Update propagation strategies for high-performance OLTP

Abstract

Traditional transaction processing architectures employ a buffer pool where page updates are absorbed in main memory and asynchronously propagated to the persistent database. In a scenario where transaction throughput is limited by I/O bandwidth—which was typical when OLTP systems first arrived—such propagation usually happens on demand, as a consequence of evicting a page. However, as the cost of main memory decreases and larger portions of an application’s working set fit into the buffer pool, running transactions are less likely to depend on page I/O to make progress. In this scenario, update propagation plays a more independent and proactive role, where the main goal is to control the amount of cached dirty data. This is crucial to maintain high performance as well as to reduce recovery time in case of a system failure. In this paper, we analyze different propagation strategies and measure their effectiveness in reducing the number of dirty pages in the buffer pool. We show that typical strategies have a complex parametrization space, yet fail to robustly deliver high propagation rates. As a solution, we propose a propagation strategy based on efficient log replay rather than writing page images from the buffer pool. This novel technique not only maximizes propagation efficiency, but also has interesting properties that can be exploited for novel logging and recovery schemes.