Benchmarks like this are often considered red herrings by language
developers. Mostly because they are testing the wrong thing. In this case
you are basically testing the performance of big ints in Python to the
performance of big ints in Clojure (and Java). Since no one really ever
uses big integers in production (at least I've never encountered them in
the wild), they tend to be rather poorly optimized.

So the gist of the whole thing is....don't do micro-benchmarks.

Timothy

On Wed, Dec 31, 2014 at 5:19 PM, shintotomoe <tstei...@atlassian.com> wrote:

> My results with hotspot 1.7.0_51, clojure 1.7.0-alpha4 are 13s for python
> and 15s for clojure.
>
> I also tested the python version translated to clojure:
>
> (defn fib [n]
>   (loop [n n a 0N b 1N]
>     (if (zero? n) a (recur (dec n) b (+ a b)))))
>
> Which was also 15s! I think all the time in the clojure version is
> probably spent in the bignum implementation. It seems the lazy-seq does not
> add any discernible overhead at all (at least in this microbenchmark).
>
> user=> (time (rem (nth (lazy-seq-fibo) 1000000) 1000))
> "Elapsed time: 15349.57006 msecs"
> 875N
>
> user=> (time (rem (fib 1000000) 1000))
> "Elapsed time: 15170.386957 msecs"
> 875N
>
>
> $ time python fib.py
> 875
>
> real    0m12.802s
> user    0m12.733s
> sys     0m0.032s
>
> $ java -version
> java version "1.7.0_51"
> Java(TM) SE Runtime Environment (build 1.7.0_51-b13)
> Java HotSpot(TM) 64-Bit Server VM (build 24.51-b03, mixed mode)
>
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zero–they had no way to indicate successful termination of their C
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