This document introduces distributed computing and compares the architectures of high-performance computing (HPC) and big data systems. It discusses that distributed computing works by taking large jobs and breaking them into smaller parallel tasks, and provides examples of HPC systems that use head and compute nodes and big data systems that use name and data nodes. The document also notes some lessons learned, such as that hybrid HPC systems can be useless and bugs found late in processing large datasets can be difficult to diagnose.