CN109408640B - Log classification method and device and storage medium - Google Patents
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- CN109408640B CN109408640B CN201811300533.6A CN201811300533A CN109408640B CN 109408640 B CN109408640 B CN 109408640B CN 201811300533 A CN201811300533 A CN 201811300533A CN 109408640 B CN109408640 B CN 109408640B
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Abstract
The invention provides a log classification method, a log classification device and a storage medium. The method realizes the automatic classification of the system to the operation logs, and improves the efficiency of log classification.
Description
Technical Field
The embodiment of the invention relates to the technical field of log classification, in particular to a log classification method, a log classification device and a storage medium.
Background
With the rapid development of internet services, internet enterprises pay more and more attention to the operation and maintenance of service systems. The operation and maintenance of the application server directly influence the user experience of the enterprise and are related to the vital interests of the enterprise. The system log is the most effective reference and investigation file for judging the system running state in the operation and maintenance, and the enterprise application service generates a large amount of log files every moment along with the improvement of the performance of the computer server and the great enlargement of the application service engineering. Therefore, it is important to classify the operation log of the application server.
At present, when most application servers have problems, the logs of system operation are classified by adopting a mode of manually checking the logs. However, as the number of enterprise application logs increases, manual logging and sorting is inefficient. Therefore, it is particularly urgent to implement automatic log-checking and sorting by the application server.
Disclosure of Invention
The log classification method, the log classification device and the log classification storage medium provided by the invention have the advantages that the automatic classification of the running logs by the system is realized, and the log classification efficiency is improved.
The invention provides a log classification method in a first aspect, which comprises the following steps:
acquiring an original log sequence of a log to be classified;
preprocessing the original log sequence to obtain a processed log sequence;
and comparing the log sequence with a preset log classification tree structure to obtain a classification result of the log to be classified.
In a possible implementation manner, the creating process of the log classification tree structure includes:
acquiring a first log generated by a system in a preset time period;
preprocessing the first log to obtain a second log;
reordering the log sequence of the second log according to a preset ordering rule to obtain a third log;
and constructing the log classification tree structure according to the third log.
In one possible implementation, the second log includes a content field; the reordering of the log sequence of the second log according to the preset ordering rule to obtain a third log comprises:
counting the frequency of different words in the content field in the preset time period;
and reordering the second log according to the frequency of the words to obtain a third log.
In a possible implementation manner, the constructing the log classification tree structure according to the third log includes:
constructing an initial log classification tree structure according to the third log;
and pruning the initial log classification tree structure according to a preset branch number to obtain the log classification tree structure.
A second aspect of the present invention provides a log sorting apparatus, including:
the acquisition module is used for acquiring an original log sequence of the log to be classified;
the preprocessing module is used for preprocessing the original log sequence to obtain a processed log sequence;
and the classification module is used for comparing the log sequence with a preset log classification tree structure to obtain a classification result of the log to be classified.
In a possible implementation manner, the obtaining module is further configured to obtain a first log generated by the system within a preset time period;
the preprocessing module is further used for preprocessing the first log to obtain a second log;
the device further comprises: the sorting module is used for re-sorting the log sequence of the second log according to a preset sorting rule to obtain a third log;
and the creating module is used for constructing the log classification tree structure according to the third log.
In one possible implementation, the second log includes a content field;
the sorting module is specifically configured to:
counting the frequency of different words in the content field in the preset time period;
and reordering the second log according to the frequency of the words to obtain a third log.
In a possible implementation manner, the creating module is specifically configured to:
constructing an initial log classification tree structure according to the third log;
and pruning the initial log classification tree structure according to a preset branch number to obtain the log classification tree structure.
A third aspect of the present invention provides a log sorting apparatus, including:
a memory;
a processor; and
a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method according to any one of the first aspect of the invention.
A fourth aspect of the invention provides a computer readable storage medium having stored thereon a computer program for execution by a processor to perform the method according to any one of the first aspect of the invention.
According to the log classification method, the log classification device and the log classification storage medium, the original log sequence of the log to be classified is obtained, the original log sequence is preprocessed to obtain the processed log sequence, and the log sequence is compared with the preset log classification tree structure to obtain the classification result of the log to be classified. The method realizes the automatic classification of the system to the operation logs, and improves the efficiency of log classification.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a schematic flowchart of a log classification method according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a process of creating a log classification tree structure according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating a log classification tree structure constructed according to a third log according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a log classifying device according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a log sorting apparatus according to another embodiment of the present invention;
fig. 6 is a schematic hardware structure diagram of a log classification device according to an embodiment of the present invention.
With the above figures, certain embodiments of the invention have been illustrated and described in more detail below. The drawings and the description are not intended to limit the scope of the inventive concept in any way, but rather to illustrate it by those skilled in the art with reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.
The terms "comprising" and "having," and any variations thereof, in the description and claims of this invention are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
"and/or" in the present invention describes an association relationship of associated objects, and indicates that three relationships may exist, for example, a and/or B, and may indicate: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.
According to the log classification method provided by the embodiment of the invention, the log classification result is obtained by establishing the log classification tree structure and comparing the log generated by the system with the preset log classification tree structure, and the log classification method does not need operation and maintenance personnel to manually check, determines the log type and improves the log classification efficiency.
The technical solution of the present invention will be described in detail below with specific examples.
Fig. 1 is a flowchart illustrating a log classification method according to an embodiment of the present invention, where the method may be performed by any device that performs the log classification method, and the device may be implemented by software and/or hardware.
As shown in fig. 1, the log classification method provided by this embodiment includes the following steps:
s101, acquiring an original log sequence of a log to be classified;
in this embodiment, the original log sequence of the log to be classified includes a time field, a content field, and other character fields.
Because the system provides various application services, a large number of system log sequences are generated at every moment, and the log sequences corresponding to different applications have differences, wherein the main difference is in a content field. Illustratively, the following is a raw log sequence generated for an application of the system:
2018-01-2120:54:45101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker-443-101.*.*.*--200 0 0 29
wherein, the '2018-01-2120: 54: 45' is a time field;
the content field is POST/media/JobFarm/controller/svc/Worker-443-101. the content field comprises other character fields, such as "-" or a space.
It should be noted that the original log sequence of the log to be classified in this embodiment may be one log sequence, or may be multiple log sequences, which is not specifically limited in this embodiment. If the original log sequence of the log to be classified is multiple, performing subsequent log preprocessing and log automatic classification on each original log sequence one by one.
S102, preprocessing an original log sequence to obtain a processed log sequence;
in this embodiment, the log classifying device first pre-processes the original log sequence of the obtained log to be classified, filters out unnecessary fields, such as a time field (e.g., "2018-01-2120: 54: 45" in the above example) and other character fields (i.e., useless character fields, such as "-" or space field "in the above example), and only reserves a content field in the original log sequence.
Illustratively, the following is a pre-processed log sequence:
101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker 443 101.*.*.*200 0 0 29
s103, comparing the log sequence with a preset log classification tree structure to obtain a classification result of the log to be classified.
Specifically, the log classification tree structure of the present embodiment sorts and stores a large number of character strings (but not limited to character strings), which are generally used for text word frequency statistics in a search engine. According to the method and the device, the automatic classification of the system logs is realized by building the tree structure of the log sequence, and the classification query efficiency of the system logs is improved.
Based on the preset log classification tree structure, the log classification device compares the log sequence processed in the step S102 with the log classification tree structure, so as to quickly obtain the classification result of the log, and thus, operation and maintenance personnel can analyze and investigate the log according to the classification result.
Specifically, the log sequence processed in S102 is sequentially compared with nodes of each layer of the log classification tree structure according to the field sequence, and the node of the log classification tree structure corresponding to each field of the log sequence is determined until the last field of the log sequence; and taking the node of the log classification tree structure corresponding to the log sequence tail field as the log classification result.
According to the log classification method provided by the embodiment of the invention, the original log sequence of the log to be classified is obtained, the original log sequence is preprocessed to obtain the processed log sequence, and the log sequence is compared with the preset log classification tree structure to obtain the classification result of the log to be classified. By the method, the automatic classification of the running logs by the system is realized, and the efficiency of log classification is improved.
The log classification method shown in the above embodiment classifies the log to be classified according to the preset log classification tree structure, which has a better query classification effect, and the following describes in detail the creation process of the log classification tree structure in the above embodiment with reference to the drawings.
Fig. 2 is a flowchart illustrating a process of creating a log classification tree structure according to an embodiment of the present invention, and as shown in fig. 2, the process of creating a log classification tree structure according to the embodiment includes the following steps:
s201, acquiring a first log generated by a system in a preset time period;
in this embodiment, the first log is a sequence of all history logs generated by the system in a preset time period, and exemplarily, the first log generated by the system in the preset time period is as follows:
2018-01-2120:54:45101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker-443-101.*.*.*--200 0 0 29
2018-01-2120:54:45101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker-443-101.*.*.*--500 0 0 39
2018-01-2120:54:45101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker-443-101.*.*.*--200 0 0 129
2018-01-2120:54:45101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker-443-101.*.*.*--500 0 0 339
2018-01-2120:54:45101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker-443-101.*.*.*--200 0 0 52
2018-01-2120:54:45101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker-443-101.*.*.*--200 0 0 54
2018-01-2120:54:45101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker-443-101.*.*.*--500 0 0 35
s202, preprocessing the first log to obtain a second log;
the preprocessing in this embodiment is similar to the above embodiment, and filters out unnecessary fields in the first log, such as time fields and other character fields (e.g., space fields, etc.), and only retains the content fields in the first log.
Illustratively, the following is the preprocessed second log:
101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker 443 101.*.*.*200 0 0 29
101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker 443 101.*.*.*500 0 0 39
101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker 443 101.*.*.*200 0 0 129
101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker 443 101.*.*.*500 0 0 339
101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker 443 101.*.*.*200 0 0 52
101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker 443 101.*.*.*200 0 0 54
101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker 443 101.*.*.*500 0 0 35
s203, reordering the log sequence of the second log according to a preset ordering rule to obtain a third log;
specifically, the log classification device counts the frequency of different words in the content field of the second log in a preset time period;
and reordering the second log according to the frequency of the occurrence of the words to obtain a third log.
Illustratively, table 1 is a log word frequency list of the second log. It can be understood that the high-frequency words are fixed words and have high relevance with the log classification, and the low-frequency words are non-fixed words and have low relevance with the log classification.
TABLE 1
| Word | Word frequency |
| 101.201.*.* | 7 |
| POST | 7 |
| /mediasite/JobFarm/Controller.svc/Worker | 7 |
| 443 | 7 |
| 101.*.*.* | 7 |
| 200 | 4 |
| 500 | 3 |
| 29 | 1 |
| 39 | 1 |
| 129 | 1 |
| 339 | 1 |
| 52 | 1 |
| 54 | 1 |
| 0 | 14 |
According to table 1, the content fields of the second log may be sorted by word frequency to form a new third log. As follows:
0 0 101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker 443 101.*.*.*200 29
0 0 101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker 443 101.*.*.*500 39
0 0 101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker 443 101.*.*.*200 129
0 0 101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker 443 101.*.*.*500 339
0 0 101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker 443 101.*.*.*200 52
0 0 101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker 443 101.*.*.*200 54
0 0 101.201.*.*POST/mediasite/JobFarm/Controller.svc/Worker 443 101.*.*.*500 35
and S204, constructing a log classification tree structure according to the third log.
Specifically, an initial log classification tree structure is constructed according to the third log;
and pruning the initial log classification tree structure according to the preset branch number to obtain a final log classification tree structure.
Fig. 3 is a schematic diagram of constructing a log classification tree structure according to a third log according to an embodiment of the present invention, and as shown in fig. 3, a process of constructing a log classification tree structure according to the third log in the above example is given:
(1) inserting a third log into the tree structure starting from the root node root;
(2) if the next word of the third log is the child node of the current node, constructing the corresponding child node;
(3) repeating (2) until all words of the third log are inserted into the tree structure;
(4) and pruning the tree structure according to the preset branch number to obtain the final log classification tree structure.
For example, if the preset branch number is 2, a node including two child nodes in the tree structure is retained, and the two child nodes of the node are deleted, such as the child nodes "29", "129", "39", "339" in fig. 3.
And deleting words irrelevant to log classification to obtain a final log classification tree structure.
According to the above process of creating a log classification tree structure, if the pre-processed log sequence is compared with the preset log classification tree structure, a classification result of the log sequence can be obtained, where the classification result includes the terminal node information in the log classification tree structure, such as "200" or "500" in fig. 3.
It should be noted that there is a possible situation that the length of the log sequence after the preprocessing is smaller than the length of the preset log sequence to be classified, at this time, the log classification device sends prompt information to the operation and maintenance personnel, so that the operation and maintenance personnel can manually check and analyze the log sequence.
Optionally, the system may periodically update the log classification tree structure, so as to ensure accuracy of the classification result of the log classification tree structure.
In the creating process of the log classification tree structure provided in this embodiment, after the historical logs of the system are preprocessed, all log sequences are reordered according to a preset ordering rule, and the log classification tree structure is created according to the reordered logs, so that the obtained log classification tree structure can determine a termination node of the log sequences to be classified, where the termination node is a classification result of the logs. The system periodically updates the log classification tree structure, thereby improving the accuracy of the classification result of the log classification tree structure.
Fig. 4 shows a log classifying device, which is only illustrated in fig. 4, and the embodiment of the present invention is not limited to this.
Fig. 4 is a schematic structural diagram of a log classifying device according to an embodiment of the present invention, and as shown in fig. 4, a log classifying device 40 according to this embodiment includes:
an obtaining module 41, configured to obtain an original log sequence of a log to be classified;
a preprocessing module 42, configured to preprocess the original log sequence to obtain a processed log sequence;
and the classification module 43 is configured to compare the log sequence with a preset log classification tree structure to obtain a classification result of the log to be classified.
The log classification device provided by the embodiment of the invention comprises an acquisition module, a preprocessing module and a classification module, wherein the acquisition module acquires an original log sequence of a log to be classified, the preprocessing module preprocesses the original log sequence to obtain a processed log sequence, and the classification module compares the log sequence with a preset log classification tree structure to obtain a classification result of the log to be classified. The device realizes the automatic classification of the system to the operation logs and improves the efficiency of log classification.
On the basis of the foregoing embodiment, in a possible implementation manner, the obtaining module 41 is further configured to obtain a first log generated by the system within a preset time period;
the preprocessing module 42 is further configured to preprocess the first log to obtain a second log.
Fig. 5 is a schematic structural diagram of a log classifying device according to another embodiment of the present invention, and based on the device shown in fig. 4, as shown in fig. 5, the log classifying device 40 according to this embodiment further includes:
the sorting module 44 is configured to reorder the log sequence of the second log according to a preset sorting rule to obtain a third log;
and a creating module 45, configured to construct the log classification tree structure according to the third log.
In one possible implementation, the second log includes a content field;
the sorting module 44 is specifically configured to:
counting the frequency of different words in the content field in the preset time period;
and reordering the second log according to the frequency of the words to obtain a third log.
In a possible implementation manner, the creating module 45 is specifically configured to:
constructing an initial log classification tree structure according to the third log;
and pruning the initial log classification tree structure according to a preset branch number to obtain the log classification tree structure.
The log classifying device provided in this embodiment may implement the technical solutions of the above method embodiments, and the implementation principles and technical effects are similar, which are not described herein again.
Fig. 6 shows a log classifying device, which is only illustrated in fig. 6, and the embodiment of the present invention does not show that the present invention is limited thereto.
Fig. 6 is a schematic diagram of a hardware structure of a log classifying device according to an embodiment of the present invention, and as shown in fig. 6, a log classifying device 60 according to this embodiment includes:
a memory 61;
a processor 62; and
a computer program;
wherein the computer program is stored in the memory 61 and configured to be executed by the processor 62 to implement the technical solution of any one of the foregoing method embodiments, and the implementation principle and technical effect thereof are similar, and are not described herein again.
Alternatively, the memory 61 may be separate or integrated with the processor 62.
When the memory 61 is a device independent of the processor 62, the log sorting apparatus 60 further includes:
a bus 63 for connecting the memory 61 and the processor 62.
Embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor 62 to implement the steps performed by the log classification device 60 in the above method embodiments.
It should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.
The memory may comprise a high-speed RAM memory, and may further comprise a non-volatile storage NVM, such as at least one disk memory, and may also be a usb disk, a removable hard disk, a read-only memory, a magnetic or optical disk, etc.
The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.
The storage medium may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an Application Specific Integrated Circuits (ASIC). Of course, the processor and the storage medium may reside as discrete components in an electronic device or host device.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (6)
1. A log classification method, comprising:
acquiring an original log sequence of a log to be classified;
preprocessing the original log sequence to obtain a processed log sequence;
comparing the log sequence with a preset log classification tree structure to obtain a classification result of the log to be classified, wherein the classification result comprises terminal node information in the log classification tree structure;
if the length of the log to be classified is smaller than the preset length, the method further comprises the following steps: sending prompt information, wherein the prompt information is used for indicating that the log to be classified is to be checked;
the creating process of the log classification tree structure comprises the following steps:
acquiring a first log generated by a system in a preset time period;
preprocessing the first log to obtain a second log;
reordering the log sequence of the second log according to a preset ordering rule to obtain a third log;
constructing the log classification tree structure according to the third log;
the second log comprises a content field; the reordering of the log sequence of the second log according to the preset ordering rule to obtain a third log comprises:
counting the frequency of different words in the content field in the preset time period;
and reordering the second log according to the frequency of the words to obtain a third log, wherein the high-frequency words are positioned at the front part of the third log.
2. The method of claim 1, wherein constructing the log classification tree structure from the third log comprises:
constructing an initial log classification tree structure according to the third log;
and pruning the initial log classification tree structure according to a preset branch number to obtain the log classification tree structure.
3. A log sorting apparatus, comprising:
the acquisition module is used for acquiring an original log sequence of the log to be classified;
the preprocessing module is used for preprocessing the original log sequence to obtain a processed log sequence;
the classification module is used for comparing the log sequence with a preset log classification tree structure to obtain a classification result of the log to be classified, wherein the classification result comprises terminal node information in the log classification tree structure;
if the length of the log to be classified is smaller than the preset length, the device further comprises: the sending module is used for sending prompt information, and the prompt information is used for indicating that the log to be classified is to be checked;
the acquisition module is further used for acquiring a first log generated by the system in a preset time period;
the preprocessing module is further used for preprocessing the first log to obtain a second log;
the device further comprises: the sorting module is used for re-sorting the log sequence of the second log according to a preset sorting rule to obtain a third log, wherein the high-frequency words are positioned at the front part of the third log;
a creating module, configured to construct the log classification tree structure according to the third log;
the second log comprises a content field; the sorting module is specifically configured to:
counting the frequency of different words in the content field in the preset time period;
and reordering the second log according to the frequency of the words to obtain a third log.
4. The apparatus according to claim 3, wherein the creating module is specifically configured to:
constructing an initial log classification tree structure according to the third log;
and pruning the initial log classification tree structure according to a preset branch number to obtain the log classification tree structure.
5. A log sorting apparatus, comprising:
a memory;
a processor; and
a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method of claim 1 or 2.
6. A computer-readable storage medium, on which a computer program is stored which is executed by a processor to implement the method according to claim 1 or 2.
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| CN112445912B (en) * | 2020-11-06 | 2022-06-07 | 苏州浪潮智能科技有限公司 | Fault log classification method, system, device and medium |
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