A batch\|parallel pyramid\|building algorithm based on the MapReduce framework is proposed.The formal description of the pyramid\|building task as well as the decomposition algorithm is given in the first place.Then, the details of the processing steps in the map and reduce phases are depicted. The experimental results show the feasibility, efficiency and scalability of the proposed approach. The tile pyramid building on massive remote\|sensing data, which is too complicated to be done on a commodity computer, can be efficiently accomplished on a server cluster. Furthermore, the proposed algorithm can be used as the basic framework for processing massive remote\|sensing images, and be applied to promote the efficiencies of some other remote\|sensing processing algorithms, e.g. the feature extraction, the image coaddition, the tile image delta,etc.