Given a massive data set and limited space, what can we learn from a single pass through the data? This talk will serve as an introduction to streaming algorithms for frequency moments in big data. I will present algorithms for problems such as counting the number of distinct elements in a data stream and finding high frequency elements.

The topics discussed in this talk are from Chapter 7.1 of the Hopcroft-Kannan book: http://www.cs.cornell.edu/jeh/book11April2014.pdf