Distributed range-based meta-data management for an in-memory storage

Abstract

Large-scale interactive applications and online graph processing require fast data access to billions of small data objects. DXRAM addresses this challenge by keeping all data always in RAM of potentially many nodes aggregated in a data center. Such storage clusters need a space-efficient and fast meta-data management. In this paper we propose a range-based meta-data management allowing fast node lookups while being space efficient by combining data object IDs in ranges. A super-peer overlay network is used to manage these ranges together with backup-node information allowing parallel and fast recovery of meta data and data of failed peers. Furthermore, the same concept can also be used for client-side caching. The measurement results show the benefits of the proposed concepts compared to other meta-data management strategies as well as its very good overall performance evaluated using the social network benchmark BG.