We explain three random sampling techniques
that are simple but widely applicable
for various problems involving huge data sets.
The first technique is
an immediate application of large deviation bounds.
The second and the third ones are
sequential sampling or adaptive sampling techniques.
We fix one simple problem
and explain these techniques
by demonstrating algorithms for this problem
and discussing their correctness and efficiency.