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OLTPShare: The Case for Sharing in OLTP Workloads

Robin Rehrmann; Carsten Binnig; Alexander Böhm; Kihong Kim; Wolfgang Lehner; Amr Rizk
In: Proceedings of the VLDB Endowment (PVLDB), Vol. 11, No. 12, Pages 1769-1780, Association for Computing Machinery (ACM), 2018.


In the past, resource sharing has been extensively studied for OLAP workloads. Naturally, the question arises, why studies mainly focus on OLAP and not on OLTP workloads? At first sight, OLTP queries - due to their short runtime - may not have enough potential for the additional overhead. In addition, OLTP workloads do not only execute read operations but also updates. In this paper, we address query sharing for OLTP workloads. We first analyze the sharing potential in real-world OLTP workloads. Based on those findings, we then present an execution strategy, called OLTPShare that implements a novel batching scheme for OLTP workloads. We analyze the sharing benefits by integrating OLTPShare into a prototype version of the commercial database system SAP HANA. Our results show for different OLTP workloads that OLTPShare enables SAP HANA to provide a significant throughput increase in high-load scenarios compared to the conventional execution strategy without sharing.

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