I have some thin (read: incomplete) notes that hint at how math-oriented the J verbs are:
<a href="http://wycd.net/notes/jlang/jlang.pdf" rel="nofollow">http://wycd.net/notes/jlang/jlang.pdf</a><p>Among my favorite parts of the language is the sole set of vocabulary[0] that you have to learn to be proficient in J. It's daunting at first, but after this "alphabet" is internalized, you can understand most code. Just as our integral symbols save us from writing out "Integral()", J's operators are shorthand for fundamental computational functions. For example, here's a very naive kNN implementation in J, without pulling in any "jlearn" external libraries or anything:<p><a href="https://github.com/wyc/snippets/blob/master/j/knn.ijs" rel="nofollow">https://github.com/wyc/snippets/blob/master/j/knn.ijs</a><p>One of the stated purposes of J is the clear expression of algorithms. How are you supposed to clearly do that with layers upon layers of abstractions? The language excels at matrix and statistical operations on sets of homogeneous data. Many financial institutions deploy J's close sister, K (also a descendant of APL) coupled with KDB[1].<p>Does it have potential for use on "Big Data"? Maybe. It's not SMP, but the interpreter is rather light, so it can be spun up in multiple processes. Cutting up the data correctly is still a problem. I would also not use J to write a webapp; CRUD isn't its strong point.<p>Some more examples of J:
<a href="https://github.com/wyc/snippets/blob/master/j/jtalk/examples.txt" rel="nofollow">https://github.com/wyc/snippets/blob/master/j/jtalk/examples...</a><p>Come hang out at #jsoftware on freenode to find people much more knowledgeable than me. :P<p>[0] <a href="http://www.jsoftware.com/help/dictionary/vocabul.htm" rel="nofollow">http://www.jsoftware.com/help/dictionary/vocabul.htm</a><p>[1] not the kernel debugger, but the time-series K database: <a href="http://kx.com/kdb-plus.php" rel="nofollow">http://kx.com/kdb-plus.php</a>