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Design and implementation of monitoring data storage and processing scheme based on distributed computing

机译:基于分布式计算的监控数据存储与处理方案的设计与实现

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The monitoring system in cloud computing environment will generate a large number of monitoring data in real time, how to achieve efficient storage and processing of monitoring data in the big data environment is particularly important. To solve this problem, a scheme of monitoring data storage and processing based on Hadoop is proposed. The scheme adopts the HBase database to store the timing monitoring data, and enhance the field method of wide table storage model improved HBase database to improve storage efficiency monitoring data; the traffic data, using MapReduce distributed computing to improve the processing efficiency. The experimental results show that the scheme is scientific and effective, and it can improve the processing speed of the monitoring system under the massive monitoring data, and solve the bottleneck problem of the monitoring data in the cloud computing environment.
机译:云计算环境中的监控系统将实时生成大量监控数据,如何在大数据环境中实现监控数据的高效存储和处理尤为重要。针对这一问题,提出了一种基于Hadoop的数据存储和处理监控方案。该方案采用HBase数据库存储时序监控数据,并通过改进宽表存储模型的现场方法改进了HBase数据库,以提高监控数据的存储效率;交通数据,使用MapReduce分布式计算来提高处理效率。实验结果表明,该方案是科学有效的,可以提高海量监控数据下监控系统的处理速度,解决了云计算环境下监控数据的瓶颈问题。

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