O$|$R$|$P$|$E -- A Data Semantics Driven Concurrency Control

TL;DR

This paper introduces extsc{O|R|P|E}, a data semantics driven concurrency control mechanism that dynamically adapts to workload conditions, significantly improving response time and concurrency over traditional snapshot isolation.

Contribution

The paper proposes a novel semantics-based concurrency control model that classifies data into four types and dynamically switches mechanisms at runtime for optimal performance.

Findings

extsc{O|R|P|E} outperforms Snapshot Isolation by 4.5 times in response time.

The concurrency degree is increased by a factor of 3.2 under heavy load.

Dynamic adaptation balances commit rate and response time effectively.

Abstract

This paper presents a concurrency control mechanism that does not follow a 'one concurrency control mechanism fits all needs' strategy. With the presented mechanism a transaction runs under several concurrency control mechanisms and the appropriate one is chosen based on the accessed data. For this purpose, the data is divided into four classes based on its access type and usage (semantics). Class $O$ (the optimistic class) implements a first-committer-wins strategy, class $R$ (the reconciliation class) implements a first-n-committers-win strategy, class $P$ (the pessimistic class) implements a first-reader-wins strategy, and class $E$ (the escrow class) implements a first-n-readers-win strategy. Accordingly, the model is called \PeFS. The selected concurrency control mechanism may be automatically adapted at run-time according to the current load or a known usage profile. This run-time adaptation allows \Pe to balance the commit rate and the response time even under changing conditions. \Pe outperforms the Snapshot Isolation concurrency control in terms of response time by a factor of approximately 4.5 under heavy transactional load (4000 concurrent transactions). As consequence, the degree of concurrency is 3.2 times higher.