|Abstract:||Users and administrators of large-scale infrastructures (e.g., datacenters and PlanetLab) are frequently in need of monitoring groups of machines in the infrastructure. Though there exist several distributed querying systems for this monitoring purpose, they are not group-based; they mostly focus on querying the entire system. In this paper, we present Moara, a new querying system that makes two novel contributions. First, Moara builds aggregation trees for different groups and adaptively maintains the trees to optimize the total message cost. Second, Moara supports a query language allowing groups to be specified implicitly via predicates consisting of arbitrarily nested unions and intersections. Our evaluations on Emulab, on PlanetLab, and with large-scale simulations, demonstrate Moara's ability to answer complex queries within a fraction of a second, to deal with high levels of dynamism in groups, and to incur a low bandwidth overhead per host per query in comparison to existing centralized and distributed aggregation systems.