Mastering Large Datasets with Python

Part 1.

Part 1 explores the map and reduce style of computing. We’ll introduce map and reduce, as well as the helper and convenience functions that you’ll need to get the most out of this style. In this section, we’ll also cover the basics of parallel computing. The tools and techniques in this part are useful for large data in categories 1 and 2: tasks that are both storable and computable locally, and tasks that are not storable locally but are still computable locally.