A new method is presented for distributing data in sparse matrix-vector multiplication by selected contraction functions. And the contraction functions are selected. The quality and the complexity of this method are theoretically ensured not to worse than those of traditional one-dimensional partitioning methods. Experimental results show that this method often produces better results than one-dimensional methods and is competitive with the best two-dimensional methods.