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An agricultural data storage mechanism based on HBase

机译:基于HBase的农业数据存储机制

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With the development of agricultural space-time localisation, sensor network and cloud computing, the amount of agricultural data is increasing rapidly and the data structure becomes more complicated and changeable. Currently, the widely used agricultural database is the relational database. This database handles a large amount of data with very limited throughput and is not suitable for organisation and management of distributed data. HBase is a non-relational database of distributed file storage built on Hadoop platform. HBase is suitable for unstructured data storage database and it can handle large volume of data with high scalability. To better store agricultural big data in HBase, we propose a special agricultural data buffer structure which stores data based on the data category and a two-level indexing memory organisation strategy on HBase. The method proposed saves more than a quarter of the time compared to traditional buffering methods. Experimental results show the higher efficiency of the agricultural data buffer structure and memory-organisation strategy.
机译:随着农业时空定位,传感器网络和云计算的发展,农业数据量正在迅速增加,数据结构变得更加复杂和变化。目前,广泛使用的农业数据库是关系数据库。该数据库以非常有限的吞吐量处理大量数据,不适合分布式数据的组织和管理。 HBase是在Hadoop平台上构建的分布式文件存储的非关系数据库。 HBase适用于非结构化数据存储数据库,它可以处理具有高可扩展性的大量数据。为了更好地存储HBase中的农业大数据,我们提出了一种特殊的农业数据缓冲区结构,它基于数据类别存储数据和HBase上的两级索引内存组织策略。与传统的缓冲方法相比,该方法可以节省超过四分之一的时间。实验结果表明,农业数据缓冲区结构和记忆组织策略的效率较高。

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