MCQs

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Overall MCQs for Reference

What is the main purpose of consistent hashing in distributed systems?
a. Evenly distribute hash codes
b. Minimize data movement upon node changes
c. Increase hash collision rate
d. Reduce computation power required
Answer: b. Minimize data movement upon node changesalgomaster+2
In consistent hashing, data and nodes are mapped to positions on what structure?
a. Binary search tree
b. Circular hash ring
c. Hash grid
d. Linear table
Answer: b. Circular hash ringpubnub+2
Which traditional hashing problem does consistent hashing solve?
a. Data sorting
b. Inefficient space usage
c. Massive rehashing after node change
d. String search complexity
Answer: c. Massive rehashing after node changegeeksforgeeks+2
When a new node is added in consistent hashing, what happens to the data?
a. All data is reassigned
b. One random data is reassigned
c. Only data in a specific range is reassigned
d. No data is reassigned
Answer: c. Only data in a specific range is reassignedalgomaster+2
The concept of the “hash ring” in consistent hashing means:
a. Nodes are linearly arranged
b. Nodes are randomly grouped
c. Both nodes and keys are mapped on a virtual circle
d. Only keys are hashed
Answer: c. Both nodes and keys are mapped on a virtual circlebytebytego+2
What is a common hash function used in consistent hashing?
a. Parity function
b. MD5
c. Caesar cipher
d. Bubble sort
Answer: b. MD5geeksforgeeks+1
In consistent hashing, if there are n nodes and k keys, how many keys on average are remapped when a node is added?
a. k
b. n
c. k/n
d. n/k
Answer: c. k/nbytebytego+2
How does consistent hashing handle the removal of a node?
a. All data is lost
b. New node processes the unknown data
c. Only keys mapped to the removed node are reassigned
d. No changes occur
Answer: c. Only keys mapped to the removed node are reassignedpubnub+2
What characteristic makes consistent hashing highly scalable?
a. Persistence of hash ring
b. Incremental data redistribution
c. Hash ring’s linear structure
d. Absence of hash functions
Answer: b. Incremental data redistributionalgomaster+2
Consistent hashing is particularly useful in which scenario?
a. Uniprocessor systems
b. Static hash table size
c. Dynamic, distributed storage systems
d. Non-networked applications
Answer: c. Dynamic, distributed storage systemspubnub+2
What is a “virtual node” in consistent hashing?
a. Placeholder for missing data
b. Duplicate entry to balance load
c. Logical partition to finer distribute keys
d. Temporary error state
Answer: c. Logical partition to finer distribute keysgeeksforgeeks+1
What happens to the keys when a node fails in a consistent hash ring?
a. They are deleted
b. They wrap to the next node clockwise
c. They are assigned randomly
d. They produce hash collisions
Answer: b. They wrap to the next node clockwisealgomaster+1
Which hash ring traversal direction is standard for locating responsible nodes?
a. Counter-clockwise
b. Clockwise
c. Both directions
d. Zigzag
Answer: b. Clockwisepubnub+2
Which is a key benefit of consistent hashing for AI’s distributed cache management?
a. Increased query latency
b. Minimal cache miss rate by reducing data relocation
c. Extra RAM usage
d. Direct I/O improvement
Answer: b. Minimal cache miss rate by reducing data relocationgeeksforgeeks+1
Which load balancing challenge is addressed directly by consistent hashing?
a. Priority inversion
b. Overloading single nodes
c. Stack overflow
d. DDoS avoidance
Answer: b. Overloading single nodesalgomaster+1
For a consistent hash ring with 360 degrees, a key hashed to 75 will be stored on the node with ID:
a. 74
b. Next node clockwise ≥ 75
c. 0
d. Closest to 0
Answer: b. Next node clockwise ≥ 75pubnub+1
What effect does increasing the number of virtual nodes have?
a. Decreases distribution evenness
b. Increases crash risk
c. Improves load balancing
d. Reduces hash space
Answer: c. Improves load balancinggeeksforgeeks+1
Which system design interview topic is consistent hashing often associated with?
a. Array sorting
b. Load balancing and sharding
c. Function overloading
d. Process scheduling
Answer: b. Load balancing and shardinginterm+1
In consistent hashing, which factor determines a node’s place on the ring?
a. Order of joining
b. Node’s identifier hashed
c. Node’s physical address
d. Node RAM size
Answer: b. Node’s identifier hashedalgomaster+1
Which of these is NOT an application of consistent hashing?
a. Distributed cache
b. DNS load balancing
c. Semaphore implementation
d. Distributed databases
Answer: c. Semaphore implementationhellointerview+2
What is the role of hash functions in consistent hashing?
a. To provide uniform mapping
b. To compress data
c. To encrypt secret keys
d. To maximize collisions
Answer: a. To provide uniform mappingpubnub+2
Which main drawback does consistent hashing face?
a. Very slow scaling
b. Needs more virtual nodes for fairness with few servers
c. Unable to rebalance loads
d. Causes linear search overhead
Answer: b. Needs more virtual nodes for fairness with few serversgeeksforgeeks+1
What is meant by a “hot spot” in a consistent hash ring?
a. Server with too little load
b. Node right after a heavily-mapped hash region
c. Unused section
d. Disabled node
Answer: b. Node right after a heavily-mapped hash regionalgomaster+1
Which type of distributed system can especially benefit from consistent hashing?
a. Peer-to-peer networks
b. Uniprocessor architectures
c. Non-persistent queues
d. Synchronous protocols only
Answer: a. Peer-to-peer networkspubnub+2
How does consistent hashing minimize downtime during scaling?
a. Buffers excess data
b. Redistributes only affected keys
c. Disables removed nodes
d. Deletes old data before adding nodes
Answer: b. Redistributes only affected keysgeeksforgeeks+1
What is the result if all nodes are equally spread across the hash ring?
a. Load is balanced
b. Clustering occurs
c. Errors increase
d. Security improves
Answer: a. Load is balancedalgomaster+1
What does a consistent hash ring NOT prevent?
a. Load spikes
b. Node failures
c. Data loss after hashing
d. Zero-collision mapping
Answer: b. Node failurespubnub+1
When designing a distributed AI model cache, consistent hashing helps:
a. Persistent connections pool
b. Evenly distribute model parts across nodes
c. Split integer arrays
d. Encrypt agent data
Answer: b. Evenly distribute model parts across nodesgeeksforgeeks+1
How does consistent hashing relate to sharding?
a. It serves as an alternative to sharding
b. It automates the mapping of data to shards
c. It prevents sharding altogether
d. It only works with vertical sharding
Answer: b. It automates the mapping of data to shardsinterm+2
Which is a typical hash function requirement for consistent hashing?
a. Non-uniformity
b. Fast computation and uniform spread
c. High entropy only
d. Symmetric encryption
Answer: b. Fast computation and uniform spreadalgomaster+1
Consistent hashing maintains efficiency by ensuring only affected keys are:
a. Erased
b. Remapped
c. Rehashed globally
d. Deleted
Answer: b. Remappedpubnub+2
Which scaling type becomes efficient with consistent hashing?
a. Horizontal scaling (adding/removing servers)
b. Vertical scaling only
c. Memory scaling
d. Latency scaling
Answer: a. Horizontal scaling (adding/removing servers)geeksforgeeks+2
Why are virtual nodes useful in consistent hashing for AI’s distributed systems?
a. They increase collision risk
b. Equalize data distribution even when some nodes are underpowered
c. Lower hashing efficiency
d. Randomize model deployment
Answer: b. Equalize data distribution even when some nodes are underpoweredalgomaster+1
What is a primary cause of uneven distribution in naive hash functions?
a. Unequal key ranges
b. Collisions from poor hash functions
c. Ring size
d. Virtual node count
Answer: b. Collisions from poor hash functionsgeeksforgeeks+1
What does the term “rehashing” refer to in distributed hashing?
a. Recomputing the hash for all keys when a node changes
b. Randomly switching servers at intervals
c. Deleting all keys
d. Encrypting node links
Answer: a. Recomputing the hash for all keys when a node changespubnub+1
What is the main effect of using consistent hashing in CDN architectures?
a. Increased load times
b. Smoother scaling and balanced distribution
c. Decreased redundancy
d. Higher miss rates
Answer: b. Smoother scaling and balanced distributiontoptal+1
Which is NOT a requirement for node assignment on the hash ring?
a. Each node must have a unique ID
b. Each node must be mapped using a consistent hash function
c. Nodes can share hash spots at random
d. Node location must be reproducible
Answer: c. Nodes can share hash spots at randomalgomaster+1
Where are consistent hashing algorithms commonly employed in AI?
a. Gradient descent optimizers
b. Distributed storage of large models
c. Training GPUs
d. Feature engineering
Answer: b. Distributed storage of large modelspubnub+2
Which aspect of machine learning deployment does consistent hashing facilitate most?
a. Model serialization
b. Deployment across elastically scaled infrastructure
c. Loss calculation
d. Data normalization
Answer: b. Deployment across elastically scaled infrastructuregeeksforgeeks+1
What would happen if the hash function is not uniform in consistent hashing?
a. Clustering of keys in some nodes
b. Even load spread
c. Quicker lookups
d. Predictable node assignment
Answer: a. Clustering of keys in some nodesalgomaster+1
What is typically NOT hashed in consistent hashing for AI cache layers?
a. Node’s network address
b. User query result identifier
c. Random memory addresses not mapped to data
d. Data keys
Answer: c. Random memory addresses not mapped to datageeksforgeeks+1
Which failure scenario is best handled by consistent hashing?
a. Node loss without major redistribution
b. Catastrophic hash ring failure
c. Application crash
d. Data transmission lag
Answer: a. Node loss without major redistributionpubnub+1
What result occurs if too few virtual nodes are assigned?
a. Uniform data spread
b. Imbalanced data load
c. Node redundancy
d. Linear scaling
Answer: b. Imbalanced data loadalgomaster+1
What is a typical outcome of consistent hashing in distributed search engines?
a. Repetitive data indexing
b. Minimal re-indexing upon server changes
c. High downtime
d. Static results lists
Answer: b. Minimal re-indexing upon server changeshellointerview+1
Which hash ring mapping strategy best supports auto-scaling in AI workloads?
a. Direct assignment by admin
b. Hash-based, dynamic key-to-node reassignment
c. Hash codes published as text
d. Round-robin with fixed regions
Answer: b. Hash-based, dynamic key-to-node reassignmentgeeksforgeeks+1
What ensures replication in consistent hashing for data redundancy?
a. Writing data to all nodes
b. Mapping data to multiple successive nodes on the ring
c. Ignoring replication entirely
d. Assigning data to random nodes outside the ring
Answer: b. Mapping data to multiple successive nodes on the ringpubnub+1
In AI’s distributed parameter servers, consistent hashing aids with:
a. Secure socket layering
b. Predictable data splits when scaling server pool
c. Model pruning
d. Node overcommitment
Answer: b. Predictable data splits when scaling server poolalgomaster+1
What is a “replica” in the context of consistent hashing?
a. Shadow server for logging
b. Multiple storage of a key’s data on different nodes for fault tolerance
c. Unused node
d. Key value cache
Answer: b. Multiple storage of a key’s data on different nodes for fault tolerancepubnub+1
In AI stream processing platforms, consistent hashing helps by:
a. Splitting streams equally among nodes
b. Queuing streams until idle
c. Increasing process contention
d. Disabling supervision
Answer: a. Splitting streams equally among nodesgeeksforgeeks+1
Which step is NOT part of implementing the consistent hashing algorithm?
a. Selecting a uniform hash function
b. Constructing the hash ring
c. Assigning random data without hashing
d. Assigning nodes and keys on the ring
Answer: c. Assigning random data without hashingalgomaster+1

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