面向查詢的高性能二級索引設計
首發時間:2018-04-28
摘要:由于傳統關系型數據庫難以應對智能電網中成千上萬的傳感器產生的海量數據和屬性,新型大數據平臺的HBase數據庫作為一個面向列的鍵值存儲數據庫,逐步成為主流的大數據平臺數據庫。然而,HBase雖然可以支撐大數據量,但仍然難以應對電網數據分析的查詢頻率較高、響應時間較短的需求。本研究中,我們提出了一個面向查詢的二級索引方案,它可以加速查詢,實驗結果表明當涉及到兩張表連接查詢時,我們的方案相比于經典二級索引方案可以提供最小1.026倍至最大4.761倍的加速比,當涉及到三張表連接查詢時,我們的方案相比于經典二級索引方案可以提供最小1.797倍至最大8.581倍的加速比,進一步優化之后,該方案還可以大量節省索引表的存儲空間。本研究提出的二級索引方案在查詢性能和存儲效率方面都有不錯的效果
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High Performance Secondary Index Design for Complex Queries
Abstract: Since the traditional relational database is difficult to cope with the massive data and properties produced by thousands of sensors in the smart grid, the HBase database of the new large data platform, as a column oriented key value storage database, has gradually become the mainstream large data platform database. ThoughHBase can support large data volume, but it is still difficult to cope with the demand of high frequency and short response time in power grid data analysis. In this study, we proposed a query oriented two level index scheme that can speed up the query. The experimental results show that when the two table connection queries are involved, our scheme can provide a minimum of 1.026 to the maximum 4.761 times the acceleration ratio compared to the classic two level index, when it involves three table connection queries, Our scheme provides a minimum of 1.797 to a maximum of 8.581 times the speed ratio of the classic two level index scheme. After further optimization, the scheme can also save much of the storage space of the index table. The two level indexing scheme proposed in this study has a good effect in terms of query performance and storage efficiency.
Keywords: Big Data Secondary Index Smart Grid
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