Efficient, Consistent Distributed Computation with Predictive Treaties
Tom Magrino, Jed Liu, Nate Foster, Johannes Gehrke, and Andrew C. Myers

To achieve good performance, modern applications often partition and replicate their state across multiple geographically-distributed nodes. While this approach reduces latency in the common case, it can be challenging for programmers to use correctly, especially in applications that require strong consistency. We show how to achieve strong consistency while avoiding coordination by using predictive treaties, a mechanism that can significantly reduce distributed coordination without losing strong consistency. The central insight behind our approach is that many computations can be expressed in terms of predicates over distributed state that can be partitioned and enforced locally. Predictive treaties improve on previous work by allowing the locally enforced predicates to depend on time. Intuitively, by predicting the evolution of system state, coordination can be significantly reduced compared to static approaches. We implemented predictive treaties in a distributed system that exposes them via an intuitive programming model. We evaluate performance on several benchmarks, including TPC-C, showing that predictive treaties can significantly increase performance by orders of magnitude and can even outperform customized algorithms.