Talk:Consistent hashing

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I am after reading this article unable to code a consistent hash. I therefore argue it has failed to explain the core concept involved; the article has only described its functionality. Toby Douglass (talk) 22:48, 5 July 2012 (UTC)

Confusing K and n notations

I might be the only one but I find the notation $K$ for the number of keys and $n$ for the number of nodes confusing. I know it is the first letter of each word but usually $K$ is used for the number of partitions and $n$ for the total number of elements and therefore considered $K<n$. I think it should either be $|K|/|n|$ or changed to $N/k$. I wanted to have some opinions before doing this correction. Cmolter (talk) —Preceding undated comment added 16:40, 15 July 2013 (UTC)

Slightly related to this, I want to add that it is not clear whether $n$ is the number of slots before or after the resize... Additionally, it be good if this article would clarify what "resizing a hash table" means... does it mean "changing the number of slots"? --Abdull (talk) 14:12, 18 July 2013 (UTC)

Additional algorithm

There is an alternative algorithm for consistent hashing that is shorter, and that is much more efficient when there is a large numbers of servers. The open source Guava hashing library contributed by Google contains an implementation. See consistentHash() here: https://code.google.com/p/guava-libraries/source/browse/guava/src/com/google/common/hash/Hashing.java

That code doesn't have an explanation of the algorithm, but a preprint now gives one: http://arxiv.org/ftp/arxiv/papers/1406/1406.2294.pdf

As an author of that preprint, it is not appropriate for me to edit this page, but it seems like appropriate subject matter for this page. Johnlamping (talk) 05:02, 13 June 2014 (UTC)

Technique clarification needed

"Since each bucket is associated with many pseudo-randomly distributed points, the resources that were held by that bucket will now map to many different buckets."

Please explain what this (emphasized part) means. I see that the values for the keys were distributed randomly, but the keys themselves were a contiguous block (the bucket), not random "points" (points on the circle, I assume — the circle analogy is confusing).

"Since each bucket is associated with many pseudo-randomly distributed points, the resources that were held by that bucket will now map to many different buckets."

How?

209.49.110.163 (talk) 21:45, 20 August 2014 (UTC)

I was also confused by this. The confusing bit is that part of the text says a bucket is associated with many points on the circle, but this text seems to suggest that a bucket is a single point. It might be easier to remove the confusing notion of a bucket, and just call it a machine.

"then walks around the circle until falling into the first bucket it encounters (or equivalently, the first available bucket with a higher angle). The result is that each bucket contains all the resources located between its point and the previous bucket point. — Preceding unsigned comment added by 50.158.132.159 (talk) 17:54, 8 February 2015 (UTC)

Jungleh (talk) 09:40, 9 October 2016 (UTC)

I clarified the confusion. It seems that the original text mixed the simplistic one-point-per-bucket technique with the more elaborate technique of having many different points around the circle map to the same bucket.

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Removal of citation needed tag

A citation needed tag was added to the claim of rendezvous hashing being first invented in 1996. A reference is present on the appropriate page and has hence been removed from this page. AB1908 (talk) 06:09, 16 April 2020 (UTC)

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