My impression is that this article has a lot of technical insight into how bzip compares to gzip, but it fails actually account for the real cause of the diminished popularity of bzip in favor of the non-gzip alternatives that it admits are the more popular choices in recent years.
https://insanity.industries/post/pareto-optimal-compression/
(Omissions theirs.)
Wasn't that zstandard's stated goal? Not very surprising that it has this property, also considering it's much newer (2015) than the established tools like gzip (1992), bzip2 (1996), LZMA as used by xz utils (1999)
Edit: https://github.com/facebook/zstd/blob/4856a00164c1d7b947bd38... initial commit indeed states it's meant to have good ratios and good (de)compression speeds as compared to other tools, without sacrificing one for the other (»"Standard" translates into everyday situations which neither look for highest possible ratio (which LZMA and ZPAQ cover) nor extreme speeds (which LZ4 covers).«). So Pareto by design, just not using that name
uncompressed: 327005
(gzip) zopfli --i100: 75882
zstd -22 --long --ultra: 69018
xz -9: 67940
brotli -Z: 67859
lzip -9: 67651
bzip2 -9: 63727
bzip3: 61067
> bzip might be suboptimal as a general-purpose compression format, but it’s great for text and code. One might even say the b in bzip stands for “best”.
I've just checked again with a 1GB SQL file. `bzip2 -9` shrinks it to 83MB. `zstd -19 --long` to 52MB.
Others have compressed the Linux kernel and found that bzip2's is about 15% larger than zstd's.
It wouldn't surprise me at all that "more modern" compression techniques work better on larger files. It also wouldn't surprise me too much if there was no such thing as a 1GB file when bzip was originally written, according to Wikipedia bzip2 is almost 30 years old "Initial releases 18 July 1996". And there are mentions of the preceding bzip (without the 2) which must have been even earlier than that. In the mid/late 90s I was flying round the world trips with a dozen or so 380 or 500MB hard drives in my luggage to screw into our colo boxen in Singapore London and San Francisco (because out office only has 56k adsl internet).
For instance, "lrzip -b", which uses bzip2 for compression, typically achieves much higher compression ratios on big files than using either xz or zstd alone. Of course, you can also use lrzip with xz or zstd, with various parameters, but among the many existing possibilities you must find an optimum compromise between compression ratio and compression/decompression times.
I compressed kernel 6.19.8 with zstd -19 --long and bzip3 (default settings). The latter compressed better and was about 8x faster.
It was long surpassed by lzma and zstd.
But back in roughly the 00s, it was the best standard for compression, because the competition was DEFLATE/gzip.
Consider "bananarama":
"abananaram"
"amabananar"
"ananaramab"
"anaramaban"
"aramabanan"
"bananarama"
"mabananara"
"nanaramaba"
"naramabana"
"ramabanana"
But, due to sorting, contexts are not contiguous for the (last) character predicted and long dependencies are broken. Because of broken long dependencies, it is why MTF, which implicitly transforms direct symbols statistics into something like Zipfian [1] statistics, does encode BWT's output well.
[1] https://en.wikipedia.org/wiki/Zipf%27s_law
Given that, author may find PPM*-based compressors to be more compression-wise performant. Large Text Compression Benchmark [2] tells us exactly that: some "durilka-bububu" compressor that uses PPM fares better than BWT, almost by third.
Also making good progress on getting a slimmer version of zstd into the stdlib and improving the stdlib deflate.
Awesome! Please let me know if there is anything I can do to help
I tried looking it up myself but it doesn't say in the readme or doc/ folder, there is no mention of any of the Bzip2 authors, and there is no website listed so I presume this Github page is canonical
Also, the name is the algorithm. Bzip2 has versions and bzip3 is something else which has its own updated versions. Programs that implement a single algorithm often follow this pattern.
https://man.archlinux.org/man/pbzip2.1.en
And zstd is multi threaded from the beginning.
This depends on the setting. At setting -19 (not even using --long or other tuning), Zstd is 10x slower to compress than bzip2, and 20x slower than xz, and it still gets a worse compression ratio for anything that vaguely looks like text!
But I agree if you look at the decompression side of things. Bzip2 and xz are just no competition for zstd or the gzip family (but then gzip and friends have worse ratios again, so we're left with zstd). Overall I agree with your point ("just use zstd") but not for the fast compression speed, if you care somewhat about ratios at least
In my own testing of compressing internal generic json blobs, I found brotli a clear winner when comparing space and time.
If I want higher compatibility and fast speeds, I'd probably just reach for gzip.
zstd is good for many use cases, too, perhaps even most...but I think just telling everyone to always use it isn't necessarily the best advice.
It’s slower and compresses less than zstd. gzip should only be reached for as a compatibility option, that’s the only place it wins, it’s everywhere.
EDIT: If you must use it, use the modern implementation, https://www.zlib.net/pigz/
size and decompression are the main limitations
Consider that you could hand-code an algorithm to recognize cats in images but we would rather let the machine just figure it out for itself. We're kind of averse to manual work and complexity where we can brute force or heuristic our way out of the problem. For the 80% of situations where piping it into zstd gets you to stay within budget (bandwidth, storage, cpu time, whatever your constraint is), it's not really worth doing about 5000% more effort to squeeze out thrice the speed and a third less size
It really is considerably better, but I wonder how many people will do it, which means less implicit marketing by seeing it everywhere like we do the other tools, which means even fewer people will know to do it, etc.
Does gmail use a special codec for storing emails ?
Yes, there are better compression options today.
I suggest implementing Scott's Bijective Burrows-Wheeler variant on bits rather than bytes, and do bijective run-length encoding of the resulting string. It's not exactly on the "pareto frontier", but it's fun!
I ran a bunch of benchmarks, and found that the only thing that mattered was if a particular tool or format supported parallel compression and/or parallel decompression. Nothing else was even close as a relevant factor.
If you're developing software for processing even potentially large files and you're using a format that is inherently serial, you've made a mistake. You're wasting 99.5% of a modern server's capacity, and soon that'll be 99.9%.
It really, really doesn't matter if one format is 5% faster or 5% bigger or whatever if you're throwing away a factor of 200 to 1,000 speedup that could be achieved through parallelism! Or conversely, the ability to throw up to 1,000x the compute at improving the compression ratio in the available wall clock time.
Checksumming, compression, decompression, encryption, and decryption over bulk data must all switch to fully parallel codecs, now. Not next year, next decade, or the year after we have 1,000+ core virtual machines in the cloud available on a whim. Oh wait, we do already: https://learn.microsoft.com/en-us/azure/virtual-machines/siz...
Not to mention: 200-400 Gbps NICs are standard now in all HPC VMs and starting to become commonplace in ordinary "database optimised" cloud virtual machines. Similarly, local and remote SSD-backed volumes that can read and write at speeds north of 10 GB/s.
There are very few (any?) compression algorithms that can keep up with a single TCP/IP stream on a data centre NIC or single file read from a modern SSD unless using parallelism. Similarly, most CPUs struggle to perform even just SHA or AES at those speeds on a single core.