4 research outputs found
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
MPSearch: Multi-Path Search for Tree-based Indexes to Exploit Internal Parallelism of Flash SSDs
Abstract Big data real-time processing aims for faster retrieval of data and analysis. Lately, in order to accelerate real-time processing, big Then we present a new I/O request concept, called psync I/O, that can exploit the internal parallelism of flash SSDs in a single process, and we propose a new search method (MPSearch) that enables tree based indexs to exploit the internal parallelism of flash SSDs. Based on MPSearch, we present a B+-tree variant, PIO B-tree (Parallel I/O B-tree). PIO B-tree enhanced B