Network management and monitoring are crucial topics in the network field, with the technologies used to achieve this being referred to as network measurement. In particular, network heavy hitter detection is an important technique of network measurement, and it is analyzed in this study. Heavy hitters are flows that exceed an established threshold in terms of occupied network resources (bandwidth or the number of packets transmitted). Detecting heavy hitters can contribute to quick anomaly detection and more efficient network operation. However, the implementation of heavy hitter detection is impacted by high-speed links. Traditional methods and software defined network (SDN)-based methods are two categories of heavy hitter detection methods that have been developed over time. This study reviews the related frameworks and algorithms, systematically summarizes the development and current status, and finally tries to predict future research directions of network heavy hitter detection.