Distributed file systems in HLD - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Architecture

intermediate

Identify the main components in a distributed file system architecture

Which of the following options correctly lists the essential components of a typical distributed file system?

A Client nodes, Metadata server, Storage nodes, Network communication layer

B Client nodes, Single storage server, Local disk, Network switch

C User interface, Database server, Cache server, Load balancer

D Web server, Application server, Database server, Firewall

💡 Hint

Think about components that handle file metadata, actual file storage, and client access.

A distributed file system typically includes client nodes that request files, metadata servers that manage file information, storage nodes that hold the actual data, and a network layer to connect them all.

❓ scaling

intermediate

Scaling storage capacity in distributed file systems

You want to increase the storage capacity of a distributed file system without downtime. Which approach is most suitable?

A Increase client cache size to reduce storage needs

B Replace existing storage nodes with larger disks one by one, shutting down the system temporarily

C Compress all files to save space without adding hardware

D Add more storage nodes and update metadata servers to include them

💡 Hint

Consider how to add capacity while keeping the system available.

Adding storage nodes and updating metadata allows the system to grow without downtime. Replacing disks or compressing files may cause downtime or performance issues.

❓ tradeoff

advanced

Tradeoff between consistency and availability in distributed file systems

In a distributed file system, choosing strong consistency over availability means:

A The system always responds to requests, even if data might be outdated

B The system may reject some requests during network partitions to ensure data correctness

C The system duplicates data to multiple nodes without synchronization

D The system uses client-side caching exclusively to improve performance

💡 Hint

Think about what happens when parts of the system cannot communicate.

Strong consistency requires all nodes to agree on data before responding, so during network issues, some requests may be rejected to avoid stale data, sacrificing availability.

🧠 Conceptual

advanced

Understanding data replication strategies in distributed file systems

Which replication strategy ensures high availability and fault tolerance by storing multiple copies of data across different nodes?

A Single-node storage

B No replication

C Synchronous replication

D Local caching only

💡 Hint

Consider how data copies are kept consistent and available.

Synchronous replication stores multiple copies on different nodes and updates them simultaneously, ensuring availability and fault tolerance.

❓ estimation

expert

Estimating metadata server capacity for a large distributed file system

A distributed file system stores 1 billion files. Each file's metadata requires 1 KB of memory. If the metadata server has 256 GB of RAM, approximately how many metadata servers are needed to hold all metadata in memory?

A At least 4 metadata servers

B At least 256 metadata servers

C At least 1 metadata server

D At least 16 metadata servers

💡 Hint

Calculate total metadata size and divide by server RAM.

Total metadata size = 1 billion files * 1 KB = 1 TB. Each server has 256 GB RAM, so 1 TB / 256 GB = 4 servers needed.

Practice

1. What is the main role of a metadata server in a distributed file system?

easy

A. To keep track of file locations and directory structure

B. To store the actual file data

C. To provide network connectivity between clients

D. To encrypt files before storage

Solution

1. Step 1: Understand metadata server function

   The metadata server manages information about where files are stored and their organization.

2. Step 2: Differentiate from storage nodes

   Storage nodes hold the actual file data, not metadata servers.

3. Final Answer:

   To keep track of file locations and directory structure -> Option A

4. Quick Check:

   Metadata server = file info tracker [OK]

Hint: Metadata servers track file info, not data storage [OK]

Common Mistakes:

• Confusing metadata server with storage node
• Thinking metadata server stores file data
• Assuming metadata server handles encryption

2. Which of the following is the correct sequence when a client reads a file in a distributed file system?

easy

A. Client contacts only the storage node

B. Client contacts storage node, then metadata server

C. Client contacts only the metadata server

D. Client contacts metadata server, then storage node

Solution

1. Step 1: Identify client interaction flow

   The client first asks the metadata server for file location details.

2. Step 2: Access data from storage node

   After getting location info, the client reads the actual file data from the storage node.

3. Final Answer:

   Client contacts metadata server, then storage node -> Option D

4. Quick Check:

   Read flow = metadata server then storage node [OK]

Hint: Client asks metadata first, then reads data [OK]

Common Mistakes:

• Reversing the order of contacting servers
• Assuming client contacts only one server type
• Ignoring metadata server role in locating files

3. Consider a distributed file system where a file is split into 3 chunks stored on different storage nodes. If the metadata server returns chunk locations as [Node1, Node2, Node3], what happens when the client requests the file?

medium

A. Client reads all chunks sequentially from Node1 only

B. Client reads chunks in parallel from Node1, Node2, and Node3

C. Client reads chunks randomly from any node

D. Client reads only the first chunk from Node1

Solution

1. Step 1: Understand chunk distribution

   The file is divided into chunks stored on separate nodes for parallel access.

2. Step 2: Client reads chunks efficiently

   To speed up reading, the client fetches all chunks at the same time from their respective nodes.

3. Final Answer:

   Client reads chunks in parallel from Node1, Node2, and Node3 -> Option B

4. Quick Check:

   Parallel chunk reads = faster file access [OK]

Hint: Chunks read in parallel from all nodes [OK]

Common Mistakes:

• Assuming client reads all chunks from one node
• Thinking chunks are read randomly
• Ignoring parallelism benefits

4. A distributed file system client tries to read a file but gets an error because the metadata server is unreachable. What is the most likely cause?

medium

A. Client has no network access to metadata server

B. Storage nodes are down

C. File data is corrupted on storage nodes

D. Client requested a non-existent file chunk

Solution

1. Step 1: Identify error source

   The error is due to inability to reach the metadata server, not storage nodes.

2. Step 2: Analyze network access

   Most likely, the client cannot connect to the metadata server because of network issues or firewall rules.

3. Final Answer:

   Client has no network access to metadata server -> Option A

4. Quick Check:

   Metadata server unreachable = network issue [OK]

Hint: Metadata server unreachable means network problem [OK]

Common Mistakes:

• Blaming storage nodes for metadata server errors
• Assuming file corruption causes metadata errors
• Confusing chunk existence with server reachability

5. You are designing a distributed file system for a company with many users reading large files frequently but rarely writing. Which design choice improves read performance the most?

hard

A. Disable caching to ensure fresh data on every read

B. Store all file chunks on a single storage node to simplify access

C. Use multiple metadata servers with caching to reduce lookup latency

D. Limit the number of storage nodes to reduce network overhead

Solution

1. Step 1: Analyze workload pattern

   Many reads and few writes mean caching metadata can speed up file location lookups.

2. Step 2: Evaluate design options

   Multiple metadata servers with caching reduce latency and avoid bottlenecks, improving read speed.

3. Step 3: Reject other options

   Storing all chunks on one node limits scalability; disabling caching slows reads; fewer nodes reduce parallelism.

4. Final Answer:

   Use multiple metadata servers with caching to reduce lookup latency -> Option C

5. Quick Check:

   Metadata caching + multiple servers = faster reads [OK]

Hint: Cache metadata and use multiple servers for fast reads [OK]

Common Mistakes:

• Putting all data on one node limits scalability
• Disabling caching hurts read performance
• Reducing nodes lowers parallel access