# High Performance Negative Database for Massive Data Management System of   The Mingantu Spectral Radioheliograph

**Authors:** Congming Shi, Feng Wang, Hui Deng, Yingbo Liu, Cuiyin Liu, Shoulin Wei

arXiv: 1705.06067 · 2017-06-28

## TL;DR

This paper introduces a negative database system for managing massive data from the Mingantu Spectral Radioheliograph, significantly reducing storage needs while maintaining efficient data retrieval for scientific analysis.

## Contribution

The paper presents a novel negative database approach tailored for large-scale radio telescope data management, demonstrating its efficiency and storage advantages over traditional systems.

## Key findings

- Reduces storage volume compared to relational databases
- Maintains comparable query and retrieval performance
- Effectively manages massive observational data

## Abstract

As a dedicated synthetic aperture radio interferometer, the MingantU SpEctral Radioheliograph (MUSER), initially known as the Chinese Spectral RadioHeliograph (CSRH), has entered the stage of routine observation. More than 23 million data records per day need to be effectively managed to provide high performance data query and retrieval for scientific data reduction. In light of these massive amounts of data generated by the MUSER, in this paper, a novel data management technique called the negative database (ND) is proposed and used to implement a data management system for the MUSER. Based on the key-value database, the ND technique makes complete utilization of the complement set of observational data to derive the requisite information. Experimental results showed that the proposed ND can significantly reduce storage volume in comparison with a relational database management system (RDBMS). Even when considering the time needed to derive records that were absent, its overall performance, including querying and deriving the data of the ND, is comparable with that of an RDBMS. The ND technique effectively solves the problem of massive data storage for the MUSER, and is a valuable reference for the massive data management required in next-generation telescopes.

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/1705.06067/full.md

## Figures

9 figures with captions in the complete paper: https://tomesphere.com/paper/1705.06067/full.md

## References

22 references — full list in the complete paper: https://tomesphere.com/paper/1705.06067/full.md

---
Source: https://tomesphere.com/paper/1705.06067