Abstract
The increase in the volume of processed data and the requirements for accuracy and speed of their processing has been observed in the world. Therefore, the problem of finding effective methods for accelerating the execution of queries with the involvement of all possible software, mathematical and hardware tools is becoming increasingly important. This article presents the results of the authors’ research in the field of creating parallel queries. These results can be used in practice to implement relational queries and in theory to improve the methods of parallelizing queries. In the article are considered various ways of performance of a complex queries both in sequential, and in a parallel type. It is proposed to use the theory of parallel computations for the transformation of queries. The results of numerical experiments confirming the authors’ assumptions are presented at the end of the article.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Biswas, R., et al.: A NASA perspective on quantum computing: opportunities and challenges. Parallel Comput. 64, 81–98 (2017). https://doi.org/10.1016/j.parco.2016.11.002
Lu, W., Wang, Y., Juang, J., Liu, J., Shen, Y., Wei, B.: Hybrid storage architecture and efficient MapReduce processing for unstructured data. Parallel Comput. 69, 63–77 (2017). https://doi.org/10.1016/j.parco.2017.08.008
Jin, P., Yang, P., Yue, L.: Optimizing B + -tree for hybrid storage systems. Distrib. Parallel Databases 33(3), 449–475 (2015). https://doi.org/10.1007/s10619-014-7157-7
Luo, Q., Teubner, J.: Special issue on data management on modern hardware. Distrib. Parallel Databases 33, 415–416 (2015). https://doi.org/10.1007/s10619-014-7168-4
Yasar, A., Gedik, B., Ferhatosmanoglu, H.: Distributed block formation and layout for disk-based management of large-scale graphs. Distrib. Parallel Databases 35(1), 23–53 (2017). https://doi.org/10.1007/s10619-017-7191-3
Amagata, D., Hara, T., Nishio, S.: Sliding window top-k dominating query processing over distributed data streams. Distrib. Parallel Databases 34(4), 535–566 (2016)
Waluyo, A.B., Srinivasan, B., Taniar, D.: Research in mobile database query optimization and processing. Mob. Inf. Syst. 1(4), 225–252 (2005)
Spiliopoulou, M., Hatzopoulos, M.: Translation of SQL queries into a graph structure: query transformations and pre-optimization issues in a pipeline multiprocessor environment. Inf. Syst. 17(2), 161–170 (1992)
Yao, S.B.: Optimization of query evaluation algorithms. ACM Trans. Database Syst. 4(2), 133–155 (1979)
Mikkilineni, K.P., Su, S.Y.W.: An evaluation of relational join algorithms in a pipelined query processing environment. IEEE Trans. Softw. Eng. 14(6), 838–848 (1988)
Jarke, M., Koch, J.: Query optimization in database systems. ACM Comput. Surv. 16(2), 111–152 (1984)
Shichkina, Y.A., Kupriyanov, M.S.: Applying the list method to the transformation of parallel algorithms into account temporal characteristics of operations. In: Proceedings of the 19th International Conference on Soft Computing and Measurements, SCM 2016, pp. 292–295 (2016). 7519759
Acknowledgments
The paper has been prepared within the scope of the state project “Initiative scientific project” of the main part of the state plan of the Ministry of Education and Science of Russian Federation (task № 2.6553.2017/8.9 BCH Basic Part).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Shichkina, Y., Kupriyanov, M., Shevsky, V. (2018). The Application of Graph Theory and Adjacency Lists to Create Parallel Queries to Relational Databases. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2018 2018. Lecture Notes in Computer Science(), vol 11118. Springer, Cham. https://doi.org/10.1007/978-3-030-01168-0_13
Download citation
DOI: https://doi.org/10.1007/978-3-030-01168-0_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-01167-3
Online ISBN: 978-3-030-01168-0
eBook Packages: Computer ScienceComputer Science (R0)