title: O(n log n) vs O(n) -- practical differences in time complexity
body: <p><code>n log n &gt; n</code> -- but this is like a <code>pseudo-linear</code> relationship. If <code>n=1 billion</code>, log n ~ 30;</p>
  
  <p>So <code>n log n</code> will be <code>30 billion</code>, which is <code>30 X n</code>, order of <code>n</code>.
  I am wondering if this time complexity difference between <code>n log n and n</code> are significant in real life.</p>
  
  <p>Eg: A <code>quick select</code> on finding kth element in an unsorted array is <code>O(n)</code> using quickselect algorithm.</p>
  
  <p>If I sort the array and find the kth element, it is <code>O(n log n)</code>. To sort an array with <code>1 trillion</code> elements, I will be <code>60 times</code> slower if I do <code>quicksort</code> and <code>index it</code>. </p>