Virtual Labs

Consistent hashing

What is the primary goal of consistent hashing in distributed systems?

a: To ensure data security Explanation

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b: To simplify the hash function Explanation

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c: To maintain a balanced load with minimal data movement Explanation

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d: To increase the speed of data retrieval Explanation

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What is the primary disadvantage of using consistent hashing?

a: It is computationally intensive Explanation

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b: It does not handle node failures well Explanation

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c: It requires more complex implementation Explanation

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d: It cannot handle large datasets Explanation

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Consistent hashing is especially useful for which type of applications?

a: Single-threaded applications Explanation

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b: Distributed systems with dynamic membership Explanation

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c: Local file systems Explanation

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d: Simple desktop applications Explanation

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Which of the following is a common use case for consistent hashing besides distributed caching?

a: Load balancing in web servers Explanation

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b: Data replication in relational databases Explanation

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c: Session management in web applications Explanation

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d: Distributed logging Explanation

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Why is the modulo operation not ideal for consistent hashing?

a: It is computationally expensive Explanation

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b: It does not evenly distribute keys Explanation

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c: It causes significant data movement when nodes are added or removed Explanation

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d: It is not supported in many programming languages Explanation

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In consistent hashing, how are keys and machines represented?

a: As points on a line Explanation

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b: As points on a 3D sphere Explanation

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c: As points on a circle Explanation

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d: As points on a grid Explanation

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What is the role of a hash function in consistent hashing?

a: To encrypt the data Explanation

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b: To map data to a position on the hash ring Explanation

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c: To manage network traffic Explanation

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d: To compress data Explanation

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What is the range of the hash function in consistent hashing?

a: [0, ∞) Explanation

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b: [-1, 1] Explanation

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c: [0, 1) Explanation

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d: [-1, ∞) Explanation

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Why is MD5 often used in consistent hashing despite its cryptographic weaknesses?

a: Because it is faster than other hash functions Explanation

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b: Because it provides better security Explanation

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c: Because it produces 64-bit hash values Explanation

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d: Because its collisions are predictable Explanation

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Why might Python's built-in `hash` function be unsuitable for consistent hashing?

a: It is too slow Explanation

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b: It does not provide uniform distribution of keys Explanation

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c: It is not cryptographically secure Explanation

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d: It only works with integers Explanation

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What is a another potential issue with using Python's built-in `hash` function?

a: It is not uniform across different Python sessions Explanation

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b: It is slower than MD5 Explanation

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c: It produces very large hash values Explanation

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d: It is cryptographically secure Explanation

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What happens to the distribution of key-value pairs when a new machine is added in consistent hashing?

a: All key-value pairs are rehashed and redistributed Explanation

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b: Only the key-value pairs that map to the new machine's point need to be moved Explanation

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c: The distribution remains unchanged Explanation

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d: Key-value pairs are duplicated across all machines Explanation

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What does the term 'virtual nodes' refer to in consistent hashing?

a: A secondary set of nodes used for redundancy Explanation

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b: Multiple logical nodes mapped to a single physical node Explanation

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c: Nodes that do not store any data but manage metadata Explanation

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d: Temporary nodes used during data migration Explanation

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What is the purpose of using multiple points per server in consistent hashing?

a: To increase the size of the hash space Explanation

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b: To improve the resolution of the hash function Explanation

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c: To distribute the load more evenly among servers Explanation

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d: To make the hash function more secure Explanation

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In consistent hashing, what is the impact of using a high number of virtual nodes?

a: Increased complexity in managing the system Explanation

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b: Decreased load balancing efficiency Explanation

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c: Improved load distribution and fault tolerance Explanation

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d: Reduced overall performance of the system Explanation

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How does consistent hashing handle servers with different capacities?

a: By assigning them a larger number of points on the circle Explanation

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b: By using a different hash function for each server Explanation

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c: By limiting the number of keys they can store Explanation

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d: By storing keys in a hierarchical structure Explanation

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What is a 'hot spot' in the context of distributed caching?

a: A location where data is frequently accessed Explanation

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b: A node that has failed Explanation

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c: A region in the hash space with no data Explanation

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d: A backup server Explanation

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How does consistent hashing handle a sudden increase in load on a particular node?

a: By redistributing the load to all nodes evenly Explanation

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b: By assigning more virtual nodes to balance the load Explanation

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c: By shutting down the overloaded node temporarily Explanation

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d: By replicating data to neighboring nodes Explanation

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What aspect of consistent hashing helps mitigate the 'Thundering Herd' problem?

a: By adding servers gradually and increasing their points over time Explanation

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b: By shutting down the system temporarily Explanation

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c: By using a different hash function for each server Explanation

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d: By duplicating all data across all servers Explanation

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How does consistent hashing improve fault tolerance in distributed systems?

a: By replicating data across multiple nodes Explanation

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b: By using stronger hash functions Explanation

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c: By reducing the number of nodes required Explanation

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d: By simplifying the system architecture Explanation

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What is the typical effect of server failure in a consistent hashing system?

a: All data on the failed server is lost Explanation

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b: The load is redistributed among the remaining servers Explanation

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c: The entire system crashes Explanation

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d: Only the failed server's data is inaccessible Explanation

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Which popular open-source caching system has integrated consistent hashing to manage distributed caching?

a: Redis Explanation

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b: Memcached Explanation

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c: Varnish Explanation

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d: Squid Explanation

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What is the primary purpose of a distributed dictionary in the context of MapReduce?

a: To store the intermediate and final key-value pairs generated by MapReduce jobs Explanation

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b: To store the source code of MapReduce jobs Explanation

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c: To manage user sessions in a web application Explanation

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d: To index web pages for search engines Explanation

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