On 08/03/2008, at 11:20 AM, Chris Foote wrote:
>> - Dynamic languages suck for scaling up to real projects, even though
>> they're great for small scale RAD exploring.
>
> It depends what you mean by scaling.
I have to apologise for taking too much of your time with a small pot-
stir aimed at maintaining my "demon spawn" reputation with Daryl.
> database update constraints - 10M number ranges, < 0.2s response
> time to
> DNS queries regardless of load, and needed to withstand DOS attacks
> (two
> On the other hand, if what you mean by scalability is that a language
> provides a good environment for >1M lines of code across >50
> developers,
There is a third type of scaling, which is having one program running
on multiple CPUs and across clusters of machines. Google's "map-
reduce" is a one off "request-response" implementation of this, but
it is possible to scale up from this to more general programming.
For example, Erlang is nearly parallelisable by default, and
functional programming languages are automatically parallelisable
except in the case where they have unclean side-effects.
Consider this sample:
http://programming.nu/benwanu
The same technique can be used in Ruby and Python and Perl, but they
would need bridges to the C code that performs the speed-critical
section of Mandelbrot calculations. Because Nu is directly built on
the underlying framework rather than bridging across, this is the
actual code:
http://code.neontology.com/gitweb.cgi?p=Nu.git;a=blob;f=examples/
Benwanu/objc/
Benwanu.m;h=fdd0ebf5c6b9a224b5324c161b58bc7bbd21802b;hb=HEAD
Not one bit of bridging to be seen. Nu calls the function directly,
via Objective C's runtime. Any time any bit of Nu code is a bit too
slow or needs something at a lower level, it can be directly dropped
down a level without changing anything else.
This is in contrast to Ruby's C bridge, which effectively ruled out
that option for me.
http://www.onlamp.com/pub/a/onlamp/2004/11/18/extending_ruby.html
No thanks, that's just ridiculous.
> There are some good horizontal-scaling web systems written in Python.
> They easily scale for an ordinary "company web site". Even a large
I agree with what you are saying for these systems, but these are web
type workloads... a request comes in, the result is computed, and
sent back. It's all "wham bam, thank you ma'am". I want to do
computer vision algorithms, simulated annealing and run lenses
distortion calculations over 100MB image files.
While C is fast enough, and Objective C is simple enough, I'm still
lurking around dynamic languages because I want to type something and
have a response (I'm the wham-bam!), without that thinking destroyer,
the concentration disrupter, that awful edit-compile-run cycle.
> (list includes Akamai, Novell, Oxfam and many others for their primary
> web sites).
They are all web sites. They don't run large compute jobs on massive
amounts of data using grids and clusters of machines.
Steve.
--
[EMAIL PROTECTED]
_______________________________________________
sapug mailing list
[email protected]
http://mail.python.org/mailman/listinfo/sapug
