With the rapid development of smart grids and increasing data collected in these networks, analyzing this massive data for applications such as marketing, cyber-security, and performance analysis, has gained popularity. This paper focuses on analysis and performance evaluation of big data frameworks that are proposed for handling smart grid data. Since obtaining large amounts of smart grid data is difficult due to privacy concerns, we propose and implement a large scale smart grid data generator to produce massive data under conditions similar to those in real smart grids. We use four open source big data frameworks namely Hadoop-Hbase, Cassandra, Elasticsearch, and MongoDB, in our implementation. Finally, we evaluate the performance of different frameworks on smart grid big data and present a performance benchmark that includes common data analysis techniques on smart grid data.

中文翻译：

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评估大数据框架以分析智能电网

随着智能电网的快速发展和在这些网络中收集的数据的增加，分析这些海量数据以用于市场营销，网络安全和性能分析等应用程序已变得越来越流行。本文着重于为处理智能电网数据而提出的大数据框架的分析和性能评估。由于出于隐私考虑，很难获取大量智能电网数据，因此我们建议并实施大型智能电网数据生成器，以在类似于真实智能电网的条件下生成海量数据。我们在实现中使用了四个开源大数据框架，分别是Hadoop-Hbase，Cassandra，Elasticsearch和MongoDB。最后，