Column-Oriented Database Acceleration Using FPGAs
Column-Oriented Database Acceleration Using FPGAs
复制标题
使用 FPGA 进行面向列的数据库加速
DOI：
10.1109/icde.2019.00067
复制
发表时间：
2019
期刊：
影响因子：
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通讯作者：
H. Yoshino
中科院分区：
文献类型：
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作者：
Satoru Watanabe;Kazuhisa Fujimoto;Yuji Saeki;Yoshifumi Fujikawa;H. Yoshino
内存系统是提高列式数据库管理系统性能的一个重要手段。然而，与基于NAND闪存的固态驱动器（SSD）相比，动态随机存取存储器（DRAM）的价格大约高出10倍，能效高出数万倍。为了克服这个缺点，我们开发了一个面向列的数据库管理系统和现场可编程门阵列为基础的加速引擎。我们将它们集成到我们的原型系统FCAccel中。加速引擎可加速从SSD提取数据以进行SQL处理。我们比较了FCAccel与MonetDB、Impala和PostgreSQL的性能。在MonetDB和Impala将所有数据存储在DRAM中，FCAccel将所有数据存储在SSD中的条件下评估了性能。在数据提取方面，FCAccel的性能是MonetDB的0.77至1.79倍，是Impala的4.10至23.4倍。这些实验结果意味着加速引擎可以消除将所有数据存储在DRAM中的必要性。
The in-memory system is promising for improving the performance of column-oriented database management systems (DBMSs). However, in comparison with NAND-flash-based solid-state drives (SSDs), dynamic random access memories (DRAMs) are around ten times more expensive and tens to thousands of times more energy inefficient. To overcome this drawback, we developed a column-oriented DBMS and a field-programmable-gate-array-based acceleration engine. We integrated them in FCAccel, our prototype system. The acceleration engine accelerates data extraction from SSDs for SQL processing. We compared the performance of FCAccel with that of MonetDB, Impala and PostgreSQL. Performance was evaluated under the conditions that MonetDB and Impala stored all data in DRAMs and FCAccel stored all data in SSDs. With regard to data extraction, the performance of FCAccel ranged from 0.77 to 1.79 times in comparison with that of MonetDB and from 4.10 to 23.4 times in comparison with that of Impala. These experimental results imply that the acceleration engine can remove the necessity to store all data in DRAMs.