Huang / Wang Indexing on Non-Volatile Memory

Techniques, Lessons Learned and Outlook
1. Auflage 2024
ISBN: 978-3-031-47627-3
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 87 Seiten, eBook

Reihe: SpringerBriefs in Computer Science

This book focuses on online transaction processing indexes designed for scalable, byte-addressable non-volatile memory (NVM) and provides a systematic review and summary of the fundamental principles and techniques as well as an outlook on the future of this research area.In this book, the authors divide the development of NVM indexes into three “eras”— pre-Optane, Optane and post-Optane—based on when the first major scalable NVM device (Optane) became commercially available and when it was announced to be discontinued. The book will analyze the reasons for the slow adoption of NVM and give an outlook for indexing techniques in the post-Optane era.The book assumes only basic undergraduate-level understanding on indexing (e.g., B+-trees, hash tables) and database systems in general. It is otherwise self-contained with the necessary background information, including an introduction to NVM hardware and software/programming issues, a detailed description of different indexes in highly concurrent systems for non-experts and new researchers to get started in this area.

Zielgruppe

Research

Autoren/Hrsg.

Huang, Kaisong

Wang, Tianzheng

Inhaltsverzeichnis

1. Introduction.- 2. NVM Hardware and Software.- 3. A Primer on Database Indexing.- 4. Range Indexes on Non-Volatile Memory.- 5. Hash Tables on Non-Volatile Memory.- 6. Summary.- 7. Lessons Learned and Outlook.

Über Autor(innen)

Kaisong Huang is a PhD student advised by Dr. Tianzheng Wang in the School of Computing Science at Simon Fraser University. His research interests are mainly focused on database engines, transaction processing, and storage management. In 2022, he received the ACM SIGMOD Research Highlight Award.Tianzheng Wang is an assistant professor in the School of Computing Science at Simon Fraser University (SFU) in Vancouver, Canada. His research centers around the making of database systems in the context of modern hardware, new programming language features and primitives, and new applications. His work has been recognized by two ACM SIGMOD Research Highlight Awards (2020 and 2022), a 2019 IEEE TCSC Award for Excellence in Scalable Computing (Early Career Researchers) and several nominations for best/memorable paper awards.