Log-Structured Merge-tree (LSM-tree) organizes write-friendly and hierarchical structure, which leads to inevitable disk I/O from data compaction occuring between layers. Previous research tried to reduce write bottlenecks of LSM-tree by using non-volatile memory (NVM) to LSM-tree, but write amplification on compaction does not resolved. In this paper, we present tiered LSM (TLSM), a persistent LSM-based key-value database tiering NVM, which is regarded as fast storage device. Our design aims to exploit multi-layered LSM system utilizing NVM and reduce redundant cost on compaction. We address 4 key points: (1) analysis of disk I/O overhead on current LSM-tree, (2) novel design of TLSM preserving the concept of LSM-tree and utilizing NVM, (3) persistent and byte-addressable data compaction minimizing disk write, and (4) tiering policy for increasing usability to TLSM. To implement TLSM-tree, we extended LevelDB, which is a simple LSM-based key-value store. On micro-benchmark DB Bench, the write and read latencies of TLSM are improved up to 34% and 57%, respectively, compared to those of LevelDB-NVM. In evaluation of YCSB, TLSM also reduces the write and read latencies of existing LevelDB up to 25%, 33%, respectively. Furthermore, frequency of write stall and total amount of data write are reduced significantly in TLSM.
Bibliographical noteFunding Information:
This work was supported by the Institute for Information and Communications Technology Promotion (IITP) funded by the Korea Government, Ministry of Science and ICT (MSIT), through the SW Starlab Research and Development of the High Performance In-Memory Distributed Database Management System Based on Flash Memory Storage in the IoT Environment, under Grant IITP-2017-0-00477.
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Materials Science(all)