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Useful papers for distributed system

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What are Bloom filters?

Bloom filters can very quickly answer variations on the Yes/No question “is this item in the set?”,
like “have I seen this item before?”. There are two important caveats though.

Very rarely, it will say Yes when the answer is actually No (although it will never say No,
when the answer is actually Yes). You also can’t remove an item from a Bloom filter.
Like elephants and unrelenting Polish designers, Bloom filters never forget.

More detailed from below

https://blog.medium.com/what-are-bloom-filters-1ec2a50c68ff

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Generating unique IDs in a distributed environment At high scale

Solution from Twitter Snowflake

Twitter snowflake is a dedicated network service for generating 64-bit unique IDs at high scale. The IDs generated by this service are roughly time sortable.

The IDs are made up of the following components:

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Consistent Hashing Simplified

Distributed system problem

We want to dynamically add/remove cache servers based on usage load.

  • We should be able to distribute the keys uniformly among the set of “n” servers.
  • We should be able to dynamically add or remove a server.
  • When we add/remove a server, we need to move the minimal amount of data between the servers.

Refer to below article for detailed explanation

https://towardsdatascience.com/consistent-hashing-simplified-7fe4e512324