Revisiting Secondary Indexing in LSM-based Storage Systems with Persistent Memory.

LSM-based storage systems are widely used for superior write performance on block devices. However, they currently fail to efficiently support secondary indexing, since a secondary index query operation usually needs to retrieve multiple small values, which scatter in multiple LSM components. In this work, we revisit secondary indexing in LSM-based storage systems with byte-addressable persistent memory (PM). Existing PM-based indexes are not directly competent for efficient secondary indexing. We propose PERSEID, an efficient PM-based secondary indexing mechanism for LSM-based storage systems, which takes into account both characteristics of PM and secondary indexing. PERSEID consists of (1) a specifically designed secondary index structure that achieves high-performance insertion and query, (2) a lightweight hybrid PM-DRAM and hash-based validation approach to filter out obsolete values with subtle overhead, and (3) two adapted optimizations on primary table searching issued from secondary indexes to accelerate non-index-only queries. Our evaluation shows that PERSEID outperforms existing PM-based indexes by 3-7x and achieves about two orders of magnitude performance of state-of-the-art LSM-based secondary indexing techniques even if on PM instead of disks.