On Sat, Sep 26, 2015 at 3:04 PM, Vijay Lulla <[email protected]> wrote:
> quite easy.  But what I'm very unclear about is how does one do
> pipelining in J?  Say we have functions f, g, and h (all used
> monadically) and it is applied like f@g@h y and function g was
> particularly costly how can we parallelize (maybe the user has to
> program it himself or the interpreter can do some cost analysis [like
> query planning in SQL databases]) it to make it faster?  Isn't this
> what the presenters were mentioning when they were using the example
> of airbus pipeline system?

"Pipelining" seems to describe a variety of topics.

https://en.wikipedia.org/wiki/Pipeline_(computing)

So, I would have to say that there is no general technique. If f, g
and h are black boxes, you cannot pipeline them. If you want to
reschedule g or make it more efficient, you'll need to know details
about g. The more you know, the greater the odds are that you can do
it (or the important parts of it) differently, in a more efficient
manner.

That said, I should also point out that a lot of the automated query
planning systems are workarounds for bogus constraints underlying the
sql standard. That effort could have gone in much more useful
directions if people hadn't bought into those ideas. (But at this
point, it has turned into a multi-billion dollar industry, so it's not
going away. And there are some applications where the flaws are not
all that important.)

Thanks,

-- 
Raul
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