TY - GEN
T1 - ZQL
T2 - 14th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2016, 14th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2016, 2nd IEEE International Conference on Big Data Intelligence and Computing, DataCom 2016 and 2016 IEEE Cyber Science and Technology Congress, CyberSciTech 2016, DASC-PICom-DataCom-CyberSciTech 2016
AU - Xu, Jie
AU - Shi, Mengjie
AU - Chen, Chaoyuan
AU - Zhang, Zhen
AU - Fu, Jigao
AU - Liu, Chi Harold
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/10/11
Y1 - 2016/10/11
N2 - A large amount of unstructured data are being continuously generated by mobile applications, e.g., Facebook, Twitter and Foursquare, due to the popularity of smart devices, e.g., iPad, iWatch and smartphone. These data are undoubtedly of great value but need to be first well stored and then analyzed. Nevertheless, traditional relational database management system (RDBMS) is not well qualified for this job. As a result, NoSQL databases are proposed and become very popular. Judging from the present situations, RDMBSs play a better role in managing relational data, and thus application developers have to face the situation of co-existence of both RDBMS and NoSQL databases, and knowing the details of the underlying data distributions and structures of different databases. To this end, in this paper, we aim to propose a unified, transparent query engine, as a middleware, called "ZQL", by using MySQL and Hive as underlying two exemplary databases, however its usage goes far beyond these two databases. ZQL aims to support application development by hiding the specific details of both NoSQL databases and RDBMS. Finally, extensive experimental results show the effectiveness and functionalities of the proposed and implemented ZQL middleware.
AB - A large amount of unstructured data are being continuously generated by mobile applications, e.g., Facebook, Twitter and Foursquare, due to the popularity of smart devices, e.g., iPad, iWatch and smartphone. These data are undoubtedly of great value but need to be first well stored and then analyzed. Nevertheless, traditional relational database management system (RDBMS) is not well qualified for this job. As a result, NoSQL databases are proposed and become very popular. Judging from the present situations, RDMBSs play a better role in managing relational data, and thus application developers have to face the situation of co-existence of both RDBMS and NoSQL databases, and knowing the details of the underlying data distributions and structures of different databases. To this end, in this paper, we aim to propose a unified, transparent query engine, as a middleware, called "ZQL", by using MySQL and Hive as underlying two exemplary databases, however its usage goes far beyond these two databases. ZQL aims to support application development by hiding the specific details of both NoSQL databases and RDBMS. Finally, extensive experimental results show the effectiveness and functionalities of the proposed and implemented ZQL middleware.
KW - NoSQL database
KW - middleware
UR - https://www.scopus.com/pages/publications/84995376700
U2 - 10.1109/DASC-PICom-DataCom-CyberSciTec.2016.129
DO - 10.1109/DASC-PICom-DataCom-CyberSciTec.2016.129
M3 - Conference contribution
AN - SCOPUS:84995376700
T3 - Proceedings - 2016 IEEE 14th International Conference on Dependable, Autonomic and Secure Computing, DASC 2016, 2016 IEEE 14th International Conference on Pervasive Intelligence and Computing, PICom 2016, 2016 IEEE 2nd International Conference on Big Data Intelligence and Computing, DataCom 2016 and 2016 IEEE Cyber Science and Technology Congress, CyberSciTech 2016, DASC-PICom-DataCom-CyberSciTech 2016
SP - 730
EP - 737
BT - Proceedings - 2016 IEEE 14th International Conference on Dependable, Autonomic and Secure Computing, DASC 2016, 2016 IEEE 14th International Conference on Pervasive Intelligence and Computing, PICom 2016, 2016 IEEE 2nd International Conference on Big Data Intelligence and Computing, DataCom 2016 and 2016 IEEE Cyber Science and Technology Congress, CyberSciTech 2016, DASC-PICom-DataCom-CyberSciTech 2016
A2 - Wang, Kevin I-Kai
A2 - Jin, Qun
A2 - Bhuiyan, Md Zakirul Alam
A2 - Zhang, Qingchen
A2 - Hsu, Ching-Hsien
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 8 August 2016 through 10 August 2016
ER -