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Open Source Big Data Analytics Frameworks Written in Scala

机译:用Scala编写的开源大数据分析框架

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Frameworks for big data arguably began with Google's use of MapReduce. Since then, a huge amount of progress has been made in the development of big data frameworks, many of which have been released as open source. Further to increase portability and ease of set-up, many are coded in a Java Virtual Machine (JVM) based language, e.g., Java or Scala. In addition, processing of big data involves the flow of data, and of course, the processing of data as it flows. This computational paradigm is a natural for functional programming. Furthermore, the map, reduce and combiner have analogs in functional programming. There has been a trend in the last few years toward developing open source big data frameworks written in Scala to support big data analytics. Scala is a modern JVM language that supports both object-oriented and functional programming paradigms.
机译:可以说,大数据的框架始于Google对MapReduce的使用。从那时起,大数据框架的开发取得了巨大的进步,其中许多已作为开源发布。为了提高可移植性和设置的便利性,许多语言都使用基于Java虚拟机(JVM)的语言进行编码,例如Java或Scala。另外,大数据的处理涉及数据的流动,当然还涉及数据在流动时的处理。这种计算范例对于函数式编程是很自然的。此外,映射,归约和组合器在功能编程中具有类似物。在过去的几年中,有一种趋势是开发用Scala编写的开源大数据框架,以支持大数据分析。 Scala是一种现代JVM语言,同时支持面向对象和功能编程范例。

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