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Design and implementation of hardware cache mechanism and NIC for column-oriented databases

机译:面向列数据库的硬件缓存机制和NIC的设计和实现

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Recently some researches to utilize big data efficiently have been made vigorously. To store and process big data, structured storages (NOSQLs) that have high degree of horizontal scalability have attracted a lot of attention. Key-value stores and column-oriented stores are known as famous examples of structured storages. Especially, column-oriented stores can store variable numbers of columns for each row while maintaining high scalability. Moreover, range queries (scan operations) are supported in column-oriented stores. This paper proposes hardware cache mechanism using FPGA NIC to accelerate column-oriented databases. In this paper, it is assumed that column-oriented stores running on database servers are accessed by clients via a network. This paper aims to improve performance and power efficiency of column-oriented stores by introducing an FPGA-based 10GbE network interface (NIC) and a hardware cache mechanism (HBC) implemented on the NIC. HBC stores query results (sorted rows) as a key-value form in the DRAM implemented on the FPGA NIC, and the requested data can be returned to clients immediately if the query result has been cached. Existing work that aims to accelerate structured storages by hardware have focused only on key-value stores while column-oriented stores that support range queries (scan operations) have not been addressed. HBC deploys methods that address data mappings and range queries of caches using specific data structures that can be represented in binary-tree forms and this paper shows HBC can accelerate range queries by hardware. In experiments of this paper, HBase is running on an application layer, while HBC is implemented on an FPGA-based NIC. This paper shows that improvement of power efficiency and significant performance improvement can be achieved by the proposed HBC and also pros and cons of the proposed HBC are discussed.
机译:近来,已经进行了一些有效地利用大数据的研究。为了存储和处理大数据,具有高度水平可伸缩性的结构化存储(NOSQL)引起了很多关注。键值存储和面向列的存储被称为结构化存储的著名示例。特别是,面向列的存储可以为每行存储可变数量的列,同时保持高可伸缩性。此外,在面向列的存储中支持范围查询(扫描操作)。本文提出了使用FPGA NIC的硬件缓存机制来加速面向列的数据库。在本文中,假设客户端通过网络访问数据库服务器上运行的面向列的存储。本文旨在通过引入基于FPGA的10GbE网络接口(NIC)和在NIC上实现的硬件缓存机制(HBC)来提高面向列存储的性能和电源效率。 HBC将查询结果(排序的行)作为键值形式存储在FPGA NIC上实现的DRAM中,如果查询结果已被缓存,则所请求的数据可以立即返回给客户端。现有的旨在通过硬件加速结构化存储的工作仅集中在键值存储上,而尚未解决支持范围查询(扫描操作)的面向列的存储。 HBC部署了使用可以以二进制树形式表示的特定数据结构来解决缓存的数据映射和范围查询的方法,并且本文证明了HBC可以通过硬件来加速范围查询。在本文的实验中,HBase在应用程序层上运行,而HBC在基于FPGA的NIC上实现。本文表明,提出的HBC可以实现功率效率的提高和性能的显着提高,并且还讨论了提议的HBC的优缺点。

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