Clojure math functions compile down to the same JVM 'instruction' as from
java. See http://galdolber.tumblr.com/post/77153377251/clojure-intrinsics
On Sat, Mar 1, 2014 at 1:23 PM, dennis zhuang <killme2...@gmail.com> wrote:
> I think the remaining overhead of clojure sample code is that operators in
> java such as '++' and '<" etc.They are just an instrument of JVM -- iinc
> and if_icmpge. But they are both functions in clojure,and they will be
> called by invokevirtual instrument.It cost much more performance.
>
>
>
>
> 2014-03-01 20:07 GMT+08:00 dennis zhuang <killme2...@gmail.com>:
>
> I forgot to note hat i test the java sample and clojure sample code with
>> the same jvm options '-server'.
>>
>>
>>
>> 2014-03-01 20:03 GMT+08:00 dennis zhuang <killme2...@gmail.com>:
>>
>> The "String a=i+"another word";" is also compiled into using
>>> StringBuilder, see the byte code by javap -v:
>>>
>>> Code:
>>> stack=5, locals=5, args_size=1
>>> 0: invokestatic #2 // Method
>>> java/lang/System.nanoTime:()J
>>> 3: lstore_1
>>> 4: iconst_0
>>> 5: istore_3
>>> 6: iload_3
>>> 7: ldc #3 // int 10000000
>>> 9: if_icmpge 39
>>> 12: new #4 // class
>>> java/lang/StringBuilder
>>> 15: dup
>>> 16: invokespecial #5 // Method
>>> java/lang/StringBuilder."<init>":()V
>>> 19: iload_3
>>> 20: invokevirtual #6 // Method
>>> java/lang/StringBuilder.append:(I)Ljava/lang/StringBuilder;
>>> 23: ldc #7 // String another word
>>> 25: invokevirtual #8 // Method
>>> java/lang/StringBuilder.append:(Ljava/lang/String;)Ljava/lang/StringBuilder;
>>> 28: invokevirtual #9 // Method
>>> java/lang/StringBuilder.toString:()Ljava/lang/String;
>>> 31: astore 4
>>> 33: iinc 3, 1
>>> 36: goto 6
>>> 39: getstatic #10 // Field
>>> java/lang/System.out:Ljava/io/PrintStream;
>>> 42: invokestatic #2 // Method
>>> java/lang/System.nanoTime:()J
>>> 45: lload_1
>>> 46: lsub
>>> 47: l2d
>>> 48: ldc2_w #11 // double 1.0E9d
>>> 51: ddiv
>>> 52: invokevirtual #13 // Method
>>> java/io/PrintStream.println:(D)V
>>>
>>>
>>> I think the performance hotspot in this simple example is the object
>>> allocate/gc and function calling overhead.The str function create
>>> an anonymous function every time to concat argument strings:
>>>
>>> (^String [x & ys]
>>> ((fn [^StringBuilder sb more]
>>> (if more
>>> (recur (. sb (append (str (first more)))) (next more))
>>> (str sb)))
>>> (new StringBuilder (str x)) ys)))
>>>
>>> And we all know that a function in clojure is a java object allocated in
>>> heap.And another overhead is calling the function,it's virtual method.
>>>
>>> By watching the gc statistics using 'jstat -gcutil <pid> 2000', i found
>>> that the clojure sample ran about 670 minor gc,but the java sample is only
>>> 120 minor gc.
>>>
>>> A improved clojure version,it's performance is closed to java sample:
>>>
>>> user=> (time (dotimes [n 10000000] (-> (StringBuilder.) (.append n)
>>> (.append "another word") (.toString))))
>>> "Elapsed time: 1009.942 msecs"
>>>
>>>
>>>
>>>
>>> 2014-03-01 18:02 GMT+08:00 bob <wee....@gmail.com>:
>>>
>>> Case :
>>>>
>>>> clojure verison:
>>>>
>>>> (time (dotimes [n 10000000] (str n "another word"))) ;; take about
>>>> 5000msec
>>>>
>>>> java version
>>>>
>>>> long time = System.nanoTime();
>>>>
>>>> for(int i=0 ; i<10000000 ;i++){
>>>> String a=i+"another word";
>>>> }
>>>> System.out.println(System.nanoTime()-time);
>>>>
>>>>
>>>> The java version take about 500 msecs, I thought it might be caused by
>>>> the str implementation which is using string builder, and it might not be
>>>> the best choice in the case of no much string to concat, and then I replace
>>>> "another word" with 5 long strings as the parameter, however no surprise.
>>>>
>>>> I just wonder what make the difference, or how to find the difference.
>>>>
>>>> Thanks
>>>>
>>>>
>>>>
>>>> On Saturday, March 1, 2014 1:26:38 PM UTC+8, Shantanu Kumar wrote:
>>>>>
>>>>> I have seen (and I keep seeing) a ton of Java code that performs
>>>>> poorly. Empirically, it's equally easy to write a slow Java app. You
>>>>> always
>>>>> need a discerning programmer to get good performance from any
>>>>> language/tool.
>>>>>
>>>>> Numbers like 1/4 or 1/10 can be better discussed in presence of the
>>>>> use-cases and perf test cases. Most of the problems you listed can be
>>>>> mitigated by `-server` JIT, avoiding reflection, transients, loop-recur,
>>>>> arrays, perf libraries and some Java code.
>>>>>
>>>>> Shantanu
>>>>>
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>>>
>>>
>>>
>>> --
>>> 庄晓丹
>>> Email: killme2...@gmail.com xzhu...@avos.com
>>> Site: http://fnil.net
>>> Twitter: @killme2008
>>>
>>>
>>>
>>
>>
>> --
>> 庄晓丹
>> Email: killme2...@gmail.com xzhu...@avos.com
>> Site: http://fnil.net
>> Twitter: @killme2008
>>
>>
>>
>
>
> --
> 庄晓丹
> Email: killme2...@gmail.com xzhu...@avos.com
> Site: http://fnil.net
> Twitter: @killme2008
>
>
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