Abstract
This paper focuses on analyzing how to improve the HBase non RowKey’s query and designing an approach to improve its performance. Analyzing and summarizing the advantages and disadvantages of index technology applied in typical application scenarios, we design a secondary index approach for HBase based on the pre-partition. Through experiments, we found this method can effectively improve the query performance of HBase on non RowKey column, have little effect on the performance of the original data writing and reduce data redundancy. Compared with other methods, this approach has certain performance advantages.
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Bakshi, K.: Considerations for big data: Architecture and approach. In: Aerospace Conference, 2012 IEEE, pp. 1–7. IEEE (2012)
Wang, J.: Index and query processing technology research in the cloud computing system. HIT (2013)
Du, X.: Big data environment based on HBase distributed query optimization research. Computer CD Software And Application 8 (2014)
Vora, M.N.: Hadoop-HBase for large-scale data. In: 2011 IEEE International Conference on Computer Science and Network Technology (ICCSNT), pp. 601–605 (2011)
Liu, X.: The depth analysis of the HBase performance. Programmer 7, 102–104 (2011)
Zhuo, H.: Real-time query system desigan and implementation based on HBase huge data, BUPT (2013)
Vashishtha, H., Stroulia, E.: Enhancing query support in hbase via an extended coprocessors framework[M]. Springer, Berlin Heidelberg (2011)
Yunzhi, G.: Application of Remote Procedure Call Protocol(RPC) in Heterogeneous Dual-Core Communication[J]. Fire Control Radar Technology (2013)
Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters[J]. Commun. ACM 51(1), 107–113 (2008)
Acknowledgements
This work has been supported by the National Natural Science Foundation of China under Grant 61172072, 61271308, and Beijing Natural Science Foundation under Grant 4112045, and the Research Fund for the Doctor-al Program of Higher Education of China under Grant W11C100030, the Beijing Science and Technology Pro-gram under Grant Z121100000312024.
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Shen, B., Chao, HC., Xu, W. (2015). Multi-Column Query Method Research and Optimization on HBase. In: Uden, L., Heričko, M., Ting, IH. (eds) Knowledge Management in Organizations. KMO 2015. Lecture Notes in Business Information Processing, vol 224. Springer, Cham. https://doi.org/10.1007/978-3-319-21009-4_32
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DOI: https://doi.org/10.1007/978-3-319-21009-4_32
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