Big-O notation is about identifying the term that grows the fastest.
It doesn’t matter if the constant out the front is huge, or tiny. Its a constant and does not change how quickly a term grows.
1/123456789 * N^3 + 123456789 * N^2 + 300000000000000000000 * N
In the smaller values of N the linear term is dominant. But it is quickly over taken by the N^2 term, and that term itself is overtaken by the N^3.
As N gets large the behaviour of the function always tends toward the quickest growing term. this is why the example is gave is O(N^3) even though for small values of N it behaves more quadratically on linearly. In your example its why its O(nlogn).