Abstract
Relational data query always plays an important role in data analysis. But how to scale out the traditional SQL query system is a challenging problem. In this paper, we introduce a fast, high throughput and scalable system to perform read-only SQL well with the advantage of NoSQL's distributed architecture. We adopt HBase as the storage layer and design a distributed query engine (DQE) collaborating with it to perform SQL queries. Our system also contains distinctive index and cache mechanisms to accelerate query processing. Finally, we evaluate our system with real-world big data crawled from Sina Weibo and it achieves good performance under nineteen representative SQL queries. © 2012 Springer-Verlag.
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CITATION STYLE
Zhu, F., Liu, J., & Xu, L. (2012). A fast and high throughput SQL query system for big data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7651 LNCS, pp. 783–788). https://doi.org/10.1007/978-3-642-35063-4_66
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