Abstract
Erasure coding technology is one of the key technologies in big data storage system. A well designed erasure coding can not only improve the reliability of the big data storage system, but also greatly improve the performance. Most of the existing big data storage systems use replica strategy, which can provide good availability and real-time, but it has caused a lot of data redundancy and waste of storage space. A large part of the data stored in the storage system exists in the form of cold data. In this paper, we aim at the cold data which doesn’t require highly on data availability and real-time in the big data storage system. We have proposed a scheme to support both replica strategy and coding strategy, and designed the node scheduling and data addressing scheme. We selected Liberation code which is excellent in writing operation, and developed P-Schedule scheme to optimize the decoding speed. Through a series of designs, we can effectively improve the disk utilization and write speed of the cold data in the big data system. The test results show that the sequential write performance of erasure coding is better than that of the replica strategy. The larger the data block is, the better the performance is.
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Acknowledgements
This work was supported by National Natural Science Foundation of China (No. 61662038), Science and technology project of Jiangxi Provincial Department of Education (No. GJJ151081), the Visiting Scholar Funds by China Scholarship Council, the JiangXi Association for Science and Technology.
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Yin, C., Lv, H., Li, T., Liu, Y., Qu, X., Yuan, S. (2018). P-Schedule: Erasure Coding Schedule Strategy in Big Data Storage System. In: Vaidya, J., Li, J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2018. Lecture Notes in Computer Science(), vol 11336. Springer, Cham. https://doi.org/10.1007/978-3-030-05057-3_22
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DOI: https://doi.org/10.1007/978-3-030-05057-3_22
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