Why caching reduces latency in HLD - Quick Recap

Recall & Review

beginner

What is caching in system design?

Caching is storing copies of data in a faster storage location to quickly serve future requests without fetching from the original slower source.

beginner

How does caching reduce latency?

Caching reduces latency by serving data from a nearby, faster storage instead of waiting for slower backend or database responses.

beginner

What is latency in the context of system design?

Latency is the delay or time taken for a system to respond to a request.

intermediate

Why is accessing cache faster than accessing a database?

Cache is usually stored in memory or close to the user, making access much faster than querying a database which may be on a remote server or disk.

intermediate

What happens if cached data is outdated?

If cached data is outdated, the system may serve stale information unless cache invalidation or refresh strategies are used.

What is the main benefit of caching in reducing latency?

A Serving data from faster storage close to the user

B Increasing the size of the database

C Adding more servers to the backend

D Compressing data before sending

Caching stores data in faster storage like memory, reducing the time to access data and thus lowering latency.

Which storage is typically faster for caching?

A Hard disk drive

B In-memory storage

C Remote database server

D Cloud storage

In-memory storage is much faster than disk or remote servers, making it ideal for caching.

What does latency measure in a system?

A Amount of data stored

B Number of users connected

C Time delay to respond to a request

D Size of the cache

Latency is the time delay between sending a request and receiving a response.

If cache is not used, what usually happens to latency?

A Latency increases

B Latency stays the same

C Latency decreases

D Latency becomes zero

Without cache, data must be fetched from slower sources, increasing latency.

Which of these is a challenge when using caching?

A More network hops

B Increasing database size

C Slower data access

D Cache invalidation and stale data

Managing cache freshness and invalidation is a key challenge to avoid serving outdated data.

Explain in simple terms why caching helps reduce latency in a system.

Think about how getting something from a nearby shelf is faster than going to a distant store.

Describe the potential downside of caching related to data freshness and how it can be managed.

Consider what happens if you keep using an old map instead of updating it.

Practice

1. Why does caching reduce latency in a system?

easy

A. Because it stores frequently accessed data closer to the user, reducing access time.

B. Because it increases the number of servers in the system.

C. Because it compresses data to make it smaller.

D. Because it deletes old data from the database.

Solution

1. Step 1: Understand caching location

   Caching stores data near the user or application, such as in memory or edge servers.

2. Step 2: Effect on access time

   Accessing data from cache is faster than fetching from the main database or server, reducing waiting time.

3. Final Answer:

   Because it stores frequently accessed data closer to the user, reducing access time. -> Option A

4. Quick Check:

   Caching reduces latency by storing data close [OK]

Hint: Caching stores data near users to speed up access [OK]

Common Mistakes:

• Thinking caching increases servers
• Confusing caching with data compression
• Believing caching deletes data

2. Which of the following is the correct way to describe caching in system design?

easy

A. Caching permanently deletes old data to save space.

B. Caching is a process of storing data in a remote backup server.

C. Caching temporarily stores data in a fast-access location to reduce retrieval time.

D. Caching encrypts data to improve security.

Solution

1. Step 1: Define caching purpose

   Caching temporarily holds data in a fast-access place like memory or local storage.

2. Step 2: Identify correct description

   Only caching temporarily stores data in a fast-access location to reduce retrieval time correctly states caching reduces retrieval time by temporary storage.

3. Final Answer:

   Caching temporarily stores data in a fast-access location to reduce retrieval time. -> Option C

4. Quick Check:

   Caching = temporary fast storage [OK]

Hint: Caching is temporary fast storage, not permanent or remote [OK]

Common Mistakes:

• Confusing caching with backup storage
• Thinking caching deletes data
• Mixing caching with encryption

3. Consider a system where fetching data from the main database takes 100ms, and fetching from cache takes 10ms. If 80% of requests hit the cache, what is the average latency per request?

medium

A. 18 ms

B. 90 ms

C. 50 ms

D. 28 ms

Solution

1. Step 1: Calculate cache hit and miss times

   Cache hit latency = 10ms (80% requests), cache miss latency = 100ms (20% requests).

2. Step 2: Compute weighted average latency

   Average latency = (0.8 * 10) + (0.2 * 100) = 8 + 20 = 28 ms.

3. Final Answer:

   28 ms -> Option D

4. Quick Check:

   Average latency = hit%*hit_time + miss%*miss_time [OK]

Hint: Use weighted average: hit%*hit_time + miss%*miss_time [OK]

Common Mistakes:

• Ignoring cache miss latency
• Adding times instead of weighted average
• Using wrong percentages

4. A system uses caching but users still experience high latency. Which of the following is a likely cause?

medium

A. Cache encrypts data, increasing retrieval time.

B. Cache hit rate is very low, so most requests go to the slow database.

C. Cache size is too large, slowing down the system.

D. Cache stores data permanently, causing outdated results.

Solution

1. Step 1: Analyze cache hit rate impact

   If cache hit rate is low, most requests bypass cache and hit slow database, increasing latency.

2. Step 2: Evaluate other options

   Permanent storage or encryption are not typical causes of high latency; large cache size usually improves speed.

3. Final Answer:

   Cache hit rate is very low, so most requests go to the slow database. -> Option B

4. Quick Check:

   Low cache hit rate = high latency [OK]

Hint: Low cache hit rate means slow database access dominates [OK]

Common Mistakes:

• Assuming cache size slows system
• Confusing cache permanence with latency
• Thinking encryption is main latency cause

5. In a large-scale web application, which caching strategy best reduces latency while keeping data fresh?

hard

A. Use a cache with a short expiration time and update cache asynchronously on data changes.

B. Use a cache that never expires and manually clear it once a month.

C. Disable caching and always fetch fresh data from the database.

D. Cache only rarely accessed data to save memory.

Solution

1. Step 1: Understand freshness and latency tradeoff

   Short expiration keeps data fresh; asynchronous updates reduce latency by avoiding blocking calls.

2. Step 2: Evaluate other options

   Never expiring cache risks stale data; disabling cache increases latency; caching rarely accessed data wastes resources.

3. Final Answer:

   Use a cache with a short expiration time and update cache asynchronously on data changes. -> Option A

4. Quick Check:

   Short expiry + async update = fresh data + low latency [OK]

Hint: Short expiry plus async update balances freshness and speed [OK]

Common Mistakes:

• Choosing never expiring cache causing stale data
• Disabling cache increases latency
• Caching rarely accessed data wastes resources