This paper studies the joint user association and resource allocation in heterogeneous networks (HetNets) from a novel perspective, motivated by and generating the idea of fractional frequency reuse. By treating the multi-cell multi-user resource allocation as resource partitioning among multiple reuse patterns, we propose a unified framework to analyze and compare a wide range of user association and resource allocation strategies for HetNets, and provide a benchmark of ultimate limit on network performance. The enabling mechanisms are a novel formulation to consider all possible patterns or any pre-defined subset of patterns and an efficient sparsity-pursuit algorithm. More importantly, in view of the fact that multi-cell resource allocation is very computational demanding, our framework provides a systematic way to trade off performance for the reduction of computational complexity by restricting the candidate patterns to a small number of feature patterns. Relying on the sparsity-pursuit capability of the proposed algorithm, we develop practical guideline to identify the feature patterns in the given HetNet. Our treatment is very general in that it covers the case where users are allowed to associate with multiple base stations and the more restrictive situation where the number of serving base stations for each user is limited to one or a given number. Numerical results show that the identified feature patterns can significantly improve the existing strategies, and jointly optimizing the user association and resource allocation indeed brings considerable gain.