Distributed caching (Redis, Memcached) in HLD - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to identify the main purpose of distributed caching.

HLD

Distributed caching is used to [1] data to reduce latency and load on the main database.

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

Astore frequently accessed

Bdelete rarely used

Cencrypt sensitive

Dbackup all

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing backup or encryption instead of storing frequently accessed data.

Distributed caching stores frequently accessed data to speed up access and reduce database load.

2fill in blank

medium

Complete the code to select the correct caching strategy.

HLD

In distributed caching, the [1] strategy ensures that data is updated in the cache when the database changes.

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

Acache-aside

Bwrite-back

Clazy loading

Dwrite-through

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing write-back or cache-aside with write-through.

Write-through caching updates the cache immediately when the database is updated, keeping data consistent.

3fill in blank

hard

Fix the error in the cache invalidation approach.

HLD

To avoid stale data, the cache should be invalidated using [1] after the database update.

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

Atime-to-live (TTL)

Bwrite-back

Cmanual refresh

Dlazy expiration

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing manual refresh which requires manual intervention.

Time-to-live (TTL) automatically expires cache entries after a set time, preventing stale data.

4fill in blank

hard

Fill both blanks to complete the cache key design and eviction policy.

HLD

Cache keys should be [1] to avoid collisions, and the eviction policy [2] removes least recently used items first.

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

Aunique

Brandom

CLRU

DFIFO

Attempts:

3 left

💡 Hint

Common Mistakes

Using random keys or FIFO eviction which may not be optimal.

Unique keys prevent collisions. LRU (Least Recently Used) eviction removes the oldest accessed items first.

5fill in blank

hard

Fill all three blanks to complete the distributed cache cluster setup.

HLD

The cache cluster uses [1] to distribute data, [2] to replicate data for fault tolerance, and [3] to monitor cluster health.

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

Aconsistent hashing

Bsharding

Creplication

Dheartbeat

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing sharding with consistent hashing or missing monitoring concepts.

Consistent hashing distributes data evenly. Replication copies data for fault tolerance. Heartbeat checks cluster health.

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