Bloom Merge Strategies for Sustainable SSD Endurance in Write-Intensive LSM-Trees

LSM-Tree is a critical data structure designed for write-optimized, user-facing key-value databases. However, LSM-Trees must frequently perform data merge operations to maintain read efficiency and discard obsolete data. These operations generate a considerable amount of write activity on the storage device (e.g., an SSD), which can drastically reduce the device’s lifespan. Often, these merges involve rewriting data that has not changed, a process that could be avoided. Recognizing this, we introduce “Bloom Merge,” an innovative merge strategy for LSM-Trees specifically developed for SSD. Based on the key distribution in LSM-Tree’s SSTables, this method selectively and efficiently perform merges, only when necessary. It also mitigates the potential negative impact on read performance through the strategic use of in-memory Bloom Filters. We present several key insights into determining the optimal conditions for merging and outline strategies that achieve a balanced improvement in both read and write performance. Our evaluation demonstrates that Bloom Merge significantly enhances write efficiency while reducing unnecessary operations.