Affiliation:
1. University of Minnesota–Twin Cities, Minneapolis, MN
Abstract
Computer systems utilizing byte-addressable
Non-Volatile Memory
(
NVM
) as memory/storage can provide low-latency data persistence. The widely used key-value stores using
Log-Structured Merge Tree
(
LSM-Tree
) are still beneficial for NVM systems in aspects of the space and write efficiency. However, the significant write amplification introduced by the leveled compaction of LSM-Tree degrades the write performance of the key-value store and shortens the lifetime of the NVM devices. The existing studies propose new compaction methods to reduce write amplification. Unfortunately, they result in a relatively large read amplification. In this article, we propose NVLSM, a key-value store for NVM systems using LSM-Tree with new accumulative compaction. By fully utilizing the byte-addressability of NVM, accumulative compaction uses pointers to accumulate data into multiple floors in a logically sorted run to reduce the number of compactions required. We have also proposed a cascading searching scheme for reads among the multiple floors to reduce read amplification. Therefore, NVLSM reduces write amplification with small increases in read amplification. We compare NVLSM with key-value stores using LSM-Tree with two other compaction methods: leveled compaction and fragmented compaction. Our evaluations show that NVLSM reduces write amplification by up to 67% compared with LSM-Tree using leveled compaction without significantly increasing the read amplification. In write-intensive workloads, NVLSM reduces the average latency by 15.73%–41.2% compared to other key-value stores.
Funder
NSF I/UCRC Center Research in Intelligent Storage and NSF
Publisher
Association for Computing Machinery (ACM)
Subject
Hardware and Architecture
Reference77 articles.
1. Write-behind logging
2. Workload analysis of a large-scale key-value store
3. Operating system implications of fast, cheap, non-volatile memory;Bailey Katelin;HotOS,2011
Cited by
13 articles.
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