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.

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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.

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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.

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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.

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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.

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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.