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Significance of Restful web services in Bigdata Analytics

机译:大数据分析中宁静的Web服务的意义

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We are in Big Data technology, through which we analysis of the large volume of data like, peta data. Where there are many challenges in bigdata processing like, scalability issues, heterogeneity, error-handling, privacy, timeliness, source, and visualization, at all stages of the data analysis pipeline from data acquisition to final out come of data. To over come above significant problem, the technical challenges are common across a large variety of application domains, and cost-effective tools to addresses with the perspective of one domain itself. Apache Hadoop provide one such solution for above problem, but by analyzing the solution we identify some issues. The better solution for the above issue we purposed a restful web services. The main importance of the Restfulll Web services is scalability and heterogeneity with a variety of platform. In addition by improving MapReduce technique in Reorder phase leads to get a desirable result. In short in this paper we design and develop a framework for Big Data analytics using RestFul Web Services
机译:我们在大数据技术中,通过该数据,通过该数据,我们分析了大量数据,如peta数据。在数据分析流水线的所有阶段都有许多挑战,可扩展性问题,缩放性问题,异质性问题,异质性,错误处理,隐私,及时性,来源和可视化,从数据采集到最后一项数据。到来超越了重大问题,技术挑战在各种应用领域中是常见的,以及通过一个域本身的角度来解决的经济有效的工具。 Apache Hadoop为上述问题提供了一个这样的解决方案,而是通过分析我们确定一些问题的解决方案。我们饰有更好的解决方案,我们饰版了RESTFUL Web服务。 RESTFULLL Web服务的主要重要性是具有各种平台的可扩展性和异质性。另外,通过改进重新排序阶段的Mapreduce技术,以获得期望的结果。简而言之,在本文中,我们使用RESTful Web服务设计和开发大数据分析的框架

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