

D. Read from cache -> Return data without checking database

Solution

1. Step 1: Recall cache-aside read flow

   When reading, the system first checks the cache. If data is missing (cache miss), it reads from the database and then updates the cache.

2. Step 2: Match this flow to options

   Read from cache -> If miss, read from database -> Update cache matches this exact sequence. Other options either skip cache miss handling or update cache before reading.

3. Final Answer:

   Read from cache -> If miss, read from database -> Update cache -> Option B

4. Quick Check:

   Cache read -> DB read on miss -> Cache update [OK]

Hint: Cache read first, DB read only if cache miss [OK]

Common Mistakes:

• Updating cache before reading database
• Ignoring cache miss and reading only cache
• Reading database before checking cache

3. Consider this pseudocode using cache-aside pattern:

function getUser(id) {
  user = cache.get(id)
  if (user == null) {
    user = database.query(id)
    cache.set(id, user)
  }
  return user
}

What will getUser(5) return if the cache is empty and the database has user with id 5?

medium

A. null

B. Error due to cache miss

C. Empty object

D. User data from database

Solution

1. Step 1: Analyze cache miss handling

   Since cache is empty, cache.get(5) returns null, triggering database query.

2. Step 2: Database query and cache update

   The function queries the database for user id 5, finds the user data, updates the cache, and returns the user data.

3. Final Answer:

   User data from database -> Option D

4. Quick Check:

   Cache miss triggers DB read and cache update [OK]

Hint: Cache miss leads to DB read and cache update [OK]

Common Mistakes:

• Assuming cache miss returns null directly
• Expecting error on cache miss
• Ignoring cache update after DB read

4. A developer implemented cache-aside but notices stale data in cache after database updates. What is the likely mistake?

medium

A. Not updating cache after database write

B. Reading from cache before database

C. Preloading cache with all data

D. Using cache for write operations only

Solution

1. Step 1: Identify cause of stale cache

   Stale cache means cache has old data not reflecting recent database updates.

2. Step 2: Check cache update after DB write

   If cache is not updated or invalidated after database writes, stale data remains in cache.

3. Final Answer:

   Not updating cache after database write -> Option A

4. Quick Check:

   Cache must update after DB write to avoid stale data [OK]

Hint: Always update cache after DB write to avoid stale data [OK]

Common Mistakes:

• Ignoring cache invalidation after writes
• Assuming cache updates automatically
• Confusing read and write cache operations

5. You design a high-traffic product catalog service using cache-aside pattern. To handle frequent updates and reads, which strategy best maintains cache consistency and performance?

hard

A. Preload entire product catalog into cache at service start and never update cache

B. On product update, write to DB only and let cache expire naturally

C. On product update, write to DB then immediately update cache with new data

D. Write updates only to cache and asynchronously sync to DB later

Solution

1. Step 1: Understand cache consistency needs

   For frequent updates and reads, cache must reflect latest data quickly to avoid stale reads.

2. Step 2: Evaluate update strategies

   On product update, write to DB then immediately update cache with new data updates DB then cache immediately, ensuring cache consistency and fast reads. On product update, write to DB only and let cache expire naturally risks stale cache. Preload entire product catalog into cache at service start and never update cache ignores updates. Write updates only to cache and asynchronously sync to DB later risks data loss and inconsistency.

3. Final Answer:

   On product update, write to DB then immediately update cache with new data -> Option C

4. Quick Check:

   Update DB then cache for consistency and performance [OK]

Hint: Update DB then cache immediately for fresh data [OK]

Common Mistakes:

• Relying on cache expiration alone
• Preloading cache without updates
• Writing only to cache without DB sync