Multi-level caching in HLD - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define the first level cache type.

HLD

cache = [1]Cache()  # First level cache for fastest access

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

ADatabase

BDisk

CInMemory

DNetwork

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing disk or database for first level cache.

The first level cache is usually an in-memory cache for fastest data retrieval.

2fill in blank

medium

Complete the code to define the second level cache type.

HLD

cache = [1]Cache()  # Second level cache for larger but slower storage

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AGPU

BInMemory

CCPU

DDisk

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing in-memory cache again or hardware components.

The second level cache is often disk-based to hold more data but slower than memory.

3fill in blank

hard

Fix the error in the cache eviction policy assignment.

HLD

cache.eviction_policy = '[1]'  # Set eviction policy to remove least recently used items

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ARandom

BLRU

CFIFO

DMRU

Attempts:

3 left

💡 Hint

Common Mistakes

Using FIFO or MRU which do not fit typical cache eviction.

LRU (Least Recently Used) is a common eviction policy for caches to remove old data.

4fill in blank

hard

Fill both blanks to complete the multi-level cache lookup logic.

HLD

if [1] in L1_cache:
    return L1_cache[[2]]

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Akey

Bvalue

Ccache

Ditem

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'value' or 'item' which are not keys for lookup.

We check if the key is in the first level cache and return the value by the same key.

5fill in blank

hard

Fill all three blanks to complete the cache update after a miss.

HLD

if key not in L1_cache:
    data = [1].get(key)
    L2_cache.[2](key, data)
    L1_cache.[3](key, data)

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

Adatabase

Bput

Cset

Dfetch

Attempts:

3 left

💡 Hint

Common Mistakes

Using fetch as a method on cache or wrong data source.

On a cache miss, data is fetched from the database, then stored in L2 and L1 caches using put and set methods respectively.

Practice

1. What is the main purpose of multi-level caching in system design?

easy

A. To increase the size of the main database

B. To reduce data access time by storing data in multiple cache layers

C. To slow down data retrieval for security reasons

D. To store data only in the slowest storage layer

Solution

1. Step 1: Understand the role of caching

   Caching stores frequently accessed data closer to the user to reduce access time.

2. Step 2: Identify multi-level caching benefits

   Multi-level caching uses several layers from fastest to slowest to optimize speed and reduce load on main storage.

3. Final Answer:

   To reduce data access time by storing data in multiple cache layers -> Option B

4. Quick Check:

   Multi-level caching = Faster data access [OK]

Hint: Multi-level caching speeds up data access using layers [OK]

Common Mistakes:

• Thinking caching increases database size
• Assuming caching slows down retrieval
• Believing data is stored only in slow storage

2. Which of the following correctly describes the order of cache levels from fastest to slowest?

easy

A. L3 Cache, L2 Cache, L1 Cache, Main Memory

B. Main Memory, L3 Cache, L2 Cache, L1 Cache

C. L1 Cache, L2 Cache, L3 Cache, Main Memory

D. Main Memory, L1 Cache, L2 Cache, L3 Cache

Solution

1. Step 1: Recall cache hierarchy

   Cache levels are arranged by speed and size: L1 is fastest and smallest, followed by L2, then L3, then main memory.

2. Step 2: Match the correct order

   L1 Cache, L2 Cache, L3 Cache, Main Memory lists caches from fastest (L1) to slowest (main memory) correctly.

3. Final Answer:

   L1 Cache, L2 Cache, L3 Cache, Main Memory -> Option C

4. Quick Check:

   Cache order = L1 -> L2 -> L3 -> Memory [OK]

Hint: Remember L1 is fastest cache closest to CPU [OK]

Common Mistakes:

• Confusing cache order with memory order
• Assuming main memory is faster than caches
• Mixing up L2 and L3 cache speeds

3. Consider a system with three cache levels: L1, L2, and L3. If a data request misses in L1 and L2 but hits in L3, what happens next?

medium

A. Data is discarded and request fails

B. Data is fetched only from L3 and not stored anywhere else

C. Data is fetched from main memory directly, ignoring L3

D. Data is fetched from L3 and copied to L1 and L2 caches

Solution

1. Step 1: Understand cache hit and miss

   A miss means data is not found in that cache level; a hit means data is found.

2. Step 2: Follow multi-level caching behavior

   When data is found in a lower cache (L3), it is promoted to higher caches (L1, L2) to speed future access.

3. Final Answer:

   Data is fetched from L3 and copied to L1 and L2 caches -> Option D

4. Quick Check:

   Cache hit in L3 promotes data up [OK]

Hint: Data moves up cache levels on hit to speed access [OK]

Common Mistakes:

• Assuming data is not copied to higher caches
• Thinking data is fetched from main memory after L3 hit
• Believing request fails on cache miss

4. A multi-level cache system is experiencing frequent cache misses at all levels. Which of the following is the most likely cause?

medium

A. Cache sizes are too small to hold working data set

B. Cache levels are ordered from slowest to fastest

C. Data is always fetched from the highest cache level

D. Cache eviction policy is set to never remove data

Solution

1. Step 1: Analyze cache miss causes

   Frequent misses usually happen if caches cannot hold the data needed, causing constant reloads.

2. Step 2: Evaluate given options

   Cache sizes are too small to hold working data set correctly identifies small cache size as cause; other options describe incorrect or impossible scenarios.

3. Final Answer:

   Cache sizes are too small to hold working data set -> Option A

4. Quick Check:

   Small cache size = frequent misses [OK]

Hint: Small caches cause more misses due to limited space [OK]

Common Mistakes:

• Confusing cache order with miss frequency
• Assuming data always fetched from highest cache
• Believing no eviction means no misses

5. You are designing a multi-level caching system for a high-traffic web application. Which strategy best balances speed and storage cost?

hard

A. Use a small, fast L1 cache; medium L2 cache; large, slower L3 cache

B. Use equally sized caches at all levels for uniform speed

C. Use only one large cache to simplify design

D. Use a large L1 cache and small L3 cache to prioritize speed

Solution

1. Step 1: Understand cache size and speed tradeoff

   Fast caches are expensive and small; slower caches are cheaper and larger.

2. Step 2: Apply multi-level caching best practice

   Using small fast L1, medium L2, and large slower L3 balances cost and performance effectively.

3. Final Answer:

   Use a small, fast L1 cache; medium L2 cache; large, slower L3 cache -> Option A

4. Quick Check:

   Cache size-speed tradeoff = small fast + large slow [OK]

Hint: Small fast + large slow caches balance cost and speed [OK]

Common Mistakes:

• Assuming equal cache sizes improve speed
• Using only one cache ignores multi-level benefits
• Making L1 cache large wastes cost without speed gain