An Improved Index Based on MapReduce for Path Queries in Public Transportation Networks

In this paper, we consider the path queries in public transportation networks which are widely used in path planning and location-based services. In general, path index is often adopted to speed up the path queries in public transportation networks. However, the pre-processing for building path index for the existing best-known query algorithms is often not efficient. Aimed at this shortcoming, we propose an improved index, which is based on MapReduce for path queries. Specifically, the proposed algorithm includes the map and reduce phases. In map phase, the public transportation network is divided into different subgraphs and generate key-value pairs of index for subgraphs. In reduce phase, the result of map function are aggregated by subgraphs' key-value pairs to obtain the index. The experimental results based on the real datasets show the effectiveness of the proposed algorithms.