compress
zstd
compress | zstd | |
---|---|---|
17 | 109 | |
4,532 | 22,523 | |
- | 1.9% | |
8.4 | 9.7 | |
20 days ago | 7 days ago | |
Go | C | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
compress
- Chrome Feature: ZSTD Content-Encoding
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Show HN: Gogosseract, a Go Lib for CGo-Free Tesseract OCR via Wazero
There's a pure-go zstd at https://github.com/klauspost/compress - it's likely faster than running the upstream zstd under Wazero.
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When is go not a good choice?
It's no surprise that "fast" Go libraries are actually just assembly: https://github.com/klauspost/compress/blob/master/zstd/seqdec_amd64.s (just one file out of several, for just one architecture, for just one compression algorithm!)
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zstd
There is a reasonably feature complete implementation of Zstd for Go: https://github.com/klauspost/compress/tree/master/zstd
It may not offer the same API 1:1, but it has no interoperability issues that I've encountered. So, I just think no one has bothered to implement it in Rust because most use cases don't mind the added bloat you're talking about. Plus, other comments I've seen suggest that you can actually tune the size of the zstd library, although I'm not sure if the Rust bindings expose that.
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Medical image parser in Go
Thanks again for your review/comment!!! Btw, are you the author of this repo https://github.com/klauspost/compress because I love it!!!
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Ask HN: Does https://github.com/klauspost/compress returns 502 for you?
I noticed Github returns "This page is taking too long to load" with status code 502 for https://github.com/klauspost/compress but rest of their urls works fine. Anyone know why would that be the case ?
Cloning the repo works perfectly well.
git clone https://github.com/klauspost/compress
- S2 Compression
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Zstandard – Real-time data compression algorithm
Recent versions of zstd definitely don't obsolete LZ4, or else I don't think the author would still be contributing to both...
And if you're going to play with Snappy, you might find S2, which was linked on HN relatively recently, interesting. [1]
[1] - https://github.com/klauspost/compress/tree/master/s2
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Restic 0.14.0 Released (with highly anticipated feature – compression)
Compression method appears to be zstandard and uses https://github.com/klauspost/compress, for those wondering like I was.
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MinIO Object Placement Strategy in Distributed deployments
OMG u/klauspost is this you? https://github.com/klauspost/compress/tree/master/s2
zstd
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Rethinking string encoding: a 37.5% space efficient encoding than UTF-8 in Fury
> In such cases, the serialized binary are mostly in 200~1000 bytes. Not big enough for zstd to work
You're not referring to the same dictionary that I am. Look at --train in [1].
If you have a training corpus of representative data, you can generate a dictionary that you preshare on both sides which will perform much better for very small binaries (including 200-1k bytes).
If you want maximum flexibility (i.e. you don't know the universe of representative messages ahead of time or you want maximum compression performance), you can gather this corpus transparently as messages are generated & then generate a dictionary & attach it as sideband metadata to a message. You'll probably need to defer the decoding if it references a dictionary not yet received (i.e. send delivers messages out-of-order from generation). There are other techniques you can apply, but the general rule is that your custom encoding scheme is unlikely to outperform zstd + a representative training corpus. If it does, you'd need to actually show this rather than try to argue from first principles.
[1] https://github.com/facebook/zstd/blob/dev/programs/zstd.1.md
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Drink Me: (Ab)Using a LLM to Compress Text
> Doesn't take large amount of GPU resources
This is an understatement, zstd dictionary compression and decompression are blazingly fast: https://github.com/facebook/zstd/blob/dev/README.md#the-case...
My real-world use case for this was JSON files in a particular schema, and the results were fantastic.
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SQLite VFS for ZSTD seekable format
This VFS will read a sqlite file after it has been compressed using [zstd seekable format](https://github.com/facebook/zstd/blob/dev/contrib/seekable_f...). Built to support read-only databases for full-text search. Benchmarks are provided in README.
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Chrome Feature: ZSTD Content-Encoding
Of course, you may get different results with another dataset.
gzip (zlib -6) [ratio=32%] [compr=35Mo/s] [dec=407Mo/s]
zstd (zstd -2) [ratio=32%] [compr=356Mo/s] [dec=1067Mo/s]
NB1: The default for zstd is -3, but the table only had -2. The difference is probably small. The range is 1-22 for zstd and 1-9 for gzip.
NB2: The default program for gzip (at least with Debian) is the executable from zlib. With my workflows, libdeflate-gzip iscompatible and noticably faster.
NB3: This benchmark is 2 years old. The latest releases of zstd are much better, see https://github.com/facebook/zstd/releases
For a high compression, according to this benchmark xz can do slightly better, if you're willing to pay a 10× penalty on decompression.
xz -9 [ratio=23%] [compr=2.6Mo/s] [dec=88Mo/s]
zstd -9 [ratio=23%] [compr=2.6Mo/s] [dec=88Mo/s]
- Zstandard v1.5.6 – Chrome Edition
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Optimizating Rabin-Karp Hashing
Compression, synchronization and backup systems often use rolling hash to implement "content-defined chunking", an effective form of deduplication.
In optimized implementations, Rabin-Karp is likely to be the bottleneck. See for instance https://github.com/facebook/zstd/pull/2483 which replaces a Rabin-Karp variant by a >2x faster Gear-Hashing.
- Show HN: macOS-cross-compiler – Compile binaries for macOS on Linux
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Cyberpunk 2077 dev release
Get the data https://publicdistst.blob.core.windows.net/data/root.tar.zst magnet:?xt=urn:btih:84931cd80409ba6331f2fcfbe64ba64d4381aec5&dn=root.tar.zst How to extract https://github.com/facebook/zstd Linux (debian): `sudo apt install zstd` ``` tar -I 'zstd -d -T0' -xvf root.tar.zst ```
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Honey, I shrunk the NPM package · Jamie Magee
I've done that experiment with zstd before.
https://github.com/facebook/zstd/blob/dev/programs/zstd.1.md...
Not sure about brotli though.
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How in the world should we unpack archive.org zst files on Windows?
If you want this functionality in zstd itself, check this out: https://github.com/facebook/zstd/pull/2349
What are some alternatives?
nodejs-js-compress-benchmark - Benchmark NodeJS/JS compression libraries
LZ4 - Extremely Fast Compression algorithm
go - The Go programming language
Snappy - A fast compressor/decompressor
sqlite-zstd - Transparent dictionary-based row-level compression for SQLite
LZMA - (Unofficial) Git mirror of LZMA SDK releases
jsoniter - A high-performance 100% compatible drop-in replacement of "encoding/json"
7-Zip-zstd - 7-Zip with support for Brotli, Fast-LZMA2, Lizard, LZ4, LZ5 and Zstandard
easyjson - Fast JSON serializer for golang.
ZLib - A massively spiffy yet delicately unobtrusive compression library.
gzipped - Replacement for golang http.FileServer which supports precompressed static assets.
brotli - Brotli compression format