With the GPS mobile devices were widely used and the rapid development of wireless network communication technology. A large number of Moving-Object data that contains spatiotemporal attributes has appeared in our worldwide. However, it is always a hot research issue about how to efficiently store, manage, query, and analyze these massive but valuable spatiotemporal data.This paper proposes a distributed NoSQL index, DWPMIndex (Distributed Weighted Phase-point Moving Object Index) which is based on the Hadoop platform, a distributed infrastructure developed by Apache. DWPMIndex mainly provides data partitioning technology, global index, and local index. We adopted a data partition algorithm for moving objects based on the sampled road segment data which satisfied "balanced partition" and "local dispersion". Furthermore, we creatively design two indexing data structures, i.e., QMS-tree (Quad-tree based on Median point to Split) and WPM-tree (Weighted Phase-point Moving Object Tree), which accelerates global and local indexing tremendously. DWPMIndex can support plentiful queries efficiently, including Spatio-temporal range query, spatial range query, and trajectory query. Experimental results show the powerful query efficiency and scalability of DWPMIndex.