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LFLogging: A Latch-Free Logging Scheme for PCM-Based Big Data Management Systems

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Database Systems for Advanced Applications (DASFAA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10179))

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Abstract

Big data introduces new challenges to database systems because of its big-volume and big-velocity properties. Specially, the big velocity, i.e., data arrives very fast, requires that database systems have to provide efficient solutions to process continuously-arriving queries. However, traditional disk-based DBMSs have a large overhead in maintaining database consistency. This is mainly due to the logging, locking, and latching mechanisms inside traditional DBMSs. In this paper, we aim to reduce the logging overheads for DBMSs by using new kinds of storage media such as PCM. Particularly, we propose a latch-free logging scheme named LFLogging. It uses PCM for both updating and transaction logging in disk-based DBMSs. Different from the traditional approaches where latches contention and complex logging schemes like WAL, LFLogging provides high performance by reducing latches and explicit logging. We conduct trace-driven experiments on the TPC-C benchmark to measure the performance of our proposal. The results show that LFLogging achieves up to 4~5X improvement in system throughput than existing approaches including WAL and PCMLogging.

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Acknowledgements

This work is partially supported by the National Science Foundation of China under the grant numbers 61472376 and 61672479, the Fundamental Research Funds for the Central Universities, and a fund from the Science and Technology on Electronic Information Control Laboratory.

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Authors and Affiliations

  1. School of Computer Science and Technology, University of Science and Technology of China, Hefei, 230027, China

    Wenqiang Wang, Peiquan Jin, Shouhong Wan & Lihua Yue

  2. Science and Technology on Electronic Information Control Laboratory, Chengdu, 610036, China

    Wenqiang Wang & Peiquan Jin

  3. Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, Hefei, 230027, China

    Shouhong Wan & Lihua Yue

Authors
  1. Wenqiang Wang
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  2. Peiquan Jin
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  3. Shouhong Wan
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  4. Lihua Yue
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Corresponding author

Correspondence to Peiquan Jin .

Editor information

Editors and Affiliations

  1. Royal Melbourne Institute of Technology , Melbourne, Australia

    Zhifeng Bao

  2. Northwestern University , Evanston, Illinois, USA

    Goce Trajcevski

  3. University of New South Wales , Sydney, New South Wales, Australia

    Lijun Chang

  4. The University of Queensland , Brisbane, Queensland, Australia

    Wen Hua

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Wang, W., Jin, P., Wan, S., Yue, L. (2017). LFLogging: A Latch-Free Logging Scheme for PCM-Based Big Data Management Systems. In: Bao, Z., Trajcevski, G., Chang, L., Hua, W. (eds) Database Systems for Advanced Applications. DASFAA 2017. Lecture Notes in Computer Science(), vol 10179. Springer, Cham. https://doi.org/10.1007/978-3-319-55705-2_7

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  • DOI: https://doi.org/10.1007/978-3-319-55705-2_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55704-5

  • Online ISBN: 978-3-319-55705-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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