A method and system for upgrading software basic data

Abstract

The present invention relates to the field of data upgrade technology, specifically a method and system for upgrading software basic data, comprising the following steps: configuring a snapshot storage area in the software, assigning a timestamp identifier to each data snapshot, and recording the time and data upgrade content of each snapshot, and generating a snapshot index record. In the present invention, by configuring a snapshot storage area, assigning a timestamp identifier to a data snapshot, and recording the time and content of the snapshot, the management efficiency and traceability in the data upgrade process are effectively improved, the changes in basic data are captured in real time, and incremental data snapshots are recorded, so that the operation of restoring data to a target time point is more accurate, ensuring seamless connection between data relevance and integrity, and by analyzing and converting data encoding, enhancing the consistency and readability of upgraded data, improving the overall data processing capability, providing real-time monitoring and risk management tools for data upgrades, and ensuring the improvement of data integrity and stability.

Description

Technical Field

[0001] The present invention relates to the technical field of data upgrade, and in particular to a method and system for upgrading software basic data. Background Art

[0002] The field of data upgrade technology deals with methods and strategies for modifying or converting databases or data structures in information technology and software engineering to support new versions or improved functionality of software systems. The key is to ensure that the integrity, confidentiality, and accessibility of data are not affected during the upgrade process while minimizing disruption to existing operations. Data upgrades need to be precisely planned and executed to avoid data loss or system malfunctions. The processes involved include data backup, data cleaning, data migration, and data synchronization between old and new systems, which requires not only a deep understanding of database management systems, but also a full understanding of the associated applications and business logic.

[0003] Among them, the software basic data upgrade method refers to a series of operations and technologies for upgrading or optimizing the basic data structure of the software in order to adapt to new system requirements or improve existing functions during the software development and maintenance process. The core is to ensure that the data structure can support new software functions or improve system performance after the upgrade. The upgrade method has a wide range of uses, including enhancing data processing speed, expanding database functions, improving user interfaces and experience, and improving system security. Through effective data upgrades, enterprises can ensure the continued adaptability and competitiveness of their IT systems while reducing the risks caused by outdated technology.

[0004] Existing data upgrade technologies have problems with insufficient data management and recovery accuracy when dealing with large-scale data and complex systems. In particular, in scenarios involving multiple versions and large-scale data migration, existing technologies cannot provide sufficient data traceability and real-time monitoring methods, resulting in increased error rates in the data recovery process and limited system stability and performance optimization. For example, in the absence of an effective data snapshot and timestamp identification system, it is difficult to accurately correspond to a specific historical state during data recovery, resulting in damage to data integrity. Existing technologies lack effective automatic detection and conversion mechanisms in the case of inconsistent data encoding, which is particularly evident in multi-language and multi-format data environments, resulting in inefficient data use and even data access errors. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a software basic data upgrading method and system.

[0006] In order to achieve the above object, the present invention adopts the following technical solution, a method for upgrading software basic data, comprising the following steps:

[0007] S1: Configure the snapshot storage area in the software, assign a timestamp identifier to each data snapshot, record the time and data upgrade content of each snapshot, and generate a snapshot index record;

[0008] S2: Identify the difference between the real-time basic data upgrade and the snapshot index record, capture and record the changed basic data, identify the storage space requirements of the software, and obtain an incremental data snapshot;

[0009] S3: Using the incremental data snapshot, rebuild the state of the basic data upgrade to the target time point, identify the historical state of the software basic data by adjusting the relevance and integrity of the basic data, and generate a recovery data state;

[0010] S4: Analyze the character encodings of the software basic data and the target data according to the restored data state, automatically detect and convert mismatched encodings, verify the consistency and readability of the data after the upgrade, and obtain the encoding conversion result;

[0011] S5: Based on the encoding conversion result, by calculating the hash value of the basic data, assigning a summary identifier to each data block, and recording the relationship between the summary identifier and the basic data timestamp, generating a data synchronization check point;

[0012] S6: By comparing the data summary in the data synchronization checkpoint with the current state of the target basic data, the data synchronization mechanism of the software is started, the deviation and potential risks in the data upgrade are identified, and the data upgrade plan is obtained.

[0013] As a further solution of the present invention, the snapshot index record includes the timestamp of the data, the generation time of the snapshot, and the type and scope of the data change; the incremental data snapshot includes the timestamp of the changed data, the description of the changed content, and the original and new values ​​of the changed data; the restored data state includes the reconstructed data time point, the integrity status of the data content, and the adjustment of data association; the encoding conversion result includes the character encoding type before and after the conversion, the success rate of the encoding conversion, and data loss information; the data synchronization check point includes the hash value of the data block, the timestamp of the data block, and the relationship between the hash value and the timestamp; the data upgrade plan includes the identified data deviation type, the impact scope of the deviation data, and the prevention and correction measures.

[0014] As a further solution of the present invention, a snapshot storage area is configured in the software, a timestamp identifier is assigned to each data snapshot, and the time and data upgrade content of each snapshot are recorded. The steps of generating a snapshot index record are specifically as follows:

[0015] S101: configuring a snapshot storage area in the software, configuring an independent storage space for each snapshot, and assigning a timestamp identifier to the snapshot, checking the utilization of the software basic data by selecting a storage medium and allocating storage capacity, and generating a snapshot time identifier;

[0016] S102: Based on the snapshot time identifier, record the time of each data snapshot and the associated software basic data upgrade content, including deletion and modification of data items, and set the software basic data record format and storage structure to generate a snapshot content record;

[0017] S103: According to the snapshot content record, in combination with the snapshot information, the snapshot and the associated timestamp and data upgrade content are identified, and the snapshot index record is generated by optimizing the index structure and processing the information of the software basic data.

[0018] As a further solution of the present invention, the steps of identifying the difference between the real-time basic data upgrade and the snapshot index record, capturing and recording the changed basic data, identifying the storage space requirement of the software, and obtaining the incremental data snapshot are specifically as follows:

[0019] S201: monitoring the changes between the real-time basic data upgrade and the snapshot index record, comparing the real-time data status with the status recorded in the snapshot index, querying and detecting changes to the software basic data upgrade status, and generating a change detection result;

[0020] S202: Based on the change detection result, capture the data items that have been changed after the software basic data is upgraded, record the status before and after and the change time of each data item, set data capture rules and the format for storing changes, and generate change data records;

[0021] S203: Analyze the change data record to evaluate the storage space demand of the software, predict the data change trend in the future time period, adjust the storage configuration and expansion plan of the software by analyzing the amount and type of change data, and obtain an incremental data snapshot.

[0022] As a further solution of the present invention, the incremental data snapshot is used to rebuild the state of the basic data upgrade to the target time point, and the historical state of the software basic data is identified by adjusting the relevance and integrity of the basic data. The steps of generating the recovery data state are specifically as follows:

[0023] S301: Based on the incremental data snapshot, the software basic data is rebuilt to the target time point according to the recorded timestamps, and the time sequence arrangement and historical state of the snapshot data are gradually reconstructed, including changes in data hierarchy and dependency relationships, to generate the data state at the target time point;

[0024] S302: Based on the data state at the target time point, adjust the association between data items, check relational data and verify the association path of non-relational data, configure and execute data integrity rules, and generate an association adjustment record;

[0025] S303: Utilizing the relevance adjustment record, analyzing and verifying the historical status of the data, checking the queryability of the historical data, including index update and integrity verification of the historical data, and generating a restored data status.

[0026] As a further solution of the present invention, according to the restored data state, the character encoding of the software basic data and the target data is analyzed, the mismatched encoding is automatically detected and converted, and the consistency and readability of the data after the upgrade are verified. The steps of obtaining the encoding conversion result are specifically as follows:

[0027] S401: by recovering the data state, analyzing the character encoding of the software basic data and the target data, automatically detecting the character encoding, identifying the encoding format of multiple data items by scanning the software basic data, recording the detected differential encoding, and generating an encoding detection record;

[0028] S402: Based on the code detection record, automatically convert the codes identified as mismatched, check the uniformity of the basic data format of the software after the data upgrade, track and record the conversion effect after the data upgrade, and generate a code conversion log;

[0029] S403: Using the encoding conversion log, verify the consistency and readability of the data after the upgrade, check the integrity of the converted data, and perform function and performance tests on the upgraded and converted data to obtain the encoding conversion result.

[0030] As a further solution of the present invention, based on the encoding conversion result, by calculating the hash value of the basic data, assigning a summary identifier to each data block, and recording the relationship between the summary identifier and the basic data timestamp, the steps of generating a data synchronization check point are specifically as follows:

[0031] S501: Based on the encoding conversion result, the error correction coding technology is used to calculate the hash value of each data block, and the hash value is error detected and corrected, the uniqueness and reliability of the hash value are checked, and the data block hash record is generated;

[0032] S502: allocating a summary identifier to each data block through the data block hash record, verifying the uniqueness of each identifier and the tracking of the data block through mapping the hash value and the data block content, setting the association relationship between the data block and the hash identifier, and generating a summary identifier allocation record;

[0033] S503: Identify the timestamp relationship between the summary identifier allocation record and the software basic data, and perform verification and synchronization of the software basic data by setting the timestamp and summary identifier of the software basic data to generate a data synchronization verification point.

[0034] As a further solution of the present invention, the formula of the error correction coding technology is as follows:

[0035]

[0036] Among them, C ′ is the improved coded data block, H is the hash value of each data block, K is the key of the check code, G is the original generation matrix, F is the adjustment factor matrix, W is the weight coefficient, and D is the data block size adjustment factor.

[0037] As a further solution of the present invention, by comparing the data summary in the data synchronization checkpoint with the current state of the target basic data, starting the data synchronization mechanism of the software, identifying the deviation and potential risks in the data upgrade, and obtaining the data upgrade solution, the specific steps are:

[0038] S601: Compare the data summary in the data synchronization checkpoint with the real-time status of the target basic data, detect the consistency of the hash value, identify the deviation, and record the data point of the deviation to generate a data comparison analysis result;

[0039] S602: Based on the data comparison and analysis results, the data synchronization mechanism of the software is started, the data synchronization is adjusted by correcting the deviated data, and the data synchronization rules are updated, the error processing and log records of the data synchronization are identified, and the synchronization adjustment records are generated;

[0040] S603: Analyze the problem points in the synchronization adjustment record, identify the deviations and potential risks in the data upgrade, predict the impact and risks, design mitigation measures for the risks, and obtain a data upgrade plan by updating the data backup and recovery strategy.

[0041] A software basic data upgrade system, the software basic data upgrade system is used to execute the above-mentioned software basic data upgrade method, the system comprises:

[0042] The snapshot configuration module configures the snapshot storage area in the software, analyzes the time of the software basic data snapshot, and assigns a timestamp identifier, and establishes a snapshot index record by identifying and recording the data upgrade content;

[0043] The difference capture module identifies the difference between the real-time basic data upgrade and the snapshot index record, records the changed basic data, and calculates the storage space requirement of the software to obtain the incremental data snapshot;

[0044] The data adjustment module uses the incremental data snapshot to restore the software basic data to the data state at the key time point, updates the relevance and integrity of the data, identifies the historical state of the basic data, and generates a restored data state;

[0045] The encoding optimization module analyzes the character encoding of the software basic data according to the restored data state, converts the mismatched encoding, checks the consistency and readability of the software basic data, and obtains the encoding conversion result;

[0046] The synchronization verification module records the relationship between the timestamp and the summary of each data block based on the encoding conversion result, identifies the deviation and risk in the data upgrade, and obtains the data upgrade plan.

[0047] Compared with the prior art, the advantages and positive effects of the present invention are:

[0048] In the present invention, by configuring the snapshot storage area, assigning a timestamp identifier to the data snapshot, and recording the time and content of the snapshot, the management efficiency and traceability in the data upgrade process are effectively improved. The changes in the basic data are captured in real time and the incremental data snapshots are recorded, so that the operation of restoring the data to the target time point is more accurate, ensuring the seamless connection of data relevance and integrity. By analyzing and converting data encoding, the consistency and readability of the upgraded data are enhanced, and the overall data processing capability is improved. The data synchronization checkpoint provides real-time monitoring and risk management tools for data upgrades to ensure the improvement of data integrity and stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0050] Figure 2 This is a detailed flow chart of S1 of the present invention;

[0051] Figure 3 This is a detailed flow chart of S2 of the present invention;

[0052] Figure 4 This is a detailed flow chart of S3 of the present invention;

[0053] Figure 5 This is a detailed flow chart of S4 of the present invention;

[0054] Figure 6 This is a detailed flow chart of S5 of the present invention;

[0055] Figure 7 This is a detailed flow chart of S6 of the present invention;

[0056] Figure 8 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0058] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0059] Embodiment 1

[0060] See also Figure 1 The present invention provides a technical solution, a method for upgrading software basic data, comprising the following steps:

[0061] S1: Configure the snapshot storage area for basic data upgrade in the software, assign a timestamp identifier to each data snapshot, record the time of each snapshot and the data upgrade content included, and generate a snapshot index record;

[0062] S2: Identify the differences between the real-time basic data upgrade and the snapshot index record, capture and record the changed basic data, identify the storage space requirements of the software, and obtain the incremental data snapshot;

[0063] S3: Use incremental data snapshots to rebuild the state of basic data upgrade to the target time point, identify the historical state of software basic data by adjusting the relevance and integrity of basic data, and generate recovery data state;

[0064] S4: Analyze the character encodings of the software basic data and the target data according to the restored data status, automatically detect and convert mismatched encodings, verify the consistency and readability of the software basic data after the upgrade, and obtain the encoding conversion result;

[0065] S5: Based on the encoding conversion result, before synchronizing the software basic data, a summary identifier is assigned to each data block by calculating the hash value of the software basic data, and the relationship between the summary identifier and the basic data timestamp is recorded to generate a data synchronization checkpoint;

[0066] S6: By comparing the data summary recorded in the data synchronization checkpoint with the current status of the target basic data, the data synchronization mechanism of the software is started, the deviations and potential risks in the software basic data upgrade are identified, and the data upgrade plan is obtained.

[0067] The snapshot index record includes the timestamp of the data, the time when the snapshot was generated, and the type and scope of the data changes. The incremental data snapshot includes the timestamp of the changed data, the description of the changed content, and the original and new values ​​of the changed data. The restored data status includes the reconstructed data time point, the integrity status of the data content, and the adjustment of data relevance. The encoding conversion results include the character encoding types before and after the conversion, the success rate of the encoding conversion, and data loss information. The data synchronization checkpoint includes the hash value of the data block, the timestamp of the data block, and the relationship between the hash value and the timestamp. The data upgrade plan includes the identified data deviation type, the impact scope of the deviation data, and the prevention and correction measures.

[0068] See also Figure 2 , configure the snapshot storage area in the software, assign a timestamp identifier to each data snapshot, and record the time and data upgrade content of each snapshot. The specific steps for generating snapshot index records are:

[0069] S101: Configure a snapshot storage area in the software, configure an independent storage space for each snapshot, and assign a timestamp identifier to the snapshot. Check the utilization of the software basic data by selecting a storage medium and allocating storage capacity. The execution process of generating a snapshot timestamp is as follows;

[0070] Substep S101 configures the snapshot storage area in the software, creates an independent storage space for each data snapshot and assigns a unique timestamp identifier to ensure the accuracy and efficiency of data version control. The selection of appropriate storage media, such as solid-state drives (SSDs), mechanical hard disks (HDDs) or cloud-based storage, is based on performance requirements and cost-effectiveness considerations. Reasonable allocation of storage capacity is not only related to cost control, but also directly affects the speed and feasibility of data recovery. Each snapshot can be quickly located and restored when needed, improving the utilization and security of software basic data. The snapshot time identifier is generated using the formula:

[0071]

[0072] Among them, S storage represents the overall efficiency of the snapshot storage configuration, c i is the capacity of storage medium i, t i is the timestamp efficiency and n is the number of snapshots.

[0073] S102: Based on the snapshot time identifier, record the time of each data snapshot and the associated software basic data upgrade content, including the deletion and modification of data items, and set the software basic data record format and storage structure. The execution process of generating the snapshot content record is as follows;

[0074] Substep S102 records the specific time of each data snapshot and the upgrade content of the associated software basic data, including the deletion and modification of data items, based on the snapshot time identifier, to ensure the integrity and consistency of the data. The recording format and storage structure of the software basic data are set to achieve the standardization of data management. It not only facilitates data tracking and auditing, but also improves data security and traceability. The data status at any point in time can be accurately restored, enhancing the reliability and stability of the data. The snapshot content record is generated using the formula:

[0075]

[0076] Among them, R sna Indicates the detail of the snapshot content record, u j is the importance of data upgrade, v j is the accuracy of change records, and m is the number of change events.

[0077] S103: According to the snapshot content record, combined with the snapshot information, the snapshot and the associated timestamp and data upgrade content are identified, and the execution flow of generating the snapshot index record by optimizing the index structure and processing the information of the software basic data is as follows;

[0078] Substep S103 identifies the relationship between the snapshot and the associated timestamp and data upgrade content based on the snapshot content record. By optimizing the index structure and strengthening the information processing of the software basic data, not only the speed and efficiency of data retrieval are improved, but also the consistency and security of accessing data are ensured, and user queries can be quickly responded to, and the required historical data can be provided, making data management more powerful and reliable. The optimization measures also help reduce data redundancy and storage costs, improve overall data management efficiency, and generate snapshot index records using the formula:

[0079]

[0080] Among them, I index represents the efficiency of snapshot index records, x k is the optimization degree of index item k, y k is the efficiency of data processing, and p is the total number of index items.

[0081] See also Figure 3, identify the difference between the real-time basic data upgrade and the snapshot index record, capture and record the changed basic data, identify the storage space requirements of the software, and obtain the incremental data snapshot steps as follows:

[0082] S201: monitor the changes between the real-time basic data upgrade and the snapshot index record, compare the real-time data status with the status recorded in the snapshot index, and query and change the software basic data upgrade status. The execution process of generating the change detection result is as follows;

[0083] Sub-step S201 monitors the changes between real-time basic data upgrades and snapshot index records, monitors each data upgrade or change in real time, and compares it with the data status in the stored snapshot index. The monitoring and comparison operations allow administrators to promptly identify any abnormal changes or unauthorized modifications to the data, thereby enhancing the data security monitoring capabilities. Implementing query and change detection not only improves the protection of data integrity, but also ensures timely updates of data status. Through comparison and detection, the change detection results are generated, using the formula:

[0084]

[0085] Among them, C monitor represents the efficiency of monitoring and change detection, δ i is the importance weight of the i-th data change, β i is the accuracy of change detection, and n is the number of changes in the monitoring period.

[0086] S202: Based on the change detection results, the data items that have been changed after the software basic data is upgraded are captured, the state before and after each data item and the change time are recorded, the data capture rules and the format for storing changes are set, and the execution process of generating the change data record is as follows;

[0087] Based on the change detection results, sub-step S202 captures the data items that have changed after the software basic data is upgraded, including recording the status and change time of each data item before and after, ensuring that each change is recorded in detail to support the needs of data recovery and historical tracing. Setting data capture rules and storage change formats is to optimize data management and improve storage efficiency, which not only enhances data traceability, but also provides protection for data security and compliance. The change data record is generated using the formula:

[0088]

[0089] Among them, R capture Indicates the accuracy and detail of the change data record, α j is the change importance of data item j, γ j is the record accuracy, and m is the number of changed data items.

[0090] S203: Analyze the change data record to evaluate the storage space requirements of the software, predict the data change trend in the future time period, adjust the storage configuration and expansion plan of the software by analyzing the amount and type of change data, and obtain the execution process of the incremental data snapshot as follows;

[0091] Sub-step S203 analyzes the change data records to evaluate the storage space requirements of the software and predicts the trend of data changes in the future. Through detailed analysis of the amount and type of changed data, the storage configuration and expansion plan of the software can be effectively adjusted. It not only helps to optimize the use of storage resources, but also ensures scalability and flexibility in the face of data growth. According to the analysis and prediction, not only the storage requirements are reduced, but also the data recovery and access speed are accelerated, and the incremental data snapshot is generated. The formula used is:

[0092]

[0093] Among them, S incremental represents the optimization and storage efficiency of incremental data snapshots, σ k is the predicted data change, ρ k is the responsiveness of storage adjustment and p is the time period considered.

[0094] See also Figure 4 , using incremental data snapshots, rebuilding the state of basic data upgrade to the target time point, by adjusting the relevance and integrity of basic data, identifying the historical state of software basic data, and generating the steps to restore data state are as follows:

[0095] S301: Based on the incremental data snapshot, the software basic data is rebuilt to the target time point according to the recorded timestamp, and the time sequence arrangement of the snapshot data and the gradual reconstruction of the historical state, including the changes in the data hierarchy and dependency relationships, are performed to generate the data state at the target time point. The execution process is as follows;

[0096] Sub-step S301 rebuilds the basic software data to the target time point based on the incremental data snapshot, which involves data recovery technology and requires accurate processing of the temporal arrangement of snapshot data and the gradual reconstruction of historical status. By restoring the changes in data hierarchy and dependencies, the historical integrity and logical consistency of the data can be ensured, allowing administrators or users to go back to any specific point in time to view the data status at that time. During the reconstruction process, pay attention to maintaining the historical continuity and dependencies of the data, ensure the accurate representation of all data levels at the target time point, and generate the data status at the target time point. The formula used is:

[0097]

[0098] Among them, D re Indicates the accuracy and completeness of data reconstruction, τi is the data accuracy at time point i, λ i is the degree of dependency preservation, and n is the number of data points.

[0099] S302: Based on the data status at the target time point, the association between data items is adjusted, the relational data is checked and the association path of non-relational data is verified, and the data integrity rules are configured and executed. The execution process of generating the association adjustment record is as follows;

[0100] Substep S302 adjusts and verifies the associations between data items based on the data status at the target time point, including structural and integrity checks on relational data and verification of association paths for non-relational data, to ensure that all data items are logically related and consistent, and to strengthen the structural integrity of the data. It is also necessary to configure and execute data integrity rules to ensure the consistency and accuracy of data in the entire system, and to generate association adjustment records using the formula:

[0101]

[0102] Among them, A ad represents the effect of relevance adjustment record, ξ j is the association strength of data item j, η j is the adjusted data completeness, and m is the number of data items.

[0103] S303: Utilize the correlation adjustment record, analyze and verify the historical status of the data, check the queryability of the historical data, including the index update and integrity verification of the historical data, and generate the execution flow of restoring the data status as follows;

[0104] Sub-step S303 uses the association to adjust the records, analyze and verify the historical status of the data. The main task is to check the queryability and integrity of the historical data, ensure that all historical data states can be accurately retrieved through the updated index, not only update the data index, but also conduct a thorough integrity verification to ensure the correct representation and easy access to the historical state of the data, provide a comprehensive view of the data recovery and verification process, ensure the accuracy and integrity of the historical data, and generate a record of the restored data state. The formula used is:

[0105]

[0106] Among them, H recovery Indicates the effect of restoring the data state, ω k is the update degree of the data index, k is the success rate of historical data integrity verification, and p is the number of historical data points.

[0107] See also Figure 5, according to the restored data status, analyze the character encoding of the software basic data and the target data, automatically detect and convert the mismatched encoding, verify the consistency and readability of the data after the upgrade, and obtain the encoding conversion results in the following steps:

[0108] S401: by restoring the data state, analyzing the character encoding of the software basic data and the target data, automatically detecting the character encoding, identifying the encoding format of multiple data items by scanning the software basic data, recording the detected differential encoding, and generating the encoding detection record. The execution process is as follows;

[0109] Sub-step S401 performs character encoding analysis of software basic data and target data by restoring the data status, including automatically detecting and identifying the character encoding formats of various data items. In software systems, the consistency of character encoding is crucial because inconsistent encoding can lead to data parsing errors or information loss. By scanning the software basic data, multiple encoding formats used in different data items can be identified, which not only helps to understand the current data status, but also provides a basis for subsequent encoding unification and data processing, and generates encoding detection records. The formula used is:

[0110]

[0111] Among them, E detection Indicates the comprehensiveness and accuracy of coding detection, μ i is the recognition difficulty of data item i, ν i is the encoding difference and n is the total number of data items.

[0112] S402: Based on the code detection record, automatically convert the codes identified as mismatched, check the uniformity of the basic data format of the software after the data upgrade, and track and record the conversion effect after the data upgrade. The execution process of generating the code conversion log is as follows;

[0113] Sub-step S402 is based on the coding detection record. It identifies mismatched codes in the coding detection record and performs necessary automatic conversion to ensure the uniformity of the basic data format of the software during the data upgrade process. The automatic conversion mechanism can reduce manual intervention and improve the efficiency and accuracy of data processing. After the conversion is completed, the format of the basic software data will be rechecked to ensure that the coding of all data items has been unified. Track and record the conversion effect after the data upgrade to provide a reference for future data review and problem diagnosis, and generate a coding conversion log using the formula:

[0114]

[0115] Among them, T conversion represents the efficiency and success rate of the encoding conversion process, α jis the transformation complexity of data item j, β j is the consistency of the data after transformation, and m is the total number of data items to be transformed.

[0116] S403: Using the encoding conversion log, verify the consistency and readability of the data after the upgrade, check the integrity of the converted data, and perform function and performance tests on the upgraded and converted data. The execution process of obtaining the encoding conversion result is as follows;

[0117] Substep S403 uses the encoding conversion log to verify the consistency and readability of the data after the upgrade and conversion, which is related to the availability and stability of the data. Check the integrity of the converted data to ensure that all data items have not been lost or damaged after the encoding conversion. Functional and performance testing is also required for the upgraded and converted data to evaluate the effectiveness of the data processing process and the ability to handle the newly encoded data, providing a comprehensive perspective to evaluate the success of the entire process and any areas that need improvement, and generate the encoding conversion results using the formula:

[0118]

[0119] Among them, C results represents the comprehensive evaluation of the encoding conversion result, σ k is the coverage of test scenario k, ρ k is the data consistency and completeness under scenario k, and p is the total number of scenarios tested.

[0120] See also Figure 6 Based on the encoding conversion result, by calculating the hash value of the basic data, a summary identifier is assigned to each data block, and the relationship between the summary identifier and the basic data timestamp is recorded. The steps for generating data synchronization checkpoints are as follows:

[0121] S501: Based on the encoding conversion result, the error correction coding technology is used to calculate the hash value of each data block, and the hash value is error detected and corrected, and the uniqueness and reliability of the hash value are checked. The execution process of generating the data block hash record is as follows;

[0122] Based on the coding conversion result, sub-step S501 uses error correction coding technology to enhance data integrity and calculates the hash value of each data block, which not only helps identify data errors during data storage or transmission, but also detects and corrects errors. Using error correction coding, such as Hamming code or Reed-Solomon code, can effectively enhance the ability to identify and repair data errors. Verifying the uniqueness and reliability of each hash value is a key step to ensure data security, providing a basis for further processing and verification of data and generating data block hash records.

[0123] The formula for error correction coding technology is as follows:

[0124]

[0125] Among them, C ′ is the improved coded data block, H is the hash value of each data block, K is the key of the check code, G is the original generation matrix, F is the adjustment factor matrix, W is the weight coefficient, and D is the data block size adjustment factor.

[0126] The execution flow is as follows:

[0127] The hash value H of each data block is operated with the key K of the check code to increase the randomness and security of the result. The original generating matrix G is multiplied element by element with the adjustment factor matrix F to enhance the complexity and robustness of the matrix operation. The result is multiplied by the weight coefficient W to adjust the sensitivity and correction ability of error detection. The result is multiplied by the data block size adjustment factor D to adapt to data blocks of different sizes and improve the flexibility and adaptability of the encoding. The weight coefficient W is determined through experimental data analysis or machine learning model optimization to ensure the optimal error handling performance.

[0128] S502: assigning a summary identifier to each data block through the data block hash record, verifying the uniqueness of each identifier and the tracking of the data block through the mapping of the hash value and the data block content, setting the association between the data block and the hash identifier, and generating the summary identifier assignment record. The execution process is as follows;

[0129] Substep S502 allocates a summary identifier to each data block through the data block hash record, verifies the uniqueness of each identifier by mapping the hash value and the data block content, and ensures that the data block can be accurately tracked and identified. The association between the data block and the hash identifier is set to support efficient management and secure storage of data. Each change of the data block can be accurately recorded and verified, enhancing the security and traceability of the data, providing a detailed basis for further management and verification of the data, and generating a summary identifier allocation record. The formula used is:

[0130]

[0131] Among them, M digest Indicates the detail and accuracy of the summary identification allocation record, α j is the uniqueness score of data block j, β j is the success rate of mapping hash to data block content, and m is the number of data blocks processed.

[0132] S503: Identify the timestamp relationship between the summary identifier allocation record and the software basic data, and perform verification and synchronization of the software basic data by setting the timestamp and summary identifier of the software basic data. The execution flow of generating a data synchronization verification point is as follows;

[0133] Sub-step S503 identifies the timestamp relationship between the summary identifier allocation record and the software basic data. By setting the timestamp and summary identifier of the software basic data, data verification and synchronization are performed to ensure the consistency and accuracy of the software basic data. The summary identifier associated with the timestamp can quickly locate the data status at any point in time, improve the efficiency and accuracy of data recovery, provide important data recovery and audit nodes, support continuous monitoring and management of data integrity, and generate data synchronization verification points. The formula used is:

[0134]

[0135] Among them, S sync represents the stability and accuracy of the data synchronization checkpoint, γ k is the correspondence accuracy between timestamp and data state, δ k is the integrity of the synchronization operation and p is the number of checkpoints.

[0136] See also Figure 7 By comparing the data summary in the data synchronization checkpoint with the current status of the target basic data, the data synchronization mechanism of the software is started, the deviations and potential risks in the data upgrade are identified, and the steps for obtaining the data upgrade plan are as follows:

[0137] S601: Compare the data summary in the data synchronization checkpoint with the real-time status of the target basic data, detect the consistency of the hash value, identify the deviation, and record the data point of the deviation, and generate the data comparison analysis result. The execution process is as follows;

[0138] Sub-step S601 compares the data summary in the data synchronization checkpoint with the real-time status of the target basic data, and ensures the accuracy and integrity of the data by detecting the consistency of the hash value. Through comparison, any deviation or inconsistency in the data can be effectively identified. The deviated data points will be recorded to provide an accurate reference for subsequent data processing and correction, ensure the integrity of the data, help maintain the data consistency and reliability of the system, and generate data comparison and analysis results.

[0139] S602: Based on the data comparison and analysis results, the data synchronization mechanism of the software is started, the data synchronization is adjusted by correcting the deviated data, and the data synchronization rules are updated, the error processing and log records of data synchronization are identified, and the execution process of generating synchronization adjustment records is as follows;

[0140] Based on the data comparison and analysis results, sub-step S602 starts the data synchronization mechanism of the software, adjusts data synchronization by correcting deviated data, and updates data synchronization rules to adapt to the new data environment. It is also necessary to identify errors that occur during the data synchronization process and perform appropriate logging. It not only provides a detailed log of the synchronization process, but also helps administrators monitor the effectiveness and accuracy of data synchronization and generate synchronization adjustment records.

[0141] S603: Analyze the problem points in the synchronization adjustment record, identify the deviations and potential risks in the data upgrade, predict the impact and risks, design risk mitigation measures, and obtain the execution process of the data upgrade plan through the update of the data backup and recovery strategy as follows;

[0142] Sub-step S603 analyzes the problem points in the synchronization adjustment records, identifies deviations and potential risks in the data upgrade process, not only focuses on the current data status, but also predicts future impacts and risks, and designs risk mitigation measures, such as updating data backup and recovery strategies. The measures are designed to protect data security, reduce the risks of future operations, ensure data stability and system reliability, and provide a comprehensive data management and protection framework for the system to obtain a data upgrade plan.

[0143] See also Figure 8 , a software basic data upgrade system, the software basic data upgrade system is used to execute the above-mentioned software basic data upgrade method, the system comprises:

[0144] The snapshot configuration module configures the snapshot storage area in the software, analyzes the time of the software basic data snapshot, and assigns a timestamp identifier, and establishes a snapshot index record by identifying and recording the data upgrade content;

[0145] The difference capture module identifies the difference between the real-time basic data upgrade and the snapshot index record, records the changed basic data, and calculates the storage space requirements of the software to obtain the incremental data snapshot;

[0146] The data adjustment module uses incremental data snapshots to restore the basic software data to the data status at a key time point, update the relevance and integrity of the data, identify the historical status of the basic data, and generate the restored data status;

[0147] The encoding optimization module analyzes the character encoding of the software basic data according to the restored data status, converts the mismatched encoding, checks the consistency and readability of the software basic data, and obtains the encoding conversion result;

[0148] Based on the encoding conversion results, the synchronization verification module records the relationship between the timestamp and summary of each data block, identifies deviations and risks in data upgrades, and obtains a data upgrade plan.

[0149] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for upgrading software basic data, characterized in that: The following steps are involved: Configure the snapshot storage area in the software, assign a timestamp identifier to each data snapshot, record the time and data upgrade content of each snapshot, and generate a snapshot index record; Identify the difference between the real-time basic data upgrade and the snapshot index record, capture and record the changed basic data, identify the storage space requirements of the software, and obtain the incremental data snapshot; The incremental data snapshot is used to rebuild the upgraded state of the basic data to the target time point, and the historical state of the software basic data is identified by adjusting the relevance and integrity of the basic data to generate a recovery data state; According to the restored data state, the character encodings of the software basic data and the target data are analyzed, the mismatched encodings are automatically detected and converted, the consistency and readability of the data after the upgrade are verified, and the encoding conversion result is obtained; Based on the encoding conversion result, by calculating the hash value of the basic data, a summary identifier is assigned to each data block, and the relationship between the summary identifier and the basic data timestamp is recorded to generate a data synchronization check point; By comparing the data summary in the data synchronization checkpoint with the current state of the target basic data, the data synchronization mechanism of the software is started, deviations and potential risks in the data upgrade are identified, and a data upgrade plan is obtained; Based on the incremental data snapshot, the software basic data is rebuilt to the target time point according to the recorded timestamps, and the time sequence arrangement and historical state of the snapshot data are gradually reconstructed, including changes in data hierarchy and dependency relationships, to generate the data state at the target time point; Based on the data state at the target time point, adjust the association between data items, check relational data and verify the association path of non-relational data, configure and execute data integrity rules, and generate association adjustment records; The association adjustment record is used to analyze and verify the historical status of the data, check the queryability of the historical data, including index update and integrity verification of the historical data, and generate a restored data status.

2. The software basic data upgrading method according to claim 1, characterized in that: The snapshot index record includes the timestamp of the data, the generation time of the snapshot, and the type and scope of the data change; the incremental data snapshot includes the timestamp of the changed data, the description of the changed content, and the original and new values ​​of the changed data; the restored data state includes the reconstructed data time point, the integrity status of the data content, and the adjustment of data relevance; the encoding conversion result includes the character encoding type before and after the conversion, the success rate of the encoding conversion, and data loss information; the data synchronization check point includes the hash value of the data block, the timestamp of the data block, and the relationship between the hash value and the timestamp; the data upgrade plan includes the identified data deviation type, the impact scope of the deviation data, and the prevention and correction measures.

3. The software basic data upgrading method according to claim 1, characterized in that: Configure the snapshot storage area in the software, assign a timestamp identifier to each data snapshot, and record the time and data upgrade content of each snapshot. The specific steps for generating snapshot index records are as follows: Configure the snapshot storage area in the software, configure independent storage space for each snapshot, and assign a timestamp identifier to the snapshot. Check the utilization of the software basic data by selecting storage media and allocating storage capacity, and generate a snapshot time identifier. Based on the snapshot time identifier, record the time of each data snapshot and the associated software basic data upgrade content, including deletion and modification of data items, and set the software basic data record format and storage structure to generate a snapshot content record; According to the snapshot content record, combined with the snapshot information, the snapshot and the associated timestamp and data upgrade content are identified, and the snapshot index record is generated by optimizing the index structure and processing the information of the software basic data.

4. The software basic data upgrading method according to claim 1, characterized in that: The steps of identifying the difference between the real-time basic data upgrade and the snapshot index record, capturing and recording the changed basic data, identifying the storage space requirements of the software, and obtaining the incremental data snapshot are as follows: Monitor the changes between the real-time basic data upgrade and the snapshot index record, compare the real-time data status with the status recorded in the snapshot index, query and change the software basic data upgrade status, and generate change detection results; Based on the change detection results, the data items that have been changed after the software basic data is upgraded are captured, the before and after states and change time of each data item are recorded, data capture rules and a format for storing changes are set, and a change data record is generated; The storage space requirements of the software are evaluated by analyzing the change data records, and the data change trend in the future time period is predicted. By analyzing the amount and type of change data, the storage configuration and expansion plan of the software are adjusted to obtain incremental data snapshots.

5. The software basic data upgrading method according to claim 1, characterized in that: According to the restored data state, the character encoding of the software basic data and the target data is analyzed, the mismatched encoding is automatically detected and converted, and the consistency and readability of the data after the upgrade are verified. The specific steps of obtaining the encoding conversion result are: By recovering the data state, analyzing the character encoding of the software basic data and the target data, automatically detecting the character encoding, identifying the encoding format of multiple data items by scanning the software basic data, recording the detected differential encoding, and generating an encoding detection record; Based on the encoding detection record, automatically convert the encodings identified as mismatched, check the uniformity of the basic data format of the software after the data upgrade, track and record the conversion effect after the data upgrade, and generate an encoding conversion log; The encoding conversion log is used to verify the consistency and readability of the data after the upgrade, check the integrity of the converted data, and perform function and performance tests on the upgraded and converted data to obtain the encoding conversion result.

6. The software basic data upgrading method according to claim 1, characterized in that: Based on the encoding conversion result, by calculating the hash value of the basic data, assigning a summary identifier to each data block, and recording the relationship between the summary identifier and the basic data timestamp, the steps of generating a data synchronization checkpoint are specifically as follows: Based on the encoding conversion result, the error correction coding technology is used to calculate the hash value of each data block, and the hash value is error detected and corrected, the uniqueness and reliability of the hash value are checked, and the data block hash record is generated; By means of the data block hash record, a summary identifier is assigned to each data block, and by mapping the hash value and the data block content, the uniqueness of each identifier and the tracking of the data block are verified, and an association relationship between the data block and the hash identifier is set to generate a summary identifier assignment record; The relationship between the summary identifier allocation record and the timestamp of the software basic data is identified, and the timestamp and summary identifier of the software basic data are set to verify and synchronize the software basic data, thereby generating a data synchronization verification point.

7. The software basic data upgrading method according to claim 6, characterized in that: The formula for the error correction coding technique is as follows: in, For the improved coded data block, For each data block, is the key of the verification code, is the original generating matrix, To adjust the factor matrix, is the weight coefficient, The data block size adjustment factor.

8. The software basic data upgrading method according to claim 1, characterized in that: By comparing the data summary in the data synchronization checkpoint with the current state of the target basic data, starting the data synchronization mechanism of the software, identifying deviations and potential risks in the data upgrade, and obtaining the data upgrade solution, the specific steps are as follows: Compare the data summary in the data synchronization checkpoint with the real-time status of the target basic data, detect the consistency of the hash value, identify the deviation, and record the data points of the deviation to generate data comparison and analysis results; Based on the data comparison and analysis results, the data synchronization mechanism of the software is started, the data synchronization is adjusted by correcting the deviated data, and the data synchronization rules are updated, the error processing and log records of the data synchronization are identified, and the synchronization adjustment records are generated; Analyze the problem points in the synchronization adjustment record, identify deviations and potential risks in data upgrade, predict impacts and risks, design risk mitigation measures, and obtain a data upgrade plan by updating data backup and recovery strategies.

9. A software basic data upgrade system, characterized in that: According to the software basic data upgrading method according to any one of claims 1 to 8, the system comprises: The snapshot configuration module configures the snapshot storage area in the software, analyzes the time of the software basic data snapshot, and assigns a timestamp identifier, and establishes a snapshot index record by identifying and recording the data upgrade content; The difference capture module identifies the difference between the real-time basic data upgrade and the snapshot index record, records the changed basic data, and calculates the storage space requirement of the software to obtain the incremental data snapshot; The data adjustment module uses the incremental data snapshot to restore the software basic data to the data state at the key time point, updates the relevance and integrity of the data, identifies the historical state of the basic data, and generates a restored data state; The encoding optimization module analyzes the character encoding of the software basic data according to the restored data state, converts the mismatched encoding, checks the consistency and readability of the software basic data, and obtains the encoding conversion result; The synchronization verification module records the relationship between the timestamp and the summary of each data block based on the encoding conversion result, identifies the deviation and risk in the data upgrade, and obtains the data upgrade plan.

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