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A read-optimized index structure for distributed log-structured key-value store

Authors
Kang, In suKim, Bo kyeongLee, Dong ho
Issue Date
Jul-2015
Publisher
IEEE
Keywords
Bigdata; Database; Index; Key-value store; NoSQL; T-tree
Citation
Proceedings - IEEE Computer Society's International Computer Software and Applications Conference, pp 650 - 651
Pages
2
Indexed
OTHER
Journal Title
Proceedings - IEEE Computer Society's International Computer Software and Applications Conference
Start Page
650
End Page
651
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/20239
DOI
10.1109/COMPSAC.2015.85
ISSN
0730-6512
Abstract
Recently, Big Data processing is becoming a necessary technique to efficiently store, manage, and analyze massive data obtained by social media contents. NoSQL is one of databases that efficiently handle Big Data compared to the traditional database that has the limitation to manipulate Big Data. Log-structured key/value store, widely used in NoSQL, basically stores data into the disk storage in batch writing. Since this batch writing of the key/value store does not overwrite data in place, many data are accumulated in several places. Although it improves the write performance, the read performance decreases because the key/value store requires many accesses to widely-spread data. In order to address this problem, we propose T-tree index structure to reduce the search time by avoiding exploring contents stored in distributed many files. Finally, we show the performance improvement through the experimental results. © 2015 IEEE.
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Lee, Dong Ho
ERICA 소프트웨어융합대학 (DEPARTMENT OF ARTIFICIAL INTELLIGENCE)
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