A new middleware for distributed data processing in CUBRID DBMS

Hyeong Il Kim; Min Yoon; Mun Chul Choi; Jae Woo Chang

doi:10.1016/j.procs.2015.05.066

A new middleware for distributed data processing in CUBRID DBMS

Hyeong Il Kim
, Min Yoon
, Mun Chul Choi
, Jae Woo Chang^*

^*Corresponding author for this work

Jeonbuk National University

Research output: Contribution to journal › Conference article › peer-review

3 Scopus citations

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.

Original language	English
Pages (from-to)	654-658
Number of pages	5
Journal	Procedia Computer Science
Volume	52
Issue number	1
DOIs	https://doi.org/10.1016/j.procs.2015.05.066
State	Published - 2015
Event	The International Conference on Ambient Systems, Networks and Technologies, ANT-2015, the International Conference on Sustainable Energy Information Technology, SEIT-2015 - London, United Kingdom Duration: 2015.06.2 → 2015.06.5

Keywords

CUBRID;
Distributed environment
Middleware
Parallel query processing

Quacquarelli Symonds(QS) Subject Topics

Computer Science & Information Systems

Access to Document

10.1016/j.procs.2015.05.066

Cite this

@article{9144dfa27b1f424a80b2fa51f3eae4fb,

title = "A new middleware for distributed data processing in CUBRID DBMS",

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.",

keywords = "CUBRID;, Distributed environment, Middleware, Parallel query processing",

author = "Kim, \{Hyeong Il\} and Min Yoon and Choi, \{Mun Chul\} and Chang, \{Jae Woo\}",

note = "Publisher Copyright: {\textcopyright} 2015 The Authors. Published by Elsevier B.V.; The International Conference on Ambient Systems, Networks and Technologies, ANT-2015, the International Conference on Sustainable Energy Information Technology, SEIT-2015 ; Conference date: 02-06-2015 Through 05-06-2015",

year = "2015",

doi = "10.1016/j.procs.2015.05.066",

language = "English",

volume = "52",

pages = "654--658",

journal = "Procedia Computer Science",

issn = "1877-0509",

number = "1",

}

TY - JOUR

T1 - A new middleware for distributed data processing in CUBRID DBMS

AU - Kim, Hyeong Il

AU - Yoon, Min

AU - Choi, Mun Chul

AU - Chang, Jae Woo

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

KW - CUBRID;

KW - Distributed environment

KW - Middleware

KW - Parallel query processing

UR - https://www.scopus.com/pages/publications/84939170763

U2 - 10.1016/j.procs.2015.05.066

DO - 10.1016/j.procs.2015.05.066

M3 - Conference article

AN - SCOPUS:84939170763

SN - 1877-0509

VL - 52

SP - 654

EP - 658

JO - Procedia Computer Science

JF - Procedia Computer Science

IS - 1

T2 - The International Conference on Ambient Systems, Networks and Technologies, ANT-2015, the International Conference on Sustainable Energy Information Technology, SEIT-2015

Y2 - 2 June 2015 through 5 June 2015

ER -

A new middleware for distributed data processing in CUBRID DBMS

Abstract

Keywords

Quacquarelli Symonds(QS) Subject Topics

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