Interactive analyzing method for website logs

Abstract

The invention discloses an interactive analyzing method for website logs. A visual analysis system of a log visual data processing system is adopted and comprises three main assemblies including a data preprocessor, a data server and a visual interface assembly module, and an assembly separating strategy is adopted, in other words, all the assemblies of the system can be arranged on a single machine or a cluster. The data preprocessor is used for filtering, washing and extracting data and executing simple data mining operation based on original data. The data preprocessor conducts compiling based on a MapReduce normal form and processes data from a log server. When the process is executed, the data can be divided into sub-data with a file as a unit and sent to a target database. In a system architecture system, the database plays a role of a transfer station and is used for storing intermediate files, namely conversation files.

Description

1. Technical field [0001] The invention belongs to the technical field of computer large-scale data analysis, and in particular relates to an interactive analysis technology for website logs. 2. Background technology [0002] The rapid development of the Internet makes people's study and work more and more dependent on the Internet, especially in the fields of e-commerce and finance. The traditional store transaction model is largely affected by online transactions. The emergence of giant e-commerce websites such as Taobao and JD.com, and online trading websites with sudden traffic such as 12306 not only tests the traditional website architecture technology, but also tests whether merchants can respond to the needs of different groups of websites in a timely and effective manner. Variety. For these large-scale e-commerce websites, the increase in visits makes the log system generate a large number of visit records every day. How to understand users' access behavior patterns...

AI Technical Summary

Problems solved by technology

[0006] 1) In terms of data processing capabilities, in the face of large-scale data sets, traditional technical solutions are difficult to operate and visualize these data friendly in a stand-alone environment, at least the support of high-performance servers is required; 2) In interactive In terms of analysis, traditional technical solutions often only provide statistical charts, and users can only passively accept the statistical charts, which are not very friendly in interactive analysis

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