There usually are many attributes, called small-range attributes, with small number of different values in massive relations. The number of combination values of these attributes is also very few in massive relations so that there are a lot of repeated combination values of these attributes in massive relations. It is important to remove the repeated combination values to improve the efficiency of storing and querying massive relations. A compression method for removing the repeated combination values is proposed in this paper. To compress a massive relation, the method partitions the relation into two small relations: one consists of the small-range attributes and the other consists of the rest attributes. The key problem is to identify the small-range attributes. The NP-hardness of this problem is proved, and two approximate algorithms are proposed to solve this problem. The compression algorithms and the query processing based on the compressed method are also discussed. Experimental results show that the compression method has high compression ratio and enhances the query processing performance.