Current data plane verification (DPV) tools employ a centralized architecture, where a server collects the data planes of all devices and verifies them. This architecture is inherently unscalable (i.e., requiring a reliable management network, incurring a long control path and making the server a single point of failure). In this paper, we tackle this scalability challenge of DPV from an architectural perspective. In particular, we circumvent the scalability bottleneck of centralized design and advocate for a distributed, on-device DPV framework. Our key insight is that DPV can be transformed into a counting problem on DAG, which can be naturally decomposed into lightweight tasks executed at network devices, enabling scalability. Evaluation shows that a prototype of this framework achieves scalable DPV under various settings, with little overhead on commodity network devices.