Distributed caching (Redis, Memcached) in HLD - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is distributed caching and why is it used in system design?

Distributed caching is a method to store data across multiple cache servers to improve data retrieval speed and reduce load on databases. It helps systems scale and handle more users by keeping frequently accessed data closer to the application.

beginner

Name two popular distributed caching systems and one key difference between them.

Redis and Memcached are popular distributed caching systems. Redis supports data persistence and advanced data structures, while Memcached is simpler and focuses on fast in-memory key-value storage without persistence.

intermediate

How does cache invalidation work in distributed caching?

Cache invalidation is the process of removing or updating cached data when the original data changes. In distributed caching, this ensures that stale data is not served. Techniques include time-to-live (TTL), explicit invalidation commands, or event-driven updates.

intermediate

What is cache sharding and why is it important?

Cache sharding splits the cache data across multiple servers based on keys. It helps distribute load evenly, improves scalability, and avoids a single cache server becoming a bottleneck.

intermediate

Explain the difference between cache-aside and write-through caching strategies.

Cache-aside means the application loads data into the cache only when needed (on cache miss). Write-through means data is written to the cache and the database at the same time. Cache-aside reduces unnecessary cache writes, while write-through ensures cache and database are always consistent.

Which of the following is a key feature of Redis but not Memcached?

A Data persistence

B In-memory key-value storage

C Simple caching

D Distributed cache

Redis supports data persistence to disk, while Memcached does not.

What does cache sharding help to achieve?

A Backup cached data

B Encrypt cached data

C Compress cached data

D Distribute cache data across servers

Cache sharding splits data across multiple servers to balance load and improve scalability.

In cache-aside strategy, when is data loaded into the cache?

A Only on cache miss

B Every time data is written

C Periodically by the cache server

D Never

Cache-aside loads data into cache only when the application requests data not found in cache.

Which technique helps prevent serving stale data in distributed caches?

A Load balancing

B Data compression

C Cache invalidation

D Data encryption

Cache invalidation removes or updates outdated cached data to keep cache fresh.

Memcached is best described as:

A A file storage system

B A simple, fast in-memory key-value store without persistence

C A message queue system

D A persistent database

Memcached is designed for fast, simple caching without data persistence.

Describe how distributed caching improves system performance and scalability.

Think about how having data closer to the application helps.

Explain the differences between Redis and Memcached and when you might choose one over the other.

Consider features and use cases.

Practice

1. What is the primary purpose of using a distributed cache like Redis or Memcached in a system?

easy

A. To reduce database load by storing frequently accessed data in memory

B. To permanently store all application data for backup

C. To replace the database entirely for all data storage needs

D. To increase the size of the database by adding more servers

Solution

1. Step 1: Understand the role of distributed cache

   Distributed caches store frequently accessed data in fast memory to reduce the number of database queries.

2. Step 2: Identify the main benefit

   This reduces the load on the database and speeds up data retrieval for repeated requests.

3. Final Answer:

   To reduce database load by storing frequently accessed data in memory -> Option A

4. Quick Check:

   Distributed cache reduces DB load = C [OK]

Hint: Cache stores frequent data to reduce DB hits [OK]

Common Mistakes:

• Thinking cache permanently stores all data
• Confusing cache with database backup
• Assuming cache replaces the database

2. Which of the following is the correct way to set a key-value pair in Redis using its command syntax?

easy

A. SET key value

B. GET key value

C. STORE key value

D. PUT key value

Solution

1. Step 1: Recall Redis command for setting data

   Redis uses the command SET key value to store a value under a key.

2. Step 2: Verify other options

   GET retrieves data, STORE and PUT are not valid Redis commands.

3. Final Answer:

   SET key value -> Option A

4. Quick Check:

   Redis set command = SET key value [OK]

Hint: Remember Redis uses SET to store key-value [OK]

Common Mistakes:

• Confusing GET with SET
• Using non-existent commands like STORE or PUT
• Mixing Redis commands with SQL syntax

3. Consider this simplified Redis usage in code:

cache.set('user:1', 'Alice')
name = cache.get('user:1')
print(name)

What will be printed?

medium

A. None

B. 'Alice'

C. user:1

D. Error

Solution

1. Step 1: Analyze the cache set operation

   The key 'user:1' is set with the value 'Alice' in the cache.

2. Step 2: Analyze the cache get operation

   Retrieving 'user:1' returns the stored value 'Alice', which is then printed.

3. Final Answer:

   'Alice' -> Option B

4. Quick Check:

   Set then get returns stored value = 'Alice' [OK]

Hint: Get returns value set by set command [OK]

Common Mistakes:

• Expecting key name instead of value
• Assuming None if not careful with key format
• Thinking it causes an error without context

4. A developer tries to use Memcached but notices cache misses even after setting keys. Which of these is a likely cause?

medium

A. The database is down, so cache cannot be used

B. Memcached does not support key-value storage

C. The cache keys are expiring too quickly due to a low TTL setting

D. Memcached requires SQL queries to retrieve data

Solution

1. Step 1: Understand Memcached key expiration

   Memcached keys have a TTL (time to live). If TTL is too low, keys expire quickly causing cache misses.

2. Step 2: Eliminate incorrect options

   Memcached supports key-value storage, does not depend on database status, and does not use SQL queries.

3. Final Answer:

   The cache keys are expiring too quickly due to a low TTL setting -> Option C

4. Quick Check:

   Low TTL causes cache misses = A [OK]

Hint: Check TTL settings if cache misses occur [OK]

Common Mistakes:

• Thinking Memcached lacks key-value support
• Assuming database status affects cache directly
• Confusing Memcached with SQL databases

5. You are designing a high-traffic web app that uses Redis as a distributed cache. To ensure data consistency when multiple servers update the same cache key, which approach is best?

hard

A. Use Memcached instead because it handles concurrency automatically

B. Allow all servers to update cache keys without coordination

C. Disable caching for keys that are frequently updated

D. Use Redis transactions or Lua scripts to perform atomic updates

Solution

1. Step 1: Identify concurrency challenges in distributed cache

   When multiple servers update the same key, race conditions can cause inconsistent data.

2. Step 2: Choose atomic update methods in Redis

   Redis supports transactions and Lua scripts to ensure updates happen atomically, preventing conflicts.

3. Step 3: Evaluate other options

   Allowing uncoordinated updates risks inconsistency; disabling caching reduces performance; Memcached lacks built-in atomic scripting.

4. Final Answer:

   Use Redis transactions or Lua scripts to perform atomic updates -> Option D

5. Quick Check:

   Atomic updates ensure consistency = D [OK]

Hint: Use Redis atomic commands for safe concurrent updates [OK]

Common Mistakes:

• Ignoring concurrency causing stale data
• Thinking Memcached handles concurrency automatically
• Disabling cache unnecessarily reduces speed