Searching Algorithm in a nonrelational database

Roman Ceresnák, Michal Kvet, K. Matiaško
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Abstract

The problem of the data growth and it is storing to the nonrelational data-bases is related to their decreasing efficiency of searching. Nowadays, a very popular database in memory will help us with decreasing the efficiency of the operation searching in this paper. This paper examines the data search-ing in applications hosted in cloud service Amazon with using of nonrela-tional database DynamoDB. It develops new procedures to provide faster response to user and to obtain the data using of nonrelational database Dy-namoDB, that will provide the demanded data and subsequently, it will transfer them to the memory. The given procedure is based on two methods. The first method is a recognition of values, to which the user refers and the provision of this data to the database in memory. The second method is re-lated to the automatic storing of the data transferred to the database in memory. We perform various experiments in the paper, which are showing us a border of efficiency respectively inefficiency from a time perspective.
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非关系型数据库中的搜索算法
数据增长和存储到非关系型数据库的问题与它们的搜索效率下降有关。如今,内存中非常流行的数据库将帮助我们降低本文中的操作搜索效率。本文研究了使用非关系型数据库 DynamoDB 在亚马逊云服务托管的应用程序中进行数据搜索的问题。它开发了新的程序,为用户提供更快的响应,并使用非关系型数据库Dy-namoDB获取数据,该数据库将提供所需的数据,并随后将其传输到内存中。该程序基于两种方法。第一种方法是识别用户所指的值,并将这些数据提供给内存中的数据库。第二种方法是自动将传输到内存数据库的数据存储起来。我们在论文中进行了各种实验,从时间角度看,这些实验向我们展示了效率和低效率的边界。
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