Title :
Managing Large Scale Unstructured Data with RDBMS
Author :
Zhe Jiang ; Yi Luo ; Naihu Wu ; Chunjiang He ; Pingpeng Yuan ; Hai Jin
Author_Institution :
Shandong Electr. Power Res. Inst., Jinan, China
Abstract :
With the rapid development of information technology, the needs of unstructured data storage and processing is growing rapidly, which develops a new requirement for the database storage. Traditional row-oriented relational databases appear to be inadequate for the data query and analysis. In this paper, we propose a novel approach to store the unstructured data in a relational database. By splitting the VALUE property of the unstructured KEY/VALUE data and recreating the two-dimensional data, the original data can be stored in relational databases. The system introduced in this paper is designed to handle this task. In addition, this system rebuilds the SQL as its query language, which makes it compatible with relational databases. In experiments of the query for unstructured data, the outcomes show that the system is good at decomposing the SQL statement submitted by users, and generating the corrected sub-query statements. The results of the experiments show that the performance of this system is good.
Keywords :
SQL; data structures; relational databases; storage management; RDBMS; SQL; Structured Query Language; database storage; large scale unstructured data management; relational database; unstructured data processing; unstructured data storage; Dictionaries; Hidden Markov models; Indexes; Memory; Relational databases; Vegetation; Relational database; Unstructured data; column-oriented database; query processing;
Conference_Titel :
Dependable, Autonomic and Secure Computing (DASC), 2013 IEEE 11th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4799-3380-8
DOI :
10.1109/DASC.2013.135