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Open Source Big Data Analytics Frameworks Written in Scala

机译:开源大数据分析框架写在scala

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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:大数据的框架可以使用谷歌的MapReduce使用。从那时起,在大数据框架的发展中取得了大量的进展,其中许多已经被释放为开源。进一步提高可移植性和易于设置,许多人以Java虚拟机(JVM)的语言编码,例如Java或Scala。此外,大数据的处理涉及数据的流程,当然,当它流动时数据处理。这种计算范例是一个自然的功能规划。此外,地图,减少和组合器具有功能规划中的类似物。在过去几年中,迈出了在Scala中编写的开源大数据框架来支持大数据分析的趋势。 Scala是一种现代JVM语言,支持面向对象和功能编程范式。

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