Elastic scalable transaction processing in LeanXcale. Issue 108 (September 2022)

• Record Type: Journal Article
• Authors: Jimenez-Peris, Ricardo; Burgos-Sancho, Diego; Ballesteros, Francisco; Patiño-Martinez, Marta; Valduriez, Patrick
• Is Part Of: Information systems. Issue 108(2022)
• Publication Date: 2022-09
• Subjects: Transaction processing -- Transaction management -- NewSQL database system -- Scalability -- Elasticity -- Cloud -- TPC-C; Database management -- Periodicals; Electronic data processing -- Periodicals; Bases de données -- Gestion -- Périodiques; Informatique -- Périodiques; Database management; Electronic data processing; Periodicals; 005.7
• DOI: 10.1016/j.is.2022.102043
• Languages: English
• ISSNs: 0306-4379

Abstract

Abstract: Scaling ACID transactions in a cloud database is hard, and providing elastic scalability even harder. In this paper, we present our solution for elastic scalable transaction processing in LeanXcale, an industrial-strength NewSQL database system. Unlike previous solutions, it does not require any hardware assistance. Yet, it does scales linearly to 100s of servers. LeanXcale supports non-intrusive elasticity and can move data partitions without hurting the quality of service of transaction management. We show the correctness of LeanXcale transaction management. Finally, we provide a thorough performance evaluation of our solution on Amazon Web Services (AWS) shared cloud instances. The results show linear scalability, e.g., 5 million TPC-C NewOrder TPM with 200 nodes, which is greater than the TPC-C throughput obtained by the 9th highest result in all history using dedicated hardware used exclusively (not shared like in our evaluation) for the benchmark. Furthermore, the efficiency in terms of TPM per core is double that of the two top TPC-C results (also the only results in a cloud). Highlights: A complete solution for elastic scalable transaction processing in LeanXcale. Linear scalability to 100s of servers, without requiring any hardware assistance. Non-intrusive elasticity, without hurting the quality of service of TP. Thorough performance evaluation on AWS showing linear scalability.