基于 IoTDB 时间序列数据库的 EAST 工厂数据存储系统

IF 1.9 3区 工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY
Guang Yang , Feng Wang , Dixin Fan
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引用次数: 0

摘要

EAST(先进超导实验托卡马克)自 2006 年起开始运行。随着运行时间的增加,MySQL 中存储的工厂数据量已稳步增长到数十亿行。目前以关系数据库为核心的存储架构在面对海量时间序列数据时表现不佳,因此采用 TSDB(时间序列数据库)存储电站数据至关重要。在最初的测试中,IoTDB 在植物数据管理的写入吞吐量和大规模查询方面都比其他 TSDB 具有至少 2 倍的性能优势。然而,由于 EAST 的底层基础结构不灵活,植物数据库不能轻易直接修改。为了解决这个问题,我们提出了一种 MySQL-IoTDB 分层机制(MIHM)。具体来说,我们利用 MySQL 主从到 IoTDB 集群设计,将性能负担从关系数据库无缝转移到 TSDB IoTDB。对 EAST 工厂数据的广泛测试表明,与以前的系统相比,基于 MIHM 的工厂数据存储系统的写入吞吐量提高了 20 倍,大规模数据查询速度提高了 100 倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
EAST plant data storage system based on IoTDB time series database

EAST (Experimental Advanced Superconducting Tokamak) has been in operation since 2006. With increasing operation time, the volume of plant data stored in MySQL has steadily grown to several billion rows. The current storage architecture centered around the relational database has shown poor performance when facing massive time series data, so it is crucial to adopt TSDB (Time Series Database) for storing plant data. In initial testing, IoTDB demonstrated a performance advantage of at least 2 times over other TSDBs in terms of both write throughput and large-scale queries for plant data management. However, as the inflexible underlying infrastructure of EAST, the plant database cannot be easily modified directly. To remedy this problem, we propose a MySQL-IoTDB Hierarchical Mechanism (MIHM). Specifically, we utilized a MySQL master–slave to IoTDB cluster design to seamlessly transfer the performance burden from relational database to TSDB IoTDB. Extensive tests on the EAST plant data demonstrate that MIHM-based plant data storage system has increased the write throughput by 20 times and the large-scale data querying speed by 100 times compared to previous systems.

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来源期刊
Fusion Engineering and Design
Fusion Engineering and Design 工程技术-核科学技术
CiteScore
3.50
自引率
23.50%
发文量
275
审稿时长
3.8 months
期刊介绍: The journal accepts papers about experiments (both plasma and technology), theory, models, methods, and designs in areas relating to technology, engineering, and applied science aspects of magnetic and inertial fusion energy. Specific areas of interest include: MFE and IFE design studies for experiments and reactors; fusion nuclear technologies and materials, including blankets and shields; analysis of reactor plasmas; plasma heating, fuelling, and vacuum systems; drivers, targets, and special technologies for IFE, controls and diagnostics; fuel cycle analysis and tritium reprocessing and handling; operations and remote maintenance of reactors; safety, decommissioning, and waste management; economic and environmental analysis of components and systems.
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