How to transform large set of audio samples using FFT?
Can I transform the whole signal at once ?


Yes, this would be a 2400000 points FFT - something that is easy for a modern desktop computer (note that the sample rate is measured in Hz or samples/sec, not in Hz/s).


  If I cannot, is there away to combine the spectrum of different N sized segments?


Averaging the spectrum obtained on successive short windows is a common spectral estimation technique - but I'm not sure this is really what you need here.


  Is it reasonable to study the spectrum of a whole large signal at once ?


It makes sense if the signal is stationary. I can think of some applications in which this would be the case (for example you record 5 min of continuous hum/noise generated by a machine), but this would be an exception more than a rule - and I can't think of a practical reason why one would have to perform a FFT on such a large chunk of signal.

For signals whose characteristics change with time - such as speech or music - spectral analysis is more commonly performed on short segments. It all depends on what you want to do with the result of the FFT. If it is to extract a property of the signal (such as its pitch, or a metric like spectral centroid), make sure it is reasonable to assume that the property you want to extract is constant over the duration of the signal. If not, break down the signal into short segments during which this property can be considered constant.