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Storing and Handling Complex Content for Large-scale Data

Hong Li Xu, Hong Hua Jiang, Qiu Lan Wu, and Yuan Yuan Wang
College of Information Science and Engineering, Shan Dong Agricultural University, Shandong Taian 271018, China
Abstract—At present, the increasing growth and pervasive development of mass data raise the challenge for big data storage. When it came to large-scale data, storage and handing method of complex data were the key problems to be settled. From big data source, we studied several problems of massive data: the big data platform framework and landing, the storage mechanism and data handling of large-scale data, the node-fault handling of mapreduce and pregel superstep, spark streaming based on the storage memory, and BlueDBM-The other forms of memory storage in massive data etc. It offered storing and handling complex content for large-scale data and support the further research of big data technical challenges, support for the application of it.
Index Terms—big data platform; node fault-tolerant; streaming data handing; BlueDBM

Cite: Hong Li Xu, Hong Hua Jiang, Qiu Lan Wu, and Yuan Yuan Wang, "Storing and Handling Complex Content for Large-scale Data," Journal of Communications, vol. 13, no. 12, pp. 763-768, 2018. Doi: 10.12720/jcm.13.12.763-768
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