Does Cassandra use Consistent Hashing?

Yes, Cassandra uses Consistent Hashing as part of its data distribution mechanism. Consistent hashing allows Cassandra to evenly distribute data across its nodes in a scalable and fault-tolerant manner.

Below is how Consistent Hashing works in Cassandra:

1. Token Ring

Cassandra uses a concept called a “token ring” to represent the hash space. Each node in the Cassandra cluster is assigned a range of tokens on the hash space.

2. Data Distribution

When data is written to Cassandra, it is hashed using a hash function to produce a token value. Cassandra then uses this token value to determine which node in the cluster should be responsible for storing the data. The node responsible for storing the data is the node with the next highest token value in the token ring.

3. Adding or Removing Nodes

When a node is added to or removed from the cluster, only a portion of the data needs to be moved to rebalance the cluster. This is because the token ranges of the nodes adjacent to the added or removed node will change, but the token ranges of the other nodes remain the same.

4. Fault Tolerance

Consistent hashing also provides fault tolerance in Cassandra. If a node fails, the data that was stored on that node can be easily redistributed to other nodes in the cluster without needing to move all the data in the cluster.

Overall, Consistent Hashing in Cassandra allows for efficient and scalable data distribution, making it a key component of Cassandra’s architecture.