论文标题
金牛座：内存数据库管理系统（扩展版本）的轻巧并行记录
Taurus: Lightweight Parallel Logging for In-Memory Database Management Systems (Extended Version)
论文作者
论文摘要
现有的单流日志记录方案不适合内存数据库管理系统（DBMS），因为单日志通常是性能瓶颈。为了克服这个问题，我们提出了Taurus，Taurus是一种使用多个日志流的有效的并行日志记录方案，并且与数据和命令记录都兼容。金牛座使用对数序列编号（LSN）的向量编码事务依赖关系。这些向量确保依赖项在记录中充分捕获，并在恢复中正确执行。我们对内存DBMS进行的实验评估表明，金牛座的并行记录分别在单个数据记录和命令记录上分别达到9.9倍和2.9倍的速度。它还使DBM能够分别比这些基线的数据和命令记录快22.9倍和75.6倍。我们还将金牛座与两个最先进的并行记录方案进行了比较，并表明DBM在NVME驱动器上的性能高达2.8倍，HDD上的表现为9.2倍。
Existing single-stream logging schemes are unsuitable for in-memory database management systems (DBMSs) as the single log is often a performance bottleneck. To overcome this problem, we present Taurus, an efficient parallel logging scheme that uses multiple log streams, and is compatible with both data and command logging. Taurus tracks and encodes transaction dependencies using a vector of log sequence numbers (LSNs). These vectors ensure that the dependencies are fully captured in logging and correctly enforced in recovery. Our experimental evaluation with an in-memory DBMS shows that Taurus's parallel logging achieves up to 9.9x and 2.9x speedups over single-streamed data logging and command logging, respectively. It also enables the DBMS to recover up to 22.9x and 75.6x faster than these baselines for data and command logging, respectively. We also compare Taurus with two state-of-the-art parallel logging schemes and show that the DBMS achieves up to 2.8x better performance on NVMe drives and 9.2x on HDDs.
