DeepAI
Log In Sign Up

Taurus: Lightweight Parallel Logging for In-Memory Database Management Systems (Extended Version)

10/14/2020
by   Yu Xia, et al.
0

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

01/19/2019

Guaranteeing Recoverability via Partially Constrained Transaction Logs

Transaction logging is an essential constituent to guarantee the atomici...
04/11/2018

Stochastic Comparison of Parallel Systems with Log-Lindley Distributed Components under Random Shocks

Recently, Chowdhury and Kundu [6] compared two parallel systems of heter...
04/22/2020

Breaking Down Memory Walls: Adaptive Memory Management in LSM-based Storage Systems (Extended Version)

Log-Structured Merge-trees (LSM-trees) have been widely used in modern N...
12/17/2017

A new and five older Concurrent Memory Reclamation Schemes in Comparison (Stamp-it)

Memory management is a critical component in almost all shared-memory, c...
02/18/2020

Connecting MapReduce Computations to Realistic Machine Models

We explain how the popular, highly abstract MapReduce model of parallel ...
01/17/2021

Data stream fusion for accurate quantile tracking and analysis

UDDSKETCH is a recent algorithm for accurate tracking of quantiles in da...