A Read-Optimized Index Structure for Distributed Log-Structured Key-Value Store

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.This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2013R1A1A2059663). This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ICT/SW Creative Research program (NIPA-2014-H0502-14-3015) supervised by the NIPA (National IT Industry Promotion Agency)