REMIX: Efficient Range Query for LSM-trees


Wenshao Zhong, Chen Chen, and Xingbo Wu, University of Illinois at Chicago; Song Jiang, University of Texas at Arlington


LSM-tree based key-value (KV) stores organize data in a multi-level structure for high-speed writes. Range queries on traditional LSM-trees must seek and sort-merge data from multiple table files on the fly, which is expensive and often leads to mediocre read performance. To improve range query efficiency on LSM-trees, we introduce a space-efficient KV index data structure, named REMIX, that records a globally sorted view of KV data spanning multiple table files. A range query on multiple REMIX-indexed data files can quickly locate the target key using a binary search, and retrieve subsequent keys in sorted order without key comparisons. We build RemixDB, an LSM-tree based KV-store that adopts a write-efficient compaction strategy and employs REMIXes for fast point and range queries. Experimental results show that REMIXes can substantially improve range query performance in a write-optimized LSM-tree based KV-store.

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@inproceedings {264856,
author = {Wenshao Zhong and Chen Chen and Xingbo Wu and Song Jiang},
title = {{REMIX}: Efficient Range Query for {LSM-trees}},
booktitle = {19th USENIX Conference on File and Storage Technologies (FAST 21)},
year = {2021},
isbn = {978-1-939133-20-5},
pages = {51--64},
url = {},
publisher = {USENIX Association},
month = feb

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