Recently, we have been witnessing huge advancements in the scale of data we routinely generate and collect in pretty much everything we do, as well as our ability to exploit modern technologies to process, analyze and understand this data. The intersection of these trends is what is, nowadays, called Big Data Science. Big Data Science requires scalable architectures for storing and processing data. Cloud computing represents a practical and cost-effective solution for supporting Big Data storage, processing and for sophisticated analytics applications. We analyze in details the building blocks of the software stack for supporting Big Data Science as a commodity service for data scientists. In addition, we analyze and classify the state-of-the-art of big data analytics frameworks, available today mostly on Clouds, based on their supported service models. Furthermore, we provide various insights about the latest ongoing developments and open challenges in this domain.

最近，我们目睹了日常生成和收集的几乎所有工作的数据规模的巨大进步，以及我们利用现代技术处理，分析和理解此数据的能力。这些趋势的交集如今被称为大数据科学。大数据科学需要可扩展的体系结构来存储和处理数据。云计算代表了一种实用且经济高效的解决方案，可支持大数据存储，处理以及复杂的分析应用程序。我们将详细分析用于支持大数据科学作为数据科学家的商品服务的软件堆栈的构建模块。此外，我们根据支持的服务模型对大数据分析框架的最新技术进行了分析和分类，这些框架目前在云上大多可用。此外，我们提供有关该领域最新动态和挑战的各种见解。