大数据计算解剖学 (The Anatomy of Big Data Computing)

Advances in information technology and its widespread growth in several areas of business, engineering, medical and scientific studies are resulting in information/data explosion. Knowledge discovery and decision making from such rapidly growing voluminous data is a challenging task in terms of data organization and processing, which is an emerging trend known as Big Data Computing; a new paradigm which combines large scale compute, new data intensive techniques and mathematical models to build data analytics. Big Data computing demands a huge storage and computing for data curation and processing that could be delivered from on-premise or clouds infrastructures. This paper discusses the evolution of Big Data computing, differences between traditional data warehousing and Big Data, taxonomy of Big Data computing and underpinning technologies, integrated platform of Big Data and Clouds known as Big Data Clouds, layered architecture and components of Big Data Cloud and finally discusses open technical challenges and future directions.

翻译：信息技术的进步及其在若干商业、工程、医学和科学研究领域的广泛增长正在导致信息/数据爆炸,从这种迅速增长的大量数据中发现知识和作出决策,在数据组织和处理方面是一项具有挑战性的任务,这是被称为大数据计算的新趋势;一种新的模式,结合大规模计算、新的数据密集型技术和数学模型来建立数据分析;大数据计算需要庞大的储存和计算,用于数据整理和处理,而数据整理和处理可以来自局部或云层基础设施;本文讨论了大数据计算的变化、传统数据仓储和大数据之间的差异、大数据计算和基础技术的分类学、称为大数据云的大型数据和云的综合平台、多层结构以及大数据云的组成部分,并最后讨论了开放的技术挑战和今后的方向。

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从各种各样类型的数据中，快速获得有价值信息的能力，就是大数据技术。明白这一点至关重要，也正是这一点促使该技术具备走向众多企业的潜力。大数据的4个“V”，或者说特点有四个层面：第一，数据体量巨大。从TB级别，跃升到PB级别；第二，数据类型繁多。前文提到的网络日志、视频、图片、地理位置信息等等。第三，价值密度低。以视频为例，连续不间断监控过程中，可能有用的数据仅仅有一两秒。第四，处理速度快。