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.