  Collecting and analyzing of network traffic data (network telemetry) plays a
critical role in managing modern networks. Network administrators analyze their
traffic to troubleshoot performance and reliability problems, and to detect and
block cyberattacks. However, conventional traffic-measurement techniques offer
limited visibility into network conditions and rely on offline analysis.
Fortunately, network devices such as switches and network interface cards, are
increasingly programmable at the packet level, enabling flexible analysis of
the traffic in place, as the packets fly by. However, to operate at high speed,
these devices have limited memory and computational resources, leading to
trade-offs between accuracy and overhead. In response, an exciting research
area emerged, bringing ideas from compact data structures and streaming
algorithms to bear on important networking telemetry applications and the
unique characteristics of high-speed network devices. In this paper, we review
the research on compact data structures for network telemetry and discuss
promising directions for future research.
