Optimization of a multiversion index on SSDs to improve system performance

In this paper, we propose a multiversion index utilizing key features of SSDs (solid state drives). SSDs have many advantages, e.g., fast read/write performance, high energy efficiency, and non-volatility. Thus, SSDs have been considered for several years as a promising alternative to HDDs (hard disk drives). Many studies have made progress in optimizing and modifying HDD-based database management system (DBMS) to suit SSDs. In the case of multiversion databases, which manage not only keys and but also versions, research optimizing SSD query processing has been ignored in comparison with single versioned databases. Generally, the multiversion databases manage an evolving data which is processed in a cyber physical system or an accounting system. Therefore, the data is large and the index structure requires frequent rearrangement of its structure to maximize efficiency, which is called structure modification operation. The multiversion index based on HDDs utilizes random writes to conduct the structure modification operation. This feature can introduce crucial performance problems on SSDs, because the speed of random writes on SSDs is much slower than the speed of sequential writes. We propose a Bulk Split multiversion tree (BSMVBT) index that utilizes sequential pattern I/O and out-of-place updates of SSDs. Experimental results showed that it is 10% – 30% faster than the compared version.