Cloud computing usually provides dynamically scalable and virtualized computing resources through the Internet, and has widely been used in various fields, especially mass traffic processing. The MapReduce parallel programming model is a novel framework that supports the design of cloud computing algorithms, and can invoke clustered computers at different locations to conduct huge data processing. This study proposed a new computing logic on the base of MapReduce, and developed a parallel searching algorithm with subgraph partitions to search the shortest path in large-scale real traffic networks. In tests of the field networks, the proposed method can provide high-quality shortest path searching service within acceptable calculation time.