Cache stampede prevention in HLD - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define the cache key for storing user data.

HLD

cache_key = "user_data_[1]"

Drag options to blanks, or click blank then click option'

Arequest_id

Buser_id

Ctimestamp

Dsession_id

Attempts:

3 left

💡 Hint

Common Mistakes

Using session_id or request_id which are not stable identifiers for user data.

The cache key should uniquely identify the user data, so using user_id is correct.

2fill in blank

medium

Complete the code to check if the cache has expired before fetching fresh data.

HLD

if cache_timestamp [1] current_time:

Drag options to blanks, or click blank then click option'

A<

B>

C==

D!=

Attempts:

3 left

💡 Hint

Common Mistakes

Using > or == which do not correctly detect expiration.

We check if the cache timestamp is less than the current time to know if it expired.

3fill in blank

hard

Fix the error in the code to acquire a lock before refreshing the cache.

HLD

if cache_miss:
    if cache_lock.[1]():
        refresh_cache()

Drag options to blanks, or click blank then click option'

Await

Bunlock

Cacquire

Drelease

Attempts:

3 left

💡 Hint

Common Mistakes

Using release or unlock before acquiring the lock.

To prevent multiple processes from refreshing the cache simultaneously, we must acquire a lock first.

4fill in blank

hard

Fill both blanks to implement cache stampede prevention using a lock and cache update.

HLD

if cache_expired:
    if cache_lock.[1]():
        data = fetch_fresh_data()
        cache_store.[2](cache_key, data)

Drag options to blanks, or click blank then click option'

Aacquire

Bdelete

Cset

Drelease

Attempts:

3 left

💡 Hint

Common Mistakes

Using delete instead of set to update cache.

First, we acquire the lock to prevent others from refreshing simultaneously. Then, we set the fresh data in the cache.

5fill in blank

hard

Fill all three blanks to implement a cache with expiration, lock, and fallback to stale data.

HLD

if cache_data is None or cache_timestamp [1] current_time:
    if cache_lock.[2]():
        fresh_data = fetch_data()
        cache_store.[3](cache_key, fresh_data)
    else:
        use_stale_cache()

Drag options to blanks, or click blank then click option'

A<

Bacquire

Cset

D>

Attempts:

3 left

💡 Hint

Common Mistakes

Using '>' instead of '<' for expiration check.

Not acquiring lock before cache update.

We check if cache expired with '<'. Then we acquire the lock to refresh cache. Finally, we set fresh data in cache. If lock not acquired, fallback to stale cache.

Practice

1. What is the main goal of cache stampede prevention in system design?

easy

A. To prevent many requests from hitting the database simultaneously

B. To increase the size of the cache storage

C. To reduce the number of cache servers

D. To encrypt cached data for security

Solution

1. Step 1: Understand cache stampede problem

   Cache stampede happens when many requests try to fetch data from the database because the cache expired or missed.

2. Step 2: Identify the goal of prevention

   The goal is to stop all these requests from hitting the database at once to avoid overload.

3. Final Answer:

   To prevent many requests from hitting the database simultaneously -> Option A

4. Quick Check:

   Cache stampede prevention = prevent database overload [OK]

Hint: Focus on reducing database hits during cache misses [OK]

Common Mistakes:

• Confusing cache size with stampede prevention
• Thinking encryption is related to stampede
• Assuming reducing cache servers helps stampede

2. Which of the following is a common technique used to prevent cache stampede?

easy

A. Storing data only in the database

B. Increasing cache TTL to infinite

C. Disabling cache for all requests

D. Using distributed locks around cache refresh

Solution

1. Step 1: Review common stampede prevention methods

   Techniques include locking, early expiration, and request coalescing to control cache refresh.

2. Step 2: Match technique to options

   Distributed locks prevent multiple processes from refreshing cache simultaneously, stopping stampede.

3. Final Answer:

   Using distributed locks around cache refresh -> Option D

4. Quick Check:

   Locking = stampede prevention [OK]

Hint: Look for locking or coordination methods in options [OK]

Common Mistakes:

• Choosing infinite TTL which can cause stale data
• Disabling cache which increases load
• Ignoring locking as a prevention method

3. Consider this pseudo-code for cache stampede prevention:

if cache miss:
  acquire lock
  if cache still miss:
    data = fetch from DB
    update cache
  release lock
return cached data

What happens if the lock is not used here?

medium

A. Multiple requests fetch from DB simultaneously causing overload

B. Cache never updates and returns stale data

C. Requests wait indefinitely causing deadlock

D. Cache size increases exponentially

Solution

1. Step 1: Analyze the role of the lock

   The lock ensures only one request fetches data from DB and updates cache on miss.

2. Step 2: Consequence of missing lock

   Without lock, many requests detect cache miss and all fetch from DB, causing overload.

3. Final Answer:

   Multiple requests fetch from DB simultaneously causing overload -> Option A

4. Quick Check:

   No lock = DB overload [OK]

Hint: Lock prevents simultaneous DB fetch on cache miss [OK]

Common Mistakes:

• Thinking cache never updates without lock
• Confusing deadlock with missing lock
• Assuming cache size grows without lock

4. A system uses early expiration to prevent cache stampede by setting cache TTL shorter than data TTL. However, users report stale data sometimes. What is the likely cause?

medium

A. Cache TTL is longer than data TTL causing stale reads

B. Cache is not refreshed after early expiration due to missing lock

C. Database is down causing stale cache

D. Cache size is too small causing evictions

Solution

1. Step 1: Understand early expiration technique

   Early expiration refreshes cache before data TTL ends to avoid stampede.

2. Step 2: Identify cause of stale data

   If cache refresh is not coordinated (missing lock), cache may not update properly, causing stale data.

3. Final Answer:

   Cache is not refreshed after early expiration due to missing lock -> Option B

4. Quick Check:

   Missing lock = stale cache after early expiration [OK]

Hint: Check if locking coordinates cache refresh [OK]

Common Mistakes:

• Assuming TTL mismatch causes stale data
• Blaming database downtime without evidence
• Confusing cache size with freshness

5. You design a high-traffic API with cache stampede prevention. Which combination best prevents stampede while ensuring fresh data and minimal DB load?

hard

A. Disable cache and use database connection pooling

B. Use long cache TTL with no locking and rely on DB scaling

C. Use short cache TTL with distributed locking and request coalescing

D. Use infinite cache TTL and manual cache invalidation

Solution

1. Step 1: Evaluate each option for stampede prevention

   Use long cache TTL with no locking and rely on DB scaling risks DB overload without locking; C disables cache increasing DB load; D risks stale data.

2. Step 2: Identify best practice combination

   Short TTL triggers refresh often; distributed locking prevents multiple refreshes; request coalescing merges requests to reduce DB hits.

3. Final Answer:

   Use short cache TTL with distributed locking and request coalescing -> Option C

4. Quick Check:

   Locking + coalescing + short TTL = best stampede prevention [OK]

Hint: Combine locking and coalescing with short TTL for best results [OK]

Common Mistakes:

• Ignoring locking and causing DB overload
• Disabling cache increases latency and load
• Using infinite TTL causes stale data