SpatialHadoop is a Hadoop framework supporting spatial information handling in light of MapReduce programming worldview. A huge number of studies leads to that SpatialHadoop outperforms the traditional Hadoop in both overseeing and handling spatial data operations. Indexing at SpatialHadoop makes it better than Hadoop. However, the design of a proficient and powerful indexing technique is stay as  a major challenge. This paper presents a novel partitioning technique in SpatialHadoop. It has a better performance compared to other partitioning techniques. The proposed technique performance has been studied in several cases utilizing a real datasets on a spatial range and k-Nearest-Neighbour (kNN) queries. The experimental results have demonstrated the efficiency of the proposed technique.