I was clustering around 40000 points using kmean algorithm. In the first version of the program I wrote the euclidean distance function like this

var euclideanDistance = function( p1, p2 ) { // p1.length === p2.length == 3

    var sum = 0;

    for( var i in p1 ){

        sum += Math.pow( p1[i] - p2[i], 2 );

    }

    return Math.sqrt( sum );

};

The overall program was quite slow taking on average 7sec to execute. After some profiling I rewrote the above function like this

var euclideanDistance = function( p1, p2 ) { // p1.length === p2.length == 3

    var sum = 0;

    for( var i = 0; i < p1.length; i++ ) {

        sum += Math.pow( p1[i] - p2[i], 2 );

    }

    return Math.sqrt( sum );

};

Now the programs on average take around 400ms. That's a huge time difference just because of the way I wrote the for loop. I normally don't use for..in loop for arrays but for some reason I used it while writing this function.

Can someone explain why there is this huge difference in performance between these 2 styles?