Advantages of using Consistent Hashing

The following are some of the key advantages of using consistent hashing:

  1. Load balancing: Consistent hashing helps to evenly distribute the network’s workload among its nodes, preserving the system’s effectiveness and responsiveness even as the amount of data increases and changes over time.
  2. Scalability: Consistent hashing is extremely scalable, which means that it can adapt to changes in the number of nodes or the amount of data being processed with little to no influence on the performance of the entire system.
  3. Minimal Remapping: Consistent hashing reduces the number of keys that must be remapped when a node is added or removed, ensuring that the system is robust and consistent even as the network changes over time. 
  4. Increased Failure Tolerance: Consistent hashing makes data always accessible and current, even in the case of node failures. The stability and dependability of the system as a whole are enhanced by the capacity to replicate keys across several nodes and remap them to different nodes in the event of failure.
  5. Simplified Operations: The act of adding or removing nodes from the network is made easier by consistent hashing, which makes it simpler to administer and maintain a sizable distributed system.

Consistent Hashing | System Design

Consistent hashing is a distributed hashing technique used in computer science and distributed systems to achieve load balancing and minimize the need for rehashing when the number of nodes in a system changes. It is particularly useful in distributed hash tables (DHTs), distributed caching systems, and other distributed storage systems.

Important Topics for the Consistent Hashing

  • What is Hashing?
  • What is Consistent Hashing?
  • What is the use of Consistent Hashing?
  • Phases/Working of Consistent Hashing
  • Implementation of Consistent Hashing algorithm
  • Advantages of using Consistent Hashing
  • Disadvantages of using Consistent Hashing

Similar Reads

What is Hashing?

Hashing involves using a hash function to produce a pseudo-random number. This number is then divided by the size of the available memory space, resulting in the transformation of the random identifier into a position within the given memory space. This process can be conceptually represented as follows:...

What is Consistent Hashing?

Consistent hashing is a technique used in computer systems to distribute keys (e.g., cache keys) uniformly across a cluster of nodes (e.g., cache servers). The goal is to minimize the number of keys that need to be moved when nodes are added or removed from the cluster, thus reducing the impact of these changes on the overall system....

What is the use of Consistent Hashing?

Consistent hashing is a popular technique used in distributed systems to address the challenge of efficiently distributing keys or data elements across multiple nodes/servers in a network. Consistent hashing’s primary objective is to reduce the number of remapping operations necessary when adding or removing nodes from the network, which contributes to the stability and dependability of the system....

Phases/Working of Consistent Hashing

The following are the phases involved in the process of consistent hashing:...

Implementation of Consistent Hashing algorithm

Choose a Hash Function: Select a hash function that produces a uniformly distributed range of hash values. Common choices include MD5, SHA-1, or SHA-256. Define the Hash Ring: Represent the range of hash values as a ring. This ring should cover the entire possible range of hash values and be evenly distributed. Assign Nodes to the Ring: Assign each node in the system a position on the hash ring. This is typically done by hashing the node’s identifier using the chosen hash function. Key Mapping: When a key needs to be stored or retrieved, hash the key using the chosen hash function to obtain a hash value. Find the position on the hash ring where the hash value falls. Walk clockwise on the ring to find the first node encountered. This node becomes the owner of the key. Node Additions: When a new node is added, compute its position on the hash ring using the hash function. Identify the range of keys that will be owned by the new node. This typically involves finding the predecessor node on the ring. Update the ring to include the new node and remap the affected keys to the new node. Node Removals: When a node is removed, identify its position on the hash ring. Identify the range of keys that will be affected by the removal. This typically involves finding the successor node on the ring. Update the ring to exclude the removed node and remap the affected keys to the successor node. Load Balancing: Periodically check the load on each node by monitoring the number of keys it owns. If there is an imbalance, consider redistributing some keys to achieve a more even distribution....

Advantages of using Consistent Hashing

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Disadvantages of using Consistent Hashing

The following are some of the key advantages of using consistent hashing:...