@inproceedings{66903211a9b741efad85fc3bd28b209c,
title = "Evaluating index systems of high energy physics",
abstract = "Nowadays, more and more scientific data has been produced through high-energy physics (HEP) facilities. Even in one particle physics experiment, the generated data reaches to petabytes scale. Retrieving data from massive data occupies a large proportion of data processing in HEP. Hence, the data query latency and throughput are the most important metrics for HEP data management. Inspired by the indexing technology of databases, the technology that improves the performance of data retrieval through the HEP data indexing, becomes the mainstream in the HEP data management. In this paper, focusing on two typical index systems–MySQL and HBase–for HEP data management, which are the typical SQL and NoSQL system respectively, we evaluate them from the perspectives of overall performance, system and micro-architecture behaviors. We find that HBase achieves higher performance than MySQL with the data scale increasing.",
keywords = "Data management, Event index, HBase, High-energy physics, MySQL",
author = "Shaopeng Dai and Wanling Gao and Biwei Xie and Minghe Yu and Jia'nan Chen and Defei Kong and Rui Han and Jinheng Li",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Singapore Pte Ltd.; 1st Workshop on Big Scientific Data Benchmarks, Architecture, and Systems, SDBA 2018 ; Conference date: 12-06-2018 Through 12-06-2018",
year = "2019",
doi = "10.1007/978-981-13-5910-1_2",
language = "English",
isbn = "9789811359095",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "15--26",
editor = "Rui Ren and Chen Zheng and Jianfeng Zhan",
booktitle = "Big Scientific Data Benchmarks, Architecture, and Systems - 1st Workshop, SDBA 2018, Revised Selected Papers",
address = "Germany",
}