feat: consistent hashing

courses/itmo-software-design/consistent-hashing.md

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+## Consistent hashing
+
+Is a distributed hashing scheme that operates independently of the number of servers/objects
+in a distributed hash table. 
+
+Hashing:
+
+- based on some simple fn (hash tables)
+- cryptographic hash fn (password security, blockchain)
+
+In some situations, it may be necessary to split a hash table into several parts, hosted on 
+different servers. (objects and there keys are distributed across multiple servers)
+
+Motivation: bypass the memory limitations of a single server, or to distribute the load.
+
+Typical use case: distributed cache (memcached, redis)
+
+Such setups consist of a pool of caching servers that host many kv pairs and are used to provide 
+fast access to data originally stored elsewhere.
+
+> Reducing the load on a OLTP database and improve performance.
+>
+> Fetching from cache before fetching from the database, if cache miss, fetch from database and 
+> store in cache.
+
+### How to distribute the data across the servers? 
+
+The simplest way is to take the hash % number of servers.
+
+> Works fine until we add/remove a server. Need to redistribute the data across the servers.
+>
+> This may very well degrade performance severely and possibly crash the origin servers.
+
+We need a distribution scheme that doesn't depend directly on the number of servers, when 
+we +/- servers the data should be redistributed minimally.
+
+Consistent hashing is a distributed scheme that operates independently of the number 
+of servers or objects in distributed hash table by assigning them a position on an abstract
+circle, or hash ring. 
+
+This allows servers and objects to scale without affecting the overall system.
+
+Each object key will belong in the server whose key is closest, in a clockwise direction,
+following the object key's position on the ring.
+
+> From a programming perspective, the ring is a sorted list of server values, 
+> that means we can use binary search to find the correct server for an object key.
+
+To encure object keys are evenly distributed across the servers, we can add virtual nodes
+to the ring. (A -> A0..An)
+
+![](./docs/ch/virtual-nodes.png)
+
+Benefit:
+
+- when removing some server, the data will be redistributed across the remaining servers
+and the load will be balanced, without affecting the previous distribution.
+
+- something similar happens when adding a new server, only some part of the data will be
+redistributed to the new server.
+
+
+## Resources
+
+About consistent hashing:
+- https://www.toptal.com/big-data/consistent-hashing
+
+About Amazon DynamoDB replication:
+- https://medium.com/omarelgabrys-blog/consistent-hashing-beyond-the-basics-525304a12ba