@inproceedings{94fc4baee5f743da8169722b8bb2b555,
title = "Performance Optimization of the Open XDMoD Datawarehouse",
abstract = "Open XDMoD is an open source tool to facilitate the management of high performance computing resources. It is widely deployed at academic, industrial, and governmental HPC centers and is used to monitor large and small HPC and cloud systems. The core of Open XDMoD is a MySQL based data warehouse that is designed to support the storage of historical information for hundreds of millions of jobs with a fast query time for the interactive web portal. In this paper, we describe the transition that we made from the MyISAM to the InnoDB storage engine. In addition, other improvements were also made to the database queries such as reordering and adding indices. We were able to attain substantial performance improvements in both the query execution and in the data ingestion/aggregation. It is a common trend that databases tend to grow in size and complexity throughout their lifetime; this work presents a practical guide for the types of practices and procedures that can be done to maintain data retrieval and ingestion performance.",
keywords = "MySQL, XDMoD, databases",
author = "Gregary Dean and Joshua Moraes and Joseph White and Robert Deleon and Matthew Jones and Thomas Furlani",
note = "Publisher Copyright: {\textcopyright} 2022 ACM.; 2022 Conference on Practice and Experience in Advanced Research Computing: Revolutionary: Computing, Connections, You, PEARC 2022 ; Conference date: 10-07-2022 Through 14-07-2022",
year = "2022",
month = jul,
day = "8",
doi = "10.1145/3491418.3530290",
language = "English",
series = "PEARC 2022 Conference Series - Practice and Experience in Advanced Research Computing 2022 - Revolutionary: Computing, Connections, You",
publisher = "Association for Computing Machinery, Inc",
booktitle = "PEARC 2022 Conference Series - Practice and Experience in Advanced Research Computing 2022 - Revolutionary",
}