Real-time data management method and device based on grain storage data and medium

Abstract

The embodiment of the invention provides a real-time data management method and device based on stored grain data and a medium, and the method comprises the steps: carrying out the increment recognition of stored grain update data, so as to determine the change data of a stored grain data table; performing format conversion on the grain storage data table change data, and inserting the grain storage data table change data after format conversion into a preset target data table to obtain to-be-analyzed grain storage update data; based on the to-be-analyzed stored grain updating data, determining a multi-version data storage table through newly-added data primary key judgment; wherein the multi-version data storage table comprises a historical version data table and a data stock table; performing grain storage data influence relationship evaluation on the historical version data table to obtain historical grain storage data change analysis data; and performing grain storage state analysis on the data stock table to determine a current grain storage state parameter. Through the method, the technical problem that historical data cannot be reasonably stored and analyzed when existing stored grain data is updated is solved.

Description

Technical Field

[0001] The present application relates to the technical field of database management, and in particular to a real-time data management method, device and medium based on grain storage data. Background Art

[0002] "Food security is a national priority" and is the "ballast stone" that affects the national economy and people's livelihood, social stability and economic development, and is an important foundation for maintaining national security. Dynamic supervision of grain data generally requires the possible problems in grain inventory, warehousing, grain conditions, and quality inspection data, such as circulating grain, quality inspection anomalies, abnormal grain temperature, excessive loss, and excessive idle period. For possible problems with data changes during grain storage and circulation, it is necessary to retain historical version data to support early warning data.

[0003] When the grain database data changes or needs to be updated or changed, the existing technology usually adopts the processing method of incremental update or full update. The above two data processing methods can realize the data import of the grain database under different requirements, but in actual applications, historical data needs to be analyzed and saved. The existing grain database data processing method cannot take into account both data update and historical data retention, nor can it realize the real-time analysis of historical data and the configuration of response strategies. Summary of the invention

[0004] The embodiments of the present application provide a real-time data management method, device and medium based on grain storage data, which solves the technical problem that historical data cannot be reasonably preserved and analyzed when the existing grain storage data is updated.

[0005] In a first aspect, an embodiment of the present application provides a real-time data management method based on grain storage data, characterized in that the method includes: obtaining grain storage update data, and performing incremental identification on the grain storage update data to determine grain storage data table change data; performing format conversion on the grain storage data table change data, and inserting the format-converted grain storage data table change data into a preset target data table to obtain grain storage update data to be analyzed; based on the grain storage update data to be analyzed, determining a multi-version data storage table through a newly added data primary key judgment; wherein the multi-version data storage table includes: a historical version data table and a data inventory table; performing a grain storage data impact relationship evaluation on the historical version data table to obtain historical grain storage data change analysis data; performing a grain storage status analysis on the data inventory table to determine current grain storage status parameters.

[0006] In one implementation of the present application, incremental identification is performed on the grain storage update data to determine the grain storage data table change data, specifically including: performing identification field judgment on the grain storage update data to determine the identification field type; wherein the identification field types include: timestamp field, update flag field; based on the identification field type, determining the first grain storage data table change data through field incremental identification; when the result of the identification field judgment on the grain storage update data is that there is no identification field, querying the EXCEPT function statement, and performing a difference set operation on the SELECT statement group connected to the EXCEPT function statement to obtain the second grain storage data table change data; determining the grain storage data table change data based on the first grain storage data table change data and the second grain storage data table change data.

[0007] In one implementation of the present application, the format of the grain storage data table change data is converted, specifically including: inserting the grain storage data table change data into a preset data table to obtain the RKD_RESULT table; exporting the grain storage data table change data in the RKD_RESULT table through an integrated development tool to obtain the grain storage data table change data in CSV format.

[0008] In one implementation of the present application, based on the updated grain storage data to be analyzed, a multi-version data storage table is determined by adding a data primary key judgment, specifically including: determining a data inventory table based on the updated grain storage data to be analyzed; performing a primary key existence judgment on the data inventory table, and when the primary key of the updated grain storage data to be analyzed is consistent with the primary key of the preset inventory table data of the warehouse entry form, inserting the data corresponding to the consistent primary key part into the warehouse entry form data table to obtain the updated data of the warehouse entry form; adding a timestamp field to the updated data of the warehouse entry form to obtain the historical version data table.

[0009] In one implementation of the present application, a grain storage data impact relationship assessment is performed on a historical version data table to obtain historical grain storage data change analysis data, specifically including: obtaining historical data on grain storage facilities, and performing a grain storage effect correlation assessment on the historical version data table and the historical data on grain storage facilities to determine historical grain storage data change data; dividing the historical grain storage data change analysis data into grain categories to obtain historical grain storage change classification data; and obtaining historical grain storage data change analysis data through grain storage condition parameter analysis based on the historical grain storage change classification data.

[0010] In one implementation of the present application, based on historical grain storage change classification data, historical grain storage data change analysis data is obtained through grain storage condition parameter analysis, specifically including: performing grain quality status analysis on the historical grain storage change analysis data to determine grain quality change analysis parameters; wherein the grain quality status analysis includes: grain moisture analysis, grain impurity analysis, and perfect grain analysis; performing granary performance analysis on preset grain storage equipment to obtain granary performance historical analysis parameters, and determining granary grain storage change analysis data through granary environmental change analysis based on the granary performance historical analysis parameters; and determining historical grain storage data change analysis data based on the grain quality change analysis parameters and the granary grain storage change analysis data.

[0011] In one implementation of the present application, a grain storage status analysis is performed on a data inventory table to determine current grain storage status parameters, specifically including: determining real-time grain storage data based on the data inventory table, and performing a storage environment analysis on the real-time grain storage data to obtain a first current grain storage status parameter; performing a grain status assessment on the real-time grain storage data to obtain a second current grain storage status parameter; and determining the current grain storage status parameter based on the first current grain storage status parameter and the second current grain storage status parameter.

[0012] In one implementation of the present application, after performing a grain storage status analysis on the data inventory table to determine the current grain storage status parameters, the method also includes: determining the grain storage status trend data through grain storage trend analysis based on the historical grain storage data change analysis data and the current grain storage status parameters; matching the grain storage status trend data with the grain storage response strategy to obtain the future grain storage response strategy.

[0013] In a second aspect, an embodiment of the present application also provides a real-time data management device based on grain storage data, characterized in that the device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can: obtain grain storage update data, and perform incremental identification on the grain storage update data to determine the grain storage data table change data; perform format conversion on the grain storage data table change data, and insert the format-converted grain storage data table change data into a preset target data table to obtain the grain storage update data to be analyzed; based on the grain storage update data to be analyzed, determine a multi-version data storage table by judging the primary key of the newly added data; wherein the multi-version data storage table includes: a historical version data table and a data inventory table; perform a grain storage data impact relationship evaluation on the historical version data table to obtain historical grain storage data change analysis data; perform a grain storage status analysis on the data inventory table to determine the current grain storage status parameters.

[0014] In a third aspect, an embodiment of the present application further provides a non-volatile computer storage medium for real-time data management based on grain storage data, storing computer executable instructions, characterized in that the computer executable instructions are configured to: obtain grain storage update data, and perform incremental identification on the grain storage update data to determine grain storage data table change data; perform format conversion on the grain storage data table change data, and insert the format-converted grain storage data table change data into a preset target data table to obtain grain storage update data to be analyzed; based on the grain storage update data to be analyzed, determine a multi-version data storage table through a newly added data primary key judgment; wherein the multi-version data storage table includes: a historical version data table and a data inventory table; perform a grain storage data impact relationship evaluation on the historical version data table to obtain historical grain storage data change analysis data; perform a grain storage status analysis on the data inventory table to determine current grain storage status parameters.

[0015] The embodiments of the present application provide a real-time data management method, device and medium based on grain storage data. By separately managing the historical data and updated data of grain storage data and analyzing the parameters related to the grain storage status, the technical problem that the historical data cannot be reasonably preserved and analyzed when the existing grain storage data is updated is solved, and the grain storage data can be backed up in real time in different data tables and the grain storage data can be analyzed instantly through different data labels. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0017] Figure 1 A flow chart of a real-time data management method based on grain storage data provided in an embodiment of the present application;

[0018] Figure 2 A schematic diagram of the internal structure of a real-time data management device based on stored grain data provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0020] The embodiments of the present application provide a real-time data management method, device and medium based on grain storage data. By separately managing the historical data and updated data of grain storage data and analyzing the parameters related to the grain storage status, the technical problem that the historical data cannot be reasonably preserved and analyzed when the existing grain storage data is updated is solved, and the grain storage data can be backed up in real time in different data tables and the grain storage data can be analyzed instantly through different data labels.

[0021] The technical solution proposed in the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0022] Figure 1 A flow chart of a real-time data management method based on grain storage data provided in the embodiment of the present application. Figure 1 As shown, a real-time data management method based on grain storage data provided in an embodiment of the present application specifically comprises the following steps:

[0023] Step 101: Obtain grain storage update data, and perform incremental identification on the grain storage update data to determine the change data of the grain storage data table.

[0024] Specifically, it includes: performing identification field judgment on the grain storage update data to determine the identification field type; wherein the identification field types include: timestamp field, update flag field; based on the identification field type, determining the change data of the first grain storage data table through field increment recognition; when the result of the identification field judgment on the grain storage update data is that there is no identification field, querying the EXCEPT function statement, and performing a difference operation on the SELECT statement group connected to the EXCEPT function statement to obtain the change data of the second grain storage data table; determining the change data of the grain storage data table according to the change data of the first grain storage data table and the change data of the second grain storage data table.

[0025] This application obtains grain storage update data and performs incremental identification on the grain storage update data to determine the change data in the grain storage data table, thereby realizing the identification and storage of incremental data in grain storage changes.

[0026] In the examples of the present application, detailed explanation is given by the following Example 1.

[0027] Example 1: Identify incremental data through the EXCEPT function statement of the database.

[0028] The EXCEPT clause / operator is used to join two SELECT statements together and return those records from the first SELECT statement's results that are not present in the second SELECT statement's results.

[0029] That is, EXCEPT returns only those records that do not exist in the result of the second SELECT statement (difference set). By identifying the changed data in the NEW table and the OLD table of the incoming order and inserting the changed data into a RESULT table, the specific implementation logic can be expressed by the following code:

[0030] insert into RKD_RESULT(COLUMNS1,COLUMNS2,COLUMNS3,……)

[0031] select COLUMNS1,COLUMNS2,COLUMNS3,…FROM RKD_NEW

[0032] EXCEPT

[0033] select COLUMNS1,COLUMNS2,COLUMNS3,…FROM RKD_OLD

[0034] Step 102: convert the format of the grain storage data table change data, and insert the converted grain storage data table change data into a preset target data table to obtain the grain storage update data to be analyzed.

[0035] Specifically, the method includes: inserting the grain storage data table change data into a preset data table to obtain the RKD_RESULT table; exporting the grain storage data table change data in the RKD_RESULT table through an integrated development tool to obtain the grain storage data table change data in a CSV format.

[0036] The present application realizes data insertion of the grain storage data table change data by format conversion of the grain storage data table change data and inserting the format converted grain storage data table change data into a preset target data table to obtain the grain storage update data to be analyzed.

[0037] In the examples of the present application, detailed explanation is given by the following Example 2.

[0038] Example 2: The result set of the changed data is stored in the preset RKD_RESULT table. You can use the IDI tool to export the data in the table into a CSV file and transfer the file to the server where the target database is located for subsequent import operations.

[0039] After the incremental data CSV file or executable SQL statement file is transferred to the target server, the import operation will be performed first to import the incremental data into a temporary NEW table, which is a table dedicated to storing incremental data. You can use the IDI tool to import. If it is a CSV file, use the text file input control to parse the data content in the CSV file, and then use the table output control to insert the parsed data into the target table. If it is an SQL statement file, you can directly use the SQL statement execution control to execute the SQL script in the file, and the data can also be inserted into the target table.

[0040] Step 103: Based on the updated stored grain data to be analyzed, determine the multi-version data storage table by adding the primary key of the data.

[0041] Among them, the multi-version data storage table includes: historical version data table and data inventory table.

[0042] Specifically, it includes: determining the data inventory table based on the updated data of stored grain to be analyzed; judging the existence of the primary key of the data inventory table, and when the primary key of the updated data of stored grain to be analyzed is consistent with the primary key of the preset inventory table data of the incoming order, inserting the data corresponding to the consistent primary key part into the incoming order data table to obtain the updated data of the incoming order; adding a timestamp field to the updated data of the incoming order to obtain the historical version data table.

[0043] This application is based on the updated stored grain data to be analyzed. By adding a new data primary key, a multi-version data storage table is determined, so that the latest data is stored in the data inventory table, and the historical multi-version data is stored in the HIS table, which serves as the basis for subsequent data analysis.

[0044] In the examples of the present application, this is explained in detail through the following Example 3.

[0045] Example 3: After the incremental data is imported into the target table, it is judged by the primary key and the stock data to see whether the primary key of the newly added data is in the stock table. If it is, it means that this data is an updated data and the old data in the stock table needs to be managed in multiple versions. Data judgment uses the database EXTSTS keyword. For example, it is judged that the data in the NEW table of the incoming order is consistent with the primary key of the data in the stock table of the incoming order, and the consistent data is inserted into the HIS table of the incoming order. At the same time, the timestamp field HIST_GDSJ is added to record the time when this data was inserted into the HIS table. In this way, the HIS table is a multi-version data record table. The updated data is stored in the HIS table, and there is a timestamp to record the time when the data was inserted. The specific implementation logic of distinguishing different versions can be expressed by the following code:

[0046] delete from RC_RKD_HIST WHEREHIST_GDSJ=TO_CHAR(SYSDATE,'YYYYMMDD');

[0047] insert into RC_RKD_HIST(COLUMNS1, COLUMNS2, COLUMNS3, ..., HIST_GDSJ)

[0048] select

[0049] COLUMNS1

[0050] COLUMNS2

[0051] COLUMNS3 ......

[0053] TO_CHAR(SYSDATE,'YYYYMMDD')

[0054] FROM RC_RKD A where 1=1and exists(select*from RC_RKD_NEW BwhereA.RC_RKD_RKDNM=B.RC_RKD_RKDNM);

[0055] COMMIT

[0056] Through the above processing, the latest data is saved in the data stock table, and the historical multi-version data is saved in the HIS table. Subsequent data analysis can use the data of the two tables respectively.

[0057] Step 104: Evaluate the impact relationship of grain storage data on the historical version data table to obtain historical grain storage data change analysis data.

[0058] Specifically, it includes: obtaining historical data of grain storage facilities, and evaluating the correlation between historical version data tables and historical data of grain storage facilities to determine the historical grain storage data change data; dividing the historical grain storage data change analysis data into grain categories to obtain historical grain storage change classification data; based on the historical grain storage change classification data, through grain storage condition parameter analysis, obtain historical grain storage data change analysis data.

[0059] Based on the historical grain storage change classification data, the historical grain storage data change analysis data is obtained through grain storage condition parameter analysis, specifically including: conducting grain quality status analysis on the historical grain storage change analysis data to determine the grain quality change analysis parameters; wherein, the grain quality status analysis includes: grain moisture analysis, grain impurity analysis, and perfect grain analysis; conducting granary performance analysis on the preset grain storage equipment to obtain granary performance historical analysis parameters, and according to the granary performance historical analysis parameters, determining the granary grain storage change analysis data through granary environmental change analysis; determining the historical grain storage data change analysis data based on the grain quality change analysis parameters and the granary grain storage change analysis data.

[0060] This application evaluates the impact relationship of grain storage data on historical version data tables to obtain historical grain storage data change analysis data, thereby realizing the analysis of historical grain storage status changes, improving the security of grain storage data and the analysis efficiency of historical grain storage data.

[0061] Step 105: Analyze the grain storage status of the data inventory table to determine the current grain storage status parameters.

[0062] Specifically, it includes: determining the real-time data of grain storage according to the data inventory table, and performing storage environment analysis on the real-time data of grain storage to obtain a first current grain storage status parameter; performing grain status evaluation on the real-time data of grain storage to obtain a second current grain storage status parameter; and determining the current grain storage status parameter based on the first current grain storage status parameter and the second current grain storage status parameter.

[0063] After performing a grain storage status analysis on the data inventory table to determine the current grain storage status parameters, the method also includes: determining the grain storage status trend data through grain storage trend analysis based on the historical grain storage data change analysis data and the current grain storage status parameters; matching the grain storage status trend data with the grain storage response strategy to obtain the future grain storage response strategy.

[0064] This application analyzes the grain storage status of the data inventory table to determine the current grain storage status parameters, thereby achieving instant analysis of the current grain storage status and improving the stability of grain storage safety.

[0065] The above is an embodiment of the method proposed in this application. Based on the same inventive concept, the embodiment of this application also provides a real-time data management device based on grain storage data, and its structure is as follows: Figure 2 shown.

[0066] Figure 2 A schematic diagram of the internal structure of a real-time data management device based on grain storage data provided in an embodiment of the present application. Figure 2 As shown, the device includes:

[0067] at least one processor 201;

[0068] and, a memory 202 communicatively connected to the at least one processor;

[0069] The memory 202 stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor 201 to enable at least one processor 201 to:

[0070] Acquire grain storage update data, and perform incremental identification on the grain storage update data to determine the change data of the grain storage data table; perform format conversion on the change data of the grain storage data table, and insert the format-converted change data of the grain storage data table into a preset target data table to obtain the grain storage update data to be analyzed; based on the grain storage update data to be analyzed, determine the multi-version data storage table through the newly added data primary key judgment; wherein the multi-version data storage table includes: a historical version data table and a data stock table; perform a grain storage data impact relationship assessment on the historical version data table to obtain the historical grain storage data change analysis data; perform a grain storage status analysis on the data stock table to determine the current grain storage status parameters.

[0071] Some embodiments of the present application provide corresponding Figure 1 A non-volatile computer storage medium for real-time data management based on grain storage data stores computer executable instructions, wherein the computer executable instructions are set as follows:

[0072] Acquire grain storage update data, and perform incremental identification on the grain storage update data to determine the change data of the grain storage data table; perform format conversion on the change data of the grain storage data table, and insert the format-converted change data of the grain storage data table into a preset target data table to obtain the grain storage update data to be analyzed; based on the grain storage update data to be analyzed, determine the multi-version data storage table through the newly added data primary key judgment; wherein the multi-version data storage table includes: a historical version data table and a data stock table; perform a grain storage data impact relationship assessment on the historical version data table to obtain the historical grain storage data change analysis data; perform a grain storage status analysis on the data stock table to determine the current grain storage status parameters.

[0073] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the IoT device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0074] The system and medium provided in the embodiments of the present application correspond one-to-one to the method. Therefore, the system and medium also have similar beneficial technical effects to the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the system and medium will not be repeated here.

[0075] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0076] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0077] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0078] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0079] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0080] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0081] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0082] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0083] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A real-time data management method based on grain storage data, characterized in that: The method comprises: Acquire grain storage update data, and perform incremental recognition on the grain storage update data to determine grain storage data table change data; Performing format conversion on the grain storage data table change data, and inserting the format-converted grain storage data table change data into a preset target data table to obtain the grain storage update data to be analyzed; Based on the grain storage update data to be analyzed, a multi-version data storage table is determined by adding a data primary key; wherein the multi-version data storage table includes: a historical version data table and a data inventory table; Performing a grain storage data impact relationship assessment on the historical version data table to obtain historical grain storage data change analysis data; The grain storage status analysis is performed on the data inventory table to determine the current grain storage status parameters.

2. A real-time data management method based on grain storage data according to claim 1, characterized in that: Incremental identification is performed on the grain storage update data to determine the change data of the grain storage data table, specifically including: Performing identification field judgment on the grain storage update data to determine the identification field type; wherein the identification field type includes: a timestamp field and an update flag field; Based on the identified field type, determining the first grain storage data table change data through field increment identification; When the identification field judgment result of the grain storage update data is that there is no identification field, querying the EXCEPT function statement, and performing a difference operation on the SELECT statement group connected to the EXCEPT function statement to obtain the second grain storage data table change data; The grain storage data table change data is determined according to the first grain storage data table change data and the second grain storage data table change data.

3. A real-time data management method based on grain storage data according to claim 1, characterized in that: The format of the change data in the grain storage data table is converted, specifically including: Insert the grain storage data table change data into a preset data table to obtain the RKD_RESULT table; By using the integrated development tool, the grain storage data table change data in the RKD_RESULT table is exported to obtain the grain storage data table change data in CSV format.

4. A real-time data management method based on grain storage data according to claim 1, characterized in that: Based on the updated grain storage data to be analyzed, a multi-version data storage table is determined by adding a primary key of the data, specifically including: Determining the data inventory table based on the grain storage update data to be analyzed; The data inventory table is judged to have a primary key, and when the primary key of the grain storage update data to be analyzed is consistent with the primary key of the preset storage order inventory table data, the data corresponding to the consistent primary key part is inserted into the storage order data table to obtain the storage order update data; A timestamp field is added to the updated data of the warehouse entry form to obtain the historical version data table.

5. The real-time data management method based on grain storage data according to claim 1, characterized in that: The grain storage data impact relationship is evaluated on the historical version data table to obtain historical grain storage data change analysis data, specifically including: Acquire historical data of grain storage facilities, and evaluate the correlation between the historical version data table and the historical data of grain storage facilities to determine the change data of historical grain storage data; Classifying the historical grain storage data change analysis data into grain categories to obtain historical grain storage change classification data; Based on the historical grain storage change classification data, historical grain storage data change analysis data is obtained through grain storage condition parameter analysis.

6. A real-time data management method based on grain storage data according to claim 5, characterized in that: Based on the historical grain storage change classification data, the historical grain storage data change analysis data is obtained through grain storage condition parameter analysis, specifically including: Performing grain quality status analysis on the historical grain storage change analysis data to determine grain quality change analysis parameters; wherein the grain quality status analysis includes: grain moisture analysis, grain impurity analysis, and perfect grain analysis; Performing a granary performance analysis on the preset grain storage equipment to obtain the granary performance historical analysis parameters, and determining the granary grain storage change analysis data through the granary environment change analysis based on the granary performance historical analysis parameters; Based on the grain quality change analysis parameters and the grain storage change analysis data in the granary, the historical grain storage data change analysis data is determined.

7. A real-time data management method based on grain storage data according to claim 1, characterized in that: The grain storage status analysis is performed on the data inventory table to determine the current grain storage status parameters, specifically including: Determine the real-time grain storage data according to the data inventory table, and perform storage environment analysis on the real-time grain storage data to obtain a first current grain storage state parameter; Evaluate the grain status of grain storage real-time data to obtain a second current grain storage status parameter; The current grain storage state parameter is determined based on the first current grain storage state parameter and the second current grain storage state parameter.

8. The real-time data management method based on grain storage data according to claim 1, characterized in that: After performing grain storage status analysis on the data inventory table to determine current grain storage status parameters, the method further includes: Determine grain storage status trend data through grain storage trend analysis based on the historical grain storage data change analysis data and the current grain storage status parameters; The grain storage status trend data is matched with a grain storage response strategy to obtain a future grain storage response strategy.

9. A real-time data management device based on grain storage data, characterized in that: The device comprises: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to: Acquire grain storage update data, and perform incremental recognition on the grain storage update data to determine grain storage data table change data; Performing format conversion on the grain storage data table change data, and inserting the format-converted grain storage data table change data into a preset target data table to obtain the grain storage update data to be analyzed; Based on the grain storage update data to be analyzed, a multi-version data storage table is determined by adding a data primary key; wherein the multi-version data storage table includes: a historical version data table and a data inventory table; Performing a grain storage data impact relationship assessment on the historical version data table to obtain historical grain storage data change analysis data; The grain storage status analysis is performed on the data inventory table to determine the current grain storage status parameters.

10. A non-volatile computer storage medium for real-time data management based on grain storage data, storing computer executable instructions, characterized in that: The computer executable instructions are configured to: Acquire grain storage update data, and perform incremental recognition on the grain storage update data to determine grain storage data table change data; Performing format conversion on the grain storage data table change data, and inserting the format-converted grain storage data table change data into a preset target data table to obtain the grain storage update data to be analyzed; Based on the grain storage update data to be analyzed, a multi-version data storage table is determined by adding a data primary key; wherein the multi-version data storage table includes: a historical version data table and a data inventory table; Performing a grain storage data impact relationship assessment on the historical version data table to obtain historical grain storage data change analysis data; The grain storage status analysis is performed on the data inventory table to determine the current grain storage status parameters.

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