Browse > Article
http://dx.doi.org/10.6109/jkiice.2015.19.9.2064

Web Service Performance Improvement with the Redis  

Kim, Chul-Ho (Department of Software, Graduate School of Information Science, Soongsil University)
Park, Kyeong-Won (Department of Software, Graduate School of Software Soongsil University)
Choi, Yong-Lak (Department of Software, Graduate School of Software Soongsil University)
Abstract
To improve performance, most of Web Services produce and manage User Access Logs. Through the Access Logs, the record provides information about time when the most traffic happens and logs and which resource is mostly used. Then, the log can be used to analyze. However, in case of increasing high traffics of Web Services at the specific time, the performance of Web Service leads to deterioration because the number of processing User Access Logs is increasing rapidly. To solve this problem, we should improve the system performance, or tuning is needed, but it makes a problem cost a lot of money. Also, after it happens, it is not necessary to build such system by spending extra money. Therefore, this paper described the effective Web Service's performance as using improved User Access Log performance. Also, to process the newest data in bulk, this paper includes a method applying some parts of NoSQL using Redis.
Keywords
Redis; RDBMS; NoSQL; Web Services;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Hyung-Nam Shim, TK-Indexing:An Indexing Method for SNS Data Based on NoSQL, 2012
2 Terminology Dictionary in MK, http://dic.mk.co.kr/menu New2006/desc.php?dic_key=1765, 2014
3 PostgreSQL, http://wikipedia.org, 2014
4 http://www.postgresql.org, 2014.
5 http://ko.wikipedia.org/wiki/database schema, 2014
6 Jung Gyeong Seok, This is Redis, 2013.11
7 http://redis.io, 2014.09
8 Park, Joon Seok, Design and Implementation of Web- Application Framework for Classroom Management using REDIS, 2014
9 Kang Dae Myeong, Operation Management of Redis, 2014.03
10 Ko,Seon Pil, A Study on the non-relational database for big data of NoSQL, 2012