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Sedgewick is a very good writer IMHO. I learned algorithms with his famous book "Algorithms in C". Later I read many different algorithms books, and there are b
by antirez 10y ago
Sedgewick is a very good writer IMHO. I learned algorithms with his famous book "Algorithms in C". Later I read many different algorithms books, and there are better books from specific point of views, however as an entry level book I think that AiC is one of the most accessible for students.
Btw, Redis recently switched from HyperLogLog to the slightly better LogLog-Beta algorithm which is not listed in this publication AFAIK.
- pselbert 10y ago> Redis recently switched from HyperLogLog to the slightly better LogLog-Beta Interesting, has anything been written about that? I've learned most of what I know about cardinality estimation from Redis and your writing on the matter, so I'd love to see more. It would be great to re-visit an article I wrote about HLL[0] from a new perspective as well. [0]: https://blog.codeship.com/counting-distinct-values-with-hyperloglog/ https://blog.codeship.com/counting-distinct-values-with-hype...
- octernion 10y agoSee the Arxiv paper[0] on it. Found this from the Redis code[1] (I was curious, too). [0]:https://arxiv.org/abs/1612.02284 https://arxiv.org/abs/1612.02284 [1]:https://github.com/antirez/redis/blob/87538cb7fe19b5671189442cd604de5d58a856a7/src/hyperloglog.c#L997 https://github.com/antirez/redis/blob/87538cb7fe19b567118944...
- oertl 10y agoIf you are interested in new cardinality estimation algorithms for HyperLogLog sketches you could also have a look on the paper I am currently working on: http://oertl.github.io/hyperloglog-sketch-estimation-paper/ http://oertl.github.io/hyperloglog-sketch-estimation-paper/ There, I present two different algorithms based on theoretical considerations that are both accurate over the entire cardinality range. Unlike LogLog-Beta or HyperLogLog++, they do not need any empirically determined coefficients or bias correction data.