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

Akihiko Hamada, Hiroki Matsutani
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引用次数: 1

Abstract

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.
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面向列数据库的硬件缓存机制和网卡的设计与实现
近年来,人们对如何有效利用大数据进行了大量研究。为了存储和处理大数据,具有高度水平可扩展性的结构化存储(nosql)引起了人们的广泛关注。键值存储和面向列的存储是结构化存储的著名例子。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)。本文提出了一种基于FPGA网卡的硬件缓存机制来加速面向列的数据库。在本文中,假定运行在数据库服务器上的面向列的存储由客户端通过网络访问。本文通过引入基于fpga的10GbE网络接口(NIC)和在网卡上实现的硬件缓存机制(HBC)来提高面向列存储的性能和功耗效率。HBC将查询结果(排序行)以键值形式存储在FPGA网卡上实现的DRAM中,如果查询结果已经缓存,则可以立即将请求的数据返回给客户端。现有旨在通过硬件加速结构化存储的工作只关注键值存储,而支持范围查询(扫描操作)的面向列的存储还没有得到解决。HBC部署了一些方法来处理数据映射和缓存的范围查询,这些方法使用可以用二叉树形式表示的特定数据结构,本文展示了HBC可以通过硬件加速范围查询。在本文的实验中,HBase运行在应用层上,而HBC是在基于fpga的网卡上实现的。本文表明,采用该方法可以提高电源效率和显著改善性能,并讨论了该方法的优缺点。
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