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ronomon
hash-table
JavaScript2018–2020
ronomon / hash-table

hash-table

Fast, reliable cuckoo hash table for Node.js.

3Distinct people
14Mentions
1Explicit recommenders
304GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Fast, reliable cuckoo hash table for Node.js.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

One of the things I love about JavaScript is that you can write an almost 10x faster hash table than the standard library if you take care of cache misses and GC:…

_urga used a recommendation phrase. One indexed comment matches. This is a phrase match, not a verdict.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 12:45:45 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month14 dated mentions

Observed mentions: 2018-09-06 16:15:55 UTC to 2020-06-17 21:40:41 UTC.

01232018-09-01 00:00:00 UTC to 2018-10-01 00:00:00 UTC (exclusive): 3 mentions; 2 submissions, 1 commentsSep 20182018-10-01 00:00:00 UTC to 2018-11-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments2018-11-01 00:00:00 UTC to 2018-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2018-12-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019-01-01 00:00:00 UTC to 2019-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-02-01 00:00:00 UTC to 2019-03-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019-03-01 00:00:00 UTC to 2019-04-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019-04-01 00:00:00 UTC to 2019-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-05-01 00:00:00 UTC to 2019-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-06-01 00:00:00 UTC to 2019-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-07-01 00:00:00 UTC to 2019-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJul 20192019-08-01 00:00:00 UTC to 2019-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-09-01 00:00:00 UTC to 2019-10-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2019-10-01 00:00:00 UTC to 2019-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-11-01 00:00:00 UTC to 2019-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-12-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2020-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-02-01 00:00:00 UTC to 2020-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-03-01 00:00:00 UTC to 2020-04-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2020-04-01 00:00:00 UTC to 2020-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-05-01 00:00:00 UTC to 2020-06-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2020-06-01 00:00:00 UTC to 2020-07-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 commentsJun 2020

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Sep 20182018-09-01 00:00:00 UTC2018-10-01 00:00:00 UTC321
Oct 20182018-10-01 00:00:00 UTC2018-11-01 00:00:00 UTC312
Nov 20182018-11-01 00:00:00 UTC2018-12-01 00:00:00 UTC000
Dec 20182018-12-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
Jan 20192019-01-01 00:00:00 UTC2019-02-01 00:00:00 UTC000
Feb 20192019-02-01 00:00:00 UTC2019-03-01 00:00:00 UTC101
Mar 20192019-03-01 00:00:00 UTC2019-04-01 00:00:00 UTC101
Apr 20192019-04-01 00:00:00 UTC2019-05-01 00:00:00 UTC000
May 20192019-05-01 00:00:00 UTC2019-06-01 00:00:00 UTC000
Jun 20192019-06-01 00:00:00 UTC2019-07-01 00:00:00 UTC000
Jul 20192019-07-01 00:00:00 UTC2019-08-01 00:00:00 UTC000
Aug 20192019-08-01 00:00:00 UTC2019-09-01 00:00:00 UTC000
Sep 20192019-09-01 00:00:00 UTC2019-10-01 00:00:00 UTC110
Oct 20192019-10-01 00:00:00 UTC2019-11-01 00:00:00 UTC000
Nov 20192019-11-01 00:00:00 UTC2019-12-01 00:00:00 UTC000
Dec 20192019-12-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
Jan 20202020-01-01 00:00:00 UTC2020-02-01 00:00:00 UTC000
Feb 20202020-02-01 00:00:00 UTC2020-03-01 00:00:00 UTC000
Mar 20202020-03-01 00:00:00 UTC2020-04-01 00:00:00 UTC101
Apr 20202020-04-01 00:00:00 UTC2020-05-01 00:00:00 UTC000
May 20202020-05-01 00:00:00 UTC2020-06-01 00:00:00 UTC101
Jun 20202020-06-01 00:00:00 UTC2020-07-01 00:00:00 UTC202

What Hacker News says

3 sources
Thanks, I added Set into the rough vanilla comparison. It's slightly better than a vanilla object, but it's still almost an order of magnitude slower, and is most likely still going to have issues with GC overhead when storing millions of pointers. GC issues blocking the event loop are not fun when you have a hash table with billions of elements. Also, while a Set can technically receive an Array (or iterable) upfront in the constructor, this requires you to have your Array available upfront, which is not always the case, and an Array is also not meant for millions of objects in the first place. For example, AFAIK (and I may be wrong since last I checked) but V8's Array will switch mode and degrade into an object at around 10,000 elements. So with Set (or Map) there's still no production-quality way to allocate and reserve capacity upfron
Read the rest
t by the number of elements or size in bytes. Please note, the `vanilla.js` comparison in the Motivation section is not meant as a benchmark, but just to sketch the principles outlined there. You don't actually even see the 10× differential with `vanilla.js` because it only inserts 4,000,000 elements - I would have set it higher but Set and Object start taking forever or cause OOM crashes beyond that. More accurate, in-depth performance numbers are here: https://github.com/ronomon/hash-table#performance
In A 10× Faster Hash Table for Node.js

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