A data computing method, device and electronic equipment
By obtaining the privacy data registry and field information table, the user list is determined and calculations are performed, solving the data sharing problem in a multi-user environment of a Hadoop cluster, and realizing secure sharing of data calculation results and protection of source data.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- AGRICULTURAL BANK OF CHINA
- Filing Date
- 2022-09-08
- Publication Date
- 2026-06-16
AI Technical Summary
In a multi-user Hadoop cluster environment, how can we prevent the leakage of source data from various business departments during data sharing, especially when commercial banks conduct multi-dimensional data-driven accurate credit risk assessments, where data from a single business department is insufficient and obtaining compliant data from third parties is difficult?
By receiving data calculation requests from target users, the system obtains the privacy data registry and privacy data field information table, determines the user list and field data, performs calculation operations, and only returns the calculation results, thus avoiding the leakage of source data.
It enables the sharing of data computation results in a multi-user environment of a Hadoop cluster, while avoiding the leakage of source data, enhancing data value, and supporting joint marketing and risk control for commercial banks.
Smart Images
Figure CN115688161B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of data computing, and more specifically, to a data computing method, apparatus, and electronic device. Background Technology
[0002] Commercial banks store massive amounts of business data in a Hadoop big data environment. This data may come from multiple business departments and has a certain degree of independence. Each business department requires that this data be stored in its own Hadoop user space to achieve logical data isolation.
[0003] During the use of data, various business departments sometimes need to use multidimensional data to conduct accurate credit risk assessments of customers. However, the data of a single business department is insufficient, and it is difficult to obtain compliant data from third parties, resulting in the lack of suitable data available. Therefore, it is urgent to share data with other business departments on the basis of compliance.
[0004] Therefore, in a multi-user environment of a Hadoop cluster, when data sharing is required, how to prevent the leakage of source data from various business departments is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention
[0005] In view of this, the present invention provides a data computing method, apparatus and electronic device to solve the problem of avoiding the leakage of source data of various business departments when data sharing is required in a multi-user environment of Hadoop cluster.
[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:
[0007] A data calculation method, comprising:
[0008] Receive a data calculation request from a target user, the data calculation request including a data table name, field names in the data table name, and data calculation rules;
[0009] Obtain a privacy data registry and a privacy data field information table; the privacy data registry includes the mapping relationship between registered privacy data tables and users; the privacy data field information table includes the field information of the registered privacy data tables;
[0010] Based on the privacy data registry, a list of users who have registered privacy data tables corresponding to the data table names is determined;
[0011] If the user list includes not only the target user, based on the privacy data field information table, determine the field data of the field name in the registered privacy data table corresponding to the data table name;
[0012] According to the data calculation rules, the field data is calculated to obtain the data calculation result, and only the data calculation result is returned to the target user.
[0013] Optionally, if the user list includes only the target user, it also includes:
[0014] Output target information to the target user; the target information indicates that no other user data is available.
[0015] Optionally, based on the privacy data registry, a list of users who have registered privacy data tables corresponding to the data table names is determined, including:
[0016] Query the privacy data registry to identify users who have registered a privacy data table corresponding to the data table name;
[0017] The identified users are grouped into a user list.
[0018] Optionally, based on the privacy data field information table, the field data of the field name in the registered privacy data table corresponding to the data table name is determined, including:
[0019] For each registered privacy data table corresponding to the data table name, query the field information in the registered privacy data table from the privacy data field information table;
[0020] The field data for the field name is determined from the field information.
[0021] Optionally, returning the data calculation result to the target user includes:
[0022] The data calculation results are written into a multi-user security calculation result table, and the multi-user security calculation result table is sent to the target user.
[0023] A data computing device, comprising:
[0024] The request receiving module is used to receive data calculation requests from target users. The data calculation request includes a data table name, field names in the data table name, and data calculation rules.
[0025] The data acquisition module is used to acquire a privacy data registry and a privacy data field information table; the privacy data registry includes the mapping relationship between registered privacy data tables and users; the privacy data field information table includes the field information of the registered privacy data tables;
[0026] The list determination module is used to determine a list of users who have registered privacy data tables corresponding to the data table names based on the privacy data registry.
[0027] The data determination module is used to determine, based on the privacy data field information table, the field data of the field name in the registered privacy data table corresponding to the data table name when the user list includes not only the target user;
[0028] The calculation module is used to perform calculation operations on the field data according to the data calculation rules, obtain the data calculation results, and return only the data calculation results to the target user.
[0029] Optionally, it also includes:
[0030] The information output module is used to output target information to the target user when the user list only includes the target user; the target information indicates that no other user data is available.
[0031] Optionally, the list determination module is specifically used for:
[0032] The privacy data registry is queried to identify users who have registered for the privacy data table corresponding to the data table name, and the identified users are compiled into a user list.
[0033] Optionally, the data determination module is specifically used for:
[0034] For each registered privacy data table corresponding to the data table name, query the field information in the registered privacy data table in the privacy data field information table, and determine the field data of the field name from the field information.
[0035] An electronic device includes: a memory and a processor;
[0036] The memory is used to store programs;
[0037] The processor calls the program and uses it to execute the data calculation method described above.
[0038] Compared with the prior art, the present invention has the following beneficial effects:
[0039] This invention provides a data calculation method, apparatus, and electronic device. In this invention, after receiving a data calculation request from a target user, instead of directly returning the source data of other users involved in the calculation to the target user, a privacy data registry and a privacy data field information table are obtained. Based on the privacy data registry, a list of users with registered privacy data tables corresponding to the data table name is determined. If the user list includes more than just the target user, based on the privacy data field information table, the field data of the field name in the registered privacy data table corresponding to the data table name is determined. The field data is then calculated according to the data calculation rules to obtain the data calculation result. Only the data calculation result is returned to the target user. This ensures that the target user only receives the data calculation result and does not obtain the source data required for intermediate calculations. This achieves data calculation result sharing while preventing source data leakage in a multi-user environment of a Hadoop cluster. Attached Figure Description
[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.
[0041] Figure 1 A flowchart of a data calculation method provided in an embodiment of the present invention;
[0042] Figure 2 A flowchart illustrating another data calculation method provided in an embodiment of the present invention;
[0043] Figure 3 This is a schematic diagram of the structure of a data computing device provided in an embodiment of the present invention. Detailed Implementation
[0044] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0045] A new wave of technological innovation, represented by cloud computing, big data, and artificial intelligence, is profoundly impacting people's production and lifestyles. As a pillar of the national economy, the financial industry's ability to effectively utilize big data for digital transformation will determine its future sustainable development. Hadoop, with its low-cost hardware and software, powerful parallel computing capabilities, and distributed query engine, provides solutions for commercial banks to build big data platforms.
[0046] Hadoop is a distributed system infrastructure developed by the Apache Software Foundation. Users can develop distributed programs without understanding the underlying details of distributed systems, and fully utilize the performance of clusters for high-speed computing and storage.
[0047] Commercial banks store massive amounts of business data in a Hadoop big data environment. This data may come from multiple business departments and has a certain degree of independence. Each business department requires that this data be stored in its own Hadoop user space to achieve logical data isolation.
[0048] During the use of data, various business departments sometimes need to use multidimensional data to conduct accurate credit risk assessments of customers. However, the data of a single business department is insufficient, and it is difficult to obtain compliant data from third parties, resulting in the lack of suitable data available. Therefore, it is urgent to share data with other business departments on the basis of compliance.
[0049] Therefore, in a multi-user environment of a Hadoop cluster, when data sharing is required, how to prevent the leakage of source data from various business departments is a technical problem that urgently needs to be solved by those skilled in the art.
[0050] Current Hadoop data computation focuses only on the authentication, access control, and data encryption of individual users' data within the Hadoop cluster, as well as preventing unauthorized or unauthorized access. It does not consider the data sharing issues between multiple different users in Hadoop and the security issues during data sharing. This may lead to the leakage of multi-user data during shared computation, and there is a certain degree of one-sidedness in data security protection.
[0051] To address this issue, this invention provides a data calculation method, apparatus, and electronic device. In this invention, after receiving a data calculation request from a target user, instead of directly returning the source data of other users involved in the calculation to the target user, a privacy data registry and a privacy data field information table are obtained. Based on the privacy data registry, a list of users with registered privacy data tables corresponding to the data table name is determined. If the user list includes more than just the target user, based on the privacy data field information table, the field data of the field name in the registered privacy data table corresponding to the data table name is determined. The field data is then calculated according to the data calculation rules to obtain the data calculation result. Only the data calculation result is returned to the target user. This ensures that the target user only receives the data calculation result and does not obtain the source data required for intermediate calculations. This achieves data calculation result sharing while preventing source data leakage in a multi-user environment of a Hadoop cluster.
[0052] This invention enables joint computation of data from multiple business departments while ensuring the privacy of the source data of each participating business department is not leaked. The computation results are then applied to joint marketing and joint risk control among different business departments of commercial banks, effectively enhancing the data value of Hadoop.
[0053] It should be noted that this invention primarily employs a privacy-preserving computation strategy. This strategy separates the visible, concrete information portion of data from the invisible computational value portion, achieving "data usable (computable) but invisible (unaccessible)." This eliminates concerns among data collaborators regarding data work and privacy leaks, effectively addressing the "data silo" dilemma through technological means. Essentially, it is a technology where multiple participants perform joint computations under conditions of trust. Without disclosing their original data or business privacy, each participant collaborates through an encrypted mechanism to jointly compute and analyze the data, realizing the fusion value of the data and enabling data intelligence to evolve from local insights to global insights.
[0054] Based on the above, one embodiment of the present invention provides a data calculation method. It should be noted that the data calculation method of the present invention is applied in a multi-user environment of a Hadoop cluster. The users of Hadoop can include user1, user2, user3, etc., but only the system administrator user in Hadoop can obtain the source data of other users and perform calculations. The calculation result is returned to the user who initiated the calculation request.
[0055] Reference Figure 1 Data calculation methods may include:
[0056] S11. Receive the data calculation request from the target user.
[0057] The data calculation request includes the data table name, the field names in the data table, and the data calculation rules.
[0058] For example, when user MRI initiates a data calculation request, the request includes the specific table name, field names, and data calculation rules.
[0059] The data table name refers to the name of the data table that needs to be calculated, and it can be the English name of the data table.
[0060] The field name refers to the specific field in the data table corresponding to the data table name that needs to be calculated when performing data calculations.
[0061] Data calculation rules refer to the rules for calculating the data of a field with a given field name. Data calculation rules can be calculation functions, such as summation functions, average functions, etc.
[0062] S12. Obtain the privacy data registry and privacy data field information table.
[0063] The privacy data registry includes registered privacy data tables and mapping relationships between users.
[0064] In practical applications, a "Privacy Data Registration Management" component can be set up, allowing administrators to uniformly manage the metadata registration information of different users' privacy data, forming a mapping relationship between the privacy data table and users.
[0065] First, define a "Privacy Data Registry" to store the mapping between registered privacy data tables and users, including fields such as "Hadoop Username," "Privacy Data Table Name," and "HDFS File System Storage Path." An example of a "Privacy Data Registry" is shown in Table 1.
[0066] Table 1
[0067]
[0068] Secondly, a new "Privacy Data Field Information Table" needs to be added to store the field information of the privacy data tables. This table includes the field information of the registered privacy data tables, and the field information can include fields such as "Field Name (English)," "Field Name (Chinese)," and "Privacy Data Table Name (English)." An example of a "Privacy Data Field Information Table" is shown in Table 2.
[0069] Table 2
[0070]
[0071] Before importing private data into their HDFS (Hadoop Distributed File System, designed to run on general-purpose hardware) storage space, each Hadoop user must first register in the "Privacy Data Registry." If the corresponding field configuration is not in the "Privacy Data Field Information Table," the user must add the field configuration information in the "Privacy Data Field Information Table." After completing the "Privacy Data Registry" registration, the user can then import the source data into their Hadoop storage space.
[0072] S13. Based on the privacy data registry, determine a list of users who have registered privacy data tables corresponding to the data table names.
[0073] In this embodiment, a "multi-user privacy data security calculation" component can be set up to query the mapping relationship between the privacy data table and the user based on the data calculation request submitted by the user, and complete the loading, calculation and storage of different user data.
[0074] In practical applications, during data computation, it is generally required that the user space of the target user issuing the data computation request possesses the registered privacy data table corresponding to the data table name in the data computation request. Furthermore, at least one other user must also possess this table to meet data sharing requirements.
[0075] If only the target user has this table, then this calculation does not involve data sharing, and therefore this calculation can be skipped.
[0076] Reference Figure 2 Step S13 may include:
[0077] S21. Query the privacy data registry to identify users who have registered privacy data tables corresponding to the data table names.
[0078] Specifically, based on the data table name submitted by the user, such as the English name of the data table, the "Privacy Data Registry" is queried to find the user who owns this table.
[0079] S22. Assemble the identified users into a user list.
[0080] Once all users are found, they can be grouped into a user list in order.
[0081] S14. If the user list includes not only the target user, determine the field data of the field name in the registered privacy data table corresponding to the data table name based on the privacy data field information table.
[0082] Specifically, if the user list includes not only the target user, it means that other users also use this data table. In this case, for each registered privacy data table corresponding to the data table name, the field information in the registered privacy data table can be queried, and the field data of the field name can be determined from the field information.
[0083] For example, if there are 5 data tables and the field required for data calculation is Field1, then the content of Field1 in the 5 data tables will be extracted. Then, the extracted field data will be loaded into Hadoop memory.
[0084] In another implementation of the present invention, when the user list includes only the target user, the method further includes:
[0085] Output target information to the target user; the target information indicates that no other user data is available.
[0086] Specifically, if the user list only contains the target user MRI itself, then "No other user data is available" is returned, and the process ends.
[0087] S15. Perform calculation operations on the field data according to the data calculation rules to obtain the data calculation results, and return only the data calculation results to the target user.
[0088] Specifically, after obtaining the field data, calculations are performed on the field data according to the data calculation rules. The obtained data calculation results can be written into a multi-user secure calculation result table, and the multi-user secure calculation result table is sent to the target user. The target user can store the "multi-user secure calculation result table" in their own Hadoop storage space.
[0089] To enable those skilled in the art to better understand the present invention, examples are provided below.
[0090] User mr1 initiates a multi-user data security computation request, requesting the sum of Field3 in table Table1. Based on the submitted table name Table1, the "Privacy Data Registry" is queried to find the list of users mr1, mr2, and mr4 who own this table. The privacy data from user lists mr1, mr2, and mr4 is loaded into Hadoop memory. The privacy data computation is completed according to the user's security computation request "summing Field3 in table Table1," resulting in the "Multi-User Security Computation Result Table Result." The "Multi-User Security Computation Result Table Result" is returned to user mr1, who then stores it in their own Hadoop storage space.
[0091] In practical applications, a "Multi-User Data Computation Result Query" component can also be set up. Users can query multi-user secure computation result data, and the query results are returned to the upper-layer application. The upper-layer application initiates a multi-user data computation result query request, and users query the data in the "Multi-User Secure Computation Result Table" stored in their own storage space, returning the query results to the upper-layer application. From the query process perspective, querying the "Multi-User Secure Computation Result Table" in the user's storage space is no different from querying a regular data table in the user's storage space.
[0092] Compared to traditional methods, which focus solely on authentication, access control, data encryption, and prevention of unauthorized or unauthorized access to individual Hadoop user data, this invention addresses data security issues arising from shared computation among multiple users. While protecting user privacy, it enables cross-departmental data collaboration for joint computation across different business departments, resolving the data insufficiency issue of single business departments. This allows for compliant data sharing with high-quality data departments, and the computation results are widely applied to joint risk control within business departments, effectively reducing the credit risk of commercial banks.
[0093] In this embodiment, after receiving the data calculation request from the target user, the source data of other users participating in the calculation is not directly returned to the target user. Instead, a privacy data registry and a privacy data field information table are obtained. Based on the privacy data registry, a list of users with registered privacy data tables corresponding to the data table name is determined. If the user list includes more than just the target user, the field data of the field name in the registered privacy data table corresponding to the data table name is determined based on the privacy data field information table. The field data is then calculated according to the data calculation rules to obtain the data calculation result. Only the data calculation result is returned to the target user. This ensures that the target user can only obtain the data calculation result and not the source data required for intermediate calculations. This achieves the goal of ensuring data calculation result sharing while avoiding source data leakage in a multi-user environment of a Hadoop cluster.
[0094] Optionally, based on the embodiments of the above data calculation method, another embodiment of the present invention provides a data calculation apparatus, referring to... Figure 3 It can include:
[0095] The request receiving module 11 is used to receive a data calculation request from a target user. The data calculation request includes a data table name, field names in the data table name, and data calculation rules.
[0096] The data acquisition module 12 is used to acquire a privacy data registry and a privacy data field information table; the privacy data registry includes the mapping relationship between registered privacy data tables and users; the privacy data field information table includes the field information of the registered privacy data tables;
[0097] The list determination module 13 is used to determine a list of users who have registered privacy data tables corresponding to the data table names based on the privacy data registry.
[0098] The data determination module 14 is used to determine, based on the privacy data field information table, the field data of the field name in the registered privacy data table corresponding to the data table name when the user list includes not only the target user;
[0099] The calculation module 15 is used to perform calculation operations on the field data according to the data calculation rules, obtain the data calculation results, and return only the data calculation results to the target user.
[0100] Furthermore, it also includes:
[0101] The information output module is used to output target information to the target user when the user list only includes the target user; the target information indicates that no other user data is available.
[0102] Furthermore, the list determination module is specifically used for:
[0103] The privacy data registry is queried to identify users who have registered for the privacy data table corresponding to the data table name, and the identified users are compiled into a user list.
[0104] Furthermore, the data determination module is specifically used for:
[0105] For each registered privacy data table corresponding to the data table name, query the field information in the registered privacy data table in the privacy data field information table, and determine the field data of the field name from the field information.
[0106] Furthermore, when the calculation module 15 returns the data calculation result to the target user, it is specifically used for:
[0107] The data calculation results are written into a multi-user security calculation result table, and the multi-user security calculation result table is sent to the target user.
[0108] In this embodiment, after receiving the data calculation request from the target user, the source data of other users participating in the calculation is not directly returned to the target user. Instead, a privacy data registry and a privacy data field information table are obtained. Based on the privacy data registry, a list of users with registered privacy data tables corresponding to the data table name is determined. If the user list includes more than just the target user, the field data of the field name in the registered privacy data table corresponding to the data table name is determined based on the privacy data field information table. The field data is then calculated according to the data calculation rules to obtain the data calculation result. Only the data calculation result is returned to the target user. This ensures that the target user can only obtain the data calculation result and not the source data required for intermediate calculations. This achieves the goal of ensuring data calculation result sharing while avoiding source data leakage in a multi-user environment of a Hadoop cluster.
[0109] It should be noted that the working process of each module in this embodiment is described in the corresponding descriptions in the above embodiments, and will not be repeated here.
[0110] Optionally, based on the embodiments of the above data calculation method and apparatus, another embodiment of the present invention provides an electronic device, including: a memory and a processor;
[0111] The memory is used to store programs;
[0112] The processor calls the program and uses it to execute the data calculation method described above.
[0113] Specifically, a data calculation method includes:
[0114] Receive a data calculation request from a target user, the data calculation request including a data table name, field names in the data table name, and data calculation rules;
[0115] Obtain a privacy data registry and a privacy data field information table; the privacy data registry includes the mapping relationship between registered privacy data tables and users; the privacy data field information table includes the field information of the registered privacy data tables;
[0116] Based on the privacy data registry, a list of users who have registered privacy data tables corresponding to the data table names is determined;
[0117] If the user list includes not only the target user, based on the privacy data field information table, determine the field data of the field name in the registered privacy data table corresponding to the data table name;
[0118] According to the data calculation rules, the field data is calculated to obtain the data calculation result, and only the data calculation result is returned to the target user.
[0119] Furthermore, if the user list only includes the target user, it also includes:
[0120] Output target information to the target user; the target information indicates that no other user data is available.
[0121] Furthermore, based on the privacy data registry, a list of users who have registered for the privacy data table corresponding to the data table name is determined, including:
[0122] Query the privacy data registry to identify users who have registered a privacy data table corresponding to the data table name;
[0123] The identified users are grouped into a user list.
[0124] Furthermore, based on the privacy data field information table, the field data of the field name in the registered privacy data table corresponding to the data table name is determined, including:
[0125] For each registered privacy data table corresponding to the data table name, query the field information in the registered privacy data table from the privacy data field information table;
[0126] The field data for the field name is determined from the field information.
[0127] Furthermore, returning the data calculation results to the target user includes:
[0128] The data calculation results are written into a multi-user security calculation result table, and the multi-user security calculation result table is sent to the target user.
[0129] In this embodiment, after receiving the data calculation request from the target user, the source data of other users participating in the calculation is not directly returned to the target user. Instead, a privacy data registry and a privacy data field information table are obtained. Based on the privacy data registry, a list of users with registered privacy data tables corresponding to the data table name is determined. If the user list includes more than just the target user, the field data of the field name in the registered privacy data table corresponding to the data table name is determined based on the privacy data field information table. The field data is then calculated according to the data calculation rules to obtain the data calculation result. Only the data calculation result is returned to the target user. This ensures that the target user can only obtain the data calculation result and not the source data required for intermediate calculations. This achieves the goal of ensuring data calculation result sharing while avoiding source data leakage in a multi-user environment of a Hadoop cluster.
[0130] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A data calculation method, characterized in that, include: Receive a data calculation request from a target user, the data calculation request including a data table name, field names in the data table name, and data calculation rules; Obtain the privacy data registry and privacy data field information table; The privacy data registry includes a mapping relationship between registered privacy data tables and users; the privacy data field information table includes field information of the registered privacy data tables; Based on the privacy data registry, a list of users who have registered privacy data tables corresponding to the data table names is determined; If the user list includes not only the target user, based on the privacy data field information table, determine the field data of the field name in the registered privacy data table corresponding to the data table name; According to the data calculation rules, the field data is calculated to obtain the data calculation result, and only the data calculation result is returned to the target user; If the user list includes only the target user, it also includes: Output the target information to the target user; The target information indicates that no other user data is available.
2. The data calculation method according to claim 1, characterized in that, Based on the privacy data registry, a list of users who have registered for the privacy data table corresponding to the data table name is determined, including: Query the privacy data registry to identify users who have registered a privacy data table corresponding to the data table name; The identified users are grouped into a user list.
3. The data calculation method according to claim 1, characterized in that, Based on the privacy data field information table, determine the field data of the field name in the registered privacy data table corresponding to the data table name, including: For each registered privacy data table corresponding to the data table name, query the field information in the registered privacy data table from the privacy data field information table; The field data for the field name is determined from the field information.
4. The data calculation method according to claim 1, characterized in that, Returning the calculated data results to the target user includes: The data calculation results are written into a multi-user security calculation result table, and the multi-user security calculation result table is sent to the target user.
5. A data computing device, characterized in that, include: The request receiving module is used to receive data calculation requests from target users. The data calculation request includes a data table name, field names in the data table name, and data calculation rules. The data acquisition module is used to acquire a privacy data registry and a privacy data field information table; the privacy data registry includes the mapping relationship between registered privacy data tables and users; the privacy data field information table includes the field information of the registered privacy data tables; The list determination module is used to determine a list of users who have registered privacy data tables corresponding to the data table names based on the privacy data registry. The data determination module is used to determine, based on the privacy data field information table, the field data of the field name in the registered privacy data table corresponding to the data table name when the user list includes not only the target user; The calculation module is used to perform calculation operations on the field data according to the data calculation rules, obtain the data calculation results, and return only the data calculation results to the target user; Also includes: The information output module is used to output target information to the target user when the user list only includes the target user; The target information indicates that no other user data is available.
6. The data computing device according to claim 5, characterized in that, The list determination module is specifically used for: The privacy data registry is queried to identify users who have registered for the privacy data table corresponding to the data table name, and the identified users are compiled into a user list.
7. The data computing device according to claim 5, characterized in that, The data determination module is specifically used for: For each registered privacy data table corresponding to the data table name, query the field information in the registered privacy data table in the privacy data field information table, and determine the field data of the field name from the field information.
8. An electronic device, characterized in that, include: Memory and processor; The memory is used to store programs; The processor calls the program and performs the data calculation method as described in any one of claims 1-4.