LFLogging: A Latch-Free Logging Scheme for PCM-Based Big Data Management Systems

Big data introduces new challenges to database systems because of its big-volume and big-velocity properties. Specially, the big velocity, i.e., data arrives very fast, requires that database systems have to provide efficient solutions to process continuously-arriving queries. However, traditional disk-based DBMSs have a large overhead in maintaining database consistency. This is mainly due to the logging, locking, and latching mechanisms inside traditional DBMSs. In this paper, we aim to reduce the logging overheads for DBMSs by using new kinds of storage media such as PCM. Particularly, we propose a latch-free logging scheme named LFLogging. It uses PCM for both updating and transaction logging in disk-based DBMSs. Different from the traditional approaches where latches contention and complex logging schemes like WAL, LFLogging provides high performance by reducing latches and explicit logging. We conduct trace-driven experiments on the TPC-C benchmark to measure the performance of our proposal. The results show that LFLogging achieves up to 4~5X improvement in system throughput than existing approaches including WAL and PCMLogging.