Data acquisition method and device and computer equipment
By receiving data acquisition requests from target objects, filtering candidate data rows based on object identifiers and data table attribute information, determining target data rows, and matching target data, the problem of insufficient data consistency in database operations is solved, and the security and flexibility of data acquisition are improved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-26
- Publication Date
- 2026-04-03
AI Technical Summary
In existing technologies, it is difficult to guarantee data consistency between different objects during database operations, resulting in insufficient data security and operational flexibility.
By receiving data acquisition requests from target objects, candidate data rows are selected from the data rows based on object identifiers and data table attribute information. The target data rows are then determined based on the identifier data of the candidate data rows, and target data matching the data selection criteria are selected from the target data rows.
It significantly improves the security and accuracy of data acquisition, reduces the risk of data leakage, and enhances the flexibility of data operations and optimizes storage space.
Smart Images
Figure CN121786085A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of databases, specifically to a data acquisition method, apparatus, and computer equipment. Background Technology
[0002] As a crucial component of computer science, databases have provided an indispensable technological foundation for the advent of the high-speed information age. Today, people can quickly retrieve data from local or remote databases by controlling computer devices. Because databases typically aggregate massive amounts of data supporting specific services, they support multiple objects associated with that specific service to perform operations such as querying and modifying it. Currently, the database data that different objects can operate on is consistent. Summary of the Invention
[0003] This application provides a data acquisition method, apparatus, and computer device that can acquire data from a data table from the perspective of a target object, significantly improving the security of data operations.
[0004] This application provides a data acquisition method, including:
[0005] Receive a data retrieval request from the target object for a data table. The data retrieval request carries the object identifier of the target object and data filtering conditions. The data table includes at least one data row, and the data row includes multiple identifier data.
[0006] Based on the object identifier and the attribute information of the data table, at least one candidate data row is selected from the data rows;
[0007] Based on at least one identifier data of the candidate data rows, determine at least one target data row corresponding to the data acquisition request;
[0008] Filter out at least one target data item that matches the data filtering criteria from the target data row, and return the target data to the target object.
[0009] Accordingly, this application also provides a data acquisition device, including:
[0010] The acquisition module is used to receive data acquisition requests from the target object for a data table. The data acquisition request carries the object identifier of the target object and data filtering conditions. The data table includes at least one data row, and the data row includes multiple identifier data.
[0011] The filtering module is used to filter out at least one candidate data row from the data rows based on the object identifier and the attribute information of the data table;
[0012] The determination module is used to determine at least one target data row corresponding to the data acquisition request based on at least one identifier data of the candidate data row;
[0013] The matching module is used to filter out at least one target data that matches the data filtering criteria in the target data row and return the target data to the target object.
[0014] In some embodiments of this application, the identification data includes inserted identification data, the attribute information includes the creator identifier, and the filtering module can be specifically used for:
[0015] If the insertion identifier data of a data row includes an object identifier or a data table creator identifier, the data row is determined to be a candidate data row.
[0016] In some embodiments of this application, the identification data includes deleting identification data and updating identification data, and the determining module can be specifically used for:
[0017] If the deletion identifier data of the candidate data row does not include the object identifier and the update identifier data is empty, the candidate data row is determined to be the target data row;
[0018] If the deletion identifier data of the candidate data row includes the object identifier and the update identifier data is not empty, the first data row that determines the unique identifier of the update identifier data is the target data row.
[0019] In some embodiments of this application, the data filtering conditions include target filtering conditions for at least one filtering identifier, and the matching module may be specifically used for:
[0020] Identify the filter identifier data corresponding to the filter identifier in the target data row, and if the filter identifier data matches the target filter condition, determine the filter identifier data as the target data and return the target data to the target object.
[0021] In some embodiments of this application, the data acquisition device further includes a request module and an adjustment module, wherein,
[0022] The request module is used to receive data adjustment requests initiated by the target object. The data adjustment request includes the object identifier of the target object and adjustment information for at least one data row in the data table. The adjustment information includes data information corresponding to at least one adjustment method.
[0023] The adjustment module is used to adjust data rows based on adjustment information and object identifiers to obtain an adjusted data table.
[0024] In some embodiments of this application, the adjustment module may include an adjustment submodule, wherein,
[0025] The adjustment submodule is used to add a second data row to the data table if the adjustment information includes the new identifier data of the new data row, and to determine the object identifier as the insertion identifier data of the second data row, so as to obtain the adjusted data table.
[0026] In some embodiments of this application, the adjustment submodule includes a first adjustment unit and a second adjustment unit, wherein,
[0027] The first adjustment unit is used to add a second data row including the new identification data in the data table if the adjustment information includes the new identification data of the new data row, and to determine the object identifier as the insertion identification data of the second data row.
[0028] The second adjustment unit is used to determine the object identifier as the deletion identifier data of the third data row if the adjustment information also includes deletion information for the third data row, so as to obtain the adjusted data table.
[0029] In some embodiments of this application, the second adjustment unit may be specifically used for:
[0030] If the adjustment information also includes deletion information for the third data row, the object identifier will be determined as the deletion identifier data for the third data row;
[0031] If the adjustment information also includes update identifier data for the fourth data row, the object identifier is determined as the deletion identifier data of the fourth data row. A fifth data row including update identifier data is added to the data table, the object identifier is determined as the insertion identifier data of the fifth data row, and the row identifier of the fifth data row is determined as the update identifier data of the fourth data row, so as to obtain the adjusted data table.
[0032] Accordingly, this application also provides a computer device, including a processor and a memory, wherein the memory stores a computer program, and the processor is used to run the computer program in the memory to implement the steps in the data acquisition method provided in this application.
[0033] Accordingly, embodiments of this application also provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the steps in the data acquisition method provided in embodiments of this application.
[0034] Accordingly, embodiments of this application also provide a computer program product, including a computer program or instructions, which are executed by a processor to implement the steps in the data acquisition method provided in embodiments of this application.
[0035] This application embodiment can first receive a data acquisition request from a target object for a data table. The data acquisition request carries the object identifier of the target object and data filtering conditions. The data table here includes at least one data row, and the data row includes multiple identifier data. Then, based on the object identifier and the attribute information of the data table, candidate data rows can be filtered from the data rows. All candidate data rows form a data table from the perspective of the target object. Then, based on the identifier data in the candidate data rows, the target data row required for this data acquisition request can be determined. Then, at least one target data matching the data filtering conditions can be filtered from the target data row. The process of acquiring target data from the data table is strongly related to the target object, which can significantly improve the security of data acquisition. Attached Figure Description
[0036] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0037] Figure 1 This is a schematic diagram of a scenario illustrating the data acquisition method provided in an embodiment of this application;
[0038] Figure 2 This is a flowchart illustrating the data acquisition method provided in an embodiment of this application;
[0039] Figure 3 This is another flowchart illustrating the data acquisition method provided in the embodiments of this application;
[0040] Figure 4 This is another flowchart illustrating the data acquisition method provided in the embodiments of this application;
[0041] Figure 5 This is a schematic diagram of the structure of the data acquisition device provided in the embodiments of this application;
[0042] Figure 6 This is a schematic diagram of the structure of the computer device provided in the embodiments of this application. Detailed Implementation
[0043] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0044] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “corresponding,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0045] This application provides a data acquisition method, apparatus, and computer device. The data acquisition apparatus can be integrated into a data acquisition system, and the data acquisition system can be integrated into at least one computer device, which may include at least one of a terminal and a server.
[0046] The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. The terminal and server can be directly or indirectly connected via wired or wireless communication, which is not restricted herein.
[0047] The data acquisition system can be integrated into a terminal and a server. The server has a data table, which can include multiple data rows. Each data row can include multiple identifier data. The terminal can respond to the target object's operation, generate and send a data acquisition request for the target object to the server. The server can receive the data acquisition request, which can include the target object's object identifier and data filtering conditions. Based on the object identifier and the data table's attribute information, the server can initially filter out several candidate data rows from the data table. These candidate data rows form the target object's data table. Based on the identifier data in the candidate data rows, the server can determine whether the candidate data row is the target data row containing the data requested by the target object, thereby determining at least one target data row from several candidate data rows. Finally, the server filters out at least one target data row that matches the data filtering conditions from the identifier data of the target data row, and returns the target data to the terminal. The terminal can then output the target data for the target object to use.
[0048] For example, see Figure 1 The data acquisition system may include a terminal 10 and a server 20. The terminal 10 can receive the data filtering condition p input by the user zz and generate a data acquisition request including the user's identification information: zz and the data filtering condition p. The terminal 10 transmits the data acquisition request to the server 20. The server 20 filters out N candidate data rows (N is a positive integer) from the data table based on the identification information zz and the attribute information of the local data table A. Then, based on at least one identification data of each candidate data row, it determines M target data rows (M is a positive integer, M is less than or equal to N) from the N candidate data rows. Finally, the server 20 determines Q target data that match the data filtering condition p from the identification data of the target data rows and returns these Q target data to the terminal 10 for the user zz to view and use.
[0049] Figure 1 This is an example of an application scenario for the data acquisition system of this application. It is mainly used to introduce, and not to limit, the data acquisition system of this application. In the actual application of the technical solutions described in the embodiments of this application, the computer equipment included in the data acquisition system and the steps performed by each computer equipment can be flexibly adjusted, and it is not limited to... Figure 1 The content described in the text.
[0050] The data acquisition method of this application will be further described below with reference to embodiments. It should be noted that the order of description of the following embodiments is not intended to limit the preferred order of the embodiments. The data acquisition method can be integrated into a data acquisition device, and the data acquisition device can be integrated into a data acquisition system. Figure 2 A flowchart illustrating the data acquisition method of this application is shown, as follows: Figure 2 Data acquisition methods may include:
[0051] 110. Receive a data retrieval request from the target object for a data table. The data retrieval request carries the object identifier of the target object and data filtering conditions. The data table includes at least one data row, and the data row includes multiple identifier data.
[0052] The target objects can include users, testers / developers / maintenance personnel, intelligent agents (such as intelligent robots, voice assistants, etc.), functional interfaces, and other entities / virtual objects that need to obtain data from the data table. Object identifiers can include information that uniquely identifies the target object; object identifiers can be in the form of letters, numbers, symbols, etc.
[0053] The data table may include a collection of data for organizing, managing and storing data. The data table may exist independently in a computer device or may be configured as part of other data collections (such as a database) on at least one computer device (such as a server). The data table may include multiple data rows, and each data row may include multiple data bits. Each data bit corresponds to a data identifier and may store the identifier data of its corresponding data identifier. The data identifier may characterize the attributes of the data, and the meaning of the identifier data can be understood through the data identifier.
[0054] For example, data identifiers can include deletion identifiers, addition identifiers, and update identifiers. The data stored in the data field corresponding to the deletion identifier includes the identifier information of the object that is deleted from the current data row. The data stored in the data field corresponding to the addition identifier includes the identifier information of the object that is added to the current data row. The data stored in the data field corresponding to the update identifier includes the row identifier information of the updated data row of the current data row. In addition, identifier data can also include configuration data, business data, entity information data, etc.
[0055] It should be noted that a data bit can include at least one identifier data of the data identifier, and multiple data bits can correspond to the same data identifier. The specific settings can be flexibly configured according to the actual situation.
[0056] Among them, data acquisition requests can be used to request data from a data table. Data acquisition requests can be automatically generated by computer equipment at regular intervals / based on preset conditions, or they can be generated by computer equipment based on operations of related objects. For example, data interface A automatically generates a data acquisition request every half hour. This data acquisition request carries the identification information of data interface A and the data filtering conditions for the current time. Another example is that a tester enters data filtering conditions into the computer equipment and triggers a request control. The computer equipment responds to the tester's operation and generates a data acquisition request that includes the tester's identification information and data filtering conditions, and so on.
[0057] The data filtering conditions here may include filtering conditions for identifier data targeting at least one data identifier. Identifier data may include various forms, such as text (e.g., numbers, characters, symbols, etc.), images, audio and video. The filtering conditions can be determined according to the form of the identifier data and the needs of the target object. For example, the filtering conditions may restrict the numerical range, the number of characters in the text, characters at a specific position in the text, the memory size occupied by the data, etc. The specific settings can be flexibly configured in the application scenario, and this application does not impose any restrictions on this.
[0058] For example, receive a data retrieval request from a tester for data table 1. The data retrieval request carries the tester's object identifier: ds and the data filtering condition: P<200. Data table 1 includes multiple data rows, and each data row includes multiple identifier data.
[0059] 120. Based on the object identifier and the attribute information of the data table, filter out at least one candidate data row from the data rows.
[0060] Among them, attribute information can include information that represents a data table, data rows in a data table, and information that identifies the characteristics of data in a certain aspect within a data row. Attribute information such as information that represents the creator, creation time, number of updates, and number of data rows of a data table; information that represents the creation object, creation time, update object, and deletion object of a data row; information that represents the size, quantity, and category of data, etc.
[0061] Candidate data rows can include data rows for which the target object has data operation permissions. Specifically, there are several ways to filter candidate data rows based on object identifiers and data table attribute information. For example, one can first determine whether the object identifier of the target object and the creator identifier of the data table are the same. If they are the same, a set number of candidate data rows can be randomly selected from multiple data rows in the data table, either randomly or based on preset rules. For instance, if the object identifier "ds" is the same as the creator identifier "ds" of data table 1, then 30 candidate data rows can be randomly selected from data table 1.
[0062] In some embodiments of this application, a data row can be determined as a candidate data row based specifically on its identifier data and the object identifier of the target object. The data row may include insertion identifier data representing the object that created the data row. Therefore, if the insertion identifier data of a data row includes an object identifier or a creator identifier, the data row can be determined as a candidate data row. This allows for the initial screening of several candidate data rows operable by the target object from the data table.
[0063] For example, in data table 2, the insertion identifier data of data row 40 is: dz, which is consistent with the object identifier of the target object: dz, so data row 40 is determined to be a candidate data row. The insertion identifier data of data row 42 is dt, which is consistent with the creator identifier of data table 2, so data row 42 is also determined to be a candidate data row. Thus, 10 candidate data rows of the target object can be selected from data table 2.
[0064] 130. Based on at least one identifier data of the candidate data row, determine at least one target data row corresponding to the data acquisition request.
[0065] The target data row can be the data row containing the data required by the target object. Specifically, there are multiple ways to determine the target data row based on the identifier data in the candidate data. For example, a data row filtering rule can be set. The data row filtering rule can target the identifier data of one or more data identifiers in the candidate data row. Based on the data row filtering rule and the identifier data of the candidate data row, it can be determined whether the candidate data row is the target data row. The specific data row filtering rule can be as follows: the number of identifier data is greater than P (P is a positive integer). Thus, 8 target data rows can be determined from 10 candidate data rows.
[0066] In some embodiments of this application, the identification data may include deletion identification data and update identification data. Deletion identification data may include the identification information of the object deleting the current data row, and update identification data may include the row identification information of the updated data row. If the deletion identification data of a data row is the same as the object identification, it indicates that the target object has performed a deletion operation on that data row, and the data row is not included in the data table of the target object version.
[0067] Therefore, if the deletion identifier data of a candidate data row does not include the object identifier and the update identifier data is empty, it is determined that the target object has not performed a deletion operation on the candidate data row, and the candidate data row is the latest version of the data row, then the candidate data row is determined to be the target data row. For example, if the deletion identifier data of data row 12 does not include the object identifier: ds, and the corresponding data bit of the update identifier is empty (the update identifier data is empty), then data row 12 can be determined to be the target data row.
[0068] If the deletion identifier data of a candidate data row includes an object identifier and the update identifier data is not empty, it can be determined that the target object performs a deletion operation on the candidate data row and updates the candidate data row. Therefore, the data row uniquely identified by the update identifier data can be determined as the target data row. For example, if the deletion identifier data of data row 2 includes the object identifier "ds" and the update identifier data is not empty, then data row 21 identified by the update identifier data can be determined as the target data row.
[0069] 140. Filter out at least one target data that matches the data filtering criteria from the target data row, and return the target data to the target object.
[0070] Specifically, there are several ways to determine target data from target data rows. For example, data filtering conditions include condition 1, the quantity of identifier data for the target data row, and condition 2, the numerical value of the specific identifier data. First, it can be determined whether the quantity of identifier data in the target data row meets condition 1. If it does, then it can be determined whether the specific identifier data in the target data row meets condition 2. If it does, then the specific identifier data in the target data row is the target data.
[0071] In some embodiments of this application, data filtering conditions may include target filtering conditions for at least one filtering identifier. The filtering identifier may include a data identifier used for filtering data. First, the filtering identifier data corresponding to the filtering identifier can be determined. Then, after determining that the filtering identifier data matches the target filtering condition, the filtering identifier data is determined to be the target data. For example, the data filtering conditions include filtering condition A1 for data identifier a1 and filtering condition B1 for data identifier b1. If, in the target data row, the identifier data aa corresponding to data identifier a1 matches filtering condition A1, and the identifier data bb corresponding to data identifier b1 matches filtering condition B1, then identifier data aa and identifier data bb can be determined to be the target data.
[0072] Through the above process, this application can, based on the object identifier of the target object, first filter at least one candidate data row from the data table that the target object has operation permissions for, then further delete and update the identifier data in the candidate data row to determine the target data row from which the target object can obtain data, and finally obtain the target data from the target data row according to the data filtering conditions. This data acquisition process is bound to the object identifier of the target object, which can obtain the target data that the target object needs, reduce the risk of data leakage, and effectively improve the security and accuracy of the data acquisition process.
[0073] In this embodiment of the application, the target object can also make personalized adjustments to the data table to obtain a personal version of the data table. Specifically, it can receive a data adjustment request initiated by the target object. The data adjustment request includes the target object identifier and adjustment information for at least one data row in the data table. The adjustment information includes data information corresponding to at least one adjustment method. Based on the adjustment information and the target object identifier, the data row is adjusted to obtain the adjusted data table.
[0074] The adjustment methods can include adding, deleting, and updating. Adjustments to a data table can be made to a single data row, or to multiple data rows or to all data rows in the entire data table in batches.
[0075] When the adjustment method is to add, the adjustment information may include at least one new identifier data of the new data row. At this time, a second data row can be added to the data table, and the new identifier data can be filled into the corresponding data position of its corresponding data identifier in the second data row. In addition, the object identifier of the target object can be filled into the corresponding data position of the new identifier in the second data row.
[0076] This allows the creation of a second data row for the target object in the data table. By filling in the object identifier in the corresponding data field of the new identifier, only the target object (which may also include objects created with higher privileges) can perform queries, adjustments, and other operations on the second data row, effectively ensuring data security.
[0077] For example, when receiving a data adjustment request transmitted by a target object, the data adjustment request includes the object identifier: ds and adjustment information. The adjustment information includes new identifier data 1-10. Based on the adjustment information, a new data row 200 can be added to the data table, and the new identifier data 1-10 can be filled into the corresponding data positions respectively. The object identifier: ds can be filled into the corresponding data position of the insertion identifier.
[0078] When the adjustment method is deletion, the adjustment information can include deletion information for a specific data row (such as the third data row). In this case, the object identifier can be filled into the data field corresponding to the deletion identifier of the third data row in the data table.
[0079] By filling the object identifier into the corresponding data bit of the output identifier, the third data row can be "deleted" from the perspective of the target object. The target object will no longer consider the third data row when viewing or adjusting the data table. However, the third data row is still stored in the data table from the perspective of other objects, and related operations can still be performed on the data table, which significantly improves the operational flexibility and security of the data table.
[0080] For example, when receiving a data adjustment request transmitted by a target object, the data adjustment request includes an object identifier: ds and adjustment information. The adjustment information indicates that data row 118 should be deleted. Based on the adjustment information, the object identifier: ds can be filled into the data bit corresponding to the deletion identifier of data row 118.
[0081] When the adjustment method is update, the adjustment information can include update identifier data for a specific data row (such as the fourth data row). In this case, the object identifier can be filled into the corresponding data position of the deletion identifier in the fourth data row. When a fifth data row is added to the table, the identifier data from the fourth data row is filled into the fifth data row, and the update identifier data is filled into the corresponding data position. The object identifier is filled into the corresponding data position of the insertion identifier in the fifth data row, and the row identifier of the fifth data row is filled into the corresponding data position of the update identifier in the fourth data row. This allows for the simultaneous fulfillment of update needs for data rows by various objects without interference, maintaining the orderliness of the entire data table.
[0082] For example, when receiving a data adjustment request transmitted by a target object, the data adjustment request includes an object identifier: ds and adjustment information. The adjustment information includes update identifier data for data row 125. Based on the adjustment information, a new data row 201 can be added to the data table, and the identifier data of data row 125 can be filled into data row 201. Then, the update identifier data can be filled into the corresponding data position of data row 201, the object identifier: ds can be filled into the corresponding data position of the insertion identifier in data row 201, and finally, the row identifier of data row 201 can be filled into the corresponding data position of the update identifier of data row 125.
[0083] This application embodiment can first receive a data acquisition request from a target object for a data table. The data acquisition request carries the object identifier of the target object and data filtering conditions. The data table here includes at least one data row, and the data row includes multiple identifier data. Then, based on the object identifier and the attribute information of the data table, candidate data rows can be filtered from the data rows. All candidate data rows form a data table from the perspective of the target object. Then, based on the identifier data in the candidate data rows, the target data row required for this data acquisition request can be determined. Then, at least one target data matching the data filtering conditions can be filtered from the target data row. The process of acquiring target data from the data table is strongly related to the target object, which can significantly improve the security of data acquisition.
[0084] The data acquisition method of this application will be further described below with reference to embodiments. (See also...) Figure 3 , Figure 3 Another flowchart of this application is disclosed, including:
[0085] 210. The server receives a data retrieval request from a target object for a data table. The data retrieval request carries the object identifier of the target object and data filtering conditions. The data table includes at least one data row, and the data row includes multiple identifier data. The identifier data includes insert identifier data, delete identifier data, and update identifier data. The data filtering conditions include target filtering conditions for at least one filter identifier.
[0086] In this embodiment, the data table can exist in a distributed database system. The distributed database management system can be set up on multiple servers. The distributed database system supports multi-version concurrency control technology, so that when multiple objects perform read and write operations on the database at the same time, the data seen by all objects can be consistent (even if other objects are modifying the data at the moment).
[0087] In this embodiment, a simple, easy-to-use, and user-friendly interface can be displayed on the terminal. This interface supports various methods such as relevant personnel creating instructions, triggering controls, and voice input to transmit management requests for the database (such as data acquisition requests, data adjustment requests, etc.). The terminal can respond to the operations of relevant personnel, generate and send data acquisition requests / data adjustment requests to the server, etc.
[0088] 220. If the insertion identifier data of a data row includes an object identifier or a data table creator identifier, the server determines the data row as a candidate data row.
[0089] 230. If the deletion identifier data of the candidate data row does not include the object identifier and the update identifier data is empty, the server determines the candidate data row as the target data row.
[0090] 240. If the deletion identifier data of the candidate data row includes the object identifier and the update identifier data is not empty, the server determines the first data row that is uniquely identified by the update identifier data as the target data row.
[0091] 250. The server determines the filter identifier data corresponding to the filter identifier in the target data row. If the filter identifier data matches the target filter condition, the server determines the filter identifier data as the target data and returns the target data to the target object.
[0092] 260. The server receives a data adjustment request initiated by the target object. The data adjustment request includes the object identifier of the target object and adjustment information for at least one data row in the data table. The adjustment information includes data information corresponding to at least one adjustment method.
[0093] 270. If the adjustment information includes the new identifier data of the newly added data row, the server adds a second data row in the data table that includes the new identifier data, and determines the object identifier as the insertion identifier data of the second data row.
[0094] 280. If the adjustment information also includes deletion information for the third data row, the server will identify the object identifier as the deletion identifier data for the third data row.
[0095] 290. If the adjustment information also includes update identifier data for the fourth data row, the server determines the object identifier as the deletion identifier data for the fourth data row, adds a fifth data row to the data table including the update identifier data, determines the object identifier as the insertion identifier data for the fifth data row, and determines the row identifier of the fifth data row as the update identifier data for the fourth data row, so as to obtain the adjusted data table.
[0096] See Figure 4 , Figure 4This is a schematic diagram of the application process of this application. The table file of the data table includes multiple data rows (rows 1-3), as well as a main branch, branch one, and branch two. The main branch corresponds to the creator of the data table, and branch one and branch two can correspond to different target objects. For example, in a test verification scenario, branch one corresponds to tester 1, and branch two corresponds to tester 2. Tester 1 and tester 2 can respectively pull data from the main table (main data table) corresponding to the main branch, and can also "modify" the data in the main table. Thus, multiple people can carry out test tasks at the same time. This process will not change the original main table, ensuring the integrity of the main table while constructing multiple branch tables, significantly improving the flexibility and security of data table operations.
[0097] Specifically, the main branch can read and modify the data in rows 1-3. Branch 1 can insert a new row 4 into the data table. The insertion identifier of row 4 is the object identifier of the object corresponding to branch 1 (for example, if the insertion identifier is xmin, the data position corresponding to xmin in row 4 is filled with the identifier corresponding to branch 1). Therefore, other branches besides branch 1 cannot view or modify the value of row 4. Branch 1 can also delete row 3. At this time, the deletion identifier of row 3 is the object identifier of the object corresponding to branch 1 (for example, if the deletion identifier is xmax, the data position corresponding to the deletion identifier in row 3 is the identifier corresponding to branch 1). Thus, row 3 has been deleted for branch 1, but row 3 still exists in the data table for the main branch and other branches.
[0098] Branch 2 can update row 1. In this case, the data table includes the new row 1 from branch 2. The insertion identifier data of the new row 1 is the identifier corresponding to branch 2 / the object identifier of the corresponding object. The deletion identifier data of row 1 is the identifier corresponding to branch 2 / the object identifier of the corresponding object. The update identifier data (for example, if the update identifier is ctid, the data position corresponding to ctid in row 1 is filled with the identifier corresponding to branch 2) is the row identifier of the new row 1. Branch 2 can also delete row 3. In this case, the deletion identifier data of row 3 also includes the identifier corresponding to branch 2 / the object identifier of the corresponding object.
[0099] Through the above operations, when branch one queries the data table, it can see rows 1 and 2 created by the main branch, as well as row 4, which it newly inserted. When branch two queries the data table, it can see row 2 created by the main branch, as well as row 1, which it updated.
[0100] In the embodiments of this application, the main branch's query and / or modification permissions on the main table can be the same as those of each sub-branch (such as branch one, branch two), or they can be higher than those of some or all sub-branches. The specific handling can be flexible in actual application scenarios, and no further restrictions are imposed.
[0101] The embodiments of this application can improve the operational flexibility of the data table, enabling different objects to obtain their respective versions of the data table from a single data table, reducing the risk of data errors and conflicts, and improving the data recovery capability of the data table. Historical versions of the data table of an object can be queried from the data table. Under the premise of supporting multiple versions of data tables (multiple branches) for different objects, there is no need for repeated data copying, further optimizing the storage space usage and effectively reducing storage costs.
[0102] To better implement the above methods, embodiments of this application also provide a data acquisition device, such as... Figure 5 As shown, the data acquisition device may include an acquisition module 310, a filtering module 320, a determining module 330, and a matching module 340, wherein,
[0103] The acquisition module 310 is used to receive a data acquisition request from a target object for a data table. The data acquisition request carries the object identifier of the target object and data filtering conditions. The data table includes at least one data row, and the data row includes multiple identifier data.
[0104] The filtering module 320 is used to filter at least one candidate data row from the data rows based on the object identifier and the attribute information of the data table;
[0105] The determination module 330 is used to determine at least one target data row corresponding to the data acquisition request based on at least one identifier data of the candidate data row;
[0106] The matching module 340 is used to filter out at least one target data that matches the data filtering conditions in the target data row and return the target data to the target object.
[0107] In some embodiments of this application, the identification data includes inserted identification data, the attribute information includes the creator identifier, and the filtering module can be specifically used for:
[0108] If the insertion identifier data of a data row includes an object identifier or a data table creator identifier, the data row is determined to be a candidate data row.
[0109] In some embodiments of this application, the identification data includes deleting identification data and updating identification data, and the determining module can be specifically used for:
[0110] If the deletion identifier data of the candidate data row does not include the object identifier and the update identifier data is empty, the candidate data row is determined to be the target data row;
[0111] If the deletion identifier data of the candidate data row includes the object identifier and the update identifier data is not empty, the first data row that determines the unique identifier of the update identifier data is the target data row.
[0112] In some embodiments of this application, the data filtering conditions include target filtering conditions for at least one filtering identifier, and the matching module may be specifically used for:
[0113] Identify the filter identifier data corresponding to the filter identifier in the target data row, and if the filter identifier data matches the target filter condition, determine the filter identifier data as the target data and return the target data to the target object.
[0114] In some embodiments of this application, the data acquisition device further includes a request module and an adjustment module, wherein,
[0115] The request module is used to receive data adjustment requests initiated by the target object. The data adjustment request includes the object identifier of the target object and adjustment information for at least one data row in the data table. The adjustment information includes data information corresponding to at least one adjustment method.
[0116] The adjustment module is used to adjust data rows based on adjustment information and object identifiers to obtain an adjusted data table.
[0117] In some embodiments of this application, the adjustment module may include an adjustment submodule, wherein,
[0118] The adjustment submodule is used to add a second data row to the data table if the adjustment information includes the new identifier data of the new data row, and to determine the object identifier as the insertion identifier data of the second data row, so as to obtain the adjusted data table.
[0119] In some embodiments of this application, the adjustment submodule includes a first adjustment unit and a second adjustment unit, wherein,
[0120] The first adjustment unit is used to add a second data row including the new identification data in the data table if the adjustment information includes the new identification data of the new data row, and to determine the object identifier as the insertion identification data of the second data row.
[0121] The second adjustment unit is used to determine the object identifier as the deletion identifier data of the third data row if the adjustment information also includes deletion information for the third data row, so as to obtain the adjusted data table.
[0122] In some embodiments of this application, the second adjustment unit may be specifically used for:
[0123] If the adjustment information also includes deletion information for the third data row, the object identifier will be determined as the deletion identifier data for the third data row;
[0124] If the adjustment information also includes update identifier data for the fourth data row, the object identifier is determined as the deletion identifier data of the fourth data row. A fifth data row including update identifier data is added to the data table, the object identifier is determined as the insertion identifier data of the fifth data row, and the row identifier of the fifth data row is determined as the update identifier data of the fourth data row, so as to obtain the adjusted data table.
[0125] This application embodiment can first receive a data acquisition request from a target object for a data table. The data acquisition request carries the object identifier of the target object and data filtering conditions. The data table here includes at least one data row, and the data row includes multiple identifier data. Then, based on the object identifier and the attribute information of the data table, candidate data rows can be filtered from the data rows. All candidate data rows form a data table from the perspective of the target object. Then, based on the identifier data in the candidate data rows, the target data row required for this data acquisition request can be determined. Then, at least one target data matching the data filtering conditions can be filtered from the target data row. The process of acquiring target data from the data table is strongly related to the target object, which can significantly improve the security of data acquisition.
[0126] This application also provides a computer device, such as... Figure 6 As shown, it illustrates a structural schematic diagram of a computer device involved in an embodiment of this application. This computer device can be a terminal or a server, etc. Specifically:
[0127] The computer device may include components such as a processor 401 with one or more processing cores, a memory 402 with one or more computer-readable storage media, a power supply 403, and an input unit 404. Those skilled in the art will understand that... Figure 6 The computer device structure shown does not constitute a limitation on the computer device and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein:
[0128] The processor 401 is the control center of the computer device, connecting various parts of the computer device through various interfaces and lines. It performs various functions and processes data by running or executing computer programs and / or modules stored in the memory 402, and by calling data stored in the memory 402. Optionally, the processor 401 may include one or more processing cores; preferably, the processor 401 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and computer programs, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 401.
[0129] The memory 402 can be used to store computer programs and modules. The processor 401 executes various functional applications and data processing by running the computer programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, computer programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 402 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 402 may also include a memory controller to provide the processor 401 with access to the memory 402.
[0130] The computer device also includes a power supply 403 that supplies power to the various components. Preferably, the power supply 403 can be logically connected to the processor 401 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 403 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.
[0131] The computer device may also include an input unit 404, which can be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.
[0132] Although not shown, the computer device may also include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 401 in the computer device loads the executable files corresponding to the processes of one or more computer programs into the memory 402 according to the following instructions, and the processor 401 runs the application programs stored in the memory 402 to realize various functions, as follows:
[0133] The system receives a data retrieval request from a target object for a data table. The data retrieval request carries the target object's object identifier and data filtering conditions. The data table includes at least one data row, and each data row includes multiple identifier data. Based on the object identifier and the data table's attribute information, at least one candidate data row is selected from the data rows. Based on at least one identifier data of the candidate data rows, at least one target data row corresponding to the data retrieval request is determined. At least one target data row matching the data filtering conditions is selected from the target data row, and the target data is returned to the target object.
[0134] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.
[0135] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by a computer program, or by a computer program controlling related hardware. The computer program can be stored in a computer-readable storage medium and loaded and executed by a processor.
[0136] Therefore, embodiments of this application provide a computer-readable storage medium storing a computer program that can be loaded by a processor to execute the steps of any of the data acquisition methods provided in embodiments of this application. For example, the computer program can execute the following steps:
[0137] The system receives a data retrieval request from a target object for a data table. The data retrieval request carries the target object's object identifier and data filtering conditions. The data table includes at least one data row, and each data row includes multiple identifier data. Based on the object identifier and the data table's attribute information, at least one candidate data row is selected from the data rows. Based on at least one identifier data of the candidate data rows, at least one target data row corresponding to the data retrieval request is determined. At least one target data row matching the data filtering conditions is selected from the target data row, and the target data is returned to the target object.
[0138] The computer-readable storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.
[0139] Since the computer program stored in the computer-readable storage medium can execute the steps of any of the data acquisition methods provided in the embodiments of this application, the beneficial effects that any of the data acquisition methods provided in the embodiments of this application can achieve can be realized. For details, please refer to the previous embodiments, which will not be repeated here.
[0140] This application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. A processor of a computer device reads the computer program from the computer-readable storage medium and executes the computer program, causing the computer device to perform the methods provided in various optional implementations of the data acquisition method described above.
[0141] The data acquisition method, apparatus, and computer device provided in the embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. A data acquisition method, characterized in that, include: Receive a data retrieval request from a target object for a data table. The data retrieval request carries the object identifier of the target object and data filtering conditions. The data table includes at least one data row, and the data row includes multiple identifier data. Based on the object identifier and the attribute information of the data table, at least one candidate data row is selected from the data rows; Based on at least one identifier data of the candidate data rows, determine at least one target data row corresponding to the data acquisition request; Filter at least one target data that matches the data filtering criteria from the target data row, and return the target data to the target object.
2. The method according to claim 1, characterized in that, The identification data includes insertion identification data, the attribute information includes a creator identifier, and the step of filtering at least one candidate data row from the data rows based on the object identifier and the attribute information of the data table includes: If the insertion identifier data of a data row includes the object identifier or the creator identifier of the data table, the data row is determined to be a candidate data row.
3. The method according to claim 2, characterized in that, The identification data includes deleted identification data and updated identification data. The step of determining at least one target data row corresponding to the data acquisition request based on at least one identification data row of the candidate data rows includes: If the deletion identifier data of the candidate data row does not include the object identifier and the update identifier data is empty, the candidate data row is determined to be the target data row; If the deletion identifier data of the candidate data row includes the object identifier and the update identifier data is not empty, the first data row that is uniquely identified by the update identifier data is the target data row.
4. The method according to claim 3, characterized in that, The data filtering conditions include target filtering conditions for at least one filtering identifier, and the step of filtering at least one target data that matches the data filtering conditions in the target data row includes: Determine the filter identifier data corresponding to the filter identifier in the target data row, and if the filter identifier data matches the target filter condition, determine the filter identifier data as the target data.
5. The method according to claim 1, characterized in that, The method further includes: Receive a data adjustment request initiated by the target object. The data adjustment request includes the object identifier of the target object and adjustment information for at least one data row in the data table. The adjustment information includes data information corresponding to at least one adjustment method. Based on the adjustment information and the object identifier, the data rows are adjusted to obtain the adjusted data table.
6. The method according to claim 5, characterized in that, The step of adjusting the data rows based on the adjustment information and the object identifier to obtain the adjusted data table includes: If the adjustment information includes new identifier data for a new data row, a second data row including the new identifier data is added to the data table, and the object identifier is determined as the insertion identifier data of the second data row to obtain the adjusted data table.
7. The method according to claim 6, characterized in that, If the adjustment information includes new identifier data for a new data row, a second data row including the new identifier data is added to the data table, and the object identifier is determined as the insertion identifier data of the second data row to obtain the adjusted data table, including: If the adjustment information includes new identifier data for a new data row, a second data row including the new identifier data is added to the data table, and the object identifier is determined as the insertion identifier data of the second data row; If the adjustment information also includes deletion information for the third data row, the object identifier is determined as the deletion identifier data of the third data row to obtain the adjusted data table.
8. The method according to claim 6, characterized in that, If the adjustment information further includes deletion information for the third data row, the object identifier is determined as the deletion identifier data of the third data row to obtain the adjusted data table, including: If the adjustment information also includes deletion information for the third data row, the object identifier is determined as the deletion identifier data of the third data row; If the adjustment information also includes update identifier data for the fourth data row, the object identifier is determined as the deletion identifier data of the fourth data row, a fifth data row including the update identifier data is added to the data table, the object identifier is determined as the insertion identifier data of the fifth data row, and the row identifier of the fifth data row is determined as the update identifier data of the fourth data row, so as to obtain the adjusted data table.
9. A data acquisition device, characterized in that, include: The acquisition module is used to receive a data acquisition request from a target object for a data table. The data acquisition request carries the object identifier of the target object and data filtering conditions. The data table includes at least one data row, and the data row includes multiple identifier data. A filtering module is used to filter at least one candidate data row from the data rows based on the object identifier and the attribute information of the data table; The determining module is used to determine at least one target data row corresponding to the data acquisition request based on at least one identifier data of the candidate data row; The matching module is used to filter out at least one target data that matches the data filtering conditions from the target data row, and return the target data to the target object.
10. A computer device, characterized in that, It includes a memory and a processor; the memory stores an application program, and the processor is used to run the application program within the memory to perform the steps of the data acquisition method according to any one of claims 1 to 8.