GooseFS: Distributed Cache Service to Enhance Cloud Object Storage Performance

With advantages of scalability and low cost, cloud object storage has become the preferred storage solution for massive data. However, object storage has its own defects, such as poor performance of small I/Os, which restricts object storage from being widely used in some scenarios like Big Data. In this paper, we propose GooseFS, a distributed high-performance cache service built on top of object storage, which accelerates the access to object storage under the storage-compute separation architecture. GooseFS makes great enhancements on small I/Os performance as well as metadata performance for data stored in object storage. GooseFS introduces three key designs: (1) Compute-Side Cache, which reduces the data access latency under random small I/O with multi-granularity cache management and short circuit read mechauism. (2) Storage-Side Cache, which improves the throughput with a high-performance SSD cache pool. (3) Metadata Acceleration, which significantly improves the performance of metadata operations through special metadata organization and lock-free strong consistency cache. Experiment show that compared with native object storage, GooseFS increases the throughput of small random I/O by 5x -9 x and improves metadata operation performance by at least 3.9 x, meeting the performance requirements of various workloads.