Massive Parallel Join in NUMA Architecture

Abstract

Advance in hardware technology and growing demands for fast response of database application have led to active research in In-Memory Database (IMDB). Compared to traditional on-disk database, IMDB has advantages such as faster access to storage and simpler internal optimization algorithms. Because of the importance of join operation in database system, join algorithm is always a hot research topic and many join algorithms have been proposed for distributed database system. Nevertheless, due to the nature of memory access in Non-Uniform Memory Access (NUMA) architecture, most existing join algorithms for classic Symmetric Multi-Processing (SMP) architecture cannot be applied to NUMA architecture directly. In this work, we present the Distributed Bitmap Join algorithm designed exclusively for IMDB in NUMA architecture. This Distributed Bitmap Join algorithm aims at improving the overall performance for groups of queries, rather than just one single query, by utilizing bitmap to reduce the communication cost in NUMA architecture. The comparative experiments of Distributed Bitmap Join algorithm against no-partition hash join show that although no-partition hash join algorithm is faster than Distributed Bitmap Join in single query case, our algorithm outperforms it for a group of queries.