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In-memory transaction processing: efficiency and scalability considerations

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Abstract

Traditional disk-resident OLTP systems were mainly designed for computers with relatively small memory. Driven by the advance of hardware, OLTP systems need to be redesigned for larger memory and multi-core environments. Compared to disk-resident systems, in-memory systems have significant performance advantages, from the perspectives of both transaction throughput and query latency. Their performance is no longer limited by disk I/Os. Instead, the efficiency and scalability over multi-core CPUs become more important. In this paper, we survey and summarize a wide spectrum of design and implementation considerations that may affect the efficiency or scalability of an in-memory OLTP system. These considerations are concerned with most of the main components of databases, including concurrency control, logging, indexing and transaction compilation. For each of the components, we provide some in-depth analysis based on recent research works. This survey also aims to provide some guidance for designing or implementing high-performance in-memory OLTP systems.

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Notes

  1. Which is not visible at the transactional level.

  2. For in-place updates, the state of data is likely to be inconsistent in the caches of multiple processors.

  3. The project is ended in 2016.

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Acknowledgements

This work is supported by National Science Foundation of China under Grant Numbers 61702189, 61672232, 61772202 and Youth Science and Technology - Yang Fan Program of Shanghai under Grant Number 17YF1427800.

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  1. School of Data Science and Engineering, East China Normal University, Shanghai, China

    Huiqi Hu, Xuan Zhou, Tao Zhu, Weining Qian & Aoying Zhou

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Hu, H., Zhou, X., Zhu, T. et al. In-memory transaction processing: efficiency and scalability considerations. Knowl Inf Syst 61, 1209–1240 (2019). https://doi.org/10.1007/s10115-019-01340-7

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