Design And Implementation Of The Massive Bayonet Data Stroage And Query System Based On Solr

In recent years, with the development of economy and society, more and more serious traffic problems appered in cities. In order to regulate the behavior of people and safeguard social order, more and more traffic bayonet equipment installed on the road. However,numbers of bayonet equipments send data to the server in real time,and data is growing exponentially, traditional storage architectures can't able to store huge amounts of data. Thus it is not realistic for the users to perform fast and accurate information via the original system. The solution is to use big data platform,.Using this technology can not only solve the problem of massive amounts of data stored in real-time, but also ables its the users to easily search information quickly and accurately. In order to solve this problem, we have to adopted big data platform solutins,which is based on Hadoop,HBase,Solr.This article focused on two main issues, mass data storage and query massive data. As HBase is used to store mass data and HBase is depended on Hadoop, we should build a distributed file storage system based on Hadoop. The search is based on Solr and HBase, while using Oracle in certain circumstances, therefore we should design a middleware software, which is used to clean data and dispatch data. To solve high concurrent user requests, we have set up Solr cluster and HBase cluster, so we can scattered pressure to each node, in addition, we should continue to carry out parameter optimization based on our experience, and strive to improve the system stability and efficiency.Finally, we set up a simulated cluster environment,deploy the three major platforms on it, and simulate the massive data storage and query according to real data. By analyzing test results,we make the optimization process, and verify the feasibility of the system.