Name
Abstract | ||
|---|---|---|
With the sharply increasing amount of data, studies on bigdata processing based on NoSQL have been actively done. However, NoSQL cannot satisfy the ACID properties of database transactions. Therefore, bigdata processing based on RDBMS has been spotlighted. CUBRID Shard stores data in the distributed CUBRID servers by dividing the database. However, CUBRID Shard cannot process a query when data of a user is distributed on the multiple CUBRID servers. Therefore, in this paper we propose a CUBRID based middleware which supports distributed data processing. Through the performance evaluations, we show that our proposed scheme shows better performance than the existing work in terms of query processing time. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.procs.2015.05.066 | Procedia Computer Science |
Keywords | Field | DocType |
Middleware,distributed environment,parallel query processing,CUBRID , | Middleware,Middleware (distributed applications),Distributed Computing Environment,Computer science,Server,Shard,NoSQL,Relational database management system,Big data,Database,Distributed computing | Conference |
Volume | ISSN | Citations |
52 | 1877-0509 | 0 |
PageRank | References | Authors |
0.34 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hyeong-Il Kim | 1 | 74 | 11.46 |
| Min Yoon | 2 | 34 | 10.38 |
| MunChul Choi | 3 | 0 | 0.34 |
| Jae-Woo Chang | 4 | 401 | 99.85 |