OpenKV: LSM-tree-based key-value store for open-channel SSD

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https://hdl.handle.net/2142/106349

Title: OpenKV: LSM-tree-based key-value store for open-channel SSD
Author(s): Wang, Xiaohao
Issue Date: 2019-11-19
Director of Research (if dissertation) or Advisor (if thesis): Huang, Jian
Department of Study: Electrical & Computer Eng
Discipline: Electrical & Computer Engr
Degree Granting Institution: University of Illinois at Urbana-Champaign
Degree Name: M.S.
Degree Level: Thesis
Keyword(s): Key-Value Store, Cuckoo Filter, Open-Channel SSD
Abstract: Log-structured merge (LSM) tree-based key-value stores, such as LevelDB and RocksDB, have seen great adoption in industry due to their high write speed. However, one major issue with LSM-based databases is the high write amplification. The root cause of this problem is the LSM tree structure that demands each level to be completely sorted. In this work, we propose OpenKV, a novel key-value store for open-channel SSD that achieves very low write amplification with good read performance. We propose a design with partially sorted levels with lazy compaction to reduce write amplification, and we have designed a central lookup table based on the cuckoo filter to utilize the open-channel SSD's direct page-level access. In our evaluation we show that compared to LevelDB, our design can reduce write traffic by 2.6x to 3.5x while improving random read performance by up to 1.8x.
Graduation Semester: 2019-12
Type of Resource: text
Permalink: http://hdl.handle.net/2142/106349