One-shot Garbage Collection for In-memory OLTP through Temporality-aware Version Storage

• Published in: Proceedings of the ACM on management of data 2023-05, Vol.1 (1), p.1-25, Article 19
• Main Authors: Raza, Aunn, Chrysogelos, Periklis, Anadiotis, Angelos Christos, Ailamaki, Anastasia
• Format: Article
• Language: English
• Subjects: Data management systems; Database management system engines; Database transaction processing; DBMS engine architectures; Information systems; Main memory engines; Record and buffer management
• ISSN: 2836-6573; 2836-6573
• DOI: 10.1145/3588699

Most modern in-memory online transaction processing (OLTP) engines rely on multi-version concurrency control (MVCC) to provide data consistency guarantees in the presence of conflicting data accesses. MVCC improves concurrency by generating a new version of a record on every write, thus increasing the storage requirements. Existing approaches rely on garbage collection and chain consolidation to reduce the length of version chains and reclaim space by freeing unreachable versions. However, finding unreachable versions requires the traversal of long version chains, which incurs random accesses right into the critical path of transaction execution, hence limiting scalability. This paper introduces OneShotGC, a new multi-version storage design that eliminates version traversal during garbage collection, with minimal discovery and memory management overheads. OneShotGC leverages the temporal correlations across versions to opportunistically cluster them into contiguous memory blocks that can be released in one shot. We implement OneShotGC in Proteus and use YCSB and TPC-C to experimentally evaluate its performance with respect to the state-of-the-art, where we observe an improvement of up to 2x in transactional throughput.