Zen
| Autor: | Gang Liu, Shimin Chen, Chen Leying |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Hardware_MEMORYSTRUCTURES
Computer science 020204 information systems 0202 electrical engineering electronic engineering information engineering General Engineering Operating system Online transaction processing 020201 artificial intelligence & image processing 02 engineering and technology computer.software_genre Throughput (business) computer |
| Zdroj: | Proceedings of the VLDB Endowment. 14:835-848 |
| ISSN: | 2150-8097 |
| DOI: | 10.14778/3446095.3446105 |
| Popis: | Emerging Non-Volatile Memory (NVM) technologies like 3DX-point promise significant performance potential for OLTP databases. However, transactional databases need to be redesigned because the key assumptions that non-volatile storage is orders of magnitude slower than DRAM and only supports blocked-oriented access have changed. NVMs are byte-addressable and almost as fast as DRAM. The capacity of NVM is much (4-16x) larger than DRAM. Such NVM characteristics make it possible to build OLTP database entirely in NVM main memory. This paper studies the structure of OLTP engines with hybrid NVM and DRAM memory. We observe three challenges to design an OLTP engine for NVM: tuple metadata modifications, NVM write redundancy, and NVM space management. We propose Zen, a high-throughput log-free OLTP engine for NVM. Zen addresses the three design challenges with three novel techniques: metadata enhanced tuple cache, log-free persistent transactions, and light-weight NVM space management. Experimental results on a real machine equipped with Intel Optane DC Persistent Memory show that Zen achieves up to 10.1x improvement compared with existing solutions to run an OLTP database as large as the size of NVM while achieving fast failure recovery. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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