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I found the codemonk series on J very entertaining as well: http://drj11.wordpress.com/category/j/ http://drj11.wordpress.com/category/j/ Does anyone on the bo

I found the codemonk series on J very entertaining as well: http://drj11.wordpress.com/category/j/ http://drj11.wordpress.com/category/j/ Does anyone on the board use J / K daily? What for?

tom_b 14y ago
I do not use J daily but would like to. I know that many finance firms use KDB+ and Q to manage stock tick data - this is where I first saw KDB+ in action, oddly enough I was pulling some non-tick data from a KDB+ system for a data warehouse project. I think that J is one of those languages that would really shine in allowing a hacker with a large amount of domain specific knowledge to do wonderful work with small amounts of code. So, if you are a stats hacker interested in applied modeling, maybe you could use J to very concisely build your models. Probably bioinformatics would work as well, I can see how fastq data would be easier to deal with if you just chunked it into a KDB+ backend. There are lots of folks on HN who seem interested in J or KDB+ (see the Kona open source project) who might have better answers than this . . .
crntaylor 14y ago
I used Q (the 'friendly' version of K) heavily in my previous job. It was in a high frequency team at an investment bank. All of our tick data was stored in kdb databases. I was in research at the time. You could load the data into whatever your research environment was (R or Matlab for most people) but it was much faster to boot up a Q session and work with everything in-memory, 'closer to the metal'. To that end I wrote * An order-book builder (which takes quote data and builds it into a data structure suitable for doing research). As I remember, it was one call to 'scan' with a very complicated scanning function. * An event analysis tool, to let you ask questions like "what's the average response of this asset when event X happens". Used for anything from testing your trading strategies (how does this asset perform when I put a trade on) to news impact (how does this asset react around US employment data). * Lots and lots of plotting functions. Q actually has some really nice in-built visualization tools (as long as you only want to visualize time series...) And a bunch of other stuff I've now forgotten about. It's a fun language. I miss it a bit now I do all my work in Matlab.

I found the codemonk series on J very entertaining as well: http://drj11.wordpress.com/category/j/ http://drj11.wordpress.com/category/j/ Does anyone on the board use J / K daily? What for?

tom_b 14y ago

I do not use J daily but would like to. I know that many finance firms use KDB+ and Q to manage stock tick data - this is where I first saw KDB+ in action, oddly enough I was pulling some non-tick data from a KDB+ system for a data warehouse project. I think that J is one of those languages that would really shine in allowing a hacker with a large amount of domain specific knowledge to do wonderful work with small amounts of code. So, if you are a stats hacker interested in applied modeling, maybe you could use J to very concisely build your models. Probably bioinformatics would work as well, I can see how fastq data would be easier to deal with if you just chunked it into a KDB+ backend. There are lots of folks on HN who seem interested in J or KDB+ (see the Kona open source project) who might have better answers than this . . .

crntaylor 14y ago

I used Q (the 'friendly' version of K) heavily in my previous job. It was in a high frequency team at an investment bank. All of our tick data was stored in kdb databases. I was in research at the time. You could load the data into whatever your research environment was (R or Matlab for most people) but it was much faster to boot up a Q session and work with everything in-memory, 'closer to the metal'. To that end I wrote * An order-book builder (which takes quote data and builds it into a data structure suitable for doing research). As I remember, it was one call to 'scan' with a very complicated scanning function. * An event analysis tool, to let you ask questions like "what's the average response of this asset when event X happens". Used for anything from testing your trading strategies (how does this asset perform when I put a trade on) to news impact (how does this asset react around US employment data). * Lots and lots of plotting functions. Q actually has some really nice in-built visualization tools (as long as you only want to visualize time series...) And a bunch of other stuff I've now forgotten about. It's a fun language. I miss it a bit now I do all my work in Matlab.