Is there a way to do the reverse? There's a quite "legendary" Game Boy Advance game out there (Klonoa - Densetsu no Star Medal) that never got a translation to English because it has some sort of in-house created compression by Namco applied to the game that was made so it could fit into a GBA cartridge. AFAIK no one was ever able to crack it open and release the code to de/compress it. A while ago I had a "bounty" o…
Using machine learning to choose compression algorithms
31–40 of 60 posts
Re: Using machine learning to choose compression algorithms
#32Re: Using machine learning to choose compression algorithms
#33From the data shown it's not obvious that some of the options would ever be best, would be interesting to see if any of the non csv options ever beat the csv options and for what type of data.
Re: Using machine learning to choose compression algorithms
#34Isn't one of the benefits of time-series databases more compact storage at minimal overhead?
Does anyone know what is the leading time-series database people use today? Like, eg, bar / tick data. (I use PostgreSQL, due to my ignorance.)
Re: Using machine learning to choose compression algorithms
#35Is there a way to do the reverse? There's a quite "legendary" Game Boy Advance game out there (Klonoa - Densetsu no Star Medal) that never got a translation to English because it has some sort of in-house created compression by Namco applied to the game that was made so it could fit into a GBA cartridge. AFAIK no one was ever able to crack it open and release the code to de/compress it. A while ago I had a "bounty" o…
Re: Using machine learning to choose compression algorithms
#36From the data shown it's not obvious that some of the options would ever be best, would be interesting to see if any of the non csv options ever beat the csv options and for what type of data.
I can give you this... the larger the data the more useful parquet and compression on it will be...
Re: Using machine learning to choose compression algorithms
#37EDIT: You are missing `csv+zstd` ? It should obsolete `csv+gzip` at all speeds and compression levels.
There is a pareto-optimality frontier here - I ran my testing back in 2016 https://code.ivysaur.me/compression-performance-test/ but the numbers are now a little bit obsolete (e.g. zstd and brotli have both seen a lot of improvements).
Re: Using machine learning to choose compression algorithms
#38Earlier quoted context omitted.
Me too! A few months ago I made detailed notes on how to set up your own: https://github.com/shawwn/wiki Gwern was kind enough to assist by sending over the exact version numbers of all the Haskell libraries it depends on, and answering some questions about deployment. The version numbers turned out to be crucial to getting everything running. IMO https://www.gwern.net/ is the ideal combination of style + ease of use…
Yea, look at jekyll in combination with github pages. You can see my blog for example ( https://vks.ai ), the code is hosted here: https://github.com/kootenpv/kootenpv.github.io
Re: Using machine learning to choose compression algorithms
#39Re: Using machine learning to choose compression algorithms
#40Is there a way to do the reverse? There's a quite "legendary" Game Boy Advance game out there (Klonoa - Densetsu no Star Medal) that never got a translation to English because it has some sort of in-house created compression by Namco applied to the game that was made so it could fit into a GBA cartridge. AFAIK no one was ever able to crack it open and release the code to de/compress it. A while ago I had a "bounty" o…