Apache Flink offers a fault tolerance mechanism to consistently recover the state of data streaming applications. The mechanism ensures that even in the presence of failures, the program’s state will eventually reflect every record from the data stream exactly once. Note that there is a switch to downgrade the guarantees to at least once (described below).
I have been working on another post recently, also related to division, but I wanted to address a comment I got from several people on the previous division article. This comment invariably follows a lot of articles on using math to do things with chars and shorts. It is: “why are you doing all of this when you can just use a lookup table?”
Island management is a fundamental low level feature of physics engines and can have a big impact on solver design and performance. This was one of the first problems I decided to work on for Box2D version 3 (v3). Since I began working on v3 I've been comparing several algorithms for island management. My goal has been to make island building scale better with multiple CPU cores. Here are the three approaches I've considered:
Consensus is a fundamental problem in fault-tolerant distributed systems. Consensus involves multiple servers agreeing on values. Once they reach a decision on a value, that decision is final.
S. Jaiswal, and Y. Simmhan. IEEE International Workshop on High-Performance Big Data, Deep Learning, and Cloud Computing (HPBDC), Co-located with IEEE International Parallel and Distributed Processing Symposium (IPDPS), page 452--459. (2019)