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A Highly Scalable Index Structure for Multicore In-Memory Database Systems

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 868))

Abstract

In this paper, we present some insights from the analysis of the drawbacks of the advanced concurrency control techniques. Based on the analysis, we reveal that a commonly used technique for index structures, read-copy update (RCU), has the most significant impact on the throughput and latency of in-memory database systems. For overcoming the drawbacks, we developed Glasstree, a new index structure that produces a smaller load on the memory allocator by enhancing Masstree. Glasstree achieved high throughput and stable latency than Masstree under various workloads.

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Notes

  1. 1.

    The commit ID of git used in our evaluation is 15edde0.

References

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Correspondence to Tatsuo Nakajima .

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Mitake, H., Yamada, H., Nakajima, T. (2020). A Highly Scalable Index Structure for Multicore In-Memory Database Systems. In: Kotenko, I., Badica, C., Desnitsky, V., El Baz, D., Ivanovic, M. (eds) Intelligent Distributed Computing XIII. IDC 2019. Studies in Computational Intelligence, vol 868. Springer, Cham. https://doi.org/10.1007/978-3-030-32258-8_25

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