Cache-aside pattern in HLD - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

How does the cache-aside pattern handle cache misses?

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

A The system duplicates the request to multiple caches to find the data.

B The system fetches data from the database, stores it in the cache, then returns it to the requester.

C The system waits for the cache to update automatically before responding.

D The system immediately returns an error to the requester without fetching data.

💡 Hint

Think about what happens when the cache does not have the data and how the system ensures data availability.

In the cache-aside pattern, when data is missing in the cache, the system loads it from the database, updates the cache, and then returns the data. This ensures the cache stays updated and data is available.

❓ Architecture

intermediate

Identify the correct sequence in cache-aside pattern request flow

Which sequence correctly describes the steps when a client requests data using the cache-aside pattern?

A 1,2,3,4

B 1,4,3,2

C 1,3,2,4

D 1,3,4,2

💡 Hint

Remember the cache check happens first, then data fetch if missing, then cache update, then return.

The correct flow is: check cache, if miss fetch from database, store in cache, then return data.

❓ scaling

advanced

Scaling challenges with cache-aside pattern in high traffic systems

What is a common scaling challenge when using the cache-aside pattern under heavy load?

A Cache stampede where many requests simultaneously miss cache and hit the database.

B Cache automatically updates too frequently causing stale data.

C Database rejects all requests due to cache saturation.

D Cache never expires data leading to outdated responses.

💡 Hint

Consider what happens when many users request the same uncached data at once.

Cache stampede happens when many requests miss the cache simultaneously, causing a flood of database queries that can overwhelm the system.

❓ tradeoff

advanced

Tradeoff of cache consistency in cache-aside pattern

What is a key tradeoff of using the cache-aside pattern regarding data consistency?

A Data in cache may be stale because updates to the database do not automatically update the cache.

B Cache always has the latest data because it updates before the database.

C Cache and database are always perfectly synchronized with no delay.

D Cache automatically deletes data when the database changes.

💡 Hint

Think about how cache updates happen in cache-aside pattern after database changes.

Cache-aside pattern does not automatically update cache on database writes, so cache can serve stale data until updated.

❓ estimation

expert

Estimating cache hit ratio impact on database load in cache-aside pattern

Assume a system using cache-aside pattern has 1 million requests per hour. The cache hit ratio is 80%. How many requests per hour hit the database?

A 1,000,000 requests per hour

B 800,000 requests per hour

C 200,000 requests per hour

D 100,000 requests per hour

💡 Hint

Calculate the percentage of requests that miss the cache and must query the database.

With 80% cache hits, 20% miss and hit the database. 20% of 1,000,000 is 200,000.

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