Comment by dmw_ng | Hacker News Reader

Comment by dmw_ng | Hacker News Reader

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Picture the effect of compression ratios or decompression performance improving 1% globally, or conversely, if planes were replaced with a Wright Brothers model or cars with the T1. When discussing Deflate it's not just 1%, but regularly 200% or 2,000%, nor is it something people use once per month, but practically every time they interact with digital electronics.

Regressing to the T1 is unthinkable because they're long out of fashion and widely perceived as obsolete. Every change starts with a shift in perception, a process accelerated by a shift in language. For that I'm content with "junk", it describes exactly how we must feel about this dead technology before we'll ever be rid of it.

I'll gladly reminisce once we've escaped its legacy, be it time wasted installing an Android app and the effect it has on the battery (multiplied by billions of users), the time to open an Excel document, power up some smart TVs, fetch an itemized AWS bill over a typical S.E. Asian Internet connection, or grep that bill at speeds appropriate for a state of the art laptop manufactured this side of the millennium. You expect me to pay respect to software that wastes the finite breaths of billions of real people every single day.

So, I wanted to check so I downloaded linux source tree and ran gzip and zstd.

    Uncompressed .tar:    1064376320
    .xz (downloaded file): 117637692 (88.9%)
    .gz:                   189299444 (82.2%)
    .gz (level 9):         186533230 (82.5%)
    .zst:                  178012638 (83.3%)
    .zst --ultra -22:      119676867 (88.8%)

So, even at maximum level, zstd is only about 6% better, or about 37% if you consider .gz as baseline, while being about 10x slower than gzip level 9. There are places where having a smaller compressed file is worth the cost of 10x execution time (and much higher memory usage), but serving web pages is almost certainly not one of them.

In other words, the reason gzip is still being widely used is simply because it's good enough for its use cases. It's less like the original T1, and more like complaining that people are still driving Toyota Camry 2011 when Toyota Camry 2021 is a so much better car.

For the pile of XML in front of me just now (originally arrived in a ZIP container aka deflate, part of a much larger set), it's 1.4gb decompressed, 44M gzipped/deflated (default settings), 31mb zstd (default), 5.379s to decompress with gzip, 0.560s to decompress with zstd. Just under an order of magnitude difference in the most frequent operation (decompression).

Admittedly compressors generally love XML, this is just one example -- 28% less time on download and 89% less wasted on file open. Multiply by a few tens to a few thousand occurrences per week for 7.6 billion people, and I really struggle to call that a Camry.

You're admittedly talking about a difference in compression rate of 13MB in a 1400MB package, and a 5s difference in writing a 1400MB file to disk.

Come on, let's be honest here: that's nitpicking.

Unless you are running batch processes that store TB of compressed data, no one would even bother to switch app for thosd residual gains.

Let's put it this way: would you get any VC fund if your sales pitch was "I can improve compression in a 1400MB package by 13MB and shorten file write times by 5 seconds"? Odds are, you'd be asked why not just gzip it and get it over with.

5.3s at 1.4gb on a laptop is 53ms at 14mb, is >70ms on mobile before adding any increased download time. 14mb is one retina image, even Reddit already weighs 8mb. It's silly to pretend this stuff doesn't matter, you can't even get search ranking without addressing it, for reasons that don't require concocted scenarios to explain.

Your difference might be mainly single threaded vs multi threaded decompression. This doesn't typically transform into a real-world speedup when browsing the web, as one will typically run multiple decompression streams in parallel anyway. Zstd is definitely an improvement on Gzip, but not by that much.

> 5.3s at 1.4gb on a laptop is 53ms at 14mb, is 70ms on mobile before adding any increased download time.

Factor in how much time it takes you to unpack those 1.4GB of data in a smartphone. Those 5s amount to which percentage of the total execution time?

> You're admittedly talking about a difference in compression rate of 13MB in a 1400MB package, and a 5s difference in writing a 1400MB file to disk.

> Come on, let's be honest here: that's nitpicking.

I agree on the compression size (13 megabytes is really not very much difference) but the decompression speed improvement really is remarkable. It's an order of magnitude of difference! Amortize that over every time you make a webrequest that has to decompress data, it makes a huge difference.

I'm mostly in the "gzip is good enough" camp, but a speed improvement of 10x is not nitpicking.

> Let's put it this way: would you get any VC fund if your sales pitch was "I can improve compression in a 1400MB package by 13MB and shorten file write times by 5 seconds"? Odds are, you'd be asked why not just gzip it and get it over with.

I agree but have a different takeaway: it’s why VCs aren’t the be all and end all. Such an improvement is worth the time invested to create it. It won’t change the world but spanned across the entire globe it’s a very notable step forward. That a VC can’t get hockey stick growth and a lucrative return out of it doesn’t invalidate the idea.

A quick note on compressing XML. XML files typically have a high compression ratio because they consist of mostly redundancy, but compressing redundancy isn't free, you still end up with some overhead in the compressed file due to the redundancy. So if you pack the same data in a denser format, and then compress that, you typically end up saving a good chunk of space relative to the compressed XML file.

The tradeoff you show between compression ratio and compression speed is a misleading one.

The slow compression speed only takes place once (when compressing), while the saved bandwidth due to a better compression ratio is saved continuously.

Not if you're serving things dynamically from a web server, then it happens on the fly, every request.

True. But there you can go into optimizations like parallelization of the compression and building an optimized dictionary upfront once to make the process faster.

Cache by the ETag and/or If-Modified-Since headers, then

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