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Comment by rakoo | Hacker News Reader

FYI lz4 and zstd are made by the same guy, so there is no surprise both of them complement each other. lz4 targets the (de)compress-as-fast-as-possible domain, while zstd is for the rest (good (de)compression with slower speed).

For something that is write-once read-many-times, like a filesystem, a good compression algorithm might be more interesting in the future. lz4 is more targeted at write-once read-once, like file transfers for example

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Isn't it the opposite? If LZ4 is optimized for decompression speed as you say, then you would want to use it when you read many times, the same file, very fast.

From a quick read, ZSTD looks more about saving space while keeping reasonable speeds, both at write and read.

And I'd assume there are other algorithms that focus only on size, trading speed for it.

xz would be an example of the latter kind.

Does xz actually outperform ZSTD anywhere? IIRC even at high compression ratios ZSTD is a lot faster than xz.

Edit: Arch Linux switched from xz to ZSTD for their package manager and somebody compared both: https://sysdfree.wordpress.com/2020/01/04/293/

The Arch Linux developers state that they expect an 0.8% you increase in package size but an 1300% speedup in decompression. Not too shabby.

I'm running Arch on my personal system and it's really noticable, especially when I create by own packages, compression doesn't take longer than compiling anymore.

There definitely exist certain kinds of data which xz can compress better or as well but faster than zstd, even taking into account the more extreme compression options offered by zstd. I know because we have many terabytes of such data, and I've done thorough comparisons between xz and zstd at all different compression levels.

However in all cases zstd is much faster for decompression. It just happens that getting the best compression ratio in a not insane amount of time is still the better tradeoff for us.

Depends what "read many times" means.

- If you mean that the same archive will be distributed to many peers, such as is the case in package distribution, then in practice archives will be read only once by each process, so one "slow" compression will translate into significant gains in added decompression speed. That's the reason Archlinux switched to zstd for its packages (https://www.archlinux.org/news/now-using-zstandard-instead-o...)

- If you mean that the same archive will be read multiple times by the same machine, I don't really know what kind of scenario that is; I'd deflate the archive into its initial representation once and then let processes access that folder directly. Note that zstd claims that it isn't that much slower in decompression than competitors, even if you always use compressed archives the difference will be minimal

zstd was built more or less to "replace" all formats that favor compression over speed. From their benchmarks (which means what it means) whatever the compression/speed ratio you want, zstd is going to be better than all of them, with a hard exception on extremely fast speed that is still the kingdom of lz4.

It also depends on your workload and the speed of your disks.

If your disks are faster than your decompression algorithm when that algorithm is running alongside the rest of your workload (generally not the case) then it can make sense to use the faster decompressor (lz4). In my understanding of the tradeoffs of zstd though, having used it recently in an application, chances are you have a free hardware thread that can saturate your disk without affecting your compute workload.

Considering that nowadays many people have an SSD, for boot files that would mean LZ4 is best.

But perhaps for your data files that you don't open often, ZSTD is best because you save space on the SSD.

> Considering that nowadays many people have an SSD, for boot files that would mean LZ4 is best.

That depends on how concurrent boot is, and how fast your CPU and memory are. It may be true on a Celeron, but maybe not on a ThreadRipper.

Furthermore, if you look at the performance testing, the sequential read performance was almost always better with zstd than with lz4, in ZFS; and the zstd-fast mode was about as fast as the lz4 mode in sequential writes. This may be a matter of their specific integration of lz4, but nonetheless it pays to look at the actual numbers before drawing conclusions.

Indeed in these cases lz4 makes sense. I'm thinking of what lz4 was created to "replace" namely snappy in SSTables: the pattern is mostly write once, read at most once or twice, and both of those are sequential to benefit of non-SSDs speeds. In these situations fast (de)compression schemes are definitely a gain.

By read many times I mean a file that is opened many times. For instance, the kernel and libraries every time you boot.

From my understanding (but please correct me if I am wrong), LZ4 will decompress them significantly faster than ZSTD even if the latter compresses more.

In other words, the decompression speed is measured on the decompressed data, right?

Yes, speeds are measured relative to the uncompressed data. ZSTD outputs around 600-2000MiB/s/core (in all the higher levels), depending on how fast your processor is.

It depends on whether read rates are more likely to be limited by CPU or by disk speed. If the former, you'll probably want something like LZ4 to minimize CPU usage. If the latter, it may be better to use a more CPU intensive algorithm which provides better compression, so that there is less compressed data to read from the disk.

Zstd uses this new ANS coding: https://en.wikipedia.org/wiki/Asymmetric_numeral_systems

Guy who stands behind this has insane CV

2015- Jagiellonian University, Institute of Computer Science, assistant professor,

2013-2014 Purdue University, NSF Center for Science of Information, Postdoctoral researcher (webpage),

2006-2012 Jagiellonian University, Cracow, PhD in Theoretical Physics (thesis)

2004-2010 Jagiellonian University, Cracow, PhD in Theoretical Computer Science (thesis)

2001-2006 Jagiellonian University, Cracow, MSc in Theoretical Physics (thesis)

2000-2005 Jagiellonian University, Cracow, MSc in Theoretical Mathematics (thesis)

1999-2004 Jagiellonian University, Cracow, MSc in Computer Science (thesis)

IIRC it doesn't use ANS for every compression level, can't remember much more than that, though

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