This work studies centralized slow-timescale spectrum management in metropolitan area networks with a very large number of access points (APs) and user equipments (UEs). The joint spectrum allocation and user association problem is first formulated as a convex optimization problem with an exponential number of variables in the network size. A scalable reformulation is obtained by exploiting the geometric graph nature of the network and provable sparsity of the optimal solution. A pattern pursuit algorithm with low complexity is proposed to solve the reformulated problem with guaranteed gap to the global optimum. Efficient algorithms are developed to obtain near-optimal allocations for a network with up to 1000 APs and 2500 active users. Numerical results show that the proposed solution achieves significant gains in terms of delay and throughput over existing schemes and is within 7% to the global optimum in a typical scenario.