  Data analytics on edge devices has gained rapid growth in research, industry,
and different aspects of our daily life. This topic still faces many challenges
such as limited computation resource on edge devices. In this paper, we further
identify two main challenges: the composition and deployment of data analytics
services on edge devices. We present the Zoo system to address these two
challenge: on one hand, it provides simple and concise domain-specific language
to enable easy and and type-safe composition of different data analytics
services; on the other, it utilises multiple deployment backends, including
Docker container, JavaScript, and MirageOS, to accommodate the heterogeneous
edge deployment environment. We show the expressiveness of Zoo with a use case,
and thoroughly compare the performance of different deployment backends in
evaluation.
