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Design and implementation of an efficient flushing scheme for cloud key-value storage

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Abstract

A key-value store is an essential component that is increasingly demanded in many scale-out environments, including social networks, online retail environments, and cloud services. Modern key-value storage engines provide many features, including transaction, versioning, and replication. In storage engines, transaction processing provides atomicity and durability by using write-ahead logging (WAL), which flushes log data before the data page is written to persistent storage in synchronous commit. However, according to our observation, WAL is a performance bottleneck in key-value storage engines since the flushing of log data to persistent storage incurs a significant overhead of lock contention and fsync() calls, even with the various optimizations in the existing scheme. In this article, we propose an approach to improve the performance of key-value storage by optimizing the existing flushing scheme combined with group commit and consolidate array. Our scheme aggregates the multiple flushing of log data into a large request on the fly and completes the request early. This scheme is an efficient group commit that reduces the number of frequent lock acquisitions and fsync() calls in the synchronous commit while supporting the same transaction level that the existing scheme provides. Furthermore, we integrate our flushing scheme into the replication system and evaluate it by using multiple nodes. We implement our scheme on the WiredTiger storage engine. The experimental results show that our scheme improves the performance of the key-value workload compared to the existing scheme.

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Notes

  1. A leader is the first thread to acquire a log buffer.

  2. The offset is its own LSN.

  3. The group size is the size of the total joined log records in the slot.

  4. The completion flag denotes whether the LSN is completed or not.

  5. Replication can be broadly classified into two categories, such as synchronous and asynchronous replication. In synchronous replication, the transactions are committed simultaneously in all nodes. The master and the slave always remain synchronized. Thus, the data is guaranteed to be consistent in all nodes when the transaction is committed. Meanwhile, in asynchronous replication, the transactions are committed at the master server first and then they are replicated to the slave. This means that the master and slave may not be consistent. The advantage of using asynchronous replication is that it is faster and scales better than synchronous replication. However, the data is not guaranteed to be consistent in all nodes.

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Acknowledgements

This research was supported by Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2015M3C4A7065581, 2015M3C4A7065645). Prof. Han’s work was partly supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2014R1A1A2055032).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Seoul National University, Seoul, South Korea

    Yongseok Son & Heon Young Yeom

  2. Department of Computer Science, Dongduk Women’s University, Seoul, South Korea

    Hyuck Han

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  1. Yongseok Son
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Correspondence to Hyuck Han.

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A preliminary version [35] of this article was presented at the 1st IEEE Internaltional Workshops on Foundations and Applications of Self* Systems, Augsburg, Germany, September 2016.

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Son, Y., Yeom, H.Y. & Han, H. Design and implementation of an efficient flushing scheme for cloud key-value storage. Cluster Comput 20, 3551–3563 (2017). https://doi.org/10.1007/s10586-017-1101-3

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