摘要在科技成指数形式发展的当下，网络的发展更是势不可挡。由网络产生的信息犹如原子弹爆炸后腾空的蘑菇云迅速弥漫开来。这对于处理信息的效率和方法有了更高的要求。在我们真正走进“大数据”时代时，更有效的计算方法成了我们追求的目标。82429

在监控的交通卡口捕捉公安机关调查的伴随车辆，由于数据庞大，产生极速而需要更高效的方法去挖掘。在密集的数据中时间、伴随卡口数成了判定伴随行的重要依据。一分钟内通过相同卡口，且行驶轨迹相同的，这样的卡口数不低于5个时，可判定为伴随车。实现方法是，定义一个一分钟的时间窗口，窗口滑动，每滑动出一辆车，那么这辆车就于原来窗口里的车形成伴随关系。

毕业论文关键词  伴随车辆  hadoop  HBase   

毕业设计说明书外文摘要

Title       Anaylsis Of Traffic Big Data In Real-Time                     

Abstract In the exponential form of the development of science and technology today, network development is a trend which cannot be halted。 Produced by the network information like the atomic bomb explosion vacated the mushroom cloud rapidly spread。 There is a higher requirement for the efficiency and method of processing information。 When we really into the big data era, more effective calculation method has become the goal we pursue。

In the monitoring of traffic bayonet catch public security agencies in the investigation with the vehicle, due to the huge amount of data, resulting in speed and more efficient method to mining。 Time, in dense data with the number of the bayonet accompanying with an important basis for judging。 A minute through the same bayonet, and driving the same trajectory, so that the number of bayonet of not less than five, it can determine with a car。 The implementation method is to define a one minute time window, the window sliding, each slide out of a car, then the car is in the original window of the car to form a concomitant relationship。

Keywords  Accompanying vehicle    hadoop     HBase

目   次

1 绪论 1

1。1 研究背景 1

1。2 研究现状 1

2 相关技术 3

2。1 相关算法 3

2。2 相关工具 7

3 设计需求 10

3。1 问题描述 10

3。2 功能描述 10

3。3 数据描述 10

4 程序框架 13

5 系统实现 15

5。1 环境搭建 15

5。2 数据分析与处理 hadoop+HBase实时交通大数据分析:http://www.youerw.com/jisuanji/lunwen_96724.html