TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
An Efficient Design and Implementation of an MdbULPS in a Cloud-Computing Environment |
| 영문제목(English Title) |
An Efficient Design and Implementation of an MdbULPS in a Cloud-Computing Environment |
| 저자(Author) |
Myoungjin Kim
Yun Cui
Hanku Lee
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| 원문수록처(Citation) |
VOL 09 NO. 08 PP. 3182 ~ 3202 (2015. 08) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Flexibly expanding the storage capacity required to process a large amount of rapidly increasing unstructured log data is difficult in a conventional computing environment. In addition, implementing a log processing system providing features that categorize and analyze unstructured log data is extremely difficult. To overcome such limitations, we propose and design a MongoDB-based unstructured log processing system (MdbULPS) for collecting, categorizing, and analyzing log data generated from banks. The proposed system includes a Hadoop-based analysis module for reliable parallel-distributed processing of massive log data. Furthermore, because the Hadoop distributed file system (HDFS) stores data by generating replicas of collected log data in block units, the proposed system offers automatic system recovery against system failures and data loss. Finally, by establishing a distributed database using the NoSQL-based MongoDB, the proposed system provides methods of effectively processing unstructured log data. To evaluate the proposed system, we conducted three different performance tests on a local test bed including twelve nodes: comparing our system with a MySQL-based approach, comparing it with an Hbase-based approach, and changing the chunk size option. From the experiments, we found that our system showed better performance in processing unstructured log data.
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| 키워드(Keyword) |
NoSQL
MongoDB
Cloud Computing
Hadoop
Big data processing
Banking System
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| 파일첨부 |
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