`O(log N)`

basically means time goes up linearly while the `n`

goes up exponentially. So if it takes `1`

second to compute `10`

elements, it will take `2`

seconds to compute `100`

elements, `3`

seconds to compute `1000`

elements, and so on.

It is `O(log n)`

when we do divide and conquer type of algorithms e.g binary search. Another example is quick sort where each time we divide the array into two parts and each time it takes `O(N)`

time to find a pivot element. Hence it `N O(log N)`