WOwood_spirit·Mar 20, 2026
(Perhaps a good library for timestamp code in data pipelines https://github.com/williame/TimeMillis)
In Java is fast, code might not bewilliame
TimeMillis
Java2020–2026
williame / TimeMillis
TimeMillis
Very fast Java library for working with timestamps as longs (as returned by System.currentTimeMillis())
2Distinct people
7Mentions
0Explicit recommenders
9GitHub stars
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Very fast Java library for working with timestamps as longs (as returned by System.currentTimeMillis())
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Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.
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Observed mentions: 2020-09-12 17:57:26 UTC to 2026-03-20 16:48:41 UTC.
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| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2026 (partial) | 2026-01-01 00:00:00 UTC | 2027-01-01 00:00:00 UTC | 2 | 0 | 2 |
What Hacker News says
7 sourcesAlso zap the timestamp instant objects if you really need speed; see https://github.com/williame/TimeMillis
In Java is fast, code might not beAdmittedly in a different league speed wise but also scope wise is my very fast timestamp library for Java https://github.com/williame/TimeMillis
This focuses on string <-> timestamp and a few other utilities that are super common in data processing and where the native Java date functions are infamously slow.
I wrote it for some hot paths in some pipelines but was super pleased my employer let me share it. Hope it helps others.
In A Fast 64-Bit Date Algorithm (30–40% faster by counting dates backwards)Yeah don’t do it!
But subtle plug of something I made long ago for when you find your data pipelines are running hot parsing timestamp strings etc: https://github.com/williame/TimeMillis
I’m still pumped by the performance of the thing! :)
In Never write your own date parsing libraryIndeed! It was a while ago but Im quite proud of the fast timestamp functions I made for Java after the standard library timestamp performance turned out to be critical to some data pipelines I was working on.
The early versions of the code did cache the last parsed date etc but as the parser got quicker this became diminishing returns.
The fastest way I found for the calendar month numbers etc was to use a precomputed table etc.
https://github.com/williame/TimeMillis
In Parsing time stamps faster with SIMD instructionsin datasets that I’ve worked with it is so incredibly common and so incredibly slow that I’ve previously made a fast library to work with them: https://github.com/williame/TimeMillis
Not as fast as SIMD, perhaps, but much faster than the Java standard library…
In Parsing time stamps faster with SIMD instructionsTangentially related, last week I made a tiny one-file Java lib for working with Unix timestamps in milliseconds (as returned by System.currentTimeMillis() etc). It’s several orders of magnitude faster that Java’s time api!
https://github.com/williame/TimeMillis
It’s probably not as fast as it could be: all speed ups and improvements welcome!
In The Unix timestamp will begin with 16 this Sunday