Scheduling task execution full-link log tracing system based on business
By optimizing the processing order of scheduling tasks and data deduplication, efficient full-link log tracing is achieved, solving the problems of duplicate data storage and historical data retention, and improving data processing efficiency and flexibility.
Patent Information
- Application Number
- CN202510802086.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-16
- Publication Date
- 2025-09-26
AI Technical Summary
Existing full-link log tracing technology has problems such as duplicate data accumulation leading to waste of storage space, inability to retain historical data, and inability to automatically display data change processes.
It uses task classification module, task adjustment module, snapshot trigger module, log comparison module, JSON configuration and parsing module, log tracing module, security monitoring module and problem feedback module, combined with LRU cache and lazy reading technology to optimize the processing order of scheduling tasks and data deduplication, and achieve efficient log tracing.
It improves the processing efficiency of scheduling tasks, reduces database pressure, and optimizes the data tracking process. Users can efficiently obtain data changes and flexibly adjust the processing order.
Smart Images
Figure CN120704825A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of full-link log tracing, and in particular to a full-link log tracing system for scheduling task execution based on business. Background Art
[0002] As enterprises continue to grow, the amount of data they process is also increasing. When processing scheduling tasks, the huge amount of data puts a lot of pressure on the processing process. The multiple storage of duplicate data also results in inefficient use of space, slowing down data processing efficiency. The emergence of full-link log tracing technology solves this problem, reducing the performance loss of converting large-field JSON configurations in system memory and increasing data processing efficiency.
[0003] The existing full-link log tracing technology has the following specific defects: (1) Most of the existing full-link log tracing technologies can only directly call the stored data from the database for use, resulting in the accumulation of duplicate data and a large amount of unnecessary storage space wasted. It does not have the function of filtering and deduplicating the data with duplicate content;
[0004] (2) Most of the existing full-link log tracing technologies can only save the last used data. After the operation is completed, the historical data is not retained. The data change process can only be obtained through the previous data records. It is impossible to find the record call or use the historical data again, and it is impossible to automatically display the changes in the historical data. Summary of the Invention
[0005] In response to the above-mentioned technical deficiencies, the purpose of the present invention is to provide a business-based scheduling task execution full-link log tracing system.
[0006] To solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a business-based scheduling task execution full-link log tracing system, which includes the following modules
[0007] Task classification module: used to prioritize various scheduling tasks of the business and set the order in which tasks are processed.
[0008] Task adjustment module: used to adjust the execution order of each scheduling task.
[0009] Snapshot trigger module: used to create snapshots for each scheduling task and its data and generate log files for each data in each scheduling task.
[0010] Log comparison module: used to determine whether the data in the log files of each data in each scheduling task is the same, and to deduplicate the log file data of each data in the same scheduling task.
[0011] JSON configuration and parsing module: used to configure JSON files and parse JSON files for each data in each scheduling task, store the JSON files of each data in each scheduling task in the LRU cache, and use lazy reading to read the JSON files of each data in each scheduling task when parsing the JSON files of each data in each scheduling task.
[0012] Log tracing module: used to trace the log files of each data in each scheduling task, and complete the missing node logs to fully display the process of data changes.
[0013] Security monitoring module: used to monitor the security of the system during the execution of scheduling tasks, identify whether the log files of each data in each scheduling task contain user password information and system configuration, and add a protection mechanism for the user password information and system configuration when the log files of each data in each scheduling task contain user password information and system configuration.
[0014] Problem feedback module: used to detect whether the transmission process of the log files of each data in each scheduling task is interrupted during user use. If the transmission process of the log files of each data in each scheduling task is interrupted, the detection result will be fed back to the developer and the log files will be retransmitted;
[0015] Database: log files used to store data in each scheduling task.
[0016] Preferably, the process of prioritizing the scheduling tasks of the services is as follows:
[0017] Organize the various scheduling tasks of the business, obtain the memory space occupied by each scheduling task file, obtain the initiation time, and obtain the number of initiations.
[0018] Set the memory space occupied by each scheduling task file to R i , i represents the number of each scheduling task, i = 1, 2...n, n is any integer greater than 2, the memory space occupied by the preset scheduling task file is set to R, and the initiation time is set to T i , get the current time, set the current time to T, set the preset waiting time to WT, and set the number of initiations to N i , set the preset task standard initiation times to N, according to the formula Get the priority processing coefficient P of each scheduling task i , where μ1, μ2, and μ3 are the preset weight factors of the memory space occupied by the scheduling task file, the preset weight factor of the waiting time for the scheduling task, and the preset weight factor of the number of times the scheduling task is initiated, respectively.
[0019] Sort the priority coefficients of each scheduling task in descending order, and the result is the priority sorting of the scheduling tasks according to the business.
[0020] Preferably, the task adjustment module is used to record the task as a task to be adjusted when the user adjusts the execution order of a task, and pop up a selection to execute immediately and to execute after a certain task. If the user chooses to execute immediately, the scheduling task priority coefficient of the task to be adjusted is assigned to the average value of the scheduling task priority coefficients of the currently executing task and the next executing task in the original sequence. If the user chooses to execute after a certain task, a pop-up window will pop up to allow the user to select a task, record it as a marked task, and assign the scheduling task priority coefficient of the task to be adjusted to the average value of the scheduling task priority coefficients of the marked task and the next executing task in the original sequence marked task.
[0021] Preferably, the process of determining whether the data in the log files of each data in each scheduling task are the same is as follows:
[0022] When a new log file is detected to be stored in the database, the log files of each data in each scheduling task in the database are compared to see if there is a log file with the same data. If the log files with the same data are detected, the log files of each data in each scheduling task with the same data will be recorded as the same source file, and the log file newly stored in the database will be deleted, and all tasks using this data will be marked after the same source file.
[0023] Preferably, the specific process of configuring a JSON file and parsing the JSON file for each data in each scheduling task is as follows:
[0024] When a JSON file of certain data in a scheduling task enters the system configuration, the snapshot mechanism will directly record the data and generate a log file of the corresponding data in the corresponding scheduling task, recorded as a configuration log file, and then write the configuration log file into the LRU cache. When writing the data in the configuration log file, the data is inserted from the end of the table.
[0025] When parsing the JSON file content of a certain data in a certain scheduling task, the lazy read log file content is read from the LRU cache through lazy reading, and the source data of the log file is located and parsed before use. If the parsed file is not in the cache, the data is directly called from the database.
[0026] Preferably, the log files of each data in each scheduling task are traced back, and the specific process is as follows:
[0027] When a user traces back the log file of a certain data in a scheduling task, the log file is searched by the log name and creation time point, and the log file generated when the data corresponding to the log file of the corresponding data in the scheduling task is used for the first time is displayed, which is recorded as the initial log file. The modification data of the data corresponding to the initial log file are obtained. If there is deleted data, the position of the data in the LUR cache space is obtained from the log file of each data in the corresponding scheduling task, and the log file corresponding to the previous result storage data of the deleted data is searched. The data corresponding to the next log file of the log file is retrieved. This data is the deleted data. The data are displayed on the coordinate axis, and the points of each data are connected in sequence to form a line graph. The user can view the process of data change through the line graph and complete the data tracing.
[0028] Preferably, the process of identifying whether the log files of each data in each scheduling task contain user password information and system configuration is as follows:
[0029] When a log file corresponding to a certain data in a certain scheduling task is generated, the data that generates the log file is obtained, and the data type of the log file is identified. If the data type of the log file is a password, the log file is recorded as a password type log file, and protection is added to the password type log file. When the user calls or uses the password type log file, a prompt is popped up to enter the user password. If the user enters the wrong password more times than the preset security password tolerance rate, the user will be prohibited from continuing to operate the system. The user can unlock it by contacting the background maintenance personnel.
[0030] If the data type of the log file generated corresponding to a certain data in a scheduling task is system configuration, the log file will be recorded as a system configuration log file, and the read-only attribute will be set for the system configuration log file. When the user needs to change the system configuration, a prompt will pop up to enter the user password. If the user enters the wrong password more times than the preset security password tolerance rate, the user will be prohibited from continuing to operate the system. The user can unlock it by contacting the backend maintenance personnel.
[0031] If the user adds a protection mechanism to the log file of a certain data in a certain scheduling task, the user manually finds the log file in the LUR cache and chooses to set the log file to read-only or add password protection.
[0032] The beneficial effects of the present invention are: this product provides a business-based scheduling task execution full-link log tracing system, which provides users with a fast and efficient processing method for processing scheduling tasks. By sorting the processing order of scheduling tasks, the processing flow is optimized and the processing efficiency is improved. The adjustable processing order function makes the scheduling tasks more flexible in the processing process. The configuration of JSON greatly reduces the pressure on the database, converts data that occupies a large amount of content space into snapshot addresses that occupy very little memory space, reduces the performance loss of large field JSON configuration in the system memory, and adopts lazy reading to reduce the bandwidth pressure occupied by data when reading. The precise log tracing link optimizes the data tracking process, allowing users to obtain the data change process more efficiently, thereby improving the efficiency of processing tasks. BRIEF DESCRIPTION OF THE DRAWINGS
[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0034] Figure 1 This is a schematic diagram of the system structure connection of the present invention. DETAILED DESCRIPTION
[0035] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.
[0036] See also Figure 1As shown, the present invention provides a business-based scheduling task execution full-link log tracing system, which includes the following modules: a task classification module, a task adjustment module, a snapshot trigger module, a log comparison module, a JSON configuration and parsing module, a log tracing module, a security monitoring module, a problem feedback module, and a database, wherein the task classification module is connected to the task adjustment module, the task adjustment module is connected to the task classification module and the snapshot trigger module, the snapshot trigger module is connected to the task adjustment module, the database and the log comparison module, the log comparison module is connected to the snapshot trigger module, the database and the JSON configuration and parsing module, the JSON configuration and parsing module is connected to the log comparison module, the log tracing module and the security monitoring module, the log tracing module is connected to the database and the security monitoring module, the security monitoring module is connected to the problem feedback module, and the database is connected to the snapshot trigger module, the log comparison module and the log tracing module.
[0037] Task classification module: used to prioritize various scheduling tasks of the business and set the order in which tasks are processed.
[0038] In a specific example, the process of prioritizing the scheduling tasks of the services is as follows:
[0039] Organize the various scheduling tasks of the business, obtain the memory space occupied by each scheduling task file, obtain the initiation time, and obtain the number of initiations.
[0040] Set the memory space occupied by each scheduling task file to R i , i represents the number of each scheduling task, i = 1, 2...n, n is any integer greater than 2, the memory space occupied by the preset scheduling task file is set to R, and the initiation time is set to T i , get the current time, set the current time to T, set the preset waiting time to WT, and set the number of initiations to N i , set the preset task standard initiation times to N, according to the formula Get the priority processing coefficient P of each scheduling task i , where μ1, μ2, and μ3 are the preset weight factors of the memory space occupied by the scheduling task file, the preset weight factor of the waiting time for the scheduling task, and the preset weight factor of the number of scheduling task initiations, respectively. μ1∈(0,1), μ2∈(0,1), and μ3∈(0,1).
[0041] Sort the priority coefficients of each scheduling task in descending order, and the result is the priority sorting of the scheduling tasks according to the business.
[0042] It should be noted that by obtaining the memory space occupied by each scheduling task file in the preset period, the average value of the memory space occupied by each scheduling task file is calculated, which is recorded as the average occupied space. The occupied memory space values of each scheduling task file in the preset period are connected in sequence to form a curve on the coordinate axis, with the average occupied space as the x-axis, and the point with the occupied memory space value of the first scheduling task file in the preset period as the value when x=0. The preset period is recorded as TP, and the curve, x=0 and x=TP are used to enclose the closed space, with x=0 as the upper limit and x=TP as the lower limit, and the definite integral of the curve in the closed interval is calculated.
[0043] It should be noted that the waiting processing time of each scheduling task is calculated by obtaining the current time and the initiation time of each scheduling task within the preset period, and the average waiting processing time of each scheduling task is calculated, which is recorded as the average waiting processing time. The initiation time of each scheduling task within the preset period is used as the point in sequence to form a curve on the coordinate axis, with the average waiting processing time as the x-axis, and the first scheduling task waiting processing time point in the preset period as the value when x=0, and the preset period is recorded as TP. The curve, x=0 and x=TP are used to enclose the closed space, with x=0 as the upper limit and x=TP as the lower limit, and the definite integral of the curve in the closed interval is calculated.
[0044] It should be noted that by obtaining the number of times each scheduling task is initiated within the preset period, the average number of times each scheduling task is initiated is calculated and recorded as the average number of times of initiation. The points on the coordinate axis are connected in sequence to form a curve, with the average number of initiations as the x-axis and the point with the number of initiations of the first scheduling task file in the preset period as the value when x=0. The preset period is recorded as TP, and the curve, x=0 and x=TP are used to enclose a closed space. x=0 is taken as the upper limit and x=TP is taken as the lower limit. The definite integral of the curve in the closed interval is calculated.
[0045] The ratio of the definite integral values is recorded as the ratio of the preset weight factor of the memory space occupied by the scheduling task file, the preset weight factor of the waiting time of the scheduling task, and the preset weight factor of the number of scheduling task initiations.
[0046] Task adjustment module: used to adjust the execution order of each scheduling task.
[0047] In a specific example, the task adjustment module is used to record the task as a task to be adjusted when the user adjusts the execution order of a task, and pop up a selection to choose between immediate execution and execution after a certain task. If the user chooses immediate execution, the scheduling task priority coefficient of the task to be adjusted is assigned to the average of the scheduling task priority coefficients of the currently executing task and the next executing task in the original sequence. If the user chooses to execute after a certain task, a pop-up window will pop up to allow the user to select a task, record it as a marked task, and assign the scheduling task priority coefficient of the task to be adjusted to the average of the scheduling task priority coefficients of the marked task and the next executing task in the original sequence marked task.
[0048] Snapshot trigger module: used to create snapshots for each scheduling task and its data and generate log files for each data in each scheduling task.
[0049] Log comparison module: used to determine whether the data in the log files of each data in each scheduling task is the same, and to deduplicate the log file data of each data in the same scheduling task.
[0050] In a specific example, the determination of whether the data in the log files of each data in each scheduling task are the same is carried out in the following specific determination process:
[0051] When a new log file is detected to be stored in the database, the log files of each data in each scheduling task in the database are compared to see if there is a log file with the same data. If the log files with the same data are detected, the log files of each data in each scheduling task with the same data will be recorded as the same source file, and the log file newly stored in the database will be deleted, and all tasks using this data will be marked after the same source file.
[0052] JSON configuration and parsing module: used to configure JSON files and parse JSON files for each data in each scheduling task, store the JSON files of each data in each scheduling task in the LRU cache, and use lazy reading to read the JSON files of each data in each scheduling task when parsing the JSON files of each data in each scheduling task.
[0053] It should be noted that the JSON refers to a lightweight data exchange format, and the LRU cache is a storage mode based on a double-linked list structure.
[0054] In a specific example, the process of configuring and parsing a JSON file for each data in each scheduling task is as follows:
[0055] When a JSON file of certain data in a scheduling task enters the system configuration, the snapshot mechanism will directly record the data and generate a log file of the corresponding data in the corresponding scheduling task, recorded as a configuration log file, and then write the configuration log file into the LRU cache. When writing the data in the configuration log file, the data is inserted from the end of the table.
[0056] When parsing the JSON file content of a certain data in a certain scheduling task, the lazy read log file content is read from the LRU cache through lazy reading, and the source data of the log file is located and parsed before use. If the parsed file is not in the cache, the data is directly called from the database.
[0057] It should be noted that the LRU cache is a double-linked list structure. When data is stored, the data is stored from the end of the table, and when data is retrieved, the data is retrieved from the head of the table.
[0058] Log tracing module: used to trace the log files of each data in each scheduling task, and complete the missing node logs to fully display the process of data changes.
[0059] In a specific example, the log files of each data in each scheduling task are traced back, and the specific process is as follows:
[0060] When a user traces back the log file of a certain data in a scheduling task, the log file is searched by the log name and creation time point, and the log file generated when the data corresponding to the log file of the corresponding data in the scheduling task is used for the first time is displayed, which is recorded as the initial log file. The modification data of the data corresponding to the initial log file are obtained. If there is deleted data, the position of the data in the LUR cache space is obtained from the log file of each data in the corresponding scheduling task, and the log file corresponding to the previous result storage data of the deleted data is searched. The data corresponding to the next log file of the log file is retrieved. This data is the deleted data. The data are displayed on the coordinate axis, and the points of each data are connected in sequence to form a line graph. The user can view the process of data change through the line graph and complete the data tracing.
[0061] Security monitoring module: used to monitor the security of the system during the execution of scheduling tasks, identify whether the log files of each data in each scheduling task contain user password information and system configuration, and add a protection mechanism for the user password information and system configuration when the log files of each data in each scheduling task contain user password information and system configuration.
[0062] In a specific example, the process of identifying whether the log files of each data in each scheduling task contain user password information and system configuration is as follows:
[0063] When a log file corresponding to a certain data in a certain scheduling task is generated, the data that generates the log file is obtained, and the data type of the log file is identified. If the data type of the log file is a password, the log file is recorded as a password type log file, and protection is added to the password type log file. When the user calls or uses the password type log file, a prompt is popped up to enter the user password. If the user enters the wrong password more times than the preset security password tolerance rate, the user will be prohibited from continuing to operate the system. The user can unlock it by contacting the background maintenance personnel.
[0064] If the data type of the log file generated corresponding to a certain data in a scheduling task is system configuration, the log file will be recorded as a system configuration log file, and the read-only attribute will be set for the system configuration log file. When the user needs to change the system configuration, a prompt will pop up to enter the user password. If the user enters the wrong password more times than the preset security password tolerance rate, the user will be prohibited from continuing to operate the system. The user can unlock it by contacting the backend maintenance personnel.
[0065] If the user adds a protection mechanism to the log file of a certain data in a certain scheduling task, the user manually finds the log file in the LUR cache and chooses to set the log file to read-only or add password protection.
[0066] Problem feedback module: used to detect whether the transmission process of the log files of each data in each scheduling task is interrupted during user use. If the transmission process of the log files of each data in each scheduling task is interrupted, the detection result will be fed back to the developer and the log files will be retransmitted;
[0067] Database: log files used to store data in each scheduling task.
[0068] The beneficial effects of the present invention are: this product provides a business-based scheduling task execution full-link log tracing system, which provides users with a fast and efficient processing method for processing scheduling tasks. By sorting the processing order of scheduling tasks, the processing flow is optimized and the processing efficiency is improved. The adjustable processing order function makes the scheduling tasks more flexible in the processing process. The configuration of JSON greatly reduces the pressure on the database, converts data that occupies a large amount of content space into snapshot addresses that occupy very little memory space, reduces the performance loss of large field JSON configuration in the system memory, and adopts lazy reading to reduce the bandwidth pressure occupied by data when reading. The precise log tracing link optimizes the data tracking process, allowing users to obtain the data change process more efficiently, thereby improving the efficiency of processing tasks.
[0069] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the scope of protection of the present invention.
Claims
1. A business-based scheduling task execution full-link log tracing system, characterized by: Includes the following modules: Task classification module: used to prioritize various scheduling tasks of the business and set the order in which tasks are processed; Task adjustment module: used to adjust the execution order of each scheduling task; Snapshot trigger module: used to create snapshots for each scheduling task and its data and generate log files for each data in each scheduling task; Log comparison module: used to determine whether the data in the log files of each data in each scheduling task is the same, and to perform deduplication operations on the log files of each data in the same scheduling tasks; JSON configuration and parsing module: used to configure and parse JSON files for each data in each scheduling task, store the JSON files of each data in each scheduling task in the LRU cache, and use lazy reading to read the JSON files of each data in each scheduling task when parsing the JSON files of each data in each scheduling task; Log tracing module: used to trace the log files of each data in each scheduling task, and complete the missing node logs to fully display the process of data changes; Security monitoring module: used to monitor the security of the system during the execution of scheduling tasks, identify whether the log files of each data in each scheduling task contain user password information and system configuration, and add protection mechanisms for user password information and system configuration when the log files of each data in each scheduling task contain user password information and system configuration; Problem feedback module: used to detect whether the transmission process of the log files of each data in each scheduling task is interrupted during user use. If the transmission process of the log files of each data in each scheduling task is interrupted, the detection result will be fed back to the developer and the log files will be retransmitted; Database: log files used to store data in each scheduling task.
2. A business-based scheduling task execution full-link log tracing system according to claim 1, characterized in that: The specific process of prioritizing the scheduling tasks of the business is as follows: Organize the various scheduling tasks of the business, obtain the memory space occupied by each scheduling task file, obtain the initiation time, and obtain the number of initiations; Set the memory space occupied by each scheduling task file to R i , i represents the number of each scheduling task, i = 1, 2...n, n is any integer greater than 2, the memory space occupied by the preset scheduling task file is set to R, and the initiation time is set to T i , get the current time, set the current time to T, set the preset waiting time to WT, and set the number of initiations to N i , set the preset task standard initiation times to N, according to the formula Get the priority processing coefficient P of each scheduling task i , where μ1, μ2, and μ3 are respectively the weight factors of the memory space occupied by the preset scheduling task file, the weight factor of the preset scheduling task waiting time, and the weight factor of the preset scheduling task initiation times; Sort the priority coefficients of each scheduling task in descending order, and the result is the priority sorting of the scheduling tasks according to the business.
3. A business-based scheduling task execution full-link log tracing system according to claim 1, characterized in that: It also includes a task adjustment module, which is used to record the task as a task to be adjusted when the user adjusts the execution order of a task, and pop up a selection to choose between immediate execution and execution after a certain task. If the user chooses immediate execution, the scheduling task priority coefficient of the task to be adjusted is assigned to the average of the scheduling task priority coefficients of the currently executing task and the next executing task in the original sequence. If the user chooses to execute after a certain task, a pop-up window will pop up to let the user operate to select a task, record it as a marked task, and assign the scheduling task priority coefficient of the task to be adjusted to the average of the scheduling task priority coefficients of the marked task and the next executing task in the original sequence marked task.
4. A business-based scheduling task execution full-link log tracing system according to claim 1, characterized in that: The specific judgment process of judging whether the data in the log files of each data in each scheduling task are the same is as follows: When a new log file is detected to be stored in the database, the log files of each data in each scheduling task in the database are compared to see if there is a log file with the same data. If the log files with the same data are detected, the log files of each data in each scheduling task with the same data will be recorded as the same source file, and the log file newly stored in the database will be deleted, and all tasks using this data will be marked after the same source file.
5. A business-based scheduling task execution full-link log tracing system according to claim 1, characterized in that: The specific process of configuring and parsing JSON files for each data in each scheduling task is as follows: When a JSON file containing data from a scheduled task enters the system configuration, the snapshot mechanism directly records the data and generates a log file containing the data from the corresponding scheduled task, which is recorded as the configuration log file. The configuration log file is then written to the LRU cache. When writing data to the configuration log file, the data is inserted from the end of the table. When parsing the JSON file content of a certain data in a certain scheduling task, the lazy read log file content is read from the LRU cache through lazy reading, and the source data of the log file is located and parsed before use. If the parsed file is not in the cache, the data is directly called from the database.
6. A business-based scheduling task execution full-link log tracing system according to claim 1, characterized in that: The specific process of tracing back the log files of each data in each scheduling task is as follows: When a user traces back the log file of a certain data in a scheduling task, the log file is searched by the log name and creation time point, and the log file generated when the data corresponding to the log file of the corresponding data in the scheduling task is used for the first time is displayed, which is recorded as the initial log file. The modification data of the data corresponding to the initial log file are obtained. If there is deleted data, the position of the data in the LUR cache space is obtained from the log file of each data in the corresponding scheduling task, and the log file corresponding to the previous result storage data of the deleted data is searched. The data corresponding to the next log file of the log file is retrieved. This data is the deleted data. The data are displayed on the coordinate axis, and the points of each data are connected in sequence to form a line graph. The user can view the process of data change through the line graph and complete the data tracing.
7. A business-based scheduling task execution full-link log tracing system according to claim 1, characterized in that: The specific process of identifying whether the log files of each data in each scheduling task contain user password information and system configuration is as follows: When a log file corresponding to a certain data in a certain scheduling task is generated, the data that generates the log file is obtained, and the data type of the log file is identified. If the data type of the log file is a password, the log file is recorded as a password type log file, and protection is added to the password type log file. When the user calls or uses the password type log file, a prompt for entering the user password will pop up. If the user enters the wrong password more times than the preset security password error tolerance, the user will be prohibited from continuing to operate the system. The user can unlock it by contacting the backend maintenance personnel. If the data type of the log file generated by a certain data in a scheduling task is system configuration, the log file will be recorded as a system configuration log file and the read-only attribute will be set for the system configuration log file. When the user needs to change the system configuration, a prompt will pop up to enter the user password. If the user enters the wrong password more times than the preset security password error tolerance, the user will be prohibited from continuing to operate the system. The user can unlock it by contacting the backend maintenance personnel. If the user adds a protection mechanism to the log file of a certain data in a certain scheduling task, the user manually finds the log file in the LUR cache and chooses to set the log file to read-only or add password protection.