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Performance analysis of an efficient object-based schema oriented data storage system handling health data

机译:处理健康数据的高效对象模式的数据存储系统性能分析

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摘要

Object-based cloud storage system has an important role in handling big data. All available cloud storage systems deal with scalability, reliability or durability issues. However, there is lack of work addressing data variety. In a previous paper, a basic architecture of an object-based schema oriented data storage system has been proposed which stores data in an encapsulated way. The system comprises account layer, container layer, object layer, database layer and schema layer. In this paper, the architecture proposed in our previous paper has been elaborated. For example, the communication protocols of the proposed system are explained. Moreover, this architecture is realized to test its effectiveness on health data in terms of query execution performance and flexibility on the basis of four different queries of database computation (e.g., append, read, aggregate and delete). The result set are collected on three types of datasets (table, document, file) taken from healthcare scenario. Each type of dataset consists of four different sets of data records. The performance is compared with Amazon S3 (i.e., bucket oriented object-based data storage system) and Microsoft Azure (i.e., account-container oriented object-based data storage system). Flexibility property is also analyzed with respect to these three database operations (i.e., READ, WRITE and DELETE) on three types of experimental datasets (table, document, file) with Amazon S3.
机译:基于对象的云存储系统在处理大数据方面具有重要作用。所有可用的云存储系统处理可扩展性,可靠性或耐用性问题。但是,缺乏工作解决数据品种。在先前的论文中,已经提出了基于对象的模式定向数据存储系统的基本架构,其以封装的方式存储数据。该系统包括帐户层,容器层,对象层,数据库层和模式层。在本文中,我们在我们之前提出的架构中已经详细阐述。例如,解释所提出的系统的通信协议。此外,这种架构实现了在查询执行性能和灵活性的基础上,在数据库计算的四个不同查询的基础上测试其对健康数据的有效性(例如,附加,读取,聚合和删除)。结果集在从HealthCare情景中采取的三种类型的数据集(表,文档,文件)上收集。每种类型的数据集由四组不同的数据记录组成。将性能与亚马逊S3(即,桶导向的基于对象的数据存储系统)和Microsoft Azure(即,基于帐户容器面向对象的数据存储系统)进行比较。还针对这三种数据库操作(即,读取,写入和删除)在具有Amazon S3的三种类型的实验数据集(表,文档,文件)上的这三种数据库操作(即读取,写和删除)分析了灵活性。

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