|In Internet mapping, IP address space is divided into a set of client aggregation units, which are the finest-grained units for global load balancing. Choosing the proper level of aggregation is a complex and crucial problem, which determines the total number of aggregation units that a mapping system has to maintain and the accuracy of client redirection. In this paper, using Internet-wide measurements provided by a commercial global load balancing service provider, weshow that even for the best existing client aggregation, almost 17% of clients have latency more than 50 ms apart from the average latency of clients in the same aggregation unit. To address this, we propose a data-driven client aggregation, AP-atoms, which can tradeoff scalability for accuracy and adapts to changing network conditions. Our experimentsshow that by using the same scale of client aggregations, AP-atoms can reduce the number of widely dispered clients by almost 2 and the 98-th percentile difference in clients latencies by almost 100 ms.