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HackerThemAll • today at 3:25 PM • 2 replies • view on HN

I think this was the main reason (from the linked article) LOL:

"Brotli is a compression algorithm developed by Google."

They have no idea about Zstandard nor ANS/FSE comparing it with LZ77.

Sheer incompetence.

Replies

cortesoft • today at 6:39 PM

I can’t imagine the people actually doing the technical work don’t know about Zstandard.

mort96 • today at 5:12 PM

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 just took all PDFs I had in my downloads folder (55, totaling 47M). These are invoices, data sheets, employment contracts, schematics, research reports, a bunch of random stuff really.

I compressed them all with 'zstd --ultra -22', 'brotli -9', 'xz -9' and 'gzip -9'. Here are the results:

    +------+------+-----+------+--------+
    | none | zstd | xz  | gzip | brotli |
    +------|------|-----|------|--------|
    | 47M  | 45M  | 39M | 38M  | 37M    |
    +------+------+-----+------+--------+
Here's a table with all the files:

    +------+------+------+------+--------+
    | raw  | zstd | xz   | gzip | brotli |
    +------+------+------+------+--------+
    | 12K  | 12K  | 12K  | 12K  | 12K    |
    | 20K  | 20K  | 20K  | 20K  | 20K    | x5
    | 24K  | 20K  | 20K  | 20K  | 20K    | x5
    | 28K  | 24K  | 24K  | 24K  | 24K    |
    | 28K  | 24K  | 24K  | 24K  | 24K    |
    | 32K  | 20K  | 20K  | 20K  | 20K    | x3
    | 32K  | 24K  | 24K  | 24K  | 24K    |
    | 40K  | 32K  | 32K  | 32K  | 32K    |
    | 44K  | 40K  | 40K  | 40K  | 40K    |
    | 44K  | 40K  | 40K  | 40K  | 40K    |
    | 48K  | 36K  | 36K  | 36K  | 36K    |
    | 48K  | 48K  | 48K  | 48K  | 48K    |
    | 76K  | 128K | 72K  | 72K  | 72K    |
    | 84K  | 140K | 84K  | 80K  | 80K    | x7
    | 88K  | 136K | 76K  | 76K  | 76K    |
    | 124K | 152K | 88K  | 92K  | 92K    |
    | 124K | 152K | 92K  | 96K  | 92K    |
    | 140K | 160K | 100K | 100K | 100K   |
    | 152K | 188K | 128K | 128K | 132K   |
    | 188K | 192K | 184K | 184K | 184K   |
    | 264K | 256K | 240K | 244K | 240K   |
    | 320K | 256K | 228K | 232K | 228K   |
    | 440K | 448K | 408K | 408K | 408K   |
    | 448K | 448K | 432K | 432K | 432K   |
    | 516K | 384K | 376K | 384K | 376K   |
    | 992K | 320K | 260K | 296K | 280K   |
    | 1.0M | 2.0M | 1.0M | 1.0M | 1.0M   |
    | 1.1M | 192K | 192K | 228K | 200K   |
    | 1.1M | 2.0M | 1.1M | 1.1M | 1.1M   |
    | 1.2M | 1.1M | 1.0M | 1.0M | 1.0M   |
    | 1.3M | 2.0M | 1.1M | 1.1M | 1.1M   |
    | 1.7M | 2.0M | 1.7M | 1.7M | 1.7M   |
    | 1.9M | 960K | 896K | 952K | 916K   |
    | 2.9M | 2.0M | 1.3M | 1.4M | 1.4M   |
    | 3.2M | 4.0M | 3.1M | 3.1M | 3.0M   |
    | 3.7M | 4.0M | 3.5M | 3.5M | 3.5M   |
    | 6.4M | 4.0M | 4.1M | 3.7M | 3.5M   |
    | 6.4M | 6.0M | 6.1M | 5.8M | 5.7M   |
    | 9.7M | 10M  | 10M  | 9.5M | 9.4M   |
    +------+------+------+------+--------+
Zstd is surprisingly bad on this data set. I'm guessing it struggles with the already-compressed image data in some of these PDFs.

Going by only compression ratio, brotli is clearly better than the rest here and zstd is the worst. You'd have to find some other reason (maybe decompression speed, maybe spec complexity, or maybe you just trust Facebook more than Google) to choose zstd over brotli, going by my results.

I wish I could share the data set for reproducibility, but I obviously can't just share every PDF I happened to have laying around in my downloads folder :p

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