The Design Of Date Processing System For Counting HTTP Statistics Used By Mobile Users

Nowadays, with the development of mobile network, there comes tons ofmassive statistics from users’ online behaviors. There is an increasing need tocollect and analyze these data, come out the issues and put the results intopractice to help with the business activities. The definition of the massivestatistics here mainly refers to the general daily data in a single table with overone million levels that produces large amounts of datain real-time.Largeamounts of data will be generated when a mobile user is accessing the internet.The change of these statistics directly reflects the user’s behavior and needs.Thus, how to accurately classify and analyze the user data in a fast speed hasbecome a new problem to guide the mobile applications and mobile businessactivities. The main part is to save and analyze massive statistics. However, thetelecomindustry has its own set of saving standard and high-performancestorage devices, which always use space to exchange time, that is, to store thedata by a large storage space and establish hvarious data models to process datain order to analyze statistics timely and effectively. But the cost is also huge.In this thesis, the system is mainly designed to focus on low-profile serversystems, which will not cost a lot to purch as ehigh-performance equipment.With the help of some dedicated staffs who are responsible for maintaining data consolidation, the system will count the data accurately and pick up therelevant ones to analyze and demonstrate the result. The Http data processingsystem, which is caused by mobile users’ online behaviors, is a piece of systemthat helps count and summarizes users’ data. It can collect all the data in timeand analyze the statistics effectively, which reduces the artificial gathering timeby human beings and improves the searching accurateness at the same time.Moreover, the system can reflect the real situation of the data in order tofacilitate the staffs to distribute statistics and analyze user behaviors as well.The system in this thesis is based on windows2008server operatingsystem and developed with the help of Microsoft Visual Net platform. All themassive data is collected from the sample of the telecommunications industrydata collection machine. The thesis will illustrate the capabilities and functionsof this system through the data analysis and processes.In this thesis, the mobile users’ calls and internet records intelecommunications industry are mainly usedasthe baseline data. By utilizingORACLE database, the thesis illustrates the statistical processing methods aswell as the applicationof collecting and saving data, which may be a great helpto the storage of massive amounts of data.