| With the development of the enterprise information, more and more logistics enterprises varied gradually from traditional manual records management into the computer information management. Transport vehicle monitoring of the logistics enterprises also started real-time tracking and precise management. In order to achieve such a goal, real-time status information of the vehicle must be constantly collect. As time goes by, a logistics enterprise which contains a large number of transport vehicles, produce huge amounts of monitoring data. It would be difficult to meet the needs of system if still using the traditional database storage and query.Hadoop is a new software framework for distributed storage and processing large data. Data can be processed reliably and efficiently by using the characteristics of the cluster. Anyone can set up a cluster as well as high-performance server, using existing idle equipment or low configuration of equipment through the Hadoop, which contributed in lower overall system cost, and users don’t need to know the distributed low-level details, direct development of distributed application, easy to use. Manage the massive monitoring data with Hadoop help to meet the needs of systems better. This article is based on an existing logistics vehicle monitoring management system. Hadoop cluster technology is used to replace the old traditional database system to manage data. A cluster environment containing three nodes is built under the existing condition. Considering the characteristics of the monitoring data, the distributed database HBase which supports real-time read and write is chosen. And redesign the data format of monitoring data. Using MapReduce to analyze and process the monitoring data. Combining the traditional system with Hadoop, the new system can make more efficient management of the transport logistics vehicle monitoring data. The comparison experiment tests show that new system can meet the users’ demand better. |
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