Name
Abstract | ||
|---|---|---|
The recent rapid increase in the amount of data to be processed has led to the increased use of dispersed parallel processing of large-scale data analysis using open-source Hadoop's MapReduce framework. The large-data processing method proposed by Google and Hadoop which implemented this are representative dispersed parallel processing methods, and the data are dispersedly saved on the HDFS(Hadoop Distributed File System). Such HDFS uses its own indexing technique when it comes to searching specific values from the saved files. Techniques that use conventional index, however, leads to problems like reduced search performance by not considering update and saving index in the disc. Therefore, the paper proposes effective DB indexing technique on Hadoopbased database. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-981-10-7605-3_15 | ADVANCES IN COMPUTER SCIENCE AND UBIQUITOUS COMPUTING |
Keywords | DocType | Volume |
Hadoop,Indexing technique,BigData,DB index,B plus -tree | Conference | 474 |
ISSN | Citations | PageRank |
1876-1100 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jae-Sung Shim | 1 | 1 | 1.71 |
| Young-Hwan Jang | 2 | 0 | 1.69 |
| Yong-Wan Ju | 3 | 1 | 2.04 |
| Seok Cheon Park | 4 | 33 | 5.55 |