DROP: Facilitating distributed metadata management in EB-scale storage systems
Quanqing Xu, Rajesh Vellore Arumugam, Khai Leong Yang, Sridhar Mahadevan · 2013
Efficient and scalable distributed metadata management is critically important to overall system performance in large-scale distributed storage systems, especially in the EB era. Traditional state-of-the-art distributed metadata management schemes include hash-based mapping and subtree partitioning. The former evenly distributes workload among metadata servers, but it eliminates all hierarchical locality of metadata. It cannot efficiently handle some operations, e.g., renaming or moving a directory that requires metadata to be migrated among metadata servers. The latter does not uniformly distribute workload among metadata servers, and metadata need to be migrated to keep the load balanced roughly. In this paper, we present a ring-based metadata management scheme, called Dynamic Ring Online Partitioning (DROP). It can preserve metadata locality using locality-preserving hashing, as well as dynamically distribute metadata among metadata server cluster to keep load balancing. By conducting performance evaluation, experimental results demonstrate the effectiveness and scalability of DROP.