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Comment by dist-epoch | Hacker News Reader

You need to crank up zstd compression level.

zstd is Pareto better than brotli - compresses better and faster

I thought the same, so I ran brotli and zstd on some PDFs I had laying around.

  brotli 1.0.7 args: -q 11 -w 24
  zstd v1.5.0  args: --ultra -22 --long=31 
                 | Original | zstd    | brotli
  RandomBook.pdf | 15M      | 4.6M    | 4.5M
  Invoice.pdf    | 19.3K    | 16.3K   | 16.1K

I made a table because I wanted to test more files, but almost all PDFs I downloaded/had stored locally were already compressed and I couldn't quickly find a way to decompress them.

Brotli seemed to have a very slight edge over zstd, even on the larger pdf, which I did not expect.

Whats the assumption we can potentially target as reason for the counter-intuitive result?

that data in pdf files are noisy and zstd should perform better on noisy files?

What's counter-intuitive about this outcome?

maybe that was too strongly worded but there was an expectation for zstd to outperform. So the fact it didnt means the result was unexpected. i generally find it helpful to understand why something performs better than expected.

Isn't zstd primarily designed to provide decent compression ratios at amazing speeds? The reason it's exciting is mainly that you can add compression to places where it didn't necessarily make sense before because it's almost free in terms of CPU and memory consumption. I don't think it has ever had a stated goal of beating compression ratio focused algorithms like brotli on compression ratio.

I actually thought zstd was supposed to be better than Brotli in most cases, but a bit of searching reveals you're right... Brotli, especially at the highest compression levels (10/11), often exceeds zstd at the highest compression levels (20-22). Both are very slow at those levels, although perfectly suitable for "compress once, decompress many" applications which the PDF spec is obviously one of them.

EDIT: Something weird is going on here. When compressing zstd in parallel it produces the garbage results seen here, but when compressing on a single core, it produces result competitive with Brotli (37M). See: https://news.ycombinator.com/item?id=46723158

I did my own testing where Brotli also ended up better than ZSTD: https://news.ycombinator.com/item?id=46722044

Results by compression type across 55 PDFs:

    +------+------+-----+------+--------+
    | none | zstd | xz  | gzip | brotli |
    +------|------|-----|------|--------|
    | 47M  | 45M  | 39M | 38M  | 37M    |
    +------+------+-----+------+--------+

Turns out that these numbers are caused by APFS weirdness. I used 'du' to get them which reports the size on disk, which is weirdly bloated for some reason when compressing in parallel. I should've used 'du -A', which reports the apparent size.

Here's a table with the correct sizes, reported by 'du -A' (which shows the apparent size):

    +---------+---------+--------+--------+--------+
    |  none   |  zstd   |   xz   |  gzip  | brotli |
    +---------|---------|--------|--------|--------|
    | 47.81M  | 37.92M  | 37.96M | 38.80M | 37.06M |
    +---------+---------+--------+--------+--------+

These numbers are much more impressive. Still, Brotli has a slight edge.

Worth considering the compress/decompress overhead, which is also lower in brotli than zstd from my understanding.

Also, worth testing zopfli since it's decompression is gzip compatible.

> I couldn't quickly find a way to decompress them

    pdftk in.pdf output out.pdf decompress

Does your source .pdf material have FlateDecode'd chunks or did you fully uncompress it?

I wasn't sure. I just went in with the (probably faulty) assumption that if it compresses to less than 90% of the original size that it had enough "non-randomness" to compare compression performance.

Ran the tests again with some more files, this time decompressing the pdf in advance. I picked some widely available PDFs to make the experiment reproducable.

  file            | raw         | zstd       (%)      | brotli     (%)     |
  gawk.pdf        | 8.068.092   | 1.437.529  (17.8%)  | 1.376.106  (17.1%) |
  shannon.pdf     | 335.009     | 68.739     (20.5%)  | 65.978     (19.6%) |
  attention.pdf   | 24.742.418  | 367.367    (1.4%)   | 362.578    (1.4%)  |
  learnopengl.pdf | 253.041.425 | 37.756.229 (14.9%)  | 35.223.532 (13.9%) |

For learnopengl.pdf I also tested the decompression performance, since it is such a large file, and got the following (less surprising) results using 'perf stat -r 5':

  zstd:   0.4532 +- 0.0216 seconds time elapsed  ( +-  4.77% )
  brotli: 0.7641 +- 0.0242 seconds time elapsed  ( +-  3.17% )

The conclusion seems to be consistent with what brotli's authors have said: brotli achieves slightly better compression, at the cost of a little over half the decompression speed.

Are you sure? Admittedly I only have 1 PDF in my homedir, but no combination of flags to zstd gets it to match the size of brotli's output on that particular file. Even zstd --long --ultra -22.

on max compression (11 vs zstd's 22) of text brotli will be around 3-4% denser... and a lot slower. Decompression wise zstd is over 2x faster.

The pdfs you have are already compressed with deflate (zip).

I love zstd but this isn't necessarily true.

Not with small files.

If that's about using predefined dictionaries, zstd can use them too.

If brotli has a different advantage on small source files, you have my curiosity.

If you're talking about max compression, zstd likely loses out there, the answer seems to vary based on the tests I look at, but it seems to be better across a very wide range.

No, it's literally just compressing small files without training zstd dict or plugging external dictionaries (not counting the built-in one that brotli has). Especially for English text, brotli at the same speed as zstd gives better results for small data (in kilobyte to a few of megabyte range).

> Pareto

I don’t think you’re using that correctly.

It's correct use of Pareto, short for Pareto frontier, if the claim being made is "for every needed compression ratio, zstd is faster; and for every needed time budget, zstd is faster". (Whether this claim is true is another matter.)

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