BDGS: A Scalable Big Data Generator Suite in Big Data Benchmarking

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Provided by: Chinese Academy of Sciences
Topic: Big Data
Format: PDF
Data generation is a key issue in big data benchmarking that aims to generate application-specific data sets to meet the 4V requirements of big data. Specifically, big data generators need to generate scalable data (Volume) of different types (Variety) under controllable generation rates (Velocity) while keeping the important characteristics of raw data (Veracity). This gives rise to various new challenges about how the people design generators efficiently and successfully. To date, most existing techniques can only generate limited types of data and support specific big data systems such as Hadoop.
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