PCMLogging: Optimizing Transaction Logging and Recovery Performance with PCM

Shen Gao, Jianliang Xu, Theo Härder, Bingsheng He, Byron Choi, Haibo Hu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

16 Citations (Scopus)


Phase-change memory (PCM), as one of the most promising next-generation memory technologies, offers various attractive properties such as non-volatility, byte addressability, bit alterability, and low idle energy consumption. Recently, PCM has drawn much attention from the database community for optimizing query and transaction performance. As a complement to existing work, we present PCMLogging, a novel logging scheme that exploits PCM for both data caching and transaction logging to minimize I/O accesses in disk-based databases. Specifically, PCMLogging caches dirty pages/records in PCM and further maintains an implicit log in the cached updates to support database recovery. By integrating log and cached updates, PCMLogging enables simplified recovery and prolongs PCM lifetime. Furthermore, using PCMLogging, we develop a wear-leveling algorithm, that evenly distributes the write traffic across the PCM storage space, and a cost-based destaging algorithm that adaptively migrates cached data from PCM to external storage. Compared to classical write-ahead logging (WAL), our trace-driven simulation results reveal up to 1 ∼ 20X improvement in system throughput.
Original languageEnglish
Article number7150536
Pages (from-to)3332-3346
Number of pages15
JournalIEEE Transactions on Knowledge and Data Engineering
Issue number12
Publication statusPublished - 1 Dec 2015
Externally publishedYes


  • caching
  • database recovery
  • performance
  • Phase-change memory

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics


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