A college data filling closed-loop system based on a shadow table

Abstract

The application provides a college data filling closed-loop system based on a shadow table. The application generates and stores a mirror library of original data of a college database by using a mirror library index table storage unit, isolates the modification and approval operation of an interactive port on the original data in the college database, and generates a logical table for the corresponding data item in the index table in the mirror library by using a logical table storage unit, so as to display the modification state of the data item in the mirror library as a difference view according to the items in the logical table, and intuitively confirm and approve by the interactive port. The application uses the mirror library to isolate and protect the data in the whole closed-loop process of college data filling and approval, can share the data access business throughput by the mirror library, and more flexibly updates and synchronously triggers the different approval personnel to audit all the updated items according to the logical items, and comprehensively improves the overall operation efficiency of the college data system.

Description

Technical Field

[0001] This application relates to the field of computer data processing technology, and more specifically to a closed-loop system for college data entry based on shadow tables. Background Technology

[0002] University databases encompass a vast amount of teaching resources, student data, research data, and project management process information. The data is diverse, highly interconnected, and generated through complex processes, often distributed across several independent systems. Consequently, data entry and approval processes frequently require cross-system verification and approval by different departments. These processes are complex, lengthy, and difficult to monitor directly, making it challenging to promptly identify and address any issues that arise during the approval process.

[0003] Traditional efficient data entry and approval processes require applicants to submit materials to various departments sequentially. The approval process relies on fragmented data interaction, leading to low efficiency. Furthermore, repetitive data extraction and maintenance processes significantly waste system resources. When processing large amounts of data in batches, existing approval and entry systems are prone to database congestion, impacting the efficiency of data resource interaction.

[0004] Existing university databases often utilize interactive data entry systems built on web technologies to ensure compatibility across different hardware systems. This design is prone to high concurrency issues when multiple data streams are transmitted simultaneously. The throughput of a web system is typically measured in QPS (Query Per Second). For the web server, the more connections a client initiates, the more contexts the server needs to switch, increasing computational overhead and average response time. Furthermore, storage response time directly impacts system efficiency under high concurrency. When a business request interface malfunctions, its delayed response time postpones the entire web request response time, gradually saturating the web server's available connections. At this point, other normal business requests have no available connections. Users, finding the system unavailable, frequently refresh the page, creating a vicious cycle that ultimately locks the congested web server, forcing it to distribute traffic to other working machines, overloading them and ultimately crashing the entire web system. Summary of the Invention

[0005] This application addresses the shortcomings of existing technologies by providing a closed-loop system for university data entry based on shadow tables. This application utilizes a mirror database index table storage unit to isolate and protect the original data in the university database. Data operation commands generated at the interaction port are mapped to several data items in the mirror database through logical tables, automatically triggering the verification and validation of the logical relationships between data items, thereby improving system efficiency and actual throughput. The specific technical solution adopted in this application is as follows.

[0006] First, to achieve the above objectives, a closed-loop system for university data entry based on shadow tables is proposed, comprising: a subject database index table storage unit for storing the original data of the university database; a mirror database index table storage unit for generating and storing a mirror database of the original data of the university database; an interaction port for responding to external user operations and triggering corresponding data operation commands; a logical table storage unit for generating and storing logical tables for corresponding data items in the index tables of the mirror database in response to the data operation commands output by the interaction port, and marking the data content, data collection type, data tag category, review status, and system record information fields corresponding to each data operation command in the logical table to construct logical items; and a logical view processing unit for comparing the data items in the mirror database with the logical items in the logical table storage unit according to each logical item in the logical table storage unit, generating a difference view, and pushing the difference view to the corresponding interaction port, triggering modification of the corresponding original data of the university database in the subject database index table storage unit based on the user operations fed back by the interaction port.

[0007] Optionally, in the closed-loop system for college data entry based on shadow tables as described above, the logical view processing unit further includes a derived logic maintenance module, which stores the logical operation relationships between various original data in the college database. After the logical view processing unit pushes the difference view to the corresponding interaction port, in response to the user operation feedback from the interaction port, the corresponding original data in the college database in the theme library indicator table storage unit is modified according to the logical operation relationships between various original data in the college database.

[0008] Optionally, in the closed-loop system for university data entry based on shadow tables as described above, the subject database index table storage unit also includes several incremental tables. When modifying the corresponding original data in the university database within the subject database index table storage unit, the modified content is stored in the incremental table corresponding to the storage period according to a preset storage cycle, and a link reference pointer to the corresponding modified content in the incremental table is added at the corresponding position of the original data. When retrieving the corresponding original data in the university database within the subject database index table storage unit, the corresponding modified content in the incremental table is retrieved according to the latest link reference pointer stored in its corresponding data position. The subject database index table storage unit also triggers the retrieval of the corresponding modified content in the incremental table to replace the original data when the link reference pointer stored in any data position overflows.

[0009] Optionally, in the closed-loop system for college data entry based on shadow tables as described above, the step of generating and storing the mirror database of the original college database by the mirror database index table storage unit includes: querying the link reference pointers in each original data in the college database, retrieving the forms in the college database whose number of link reference pointers has reached a preset threshold, and storing the data in the forms into the mirror database of the original college database according to the latest link reference pointer.

[0010] Optionally, in the closed-loop system for university data entry based on shadow tables as described above, the specific steps for constructing logical items include marking the data content, data collection type, data tag category, review status, and system record information fields corresponding to each data operation instruction in the logical table. These steps include: marking data content from the ETL interface with a data collection type of "0"; marking data content from the API interface with a data collection type of "1"; marking data content from other interfaces with a data collection type of "2"; marking data content from manual entry with a data collection type of "9"; marking newly added data content with a data tag category of "I"; marking modified data content with a data tag category of "U"; marking deleted data content with a data tag category of "D"; marking data content approved by the interactive port with a review status of "1"; marking data content not approved by the interactive port with a review status of "0"; and marking the system record information fields in the data content according to the account name, response time, modifier, and modification time corresponding to the data operation instruction of the interactive port.

[0011] Optionally, in the closed-loop system for college data entry based on shadow tables as described above, for data content with data label category "U", the logical view processing unit marks all logical items of the data content and the modifier and modification time of each logical item in the difference view; the logical view processing unit also marks the modified data content and the modifier, modification time, and logical operation relationship of each logical item in the difference view when modifying the corresponding original data of the college database in the theme library index table storage unit according to the logical operation relationship between the original data of each item stored in the college database, so that the user at the interaction port can trigger a confirmation operation accordingly.

[0012] Optionally, in the closed-loop system for university data entry based on shadow tables as described above, the image library index table storage unit uses the open-source image building tool Kaniko to build the image. The specific steps for building the image include: specifying the global file path, Dockerfile file path, image push address, and source code location for the Kaniko executable program executor; the executable program executor extracts the contents of the Dockerfile file as the container's file system; then, it uses this file system to automatically clone the data in the forms of the university database that meet the preset threshold in the storage unit corresponding to the global file path to complete the construction of the image library; finally, the image is pushed to the specified image push address for caching and subsequent querying.

[0013] Optionally, in the closed-loop system for university data entry based on shadow tables as described above, the mirror database index table storage unit uses a first hash function to calculate the current dynamic secret based on the feature value corresponding to the form in the university database whose number of linked reference pointers reaches a preset threshold, and uses a second hash function to obtain a shared key based on the current dynamic secret and a global key determined by preset rules; the data in the mirror database is encrypted based on the shared key; wherein, the feature value is the maximum value of the number of linked reference pointers in the form and / or the cumulative value of the number of linked reference pointers in a single form within the current storage period.

[0014] Optionally, in the closed-loop system for college data entry based on shadow tables as described above, the interaction ports include wireless smart terminals, computers, servers, and microcomputers. Each interaction port is also used to convert user operations into data operation instructions under unified rules through API interfaces.

[0015] Optionally, in the closed-loop system for college data entry based on shadow tables as described above, the storage unit of the theme library indicator table is set independently. When its link reference pointer overflows, it triggers the retrieval of the corresponding modified content in the incremental table according to the latest link reference pointer to replace the original data. Furthermore, the original data is compressed and stored in the corresponding item of the log data according to the replacement timing. Beneficial effects

[0016] This application provides a closed-loop system for university data entry based on shadow tables. This application utilizes a mirror database index table storage unit to generate and store the original data from the university database. This isolates the modification and approval operations of the original data items in the university database from the interaction port. Furthermore, a logical table storage unit generates logical tables for the corresponding data items in the index tables of the mirror database. Based on the items in the logical tables, the modification status of the data items in the mirror database is displayed as a difference view, providing a clear visual confirmation and approval process for the interaction port. This application utilizes a mirror database for data isolation and protection throughout the entire closed-loop process of university data entry and approval. It can distribute the throughput of data access services through the mirror database and more flexibly update various related data in the system according to logical items, simultaneously triggering different approvers to review all updated items, thus comprehensively improving the overall operational efficiency of the university data system.

[0017] Other features and advantages of this application will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing this application. Attached Figure Description

[0018] The accompanying drawings are provided to further illustrate the present application and form part of the specification. Together with the embodiments of the present application, they serve to explain the present application but do not constitute a limitation thereof. In the drawings:

[0019] Figure 1 This is the overall architecture diagram of the closed-loop system for college data entry based on shadow tables implemented in this application;

[0020] Figure 2 This is a schematic diagram illustrating the construction process of the difference view in the closed-loop system for college data entry based on shadow tables, as described in this application.

[0021] Figure 3 This is a schematic diagram of the reporting and processing flow of each data item in the university database of this application system. Implementation

[0022] To make the objectives and technical solutions of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the described embodiments of this application without creative effort are within the scope of protection of this application.

[0023] Those skilled in the art will understand that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as herein.

[0024] The meaning of "and / or" as used in this application includes situations where each exists alone or both exist simultaneously.

[0025] The term "connection" as used in this application can mean a direct connection between components or an indirect connection between components through other components.

[0026] Figure 1 A closed-loop system for college data entry based on a shadow table, according to this application, includes:

[0027] The subject database index table storage unit is used to store the raw data of the university database. The raw data of the university database is generally formed into several forms according to different data attributes. Each form stores several data items. There will be certain logical connections between the data items in the forms. For example, the class scheduling form of a classroom needs to be arranged according to the class time of the corresponding teachers of several classes. That is, there is a logical mapping relationship between the class teachers' class time and the classroom's class scheduling form items.

[0028] The mirror library indicator table storage unit is used to generate and store mirror libraries containing the original data of university databases;

[0029] Interaction ports include wireless smart terminals, computers, servers, microcomputers, and other terminals that are logged in with different permissions and accounts. Each terminal responds to external user operations and triggers its login account to generate corresponding data operation instructions; for example, a teacher's account can trigger the reservation of a specific experimental classroom and experimental equipment.

[0030] The logical table storage unit generates and stores logical tables corresponding to data items in the indicator tables of the mirror library in response to data operation commands output from the interaction port. Each logical table is labeled with the corresponding data content, data acquisition type, data label category, review status, and system record information fields based on the data operation commands, thus constructing logical items. For example, taking the teacher account triggering the reservation of a specific experimental classroom and equipment in the aforementioned interaction port as an example, the logical table storage unit, in response to the interaction port's operation commands on data in the mirror library, retrieves the logical mapping relationship between course times and classroom schedules, and experimental equipment warehouse registration forms. It updates the classroom schedule form and the equipment reservation form to avoid scheduling conflicts. This logical connection relationship can be stored in the corresponding server unit as a globally callable logical item through statistical formulas or algorithmic logic to automatically detect course changes and trigger a rescheduling or notify affected course personnel.

[0031] The logical view processing unit compares the data items in the mirror database with the updated data corresponding to each logical item in the logical table storage unit, generates a difference view, and pushes the difference view to the corresponding interaction port. Based on user actions such as confirmation or rejection of modification feedback from the interaction port, it triggers the modification of the corresponding original data in the university database in the theme library indicator table storage unit. Taking the aforementioned interaction port triggering the reservation of specific experimental classrooms and equipment as an example, the logical view processing unit retrieves the logical mapping relationships related to course times and classroom schedules, and experimental equipment warehouse registration forms in the logical table storage unit. Based on the updates to the classroom schedule forms and equipment reservation forms, it triggers a comparison of data items in the mirror database, converts the data that needs to be updated into difference views, and pushes each difference view to an interaction port with corresponding approval permissions. Based on the user's approval confirmation of the updated data items received by the interaction port, it triggers the modification of the corresponding original data in the university database in the theme library indicator table storage unit and updates the mirror database.

[0032] In a preferred implementation, considering the complexity of the logical relationships between the various raw data in the university database, especially since adjusting certain basic data may require corresponding updates to the corresponding statistical items or derived items in other forms, and other related data may also need to be adjusted, this application may also preferably include a derived logic maintenance module in the logical view processing unit. This module stores the logical relationships between the various raw data in the university database. After the logical view processing unit pushes the difference view to the corresponding interaction port, in response to the user's confirmation operation at the interaction port, the corresponding raw data in the university database in the subject library indicator table storage unit is modified according to the following steps based on the logical relationships between the various raw data in the university database:

[0033] After the logical view processing unit pushes the difference view to the corresponding interaction port, in response to the user's confirmation operation at the interaction port, it triggers the logical operation relationship between the original data in the university database stored in the derived logic maintenance module. This triggers the adjustment of the relevant original data in the university database. Furthermore, based on the data items being adjusted, it queries whether the original data items involved in the adjustment step correspond to other logical operation relationships. If further logical operation relationships exist, the aforementioned steps continue: The difference view generated by adjusting other data items, calculated according to other logical operation relationships, is pushed to the corresponding interaction port. In response to the user's confirmation operation on the relevant data items at the interaction port, it triggers the query of the logical operation relationship between the original data in the university database corresponding to the data items involved in the confirmation operation, according to the derived logic maintenance module. Based on this logical operation relationship, it further triggers the adjustment of the relevant original data in the university database until the adjusted data items no longer involve logical operation relationships with other data items.

[0034] In the above iterative update steps, the triggering of adjustments to the relevant original data in the university database can be implemented in the form of incremental data tables. These incremental tables can be specifically set within the theme database indicator table storage unit, and the number of incremental tables can be set according to the update items in the form of the theme database indicator table storage unit.

[0035] When modifying the corresponding original data in the university database in the theme library index table storage unit, the modified content is stored in the incremental table corresponding to the storage period according to the preset storage period, and a link reference pointer to the corresponding modified content in the incremental table is added to the corresponding data bit of the original data to indicate the modification content of the original data at each time.

[0036] Therefore, when it is necessary to retrieve the corresponding original data of the university database in the theme library index table storage unit, the corresponding modified content in the incremental table can be retrieved according to the latest link reference pointer stored in the corresponding data bit.

[0037] When the link reference pointer stored in any data bit of the topic database index table storage unit overflows, it can trigger each form in the topic database index table storage unit to retrieve the corresponding modified content in the incremental table according to the latest link reference pointer corresponding to each data bit, and replace the modified content in the corresponding data bit of the original data.

[0038] Based on this, the mirror database index table storage unit of this application can generate and store the original data mirror database of the university database in real time according to the adjustment status of each data bit in the subject database, following the steps below:

[0039] Query the link reference pointers in each original data in the university database, retrieve the forms in the university database whose number of link reference pointers has reached a preset threshold, and store the data in the form into the mirror database of the original data in the university database according to the latest link reference pointer.

[0040] The preset threshold for the number of link reference pointers can be flexibly set according to the retrieval frequency of data in each form. For example, the preset threshold for frequently modified forms can be set to close to 1 to update the mirror library with every modification to a data item and respond promptly to modifications to other data items in the overall system. Forms that do not require frequent updates, or forms that are relatively independent compared to other forms, can have their preset thresholds set to be correspondingly larger, thereby saving the process of generating mirror library forms and reducing the consumption of system resources in building the mirror library.

[0041] refer to Figure 2 As shown in the middle: The logical table can be specifically marked with the data content, data collection type, data tag category, review status, and system record information fields corresponding to each data operation instruction, thereby constructing logical items for comparing the modified content of data items. Among them, the data collection type, data tag category, review status, and system record information fields can be marked according to the following rules:

[0042] Mark the data content from the ETL interface as having a data acquisition type of "0";

[0043] Mark the data content from the API interface as having a data collection type of "1";

[0044] Mark the data content from other interfaces as having a data acquisition type of "2";

[0045] Data from manually entered data is marked with a data collection type of "9". Different interfaces may correspond to different data rules. Therefore, data from API and other interfaces can be standardized and granularized according to the data rules of the ETL interface based on the data collection type marking. Data with the same meaning represented by different character codes can be converted into code expressions according to the standard pattern of ETL interface data content to maintain the consistency of data content and facilitate comparison of data content from different interfaces according to a unified data standard. Data granularity indicates the degree of refinement of data. It can be used to fill or delete fields in API and other interfaces according to the granularity standard of ETL interface data content to aggregate small-granular business data into large-granular data, or to supplement ambiguous large-granular data in the query form to facilitate comparison of data content from different interfaces according to a unified data standard.

[0046] The newly added data content is marked with the data tag category "I" so that it can be marked in the logical view processing unit for user confirmation;

[0047] The modified data content is marked with its data tag category "U" so that the logical view processing unit can mark all logical items of the data content, as well as the modifier and modification time of each logical item in the difference view. This will prompt the user in the difference view to confirm whether the modifier has modification permission and whether the modification content is correct.

[0048] The deleted data content is marked with its data tag category "D" so that the deleted data content can be marked in the logical view processing unit for user confirmation;

[0049] Mark the approved data content on the interactive port with an approval status of "1" to trigger the update of the corresponding data content in the theme library indicator table storage unit;

[0050] Mark the data content that has not passed the review on the interactive port with a review status of "0" to close the update permission of the topic library indicator table storage unit for that data content;

[0051] The system record information fields for each data item can be marked in the data content according to the account name, response time, modifier, and modification time corresponding to the data operation command of the interaction port. This marks the update source of the data item in the difference view of the logical view processing unit, allowing the operator of the interaction port to determine whether the modifier has modification permissions and whether the modified content is correct. Specifically, for data content marked with the data category "U", the logical view processing unit also marks the modified data content, modifier, modification time, and logical operation relationship of each logical item in the difference view when modifying the corresponding original data in the university database in the theme library indicator table storage unit according to the logical operation relationship between the original data of each item stored in the university database stored in the derived logic maintenance module. This allows the user of the interaction port to trigger a confirmation operation accordingly.

[0052] for Figure 3 The data items shown in the diagram can be processed in the following manner:

[0053] The storage unit for the subject library indicator table is set up independently to establish physical isolation for its data and ensure data security.

[0054] The interaction ports, such as mobile devices and computers, respond to the data entry requests from the currently logged-in account, such as a student's course attendance. They then generate data manipulation instructions for the data items in the university database via ETL or API interfaces. Each interaction port also translates the specific modification methods and data content of the user's operations into unified data manipulation instructions via API interfaces. The logical table storage unit generates and stores logical tables corresponding to the data items in the indicator tables of the mirror library in response to the data manipulation instructions output by the interaction ports. In each logical table, based on the data manipulation instructions, the data content of the student's attendance is marked, the data collection type is marked as 1, the data tag category is marked as U, and the audit status is marked as 0. The system record information field records the account name, response time, modifier, and modification time corresponding to the data manipulation instruction, constructing a logical item reflecting the student's course attendance.

[0055] Then, the logical view processing unit is triggered to compare the data items in the mirror database with the logical items in the logical table storage unit based on the logical item in the logical table storage unit. It generates a difference view marking the content before and after the logical item change and pushes this difference view to the corresponding interaction ports such as the class teacher and the academic affairs office. Based on the user operations fed back from the interaction ports, such as the class teacher confirming student attendance or the academic affairs office approving the attendance, the incremental table in the subject database indicator table storage unit corresponding to the storage period is modified. In the incremental table, the updated data of student course attendance is matched to the corresponding original data in the university database through linked reference pointers, marking the modification of the original data.

[0056] The logical view processing unit further triggers the derived logic maintenance module in the logical view processing unit based on the operations on the corresponding data items of the incremental table fed back by the class teacher, the academic affairs office, and other relevant interaction ports. According to the logical operation relationship between the various original data in the university database stored in the derived logic maintenance module, in response to the confirmation operation of student attendance matters fed back by the class teacher, the academic affairs office, and other interaction ports, as well as the approval operation of the academic affairs office for the attendance matters, it triggers the modification of the corresponding original data in the university database in the subject library indicator table storage unit according to the logical operation relationship between the various original data in the university database. It updates the student score data, teacher assessment data, and experimental equipment usage records directly based on the student attendance matters. In the incremental table corresponding to the current storage period, the updated data is matched to the corresponding original data in the university database through the link reference pointer, and the modification matters of the original data are marked. Then, based on the aforementioned logical operation relationship, the student rating data, teacher assessment data, experimental equipment usage records, etc. are further searched for other data related to the modification, further triggering the modification of the corresponding original data in the university database in the theme library indicator table storage unit, and further updating other data based on the modification, until there are no other further logical mapping relationships in the derived logic maintenance module.

[0057] During the aforementioned update process, the logical view processing unit also marks the modified data content, modifier, modification time, and logical operation relationship of each logical item in the difference view when modifying the corresponding original data in the university database in the theme library index table storage unit according to the logical operation relationship stored in the derived logic maintenance module, so that the user at the interaction port can trigger the confirmation operation accordingly.

[0058] Meanwhile, during the aforementioned update process, when the storage unit of the topic library indicator table is still overflowing its link reference pointer, it triggers the retrieval of the corresponding modified content in the incremental table according to the latest link reference pointer to replace the original data. Furthermore, the original data originally stored in the topic library indicator table storage unit is tagged and compressed according to the replacement timing, and the compressed data is stored in the corresponding project of the system log data for backup.

[0059] In the aforementioned system, the image repository metrics table storage unit can specifically utilize the open-source image building tool Kaniko to build images in real-time based on the updated link reference pointers in the topic repository metrics table storage unit. The main reason for choosing Kaniko is that its operation does not depend on the node's Docker daemon, thus making it easier and safer to build container images such as Kubernetes clusters in environments without root access. Furthermore, the Kaniko tool requires no manual intervention throughout the entire image building process, automatically building the images.

[0060] Specifically, to improve the timeliness of updating frequently accessed and updated form data, this application can adopt the following steps to build the mirror:

[0061] Specify the global file path, Dockerfile file path, image push address, and source code location for Kaniko's executable program. The executable program extracts the contents of the Dockerfile file as the container's file system. Then, it uses this file system to automatically clone the data in the table of the university database whose number of linked reference pointers meets the preset threshold in the storage unit corresponding to the global file path to complete the construction of the image library. Finally, it pushes the image to the specified image push address for caching and subsequent querying.

[0062] The forms filtered using a preset threshold can be further identified by using the maximum value of the number of link reference pointers in the forms within their corresponding storage period and / or the cumulative value of the number of link reference pointers in a single form as a feature. During the construction of the mirror library, a first hash function is used to calculate the dynamic secret of the current storage period based on the feature corresponding to the forms in the university database whose number of link reference pointers reaches the preset threshold. Then, a second hash function is used to obtain the shared key based on the current dynamic secret and the global key determined by preset rules. The data in the mirror library is then encrypted based on the shared key.

[0063] The decryption process of data in the mirror repository can rely on the same hash operation. First, the maximum value of the number of link reference pointers in the form within the corresponding storage period and / or the cumulative value of the number of link reference pointers in a single form are used as a feature. During the construction of the mirror repository, the same first hash function as in the encryption process is used to calculate the dynamic secret of the current storage period based on the feature corresponding to the form in the university database whose number of link reference pointers reaches a preset threshold. Then, the same second hash function as in the encryption process is used to obtain the shared key based on the current dynamic secret and the global key determined by preset rules. The data in the mirror repository is decrypted based on the shared key. The number of link reference pointers in the form within the storage period can be stored in a separate accumulator to count its maximum value or cumulative value, and to facilitate the triggering of updates to data items in the subject database based on its overflow state. The second hash function can simply calculate the shared key based on the current dynamic secret and the sequential concatenation value of the global key determined by preset rules, or the sum or XOR value of the two key values. The current dynamic secret can effectively avoid the risk of key leakage caused by the theft of accumulator data. The global key determined by the preset rules can adjust the difficulty of encryption operation according to the characteristics of the current dynamic key by setting its rules, so as to balance the contradiction between data security and throughput efficiency in accordance with the computing power of different computing systems.

[0064] In this process, the first and second hash functions can be any of the following algorithms: md5, sha-1, sha-2, DSA-SHA1, or RSA-SHA1.

[0065] For the raw data of the university database stored in the subject library indicator table storage unit, it can be encrypted using the same encryption method. Alternatively, access and update rules can be restricted to allow updates to data units triggered only by terminals with specific, secure authentication permissions. Since the update process can be directly triggered by the derived logic maintenance module in the logical view processing unit to update and confirm the related data in each logical link, it will not affect the completeness of the system update process and will not cause problems such as forgotten updates or untimely update review.

[0066] The above are merely embodiments of this application, and their descriptions are quite specific and detailed, but they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application.

Claims

1. A closed-loop system for university data entry based on shadow tables, characterized in that, include: Thematic library indicator table storage unit is used to store the raw data of the university database; The mirror library indicator table storage unit is used to generate and store mirror libraries containing the original data of university databases; The interaction port is used to respond to external user operations and trigger corresponding data operation commands. The logical table storage unit generates and stores logical tables corresponding to the data items in the indicator table of the mirror library in response to the data operation instructions output by the interactive port. In the logical table, the data content, data collection type, data tag category, audit status and system record information fields corresponding to each data operation instruction are marked accordingly to construct logical items. The logical view processing unit compares the data items in the mirror database with the logical items in the logical table storage unit according to each logical item in the logical table storage unit, generates a difference view, and pushes the difference view to the corresponding interaction port. Based on the user operation feedback from the interaction port, it triggers the modification of the corresponding original data in the university database in the theme library indicator table storage unit.

2. The closed-loop system for university data entry based on shadow tables as described in claim 1, characterized in that, The logical view processing unit also includes a derived logic maintenance module, which is used to store the logical operation relationships between various original data in the university database. After the logical view processing unit pushes the difference view to the corresponding interaction port, in response to the user operation feedback from the interaction port, the corresponding original data in the university database in the subject library indicator table storage unit is modified according to the logical operation relationships between various original data in the university database.

3. The closed-loop system for university data entry based on shadow tables as described in claim 2, characterized in that, The subject library index table storage unit also contains several incremental tables; When modifying the corresponding original data in the university database in the theme library index table storage unit, the modified content is stored in the incremental table corresponding to the storage period according to the preset storage period, and a link reference pointer to the corresponding modified content in the incremental table is added at the corresponding position of the original data. When retrieving the corresponding original data from the university database in the theme database index table storage unit, the corresponding modified content in the incremental table is retrieved according to the latest link reference pointer stored in the corresponding data bit. The storage unit of the subject library index table also triggers the retrieval of the corresponding modified content in the incremental table to replace the original data when the link reference pointer stored in any data bit overflows, according to the latest link reference pointer.

4. The closed-loop system for university data entry based on shadow tables as described in claim 3, characterized in that, The steps involved in generating and storing the original data mirror library of the university database in the mirror library index table storage unit include: Query the link reference pointers in each original data in the university database, retrieve the forms in the university database whose number of link reference pointers has reached a preset threshold, and store the data in the form into the mirror database of the original data in the university database according to the latest link reference pointer.

5. The closed-loop system for university data entry based on shadow tables as described in claim 4, characterized in that, In the logical table, each data operation instruction is labeled with its corresponding data content, data acquisition type, data label category, review status, and system record information fields. The specific steps for constructing logical items include: Mark the data content from the ETL interface as having a data acquisition type of "0"; Mark the data content from the API interface as having a data collection type of "1"; Mark the data content from other interfaces as having a data acquisition type of "2"; Mark the data content from manual entry as having a data collection type of "9"; Mark the newly added data content with its data tag category as "I"; Mark the modified data content with its data tag category as "U"; The deleted data will be marked with the data tag category "D"; Mark the approved data content on the interactive port with an approval status of "1"; Mark the data content that has not passed the review on the interaction port with a review status of "0"; The system record information field in the data content is based on the account name, response time, modifier, and modification time marker corresponding to the data operation command from the interactive port.

6. The closed-loop system for university data entry based on shadow tables as described in claim 5, characterized in that, For data content with the data label category "U", the logical view processing unit marks all logical items of the data content, as well as the modifier and modification time of each logical item in the difference view; The logical view processing unit also marks the modified data content, modifier, modification time, and logical operation relationship of each logical item in the difference view when modifying the corresponding original data in the university database in the theme library index table storage unit according to the logical operation relationship stored in the derived logic maintenance module, so that the user at the interaction port can trigger the confirmation operation accordingly.

7. The closed-loop system for university data entry based on shadow tables as described in claim 4, characterized in that, The image library indicator table storage unit uses the open-source image building tool Kaniko to build the image; The specific steps for building an image include: Specify the global file path, Dockerfile file path, image push address, and source code location for Kaniko's executable program. The executable program extracts the contents of the Dockerfile file as the container's file system, and then uses this file system to automatically clone data from the forms in the university database that meet the preset threshold in the storage unit corresponding to the global file path to complete the image library construction. Finally, push the image to the specified image push address for caching and subsequent querying and calling.

8. The closed-loop system for university data entry based on shadow tables as described in claim 7, characterized in that, The mirror database index table storage unit uses a first hash function to calculate the current dynamic secret based on the feature value corresponding to the form in the university database whose number of linked reference pointers reaches a preset threshold. It then uses a second hash function to obtain a shared key based on the current dynamic secret and a global key determined by preset rules. The data in the mirror database is then encrypted using the shared key. The feature quantity is the maximum value of the number of link reference pointers in the form and / or the cumulative value of the number of link reference pointers in a single form within the current storage cycle.

9. The closed-loop system for university data entry based on shadow tables as described in any one of claims 1-8, characterized in that, The interaction ports include wireless smart terminals, computers, servers, and microcomputers. Each interaction port is also used to convert user operations into data operation instructions under unified rules through API interfaces.

10. The closed-loop system for university data entry based on shadow tables as described in claim 1, characterized in that, The storage unit for the theme library indicator table is set up independently. When its link reference pointer overflows, it triggers the retrieval of the corresponding modified content in the incremental table to replace the original data according to the latest link reference pointer. Furthermore, the original data is compressed and stored in the corresponding item of the log data according to the replacement time.

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