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大数据在智能交通领域已经得到广泛应用,随着经济快速发展,城市机动车保有量持续增加,不仅加大了交通管理的难度,而且因此而产生的海量过车数据也面临着如何存储和高效应用等难题。为了能够解决上述问题,使得海量数据能够方便存储、快速检索、高效的研判分析,目前市场上推出了交通大数据系统解决方案。系统基于大规模集群上的分布式并行运算,在工作调度、负载平衡、容错容灾等方面都进行了深入的研究,并形成了一套便于开发、灵活定制、
Big data has been widely used in the field of intelligent transportation. With the rapid economic development, the increasing number of urban motor vehicles has not only increased the difficulty of traffic management, but also resulted in massively passing data that is also faced with how to store and efficiently Application problems. In order to solve the above problems, mass data can be conveniently stored, quickly retrieved, and highly effective analysis and judgment. At present, a solution for traffic big data system is introduced on the market. Based on the distributed parallel computing on large-scale clusters, the system has conducted in-depth research on work scheduling, load balancing, fault tolerance and disaster recovery, and has formed a set of tools that are convenient for development, flexible customization,