If you are using same algorithm then 2x difference Java vs JS is not 
something surprising, I would expect this.

How do you compute top 10? With built-in Array.search + slice(0,10) I get 
~2500ms and if I use binary heap tree ( 
https://github.com/tjfontaine/node-binaryheap ) (push every element and pop 
if tree length > 10) running time is down to 950ms

Also, try to benchmark your code after multiple runs as first run might use 
non-optimised code
 
On Sunday, 3 August 2014 05:34:26 UTC+10, Juan Sebastian wrote:
>
> Hi All
>
> I'm Coding some trees in NodeJS
> and after creating 1,000,000 elements and looping to get the top10 
> elements 
> the process ends with these stats:
>
> TOP 10 Products by ID:
> { Id: 31229, numSold: 99999741 }
> { Id: 724109, numSold: 99999702 }
> { Id: 228470, numSold: 99999663 }
> { Id: 252501, numSold: 99999630 }
> { Id: 764570, numSold: 99999462 }
> { Id: 525615, numSold: 99999414 }
> { Id: 789503, numSold: 99999379 }
> { Id: 428851, numSold: 99999260 }
> { Id: 533397, numSold: 99999244 }
> { Id: 202426, numSold: 99999146 }
> Max Quantity Item : id: 31229 Quantity: 99,999,741
> Min Quantity Item: id: 691832  Quantity: 76
> Process: 4547ms
>
> is there any way to improve the performance from the V8 side?
>
> I've tried the following line but makes no significant difference
> ./node --max_executable_size=3048 --stack_size=102400 test.js
> ./node --max_old_space_size=3048 --stack_size=102400 test.js
>
> I coded the same in Java and
> by modifying the arguments to the JVM (increase the memory)
> JRE Arguments -> -Xms1024m -Xmx2048m
> the performance was significant faster: for 1,000,000 elements-> Time: 
> 1730 ms
>
> Any advice/trick will be welcomed
>
> Best Regards
>
> Juan S.
>

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