Precise data access on distributed log-structured merge-tree

Log-structured merge tree decomposes a large database into multiple parts: an in-writing part and several read-only ones. It achieves high write throughput as well as low read latency. However, read requests have to go through multiple structures to find the required data. In a distributed database system, different parts of the LSM-tree are stored distributedly. Data access issues extra network communications for a server in the query layer to pull entries from the underlying storage layer. This work proposes the precise data access strategy. A Bloom filter-based structure is designed to test whether an element exists in the in-writing part of the LSM-tree. A lease-based synchronization strategy is used to maintain consistent copies of the Bloom filter on remote query servers. Experiments show that the solution has 6 $$\times $$ throughput improvement over existing methods.