Cloud storage log data analysis method

A data analysis and cloud storage technology, applied in the field of data analysis, can solve the problems of more time-consuming, large amount of calculation, and increased amount of calculation, and achieve the effect of shortening mining time, simplifying the calculation process, and reducing the amount of calculation.

A data analysis and cloud storage technology, applied in the field of data analysis, can solve the problems of more time-consuming, large amount of calculation, and increased amount of calculation, and achieve the effect of shortening mining time, simplifying the calculation process, and reducing the amount of calculation.

CN103995828AInactive Publication Date: 2014-08-20XIDIAN NINGBO INFORMATION TECH INST
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  • Cloud storage log data analysis method
  • Cloud storage log data analysis method

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Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0040] Such as figure 2 Shown cloud storage log data analysis method, it comprises the steps:

[0041] Step 1. Pre-analyze the cloud storage log data, that is, delete the duplicate data in the log data and fill in the missing data in the log data;

[0042] Step 2. Calculate the pre-analyzed cloud storage log data to obtain the frequent itemsets required to generate the association criteria. In this step 2, the frequent itemsets required to generate the association criteria are obtained through the following steps:

[0043] Step 2a, use the pre-analyzed cloud storage log data to generate candidate 1-itemset matrix C 1 :

[0044] Candidate 1-itemset matrix The matrix is ​​a matrix with m rows and n columns, c ij is the element of row i and column j of the matrix, and i and j are candidate 1-itemset matrix C 1 The location index of , wher...

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Abstract

The invention relates to a cloud storage log data analysis method. The method includes the steps that firstly, preanalysis is conducted on cloud storage log data; secondly, the cloud storage log data obtained after preanalysis are calculated, so that a frequent item set required for generating a relation maxim is obtained; thirdly, according to the frequent item set obtained in the second step, the relation maxim of cloud storage logs is generated; fourthly, the relation maxim obtained in the third step is output. According to the method, the frequent item set is simplified, so that the scale of a generated candidate item set matrix is reduced, and the number of candidate item sets generated in the following iterative computation process is effectively reduced; in addition, by the improvement of the technical scheme, the candidate item set matrix is computed through user-defined matrix operations, the whole computation process is relatively simple, the computation amount of the data analysis process can be reduced, and excavation time is shortened.

Description

technical field [0001] The invention belongs to the technical field of data analysis, and in particular relates to a cloud storage log data analysis method, which can be used for data analysis of cloud storage system logs. Background technique [0002] During the operation of the cloud storage system, a large number of log files will be generated. These log files record the operation of the system by the system administrator, the access of the user to the system, and various original information such as system server reception, analysis requests, and runtime errors. Data analysis of system administrator operation logs can standardize administrator operations; data analysis of user access logs can discover user behavior habits, which is conducive to querying and analyzing user operations and improving user satisfaction; cloud storage Data analysis of server logs can detect system status, troubleshoot network faults, implement intrusion detection, and discover design defects,...

Claims

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Application Information

Patent Timeline
20 Aug 2014
Publication
CN103995828A
IPC
G06F17/30; G06F11/34; H04L29/08
CPC
G06F16/1748; G06F16/1815; H04L67/1097
Inventors
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