[Proclus]

It seems they're using the standard dictionary, which is utterly bizzare.

The standard Brotli dictionary bakes in a ton of assumptions about what the Web looked like in 2015, including not just which HTML tags were particularly common but also such things as which swear words were trendy.

It doesn't seem reasonable to think that PDFs have symbol probabilities remotely similar to the web corpus Google used to come up with that dictionary.

On top of that, it seems utterly daft to be baking that into a format which is expected to fit archival use cases and thus impose that 2015 dictionary on PDF readers for a century to come.

I too would strongly prefer that they use zstd.

[bhouston]

BTW I've looked into custom dictionaries before for similar use cases and I suspect it would only offer like a 1% improvement or so for PDFs -- still good, but not a massive difference maker. The issue is that PDFs, like web pages, are incredibly repetitive in terms of their tags/structure. As such the custom dictionary only helps if the doc is really small, otherwise because of the repetitive nature, the self-inferred dictionary will resemble the custom dictionary after just a few blocks of PDF content.

The sole exception is if they are restarting the brotli stream for each page, and they are not sharing a dictionary, custom or inferred across the whole doc. Then the dictionary will have to be re-inferred on each page, and then a shared custom dictionary would make more sense.