CN115757045A - Transaction log analysis method, system and device - Google Patents
Transaction log analysis method, system and device Download PDFInfo
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Abstract
The application provides a transaction log analysis method, a system and a device, which relate to the field of log analysis, in particular to a transaction log analysis method, wherein the method comprises the following steps: acquiring a pre-made standard log model; collecting transaction log data on each system; according to the standard log model, carrying out standardization processing on the transaction log data to obtain standardized data; and performing transaction analysis according to the standardized data to obtain an analysis result. The method and the device can be compatible with logs of different systems and different formats, and can simultaneously perform centralized transaction log analysis on a plurality of systems in different deployment fields.
Description
Technical Field
The present application relates to the field of log analysis, and in particular, to a method, a system, and an apparatus for transaction log analysis.
Background
At present, the scale of an information system in the financial industry is increasingly huge, deployment modes are different, and transaction water and application logs are scattered on a plurality of systems such as a cloud platform and a local computer room. And the development standards of all transaction systems are different, and the designated logs and the flow standard are also different, so that the analysis is difficult. The existing solution is to separately build a monitoring system, collect and monitor logs on a single system or a deployment platform, or manually log in the system to perform query and data statistics of the logs. The existing scheme can not be compatible with logs of different systems and different formats, and can not simultaneously carry out centralized transaction log analysis on systems in different deployment fields.
Therefore, how to be compatible with logs of different systems and different formats, and perform centralized transaction log analysis on systems in multiple different deployment fields at the same time is a technical problem to be solved by those skilled in the art.
Disclosure of Invention
In order to solve the technical problems, the application provides a transaction log analysis method which is compatible with logs of different systems and different formats and can simultaneously perform centralized transaction log analysis on a plurality of systems in different deployment fields. The application also provides a transaction log analysis system and device, which have the same technical effect.
A first object of the present application is to provide a transaction log analysis method.
The above object of the present application is achieved by the following technical solutions:
a transaction log analysis method, comprising:
acquiring a pre-made standard log model;
collecting transaction log data on each system;
according to the standard log model, carrying out standardization processing on the transaction log data to obtain standardized data;
and performing transaction analysis according to the standardized data to obtain an analysis result.
Preferably, in the transaction log analysis method, the standard log model includes a standard pipeline structure, where:
the standard flow structure comprises a fixed field;
the fixed field includes: timestamp, transaction code, transaction description, transaction amount, transaction card number, technical success, service success, transaction result description, system name, transaction delay, response code and host name.
Preferably, in the transaction log analysis method, the normalizing the transaction log data according to the standard log model to obtain normalized data includes:
according to the standard log model, data extraction is carried out on the transaction log data to obtain first data;
converting the first data into a standard data structure to obtain second data;
and storing the second data into the corresponding fixed field in the standard pipeline structure to obtain standardized data.
Preferably, in the transaction log analysis method, after the obtaining the standardized data, the method further includes:
determining whether a fixed field of a transaction description in the standardized data is empty,
and if so, supplementing the fixed field of the transaction description according to the fixed field of the transaction code in the standardized data and a preset table.
Preferably, in the transaction log analysis method, after the transaction log data on each system is collected, the method further includes:
adding fields of transaction time, transaction system name, host name and file name on the transaction log data;
establishing a screening mechanism based on the transaction time, the transaction system name, the host name, and the file name.
Preferably, in the transaction log analysis method, after the obtaining the standardized data, the method further includes:
storing the standardized data into an elastic search.
Preferably, in the transaction log analysis method, the collection of the transaction log data on each system is completed by a lightweight log collector filehead.
Preferably, in the transaction log analysis method, the transaction log data is standardized according to the standard log model to obtain standardized data, and the standardized data is completed through a logstack or shell script.
It is a second object of the present application to provide a transaction log analysis system.
The second application object of the present application is achieved by the following technical scheme:
a transaction log analysis system, comprising:
the model acquisition module is used for acquiring a pre-made standard log model;
the data acquisition module is used for acquiring transaction log data on each system;
the data processing module is used for carrying out standardization processing on the transaction log data according to the standard log model to obtain standardized data;
and the data analysis module is used for carrying out transaction analysis according to the standardized data to obtain an analysis result.
A third object of the present application is to provide a transaction log analysis apparatus.
The third application purpose of the present application is achieved through the following technical scheme:
a transaction log analysis device comprising a storage medium and a processor, wherein the storage medium stores a computer program, and when the processor runs the computer program stored in the storage medium, the processor executes the transaction log analysis method according to any one of the above.
According to the technical scheme, transaction log data on each system are collected, and are subjected to standardization processing according to a preset standard log model to obtain standardized data, so that log compatibility of different systems and different formats can be realized; by carrying out transaction analysis on the standardized data, an analysis result is obtained, and the transaction logs of different systems can be simultaneously subjected to unified analysis and comparison. In addition, according to the technical scheme, system application does not need to be modified, deployment is simple, only a small amount of configuration files need to be modified, expansibility is strong, and other software or scripts can be linked after data integration is completed. In summary, the above technical solution can be compatible with logs of different systems and different formats, and can perform centralized transaction log analysis on a plurality of systems in different deployment fields at the same time.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic flowchart of a transaction log analysis method provided in an embodiment of the present application;
FIG. 2 is a flowchart illustrating a log normalization process according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a transaction log analysis system provided in an embodiment of the present application;
fig. 4 is a schematic structural diagram of a transaction log analysis apparatus provided in an embodiment of the present application.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed method and system may be implemented in other ways. The system embodiments described below are merely illustrative, and for example, a division of modules is only one logical functional division, and other divisions may be realized in practice, such as: multiple modules or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or modules may be electrical, mechanical or in other forms.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the following method embodiments may be implemented by program instructions and associated hardware, where the program instructions may be stored in a computer-readable storage medium, and when executed, perform the steps comprising the following method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as a removable Memory device, a Read Only Memory (ROM), a magnetic disk, or an optical disk.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or to implicitly indicate the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "plurality" or "a plurality" means two or more unless specifically limited otherwise.
The embodiments of the present application are written in a progressive manner.
As shown in fig. 1, an embodiment of the present application provides a transaction log analysis method, including:
s101, acquiring a pre-made standard log model;
in S101, a standard log model which accords with banking business conditions can be induced and formulated by investigating core elements of journal of each transaction system; preferably, the standard log model includes a standard pipeline structure, and the standard pipeline structure includes a fixed field therein, and the fixed field includes: timestamp, transaction code, transaction description, transaction amount, transaction card number, technical success, service success, transaction result description, system name, transaction delay, response code and host name. The 'timestamp' field is used for authenticating the time of generating the transaction log data, so that whether the data is tampered after being generated can be verified; the transaction description field can be obtained by analyzing transaction log data or according to a preset transaction description table; according to the 'response code' field, a 'technical success' field and a 'service success' field can be analyzed, wherein the 'technical success' field represents that the transaction is not abnormal on a technical path, the 'service success' field represents that the transaction is normally completed, the service success is bound to be technically successful, and the technical success is possibly not successful; according to the system name field and the host name field, screening conditions can be formed, and statistics on transaction success rate is facilitated; if the "transaction amount" field is null, it can be classified as a non-financial transaction, and if the "transaction amount" field is not null, it is a financial transaction.
S102, collecting transaction log data on each system;
in S102, the transaction log data may be a transaction log generated by a bank application monitoring platform, and the bank application monitoring platform has a relatively complete monitoring and warning scheme for financial transactions, and can synchronously collect the transaction log locally and reserve the transaction log as transaction log data; the transaction log data may also be other logs generated by applications and containing transaction information, for example, independent applications such as part of background tasks, subscription tasks, and the like, and monitoring and analysis of such applications need to analyze and arrange the logs according to messages, and the logs can be collected independently and used as data sources for transaction analysis. Considering that the logs to be collected are dispersed in different logs of different hosts and the collection cannot affect the computing resources of the service system, it is preferable that the collection of the transaction log data on each system is completed by a lightweight log collector filehead. The lightweight log collector filehead can well meet the log collection requirement, has the characteristics of simplicity in deployment, less occupied resources, quickness in log collection and the like, and can also perform preliminary format processing while collecting logs, such as adding fields such as host names and paths, performing line-feed merging on segments and the like.
S103, according to the standard log model, carrying out standardization processing on the transaction log data to obtain standardized data;
in S103, the purpose of the standardization processing is to be compatible with different system log output specifications, and obtain standardized data with a uniform format according to the standard log model. Meanwhile, when a new system is brought in, through the steps, the new system can be used for outputting the running water in the standard format without requiring the new system to apply, and even the flow water log can not be output. Preferably, the transaction log data is standardized according to the standard log model to obtain standardized data, and the standardized data can be completed through logstack or shell scripts. The logstack is used as an important log processing tool in ELK (elastic search, logstack, kibana) open source software, can efficiently analyze each event, identifies fields to construct a structure, converts the fields into a general format, and is not influenced by the format and the complexity. The Shell script is similar to batch processing under Windows/Dos, namely, various commands are put into a file in advance, a program file which is convenient to execute at one time is convenient, and the method is mainly convenient for an administrator to set or manage. But it is more powerful than batch processing under Windows and more efficient than programs compiled with other programming programs.
And S104, performing transaction analysis according to the standardized data to obtain an analysis result.
In S104, transaction analysis can be conveniently performed according to the integrated standardized data to obtain an analysis result, preferably, the analysis result may include forms of an alarm, a chart, and a report, and the data can be visualized by outputting the report and the chart and performing graphical display, and the purpose of fast response and troubleshooting can be achieved through the work of customizing the alarm.
At present, the scale of an information system in the financial industry is increasingly huge, deployment modes are different, and transaction water and application logs are scattered on a plurality of systems such as a cloud platform and a local computer room. And the development standards of all transaction systems are different, and the designated logs and the flow standard are also different, so that the analysis is difficult. The existing solution is to independently build a monitoring system, collect and monitor logs on a single system or a deployment platform, or manually log in the system to perform query and data statistics of the logs. The existing scheme can not be compatible with logs of different systems and different formats, and can not simultaneously carry out centralized transaction log analysis on systems in different deployment fields.
In the embodiment, by acquiring the transaction log data on each system and carrying out standardized processing on the transaction log data according to the pre-established standard log model, standardized data is obtained, and log compatibility of different systems and different formats can be realized; the transaction logs of different systems can be simultaneously analyzed and compared in a unified way by performing transaction analysis on the standardized data to obtain an analysis result. In addition, the embodiment does not need to modify the system application, is simple to deploy, can be realized by modifying a small amount of configuration files, has strong expansibility, and can link other software or scripts after the data integration is finished. In summary, the above embodiments can be compatible with logs of different systems and different formats, and can perform centralized transaction log analysis on a plurality of systems in different deployment fields at the same time.
As shown in fig. 2, on the basis of the foregoing embodiment, one implementation manner of the step of normalizing the transaction log data according to the standard log model to obtain normalized data may include the following steps:
s201, according to the standard log model, data extraction is carried out on the transaction log data to obtain first data;
in S201, specifically, data extraction may be performed on the transaction log data according to a fixed field in the standard log model, so as to obtain the first data. The first data may represent a core element of the transaction log data.
S202, converting the first data into a standard data structure to obtain second data;
in S202, considering that there is a difference in data format between different systems, the first data is converted into a standard data structure to obtain second data, so that normalization processing of the data can be implemented.
S203, storing the second data into the corresponding fixed field in the standard pipeline structure to obtain standardized data.
In S203, the second data is stored in the corresponding fixed field in the standard pipeline structure to obtain standardized data, so that the output specifications of different system logs are compatible, and standardized data with a uniform format is obtained according to the standard log model, which is also beneficial to improving the efficiency of subsequent data analysis and processing.
In the implementation step, the transaction log data is subjected to standardized processing by combining the standard flow structure and the fixed field in the standard log model, so that the compatibility of different system log output specifications is realized, and the transaction analysis efficiency is improved on the premise of keeping the core elements of the transaction log data.
On the basis of the above embodiment, after obtaining the normalized data, the method further includes:
s301, judging whether a fixed field of the transaction description in the standardized data is empty, if so, supplementing the fixed field of the transaction description according to a fixed field of a transaction code in the standardized data and a preset table.
In S301, the preset table may be a correspondence table between transaction codes and transaction descriptions, and may be formulated according to actual service requirements.
In the implementation step, aiming at the condition that the transaction description field cannot be analyzed in the transaction log data, the fixed field of the transaction code and the preset table are utilized to supplement the fixed field of the transaction description.
On the basis of the above embodiment, after collecting the transaction log data on each system, the method further includes:
s401, adding fields of transaction time, transaction system name, host name and file name to the transaction log data;
s402, establishing a screening mechanism based on the transaction time, the transaction system name, the host name and the file name.
In the implementation steps, aiming at the application log, the purpose of collecting the application log is mainly to perform centralized query, and in order to improve the query efficiency and precision, fields of transaction time, transaction system name, host name and file name are added according to the source of the application log after the log is collected, so that a multi-stage screening condition based on the transaction time, the transaction system name, the host name and the file name is formed. In practical application, the log screening function is applied, and the purposes of quick retrieval and investigation can be achieved. Preferably, in the screening mechanism, key information such as a global event tracking number, transaction time consumption, an error code, transaction description and the like can be added, so that richer multistage screening conditions are formed.
On the basis of the above embodiment, after obtaining the normalized data, the method further includes:
s501, storing the standardized data into an elastic search.
The Elasticissearch is a distributed search and analysis engine located at the core of the Elasticissearch Stack, provides near real-time search and analysis for all types of data, and can efficiently store and index data texts in a manner of supporting fast search regardless of structured or unstructured texts, digital data or log data. Specifically, the standardized data may be stored in an index corresponding to the elastic search, and the type of each field may be reasonably set and archived according to a predetermined period.
As shown in fig. 3, in another embodiment of the present application, there is further provided a transaction log analysis system, including:
the model obtaining module 10 is used for obtaining a pre-made standard log model;
the data acquisition module 11 is used for acquiring transaction log data on each system;
the data processing module 12 is configured to perform standardization processing on the transaction log data according to the standard log model to obtain standardized data;
and the data analysis module 13 is used for performing transaction analysis according to the standardized data to obtain an analysis result.
As a preferred embodiment, the transaction log analysis system further includes a display module, and the display module is configured to display the analysis result. The display module can be a display screen, and the analysis result can be checked in real time through the display screen, so that the fine analysis operation and maintenance capability of management personnel can be improved.
As shown in fig. 4, in another embodiment of the present application, there is further provided a transaction log analysis apparatus, which includes a storage medium 14 and a processor 15, where the storage medium 14 stores a computer program therein, and when the processor 15 runs the computer program stored in the storage medium 14, the processor 15 executes any one of the above transaction log analysis methods.
The processor 15 may include one or more processing cores, among others. The processor 15 invokes data stored in the storage medium 14 by executing or executing instructions, programs, code sets, or instruction sets stored in the storage medium 14 to perform the various functions of the present application and to process the data. The processor 15 may be at least one of an application specific integrated circuit, a digital signal processor, a digital signal processing device, a programmable logic device, a field programmable gate array, a central processing unit, a controller, a microcontroller, and a microprocessor. It will be appreciated that the electronics used to implement the functions of the processor 15 described above may be other for different devices.
The storage medium 14 may be used to store, among other things, instructions, programs, code sets, or instruction sets. The storage medium 14 may include a storage program area and a storage data area, wherein the storage program area may store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing any of the above transaction log analysis methods, and the like; the storage data area may store data and the like involved in any of the above transaction log analysis methods.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A transaction log analysis method, comprising:
acquiring a pre-made standard log model;
collecting transaction log data on each system;
according to the standard log model, carrying out standardization processing on the transaction log data to obtain standardized data;
and performing transaction analysis according to the standardized data to obtain an analysis result.
2. The method of claim 1, wherein the standard log model comprises a standard pipeline structure, wherein:
the standard pipeline structure comprises a fixed field;
the fixed field includes: timestamp, transaction code, transaction description, transaction amount, transaction card number, technical success, service success, transaction result description, system name, transaction delay, response code and host name.
3. The method of claim 2, wherein the normalizing the transaction log data according to the standard log model to obtain normalized data comprises:
according to the standard log model, data extraction is carried out on the transaction log data to obtain first data;
converting the first data into a standard data structure to obtain second data;
and storing the second data into the corresponding fixed field in the standard pipeline structure to obtain standardized data.
4. The method of claim 3, wherein after obtaining the normalized data, further comprising:
determining whether a fixed field of a transaction description in the standardized data is empty,
and if so, supplementing the fixed field of the transaction description according to the fixed field of the transaction code in the standardized data and a preset table.
5. The method of claim 1, wherein after collecting transaction log data on each system, further comprising:
adding fields of transaction time, transaction system name, host name and file name to the transaction log data;
establishing a screening mechanism based on the transaction time, the transaction system name, the host name and the file name.
6. The method of claim 1, wherein after obtaining the normalized data, further comprising:
storing the standardized data into an elastic search.
7. The method of claim 1, wherein the collecting transaction log data on each system is accomplished by a lightweight log collector filehead.
8. The method of claim 1, wherein the transaction log data is normalized according to the standard log model to obtain normalized data, and the normalization is performed by a logstack or shell script.
9. A transaction log analysis system, comprising:
the model acquisition module is used for acquiring a pre-made standard log model;
the data acquisition module is used for acquiring transaction log data on each system;
the data processing module is used for carrying out standardization processing on the transaction log data according to the standard log model to obtain standardized data;
and the data analysis module is used for carrying out transaction analysis according to the standardized data to obtain an analysis result.
10. A transaction log analysis apparatus comprising a storage medium having a computer program stored therein and a processor that executes the transaction log analysis method according to any one of claims 1 to 8 when the processor executes the computer program stored in the storage medium.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116225971A (en) * | 2023-05-08 | 2023-06-06 | 深圳华锐分布式技术股份有限公司 | Transaction interface compatibility detection method, device, equipment and medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116225971A (en) * | 2023-05-08 | 2023-06-06 | 深圳华锐分布式技术股份有限公司 | Transaction interface compatibility detection method, device, equipment and medium |
| CN116225971B (en) * | 2023-05-08 | 2023-07-14 | 深圳华锐分布式技术股份有限公司 | Transaction interface compatibility detection method, device, equipment and medium |
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