Scalable Eventually Consistent Counters over Unreliable Networks

TL;DR

This paper introduces Handoff Counters, a scalable, eventually consistent distributed counter mechanism suitable for unreliable networks, overcoming traditional CRDT limitations and applicable to other data types.

Contribution

It presents Handoff Counters, the first CRDT-based solution that avoids identity explosion and is scalable over unreliable networks, expanding the applicability of CRDTs.

Findings

Handoff Counters are scalable and work over unreliable networks.

They overcome identity explosion in naive CRDTs.

The approach is applicable to other associative and commutative data types.

Abstract

Counters are an important abstraction in distributed computing, and play a central role in large scale geo-replicated systems, counting events such as web page impressions or social network "likes". Classic distributed counters, strongly consistent, cannot be made both available and partition-tolerant, due to the CAP Theorem, being unsuitable to large scale scenarios. This paper defines Eventually Consistent Distributed Counters (ECDC) and presents an implementation of the concept, Handoff Counters, that is scalable and works over unreliable networks. By giving up the sequencer aspect of classic distributed counters, ECDC implementations can be made AP in the CAP design space, while retaining the essence of counting. Handoff Counters are the first CRDT (Conflict-free Replicated Data Type) based mechanism that overcomes the identity explosion problem in naive CRDTs, such as G-Counters (where state size is linear in the number of independent actors that ever incremented the counter), by managing identities towards avoiding global propagation and garbage collecting temporary entries. The approach used in Handoff Counters is not restricted to counters, being more generally applicable to other data types with associative and commutative operations.