Lazy State Determination: More concurrency for contending linearizable transactions

TL;DR

This paper introduces lazy state determination, a method that uses semantic information to increase concurrency in transactional systems, significantly improving throughput and latency while maintaining linearizability.

Contribution

It proposes a new API and concurrency control algorithms that leverage semantic information to enhance performance under high contention.

Findings

Achieves up to 5x higher throughput in TPC-C benchmark.

Reduces latency by 1.5 times compared to standard techniques.

Maintains linearizability while increasing concurrency.

Abstract

The concurrency control algorithms in transactional systems limits concurrency to provide strong semantics, which leads to poor performance under high contention. As a consequence, many transactional systems eschew strong semantics to achieve acceptable performance. We show that by leveraging semantic information associated with the transactional programs to increase concurrency, it is possible to significantly improve performance while maintaining linearizability. To this end, we introduce the lazy state determination API to easily expose the semantics of application transactions to the database, and propose new optimistic and pessimistic concurrency control algorithms that leverage this information to safely increase concurrency in the presence of contention. Our evaluation shows that our approach can achieve up to 5x more throughput with 1.5c less latency than standard techniques in the popular TPC-C benchmark.