Designing a commutative replicated data type

TL;DR

This paper introduces methods for designing commutative replicated data types that ensure convergence and support low-cost transactions, using innovative techniques like background consensus and reusing existing ideas for efficiency.

Contribution

It presents a novel approach to designing commutative data types, including a new technique called background consensus, and demonstrates their effectiveness with a shared edit buffer example.

Findings

Replicas of commutative data types converge correctly under standard assumptions.

The proposed methods support low-cost transactional operations.

Background consensus improves efficiency in ensuring commutativity.

Abstract

Commuting operations greatly simplify consistency in distributed systems. This paper focuses on designing for commutativity, a topic neglected previously. We show that the replicas of \emph{any} data type for which concurrent operations commute converges to a correct value, under some simple and standard assumptions. We also show that such a data type supports transactions with very low cost. We identify a number of approaches and techniques to ensure commutativity. We re-use some existing ideas (non-destructive updates coupled with invariant identification), but propose a much more efficient implementation. Furthermore, we propose a new technique, background consensus. We illustrate these ideas with a shared edit buffer data type.