B+-tree Index Optimization by Exploiting Internal Parallelism of Flash-based Solid State Drives

Previous research addressed the potential problems of the hard-disk oriented design of DBMSs of flashSSDs. In this paper, we focus on exploiting potential benefits of flashSSDs. First, we examine the internal parallelism issues of flashSSDs by conducting benchmarks to various flashSSDs. Then, we suggest algorithm-design principles in order to best benefit from the internal parallelism. We present a new I/O request concept, called psync I/O that can exploit the internal parallelism of flashSSDs in a single process. Based on these ideas, we introduce B+-tree optimization methods in order to utilize internal parallelism. By integrating the results of these methods, we present a B+-tree variant, PIO B-tree. We confirmed that each optimization method substantially enhances the index performance. Consequently, PIO B-tree enhanced B+-tree's insert performance by a factor of up to 16.3, while improving point-search performance by a factor of 1.2. The range search of PIO B-tree was up to 5 times faster than that of the B+-tree. Moreover, PIO B-tree outperformed other flash-aware indexes in various synthetic workloads. We also confirmed that PIO B-tree outperforms B+-tree in index traces collected inside the Postgresql DBMS with TPC-C benchmark.Comment: VLDB201

Ssd Flash Drives Used to Improve Performance with Clarity Data Warehouse

Since the introduction of solid-state devices (SSD), both storage area network (SAN) administrators and database administrators (DBA) have imagined the performance gains promised by replacing hard disk drives (HDD). The initial testing in the laboratory did not promise those gains in the real world. The SSD vendors worked between 2007 and 2010 to improve performance, which in industry standard tests showed steady progress. Despite the gains in the laboratory, there were few examples of real world usage particularly in the field of data warehousing. The process of extracting, transforming and loading (ETL) places extreme loads on the ability of the storage device to update data. This paper studies the effect on one such data warehouse