Data Processing Method, Apparatus, Communication Device, and Readable Storage Medium

Abstract

The present application provides a data processing method, apparatus, communication device, and readable storage medium. The server includes a resource management platform; the method includes: when the joint analysis permissions of at least one original table are respectively authorized by p participants, if a first input is received, a model result table and p intermediate tables corresponding to the p participants one by one are created in the resource management platform, the first input is an input that triggers joint analysis, the model result table only authorizes read permissions to the p participants, and each intermediate table only authorizes write permissions to its corresponding participant; writing data into the p intermediate tables, and the data written into the intermediate table corresponding to each participant is: the first data obtained by each participant by executing the corresponding participant execution script; when it is detected that each participant has executed the corresponding participant execution script, executing a joint analysis execution script in the resource management platform, and writing the execution result of the joint analysis execution script into the model result table.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of communication technologies, and in particular, to a data processing method, apparatus, communication device, and readable storage medium. Background Art

[0002] With the development of communication technologies, in order to promote business development, different companies or different business departments of the same company can jointly build models to achieve data cooperation. However, multi-party joint model building may involve the leakage of original data. Therefore, it is necessary to provide a data processing method that can both achieve multi-party joint model building and protect the original data from leakage. Summary of the Invention

[0003] Embodiments of the present application provide a data processing method, apparatus, communication device, and readable storage medium, which can solve the problems of multi-party joint model building and protecting the original data from leakage.

[0004] To solve the above problems, the present application is implemented as follows:

[0005] In a first aspect, an embodiment of the present application provides a data processing method, which is executed by a server, and the server includes a resource management platform; the method includes:

[0006] When the server obtains the joint analysis permissions of at least one original table authorized by p participating parties respectively, if a first input is received, a model result table and p intermediate tables corresponding to the p participating parties one by one are created in the resource management platform, where the first input is an input that triggers joint analysis, the model result table only authorizes read permissions to the p participating parties, each intermediate table only authorizes write permissions to its corresponding participating party, and p is an integer greater than 1;

[0007] Data is written into the p intermediate tables, where the data written into the intermediate table corresponding to each participating party is: the first data obtained by each participating party by executing the corresponding participating party execution script;

[0008] When it is detected that each participating party has executed the corresponding participating party execution script, a joint analysis execution script is executed in the resource management platform, and the execution result of the joint analysis execution script is written into the model result table.

[0009] In a second aspect, an embodiment of the present application provides a data processing method, which is executed by a first participating party, and the method includes:

[0010] When the first participating party authorizes the joint analysis permissions of at least one original table, obtain the first participating party execution script corresponding to the first participating party;

[0011] Execute the first participant execution script to obtain first data;

[0012] Send the first data to the server, and write the first data into the first intermediate table of the resource management platform of the server, where the first intermediate table corresponds to the first participant.

[0013] Thirdly, an embodiment of the present application further provides a data processing device, which is applied to a server, and the server includes a resource management platform; the device includes:

[0014] A creation module, configured to, when obtaining the joint analysis permissions of at least one original table authorized by p participants respectively, if receiving a first input, create a model result table and p intermediate tables corresponding to the p participants one by one in the resource management platform, where the first input is an input triggering joint analysis, the model result table only authorizes read permissions to the p participants, and each intermediate table only authorizes write permissions to its corresponding participant, and p is an integer greater than 1;

[0015] A first writing module, configured to write data into the p intermediate tables, where the data written into the intermediate table corresponding to each participant is: the first data obtained by each participant through executing the corresponding participant execution script;

[0016] A second writing module, configured to, when detecting that each participant has executed the corresponding participant execution script, execute a joint analysis execution script in the resource management platform, and write the execution result of the joint analysis execution script into the model result table.

[0017] Fourthly, an embodiment of the present application further provides a data processing device, which is applied to a first participant and includes:

[0018] A second obtaining module, configured to obtain the first participant execution script corresponding to the first participant when the first participant authorizes the joint analysis permission of at least one original table;

[0019] A first execution module, configured to execute the first participant execution script to obtain first data;

[0020] A first sending module, configured to send the first data to the server, and write the first data into the first intermediate table of the resource management platform of the server, where the first intermediate table corresponds to the first participant.

[0021] Fifthly, an embodiment of the present application further provides a communication device, which includes a processor, a memory, and a program or instruction stored on the memory and executable on the processor, and when the program or instruction is executed by the processor, it implements the data processing method as described in the first aspect.

[0022] In a sixth aspect, an embodiment of the present application further provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the data processing method described in the first aspect is implemented.

[0023] In a seventh aspect, an embodiment of the present application provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor, and the processor is configured to run a program or instruction to implement the method described in the first aspect.

[0024] In an eighth aspect, an embodiment of the present application provides a computer program product, which is stored in a storage medium and is executed by at least one processor to implement the method described in the first aspect.

[0025] In the embodiment of the present application, the joint modeling of multi-party data is realized through a resource management platform set in a server. Specifically, when the joint analysis permissions of at least one original table are respectively authorized by p participating parties, if an input for triggering joint analysis is received, a model result table and p intermediate tables corresponding to the p participating parties one by one can be created in the resource management platform, and the read permission of the model result table is only authorized to the p participating parties, and the write permission of each intermediate table is only authorized to its corresponding participating party, so as to avoid the leakage of data in each table. The p participating parties can obtain the data for joint analysis by respectively executing their own corresponding execution scripts and write the obtained data into their own corresponding intermediate tables. In this way, when it is detected that each participating party has executed the corresponding participating party execution script, the resource management platform can write the execution result of the joint analysis execution script into the model result table by executing the joint analysis execution script, so as to realize the joint modeling of the p participating parties. It can be seen that through the embodiment of the present application, the joint modeling of multi-party data and the privacy protection of multi-party data for joint analysis can be realized through the resource management platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is one of the flowcharts of the data processing method provided by the embodiment of the present application;

[0027] Figure 2 is a schematic diagram of a model editor provided by the embodiment of the present application;

[0028] Figure 3 is a second flowchart of the data processing method provided by the embodiment of the present application;

[0029] Figure 4a is the data processing architecture provided by the embodiment of the present application;

[0030] Figure 4b It is the third flowchart of the data processing method provided by an embodiment of the present application;

[0031] Figure 5 It is one of the structural diagrams of the data processing method provided by an embodiment of the present application;

[0032] Figure 6 It is the second structural diagram of the data processing method provided by an embodiment of the present application;

[0033] Figure 7 It is the structural diagram of the communication device provided by an embodiment of the present application. Detailed implementation manners

[0034] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, rather than all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without making creative efforts shall fall within the protection scope of the present application.

[0035] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are usually of the same category, and the number of objects is not limited. For example, the first object can be one or multiple. In addition, "and / or" in the specification and claims means at least one of the connected objects, and the character " / " generally indicates an "or" relationship between the associated objects before and after.

[0036] Inside a large company, between different business lines with a competitive relationship, in order to protect their own businesses, they may not jointly model the data unique to each business line, although from the perspective of the company, the data fusion of each business line can obviously bring more value.

[0037] In order to jointly model using data from multiple parties while protecting the original data of the participating parties, there are usually two solutions:

[0038] Safe area: Establish an independent third-party big data space, which contains common big data systems and corresponding data access control and auditing facilities. The participating parties can import data into the independent space through the data entrance, then perform modeling calculations in the space, and obtain the modeling result data through the data exit. All operations of the participating parties will be audited, and the input or output of data can be cut off at any time.

[0039] Federated learning: Instead of establishing an independent third-party space, the model is modified so that it can run within the participating parties. Then, by exchanging data during the model iteration process, the modeling purpose is ultimately achieved. Federated learning enables the participating parties to keep the original data locally, realizing the principle of "data can be used but not visible".

[0040] However, the above two solutions have the following defects:

[0041] Secure area: An independent area needs to be established, which usually means building an independent big data system. At the same time, a management and auditing mechanism for entering and leaving the isolation area also needs to be established, resulting in relatively high investment. For different business lines of the same company, the investment-output ratio is relatively low.

[0042] Federated learning: It has relatively high business invasiveness. The model needs to be modified to suit the operation logic of federated learning, and a large amount of development manpower is required for development. At the same time, a corresponding network communication mechanism needs to be established to exchange intermediate data during the federated learning process. During the federated learning process, there is also a possibility that the exchanged intermediate data can be restored by malicious users to obtain the original data.

[0043] Therefore, the embodiments of the present application provide a data processing method, which can realize joint modeling among multiple parties without repeatedly investing in building an independent isolation area and without investing a large amount of development manpower, and can protect the data used for joint analysis by multiple parties from being leaked.

[0044] For the convenience of understanding, some content related to the embodiments of the present application is described below:

[0045] The joint modeling of p participating parties is initiated by one of the p participating parties, where p is an integer greater than 1. In the embodiments of the present application, the initiating party that initiates the joint modeling of the p participating parties can be referred to as the target participating party or the model design party.

[0046] Before initiating the joint modeling, the target participating party can first determine the original tables expected to be used for joint analysis and the participating parties to which each original table belongs. Then, it applies to each participating party for the joint analysis permission of each original table. When each participating party agrees to authorize the joint analysis permission of each original table, a joint analysis model can be written. It can be understood that in actual applications, the number of original tables authorized for joint analysis by different participating parties can be equal or unequal, which can be determined according to the actual situation, and the embodiments of the present application do not make any limitations in this regard.

[0047] After writing the joint analysis model, the joint analysis model can be executed to obtain the data of each original table through the joint analysis model and output the joint analysis result.

[0048] It should be noted that, in the embodiments of the present application, for the original table with the combined analysis permission authorized, the combined analysis model can only read the data in the original table and cannot modify the data in the original table. That is, the combined analysis model only has the permission to read the data in the original table and does not have the permission to modify the data.

[0049] The data processing method of the embodiments of the present application can be implemented by a server and participants. The server can be understood as an existing big data platform or big data system. That is, the data processing method of the embodiments of the present application does not require repeated investment in building independent resources, and can maximize the reuse of existing big data systems, saving investment.

[0050] In the embodiments of the present application, the server is provided with a resource management platform. The resource management platform can be understood as a resource and permission management entity in a big data system, including entities such as libraries and tables, as well as permission control settings for accessing these entities.

[0051] The resource management platform can be used to store the data processed by all parties, perform combined analysis on the data processed by all parties, store the combined analysis results, and audit the combined analysis results.

[0052] The read permission of the data in the resource management platform is only authorized to each participant, thereby improving the reliability of data protection.

[0053] In practical applications, the resource management platform can be established by a department that has no competitive / cooperative relationship with each business line of the company, such as the audit / security / legal department, reflecting its "neutral" positioning. Therefore, the resource management platform can also be called a neutral zone.

[0054] Next, in combination with the accompanying drawings, through some embodiments and their application scenarios, the data processing method provided by the embodiments of the present application will be described in detail.

[0055] See Figure 1 , Figure 1 which is one of the flowcharts of the data processing method provided by the embodiments of the present application. Figure 1 The data processing method shown is executed by the server.

[0056] As Figure 1 shown, the data processing method may include the following steps:

[0057] Step 101: When the joint analysis permissions of at least one original table are authorized by p participating parties respectively, if a first input is received, a model result table and p intermediate tables corresponding to the p participating parties one by one are created in the resource management platform, where the first input is an input triggering joint analysis. The model result table only authorizes read permissions to the p participating parties, and each intermediate table only authorizes write permissions to its corresponding participating party, and p is an integer greater than 1.

[0058] In specific implementation, when the joint analysis permissions of at least one original table are authorized by p participating parties respectively, a joint analysis model can be written. After the joint analysis model is written, if a first input is received, the joint analysis model can be executed, and the first input can be an input initiated by a user for joint analysis.

[0059] In the embodiment of the present application, the execution of the joint analysis model includes: creating a model result table and p intermediate tables corresponding to the p participating parties one by one. In specific implementation, the above tables can be created by the server in the resource management platform.

[0060] After the server creates these tables, it can authorize the read permissions of the model result table to the p participating parties and authorize the write permissions of each intermediate table to the corresponding participating party. In this way, the reliability of obtaining source data for joint analysis can be ensured, and at the same time, the leakage of joint analysis results can be avoided, improving the reliability of data protection.

[0061] Step 102: Write data into the p intermediate tables, where the data written into the intermediate table corresponding to each participating party is: the first data obtained by each participating party by executing the corresponding participating party execution script.

[0062] In the embodiment of the present application, the execution of the joint analysis model further includes: executing p participating party execution scripts corresponding to the p participating parties one by one.

[0063] In specific implementation, each participating party execution script is executed by the corresponding participating party respectively. Each participating party execution script is respectively used to obtain data from the original table authorized for joint analysis by the corresponding participating party and write the obtained data into the corresponding intermediate table. Further, each participating party execution script is also used to encrypt the obtained data. In this case, the data written into the corresponding intermediate table is the encrypted data. Based on this, it can be understood that the first data may be the original data obtained from the original table or the encrypted data of the original data in the original table.

[0064] Exemplarily, denote the original table for which the first participating party authorizes the joint analysis permission as the first original table, the participating party execution script corresponding to the first participating party as the first participating party execution script, and the intermediate table corresponding to the first participating party as the first intermediate table.

[0065] Then, when executing the joint analysis model, the first participating party may execute the first participating party execution script, obtain specific data from the first original table, and directly input or encrypt and input the obtained specific data into the first intermediate table.

[0066] Step 103, when it is detected that each participating party has executed its corresponding participating party execution script, execute the joint analysis execution script on the resource management platform, and write the execution result of the joint analysis execution script into the model result table.

[0067] In the embodiment of the present application, the execution of the joint analysis model further includes: the execution of the joint analysis execution script. Specifically, when implemented, the execution of the joint analysis execution script is executed by the resource management platform.

[0068] The joint analysis execution script is used to: obtain data from at least one of the p intermediate tables, and write the obtained data into the model result table. It can be understood that the target data included in the model result table is the model analysis result of the joint analysis model.

[0069] The data processing method of this embodiment realizes the joint modeling of multi-party data through the resource management platform set in the server. Specifically, when the joint analysis permissions of at least one original table are respectively authorized by p participating parties, if an input triggering joint analysis is received, a model result table and p intermediate tables corresponding to the p participating parties one by one can be created on the resource management platform, and the read permission of the model result table is only authorized to the p participating parties, and the write permission of each intermediate table is only authorized to its corresponding participating party, so as to avoid the leakage of data in each table. The p participating parties can obtain the data for joint analysis by respectively executing their own corresponding execution scripts, and write the obtained data into their own corresponding intermediate tables. In this way, when it is detected that each participating party has executed its corresponding participating party execution script, the resource management platform can write the execution result of the joint analysis execution script into the model result table by executing the joint analysis execution script, thereby realizing the joint modeling of the p participating parties. It can be seen that through the embodiment of the present application, the joint modeling of multi-party data and the privacy protection of multi-party data for joint analysis can be realized through the resource management platform.

[0070] As can be seen from the foregoing content, in the embodiment of the present application, the execution of the joint analysis model may include:

[0071] Creation of a model result table and p intermediate tables corresponding one by one to the p participating parties;

[0072] Execution of scripts by the p participating parties corresponding one by one to the p participating parties;

[0073] Execution of a joint analysis execution script.

[0074] It can be seen from this that before executing the joint analysis model, it is at least necessary to obtain the scripts executed by the p participating parties and the joint analysis execution script first.

[0075] In some embodiments, the server further includes a model editor; before creating a model result table in the resource management platform and p intermediate tables corresponding one by one to the p participating parties, the method further includes:

[0076] Obtaining model information from the model editor, where the model information includes:

[0077] Model setting information, where the model setting information includes a model number;

[0078] p pieces of participating party setting information corresponding one by one to the p participating parties, and the participating party setting information corresponding to each participating party includes: a participating party number and a participating party execution script;

[0079] Joint analysis setting information, where the joint analysis setting information includes the joint analysis execution script;

[0080] The creation of the model result table in the resource management platform and the p intermediate tables corresponding one by one to the p participating parties includes:

[0081] Creating a model result table in the resource management platform and p intermediate tables corresponding one by one to the p participating parties according to the model information;

[0082] Among them, the name of each intermediate table is determined based on the model number and its corresponding participating party number; the name of the model result table is determined based on the model number.

[0083] In this embodiment, the scripts executed by the p participating parties and the joint analysis execution script can be written in the model editor included in the server.

[0084] In an alternative embodiment, the scripts executed by the p participating parties can be written by the corresponding participating parties respectively, and the joint analysis execution script can be written by the target participating party. In another alternative embodiment, each of the above execution scripts can be written by the target participating party.

[0085] In specific implementation, the model number and the numbers of all participating parties can be independently input by each participating party or automatically generated by the model editor. Specifically, it can be determined according to the actual situation, and the embodiments of the present application do not limit this.

[0086] The names of the intermediate tables can be: model_model number_corresponding participating party number. The name of the model result table can be: model_model number_result. Exemplarily, assuming the model number is: 43452352 and the number corresponding to Party A is A, then the name of the intermediate table corresponding to the first participating party can be: model_43452352_A; the name of the model result table can be: model_43452352_result.

[0087] It should be noted that since the participating party execution script is used to obtain specific data from the original table of the corresponding participating party and directly or encrypt and write the obtained specific data into the corresponding intermediate table, it can be understood that the participating party execution script includes: the name of the corresponding participating party, the name of the specific data to be obtained, and the name of the corresponding intermediate table. For example, assuming that it is necessary to find the id of those with an age greater than 20 and a height higher than 170 from Party A and write the id into the intermediate table model_43452352_A after encrypting it through the encryption function AES_ENC and the encryption password secret1234, then the participating party execution script executed by Party A can be: Insert into model_43452352_A Select AES_ENC(id,”secret1234”)as idfrom Awhere A.age>20and A.height>170.

[0088] Since the conjoint analysis execution script is used to obtain data from at least one of the p intermediate tables and write the obtained data into the model result table, it is understandable that the participant execution script includes: the name of the corresponding intermediate table, the name of the data to be obtained, and the name of the model result table. For example, assume that the intermediate table model_43452352_A stores the ids of those with age greater than 20 and height higher than 170, and the intermediate table model_43452352_B stores the ids of those with salary less than 100,000 and gender being male. Additionally, assume that it is required to find the ids of those with age greater than 20, height higher than 170, salary less than 100,000 and gender being male from the intermediate tables model_43452352_A and model_43452352_B and write the ids into the model result table model_43452352_result. Then the model analysis execution script can be: Insert into model_43452352_result Select id from model_43452352_A join model_43452352_B on model_43452352_A.id=model_43452352_B.id.

[0089] In specific implementation, the above-mentioned execution scripts can be input by the target participant or generated from the information input by the target participant. For the latter, the specific description is as follows:

[0090] In some embodiments, the model editor may include: a model setting area, p participant setting areas corresponding to the p participants one by one, and a conjoint analysis setting area;

[0091] Before obtaining the model information from the model editor, the method further includes:

[0092] Display in the model setting area: the model number, and the encryption and decryption information;

[0093] Display in the participant setting area corresponding to each participant: the corresponding participant number, the corresponding participant original script, and the corresponding data to be encrypted;

[0094] Generate the participant execution script corresponding to each participant according to the model number, the participant number corresponding to each participant, the participant original script corresponding to each participant, the data to be encrypted corresponding to each participant, and the encryption and decryption information;

[0095] Display in the conjoint analysis setting area: the conjoint analysis original script input by the target participant, where the target participant is the participant who initiates the conjoint analysis among the p participants;

[0096] Generate the joint analysis execution script according to the model number and the joint analysis original script, and display the joint analysis execution script in the joint analysis setting area.

[0097] In specific implementation, the encryption and decryption information includes an encryption and decryption function and an encryption and decryption password. It can be understood that the encryption function and the decryption function match. For example, when the encryption function is AES_ENC, the decryption function can be AES_DEC. In addition, the encryption password and the decryption password are the same. In practical applications, the encryption and decryption information can be input by the target participating party or default set by the model editor.

[0098] The participating party numbers corresponding to each participating party can be input by the target participating party or automatically generated by the model editor. The original scripts of each participating party and the data to be encrypted can be input by the target participating party or input by their respective corresponding participating parties. The participating party execution scripts corresponding to each participating party can be generated from the corresponding original scripts of the participating parties. After generating the participating party execution scripts corresponding to each participating party, the corresponding participating party execution scripts can be displayed in the participating party setting areas corresponding to each participating party to facilitate the user to determine whether they are the expected participating party execution scripts, thereby improving the reliability of the joint analysis.

[0099] The joint analysis original script can be input by the target participating party, and the joint analysis execution script can be generated based on the joint analysis original script. After generating the joint analysis original script, the joint analysis execution script can be displayed in the joint analysis setting area to facilitate the user to determine whether it is the expected joint analysis execution script, thereby improving the reliability of the joint analysis.

[0100] In an alternative implementation manner, the generating of the participating party execution scripts corresponding to each participating party according to the model number, the participating party numbers corresponding to each participating party, the original scripts of each participating party, the data to be encrypted corresponding to each participating party, and the encryption and decryption information may include:

[0101] Generate a first name according to the model number and the participating party number corresponding to the first participating party, where the first name is the name of the intermediate table corresponding to the first participating party, and the first participating party is any one of the p participating parties;

[0102] Generate a first field according to the encryption and decryption information and the fields to be encrypted corresponding to the first participating party;

[0103] Rewrite the original script of the first participating party corresponding to the first participating party according to the first rule to obtain the execution script of the first participating party corresponding to the first participating party;

[0104] Among them, the first rule is: replace the fields to be encrypted in the original script of the first participant with the first field, and add a second field to the original script of the first participant, where the second field is used to represent that the script execution result is input into the table corresponding to the first name.

[0105] In specific implementation, the first field can be generated based on the encryption function and encryption password in the encryption and decryption information. For example: the first field can be encryption function(to-be-encrypted field, encryption password). Exemplarily: assume that the encryption and decryption information includes the encryption function AES_ENC, the encryption and decryption password secret1234, and the to-be-encrypted field is id, then the first field can be: AES_ENC(id, "secret1234").

[0106] The second field can be: Insert into first name. The second field can be located before the first field or at the end of the original script of the first participant, which can be determined according to actual needs, and this application embodiment does not make any limitation on this.

[0107] Exemplarily, assume that the original script of the first participant is: Select id from A where A.age>20 and A.height>170. The first name is model_43452352_A. Then, rewrite the original script of the first participant, and the obtained execution script of the first participant is: Insert into model_43452352_A Select AES_ENC(id, "secret1234") as id from A where A.age>20 and A.height>170. In this case, the second field is shown as: Insert into model_43452352_A.

[0108] Through the above method, the model editor can autonomously generate the execution script of the participant, which can improve the reliability of the execution script and reduce the user operation requirements.

[0109] In an alternative embodiment, the generating the joint analysis execution script according to the model number and the joint analysis original script may include:

[0110] Generate a second name according to the model number, where the second name is the name of the model result table;

[0111] Rewrite the joint analysis original script according to the second rule to obtain the joint analysis execution script;

[0112] Among them, the second rule includes adding a third field to the original script of the joint analysis, and the third field is used to represent inputting the script execution result into the table corresponding to the second name.

[0113] The third field may be: Insert into the second name. The third field may be located at the beginning or the end of the original script of the joint analysis, and it can be determined according to actual needs specifically. The embodiments of the present application do not limit this.

[0114] Exemplarily, assume that the original script of the joint analysis is: select id from model_43452352_A join model_43452352_B on model_43452352_A.id = model_43452352_B.id. Then, the automatically generated execution script of the joint analysis may be: Insert into model_43452352_result select id from model_43452352_A join model_43452352_B on model_43452352_A.id = model_43452352_B.id.

[0115] For the convenience of understanding the model editor, reference can be made to Figure 2 . In Figure 2 , the p parties include Party A and Party B. The model editor includes: a model setting area; a party setting area corresponding to Party A; a party setting area corresponding to Party B; a joint analysis setting area.

[0116] It should be noted that each of the p parties can obtain the data used by the joint analysis model and the corresponding party execution script of itself by viewing the model editor, so as to execute the corresponding party execution script and realize the joint analysis of the data.

[0117] In the embodiments of the present application, after executing the joint analysis model and obtaining the joint analysis result, each party can read the joint analysis result in the model result table. Specifically, when implemented, each party can execute the corresponding data reading execution script, read the data from the model result table, and directly or decrypt and input the read data into the party result table corresponding to each party.

[0118] Assume that the name of the participant result table corresponding to each participant is: participant number _result, the decryption function is AES_DEC, the decryption secret is secret1234, the data to be decrypted is id, and the name of the model result table is: model_43452352_result. Then, the data reading execution script corresponding to each participant is: Insert into participant number _result select AES_DEC(id, “secret1234”) from model_43452352_result.

[0119] The data reading execution script corresponding to each participant can be written by each participant or uniformly written by the target participant, which can be determined according to the actual situation. This application embodiment does not make a limitation on this.

[0120] In addition, after executing the joint analysis model and obtaining the joint analysis result, the server can audit the joint analysis result for each participant to decide whether to continue to execute joint modeling based on the joint analysis audit result.

[0121] In some embodiments, after writing the execution result of the joint analysis execution script into the model result table, the method may further include:

[0122] Generating a joint model audit result according to the feature information of the model result table;

[0123] Displaying the joint model audit result on the target page;

[0124] Wherein, the feature information includes at least one of the following: the total number of data included in the model result table, the intermediate tables associated with each data in the model result table, and the number of times each data in the model result table is read.

[0125] The generation of the joint model audit result can be executed by the resource management platform or implemented by other devices of the server. The joint model audit result may include one of the following:

[0126] The total number of data included in the model result table;

[0127] The contribution degree corresponding to each participant;

[0128] The acquisition degree corresponding to each participant.

[0129] Specifically, when implemented, the contribution degree corresponding to each participant can be: the ratio of the number of data from the intermediate table corresponding to each participant to the total number of data included in the model result table.

[0130] The acquisition degrees corresponding to the respective participating parties may be: the number of times each participating party reads the data in the model result table. Further, it may further include the amount of data read each time.

[0131] After generating the combined model audit result, the combined model audit result may be displayed on a target page. The target page may be a page accessible to all of the p participating parties. Further, the read permission for the target page may be authorized only to the p participating parties to further improve the security of the combined analysis. In an alternative implementation, the target page may be a page of the model editor, but is not limited thereto.

[0132] In this way, each participating party may, by accessing the target page, determine whether the preset combined analysis expected result of its own is achieved based on the combined model audit result. When it is determined that the combined analysis does not bring the expected result, the participating party may choose to close the granted combined analysis permission, thereby improving the flexibility of the combined analysis.

[0133] In some embodiments, the method may further include:

[0134] Receiving an indication message sent by a second participating party, the indication message being used to indicate closing the combined analysis permission;

[0135] Closing the read permission for the model result table;

[0136] When the closing duration of the read permission for the model result table reaches a first duration, deleting the model result table.

[0137] In specific implementation, when receiving the indication message, it indicates that the second participating party determines that the combined analysis does not reach the preset combined analysis expected result of the second participating party, and the second participating party does not expect to continue the combined analysis. Therefore, the server may close the read permission for the model result table to improve the security of the data of the second participating party.

[0138] When it is detected that the closing duration of the read permission for the model result table reaches the first duration, the model result table may be deleted. Further, the p intermediate tables, and even the written combined analysis model, may be deleted to improve the security of the data of each participating party.

[0139] In practical applications, the first duration may be preset or indicated by the second participating party that sends the indication message, and may be specifically determined according to actual requirements. The embodiments of the present application do not make any limitations thereto.

[0140] In addition, the embodiments of the present application do not limit the timing of closing the joint analysis permission. That is, when receiving the indication information from any participating party at any time point, the joint analysis permission can be closed. For example, in one implementation, the reception of the above indication information can occur after the server displays the audit result of the joint model on the target page. That is, the participating party can decide whether to close the joint analysis permission based on the audit result of the joint analysis. In another implementation, the reception of the above indication information can occur during the execution of the joint analysis model.

[0141] See Figure 3 , Figure 3 is the second flowchart of the data processing method provided by the embodiments of the present application. Figure 3 The data processing method shown is executed by the participating party.

[0142] Step 301: When the first participating party authorizes the joint analysis permission for at least one original table, obtain the first participating party execution script corresponding to the first participating party.

[0143] Step 302: Execute the first participating party execution script to obtain the first data.

[0144] Step 303: Send the first data to the server. The first data is written into the first intermediate table of the resource management platform of the server, and the first intermediate table corresponds to the first participating party.

[0145] The resource management platform of the server creates a model result table and p intermediate tables corresponding to the p participating parties one by one. The model result table only authorizes the read permission to the p participating parties, and each intermediate table only authorizes the write permission to its corresponding participating party, where p is an integer greater than 1. The first participating party is any one of the p participating parties, and the first intermediate table is the intermediate table corresponding to the first participating party among the p intermediate tables.

[0146] The first participating party sends the first data to the server, so that the server writes the first data into the first intermediate table, and then enables the server to execute the joint analysis execution script in the resource management platform after each participating party executes the corresponding participating party execution script, and obtain data from at least one intermediate table, so as to realize the joint analysis of the data of each participating party.

[0147] In the data processing method of this embodiment, after authorizing the joint analysis permission, the participating party can obtain and execute its corresponding participating party execution script, extract specific data from its own original table, and directly or encrypt the specific data and write it into the corresponding intermediate table of the resource management platform of the server. In this way, the joint analysis of the data can be realized by executing the joint analysis execution script in the resource management platform.

[0148] In some embodiments, when the first participating party is the target participating party, where the target participating party is the participating party that initiates the joint analysis among p participating parties and p is an integer greater than 1, before obtaining the first participating party execution script corresponding to the first participating party, the method further includes:

[0149] Sending a first request to at least one participating party respectively, where the first request is used to request the joint analysis permission for at least one original table;

[0150] Receiving first replies sent by the at least one participating party respectively, where the first replies are used to indicate whether the first request is passed;

[0151] The obtaining of the first participating party execution script corresponding to the first participating party includes:

[0152] When it is determined based on the first reply that the p participating parties respectively authorize the joint analysis permission for at least one original table, obtaining the first participating party execution script corresponding to the first participating party.

[0153] In some embodiments, when the first participating party is not the target participating party, where the target participating party is the participating party that initiates the joint analysis among p participating parties and p is an integer greater than 1, before obtaining the first participating party execution script corresponding to the first participating party, the method further includes:

[0154] Receiving a first request sent by the target participating party, where the first request is for the joint analysis permission for at least one original table;

[0155] Sending a first reply for indicating that the first request is passed.

[0156] It should be noted that in the embodiments of the present application, the request and reply for the joint analysis permission between participating parties can be implemented through the server or through direct communication between participating parties, which can be determined according to the actual situation, and the embodiments of the present application do not make any limitations thereto.

[0157] In some embodiments, when the first participating party is the target participating party, where the target participating party is the participating party that initiates the joint analysis among p participating parties and p is an integer greater than 1, before obtaining the first participating party execution script corresponding to the first participating party, the method further includes:

[0158] Accessing the model editor of the server, where the model editor includes: a model setting area, p participating party setting areas corresponding to the p participating parties one by one, and a joint analysis setting area;

[0159] Inputting target information in the model editor;

[0160] Among them, the target information includes:

[0161] The encryption and decryption information input in the model setting area;

[0162] The original script of the corresponding participating party and the data to be encrypted corresponding to each participating party, which are input in the participating party setting area corresponding to each participating party;

[0163] The original script of the joint analysis input in the joint analysis setting area.

[0164] In some embodiments, after sending the first data to the server, the method further includes:

[0165] Execute the first data reading execution script corresponding to the first participating party, and the first data reading execution script is used to read data from the model result table of the server;

[0166] Write the execution result of the first data reading execution script into the participating party result table corresponding to the first participating party.

[0167] In some embodiments, after sending the first data to the server, the method further includes:

[0168] Access the target page, where the target page includes the joint model audit result, and the joint model audit result is generated based on the feature information of the model result table of the server. The feature information includes at least one of the following: the total number of data included in the model result table, the intermediate tables associated with each data in the model result table, and the number of times each data in the model result table is read;

[0169] Determine whether the preset joint analysis expected result is achieved according to the joint model audit result;

[0170] In the case where the preset joint analysis expected result is not achieved, send an indication message, and the indication message is used to indicate to close the joint analysis permission.

[0171] It should be noted that this embodiment is the embodiment of the participating party corresponding to the above method embodiment. Therefore, the relevant descriptions in the above method embodiment can be referred to, and the same beneficial effects can be achieved. To avoid repeated description, it will not be elaborated here.

[0172] In the embodiments of the present application, the various optional implementation manners introduced can be combined with each other without conflict, or can be implemented separately. The embodiments of the present application do not make limitations in this regard.

[0173] For easy understanding, the examples are described as follows:

[0174] The data processing method provided by this application can perform joint modeling across different businesses based on the existing big data ecosystem, and has the following characteristics:

[0175] 1) There is no need to repeatedly invest in building an independent isolation area, which can maximize the reuse of existing big data systems and save investment.

[0176] 2) It is applicable within the company. While each business line still has full control over its own data, data joint modeling can be carried out between business lines, obtaining a better business model than using their respective data alone, thus promoting the overall development of the company.

[0177] 3) It has little impact on the data analysis process, does not change the operation mode of the existing model, and has low business invasiveness.

[0178] 4) The automated joint modeling process does not require in-depth participation of data engineers. Only the model to be run needs to be written.

[0179] 5) Taking the model as the management unit, the participants can master the data used by the model, the model content, the results of the model, and the benefits brought by the model to each participant, improving the transparency of data usage.

[0180] The data processing architecture of the embodiments of this application is as Figure 4a shown, and the data processing method can be as Figure 4b shown:

[0181] 0. Application for joint analysis permission

[0182] Different from the "read" and "write" permissions on general big data platforms, this application defines a new permission:

[0183] "Joint analysis permission": allowing the receiving party to accept the model submitted by the initiating party (this model only has the permission to read data and no permission to modify data), use the specified data table, and write the model execution results to the neutral area.

[0184] Both parties that need to conduct joint analysis can apply for the "joint analysis" permission for the specified data tables of the other party. After the other party agrees, joint modeling can begin.

[0185] 1. Creation of the neutral area

[0186] The neutral area is a resource and permission management entity in the big data system, such as a project, which includes entities such as the libraries and tables it owns, as well as the permission control settings for accessing these entities. The neutral area is used to store the data processed by all parties in the joint analysis and perform related operations.

[0187] The data in the neutral area is usually encrypted, so the neutral area cannot obtain the original data of each business line.

[0188] Generally, the neutral zone can be set up by departments that have no competition / cooperation relationships with each business line of the company, such as the audit / security / legal departments, to reflect its "neutral" positioning.

[0189] 2. Initiate joint analysis

[0190] In the joint analysis model editor, write the joint analysis model. The model designer performs the writing operation of the model. Other participants cannot edit it but can access it.

[0191] The model editing tool consists of several parts:

[0192] 1) Model settings area:

[0193] Model number: Automatically generated, globally unique, which can be 8 - digit all - numbers or generated by other rules.

[0194] Encryption / decryption UDF functions and encryption keys: Optional; if not set, the data will not be encrypted when entering the neutral zone and will be input by the user or set by default.

[0195] The UDF can be a common encryption function or a user - defined function. Note that the encryption and decryption functions must be paired. The platform can provide some common encryption function pairs, such as AES, DES, etc.

[0196] 2) Participant script editing area: There can be multiple such areas, and the number is the same as the number of participants. Each area contains the following content.

[0197] Participant number: Starting from 1, numbered sequentially;

[0198] Script: Used to write the independent execution script of the participant, and these scripts only use the data of the corresponding participant;

[0199] Fields to be encrypted: When writing the result data to the neutral zone, the fields to be encrypted;

[0200] Note: In the subsequent joint analysis process, this field only serves as a data identification field and does not need to be decrypted during the analysis process.

[0201] Actual execution script: The model editor will automatically generate the actual execution script based on the filled - in script, fields to be encrypted, and encryption functions.

[0202] The method for automatically generating the actual script is as follows:

[0203] 1. Generate relevant information for the intermediate result table to be written to the neutral zone.

[0204] Table name generation rule: model_model number_participant number.

[0205] Table field generation rule: Consistent with the fields selected in the select part of the script.

[0206] 2. Rewrite the script.

[0207] The method is: After encrypting the result of the script according to the fields to be encrypted, input it into the neutral zone to be written into the table. For example: Insert into model_model number_party number select AES_ENC(id, “secret1234”) as id, xxx from table_xxx

[0208] 3) Joint analysis area: There is only one such area, which contains the following:

[0209] Script: Used to write the script executed in the neutral zone, process the data input by each party into the neutral zone. When writing the script, only the neutral zone table to be written generated in 2) is allowed to be read.

[0210] Actual execution script: The script automatically generated to be actually executed in the neutral zone.

[0211] The generation rule is:

[0212] 1. Generate relevant information for the neutral zone table to be written with the model result.

[0213] Table name generation rule: model_model number_result.

[0214] Table field generation rule: Consistent with the fields selected in the select part of the script.

[0215] 2. Rewrite the script.

[0216] The method is: Add an insert part before the script to write the script result into the model result table. For example: Insert into model_model number_result

script

[0217] 3. Model execution

[0218] After the content in the model editor is written completely, it can be executed.

[0219] The process of model execution is:

[0220] 1) Create tables: Submit the intermediate result table and model result table to be created to the neutral zone; the neutral zone creates these tables.

[0221] 2) Authorization: The neutral zone authorizes the “write” permission of the intermediate result table to the corresponding party; the “read” permission of the model result table to all parties.

[0222] 3) Participant Execution: Submit the automatically generated corresponding actual execution scripts to each participant for execution application; each participant executes its own script separately and writes the intermediate results to the neutral zone.

[0223] 4) Neutral Zone Execution: After all participants have executed their scripts, the neutral zone executes the automatically generated joint analysis script and writes the results to the model result table.

[0224] 4. Model Result Retrieval

[0225] Each participant reads the data in the model result table from the neutral zone. It should be noted that if the model is set with an encryption function, the corresponding decryption function should be used to decrypt the encrypted fields when reading the data.

[0226] 5. Model Audit

[0227] Model audit is to enable each participant to clearly understand its own contribution to the model results and the quantity of results obtained, including the following parts:

[0228] 1) Total number of results: The number of data records in the model result table.

[0229] 2) Contribution measurement of each participant: The number of times and the proportion of the data in each intermediate result table in the neutral zone appearing in the result table.

[0230] Participant contribution degree = (Number of results from the participant's intermediate result table) / (Total number of results)

[0231] 3) Acquisition measurement of each participant: The number of times each participant reads the model result table and the number of records read each time.

[0232] Participants can judge whether the joint analysis brings the expected results based on the audit results.

[0233] 6. Joint Analysis Permission Closure

[0234] Based on the model audit results, participants can close the joint analysis permissions granted to other parties at any time. After closing the permissions, the joint analysis model cannot run, and the "read" permissions of the model result table in the neutral zone for all participants are revoked. Participants cannot read the data, and after a period of time (one month or user-defined), this table will be destroyed.

[0235] Actual Execution Example:

[0236] Next, taking the following model as an example, the execution of this application is described:

[0237] Model description: Party A has the age and height characteristics of users, and Party B has the income and gender characteristics. The joint analysis model to be executed is: find users from all users where age > 20, height > 170, income < 100000, and gender is male.

[0238] The corresponding SQL is:

【

[0240] select id from

[0241] Select id from A where A.age>20 and A.height>170 as A

[0242] join

[0243] Select id from B where B.salary<100000 and B.gender=’M’ as B

[0244] On A.id=B.id 】

[0246] Then, in the model editor:

[0247] 1. Model settings area:

[0248] Model number: 43452352.

[0249] Select the encryption function as AES_ENC, the decryption function as AES_DEC, and the password "secret1234".

[0250] 2. Script editing area:

[0251] Party A

[0252] Edit the script:

[0253]

Select id from A where A.age&gt;20 and A.height&gt;170

[0254] Encrypted field:

[0255] Select "id"

[0256] The actual execution script automatically generated is:

[0257]

Insert into model_43452352_A Select AES_ENC(id,”secret1234”) as id from A where A.age&gt;20 and A.height&gt;170

[0258] Party B

[0259] Edit script:

[0260]

Select id from B where B.salary&lt;100000 and B.gender=’M’

[0261] Encrypted field:

[0262] Select “id”

[0263] The automatically generated actual execution script is:

[0264]

Insert into model_43452352_B Select AES_ENC(id,”secret1234”) as id from B where B.salary&lt;100000 and B.gender=’M’

[0265] Conjoint analysis area

[0266] Edit script:

[0267]

select id from model_43452352_A join model_43452352_B on model_43452352_A.id=model_43452352_B.id

[0268] The automatically generated actual execution script is:

[0269]

Insert into model_43452352_result select id from model_43452352_A join model_43452352_B on model_43452352_A.id=model_43452352_B.id

[0270] 3. Model execution

[0271] 1) Create tables

[0272] Create tables model_43452352_A, model_43452352_B, and model_43452352_result in the neutral area. Each table has only one field named “id” with the same type as that of Table A.

[0273] 2) Authorization

[0274] Authorize "write" of model_43452352_A to A;

[0275] Authorize "write" of model_43452352_B to B;

[0276] Authorize "read" of model_43452352_result to A and B.

[0277] 3) The participating parties execute

[0278] A executes

Insert into model_43452352_A Select AES_ENC(id,”secret1234”)asid from A where A.age&gt;20and A.height&gt;170

[0279] B executes

Insert into model_43452352_B Select AES_ENC(id,”secret1234”)asid from B where B.salary&lt;100000and B.gender=’M’

[0280] 4) Joint analysis

[0281] After both A and B have executed, the neutral zone executes

Insert into model_43452352_result select idfrom model_43452352_A join model_43452352_B on model_43452352_A.id=model_43452352_B.id

[0282] 4. Obtain the model result

[0283] After A reads the model result from the neutral zone, write it into its own result table, such as:

[0284] Insert into A_rst select AES_DEC(id,“secret1234”)frommodel_43452352_result

[0285] 5. Model result audit

[0286] Contribution calculation:

[0287] Total amount of data:

[0288]

select count(*)as cnt from model_43452352_result

[0289] Assume it is 10,000 items

[0290] Contribution degree of A:

[0291] Number of items in the model result that appear in the intermediate table of A:

[0292]

select count(id) as cntA from select id from model_43452352_A join model_43452352_result on model_43452352_A.id = model_43452352_result.id

[0293] Assume it is 9,000 items, contribution degree = cntA / cnt = 9,000 / 10,000 = 90%.

[0294] The calculation of the contribution degree of B is similar, and the contribution degree is obtained as 10%.

[0295] Participants obtain metrics:

[0296] B executed the export script to export the model result to its own table:

[0297] Insert into B_rst select AES_DEC(id, “secret1234”) from model_43452352_result.

[0298] The system records the number of exports this time as 10,000 items.

[0299] 6. Close the joint analysis permission

[0300] When A audits the model, it is found that the contribution degree of A is 90% and that of B is 10%. B exported all the model results to itself. A believes that the contribution degrees of both parties in this joint model are disproportionate and of little value to itself, so it closes the joint analysis permission and sets the model result table to be destroyed.

[0301] The embodiments of the present application can enable business lines with competitive relationships to achieve data cooperation between business lines without leaking their respective specific data, improve the overall data utilization level of the company, and promote business development.

[0302] It should be noted that for the data processing method provided by the embodiments of the present application, the execution subject can be a data processing device, or a control module in the data processing device for executing the data processing method. In the embodiments of the present application, taking the data processing device executing the data processing method as an example, the data processing device provided by the embodiments of the present application is described.

[0303] See Figure 5 , Figure 5 which is one of the structure diagrams of the data processing device provided by the embodiments of the present application.

[0304] As Figure 5 shown, the data processing device 500 includes:

[0305] A creation module 501, configured to create a model result table and p intermediate tables corresponding to the p participating parties one by one on the resource management platform when receiving a first input in the case of obtaining the joint analysis permissions of at least one original table authorized by the p participating parties respectively, where the first input is an input triggering joint analysis, the model result table only authorizes read permissions to the p participating parties, and each intermediate table only authorizes write permissions to its corresponding participating party, and p is an integer greater than 1;

[0306] A first writing module 502, configured to write data into the p intermediate tables, where the data written into the intermediate table corresponding to each participating party is: the first data obtained by each participating party by executing the corresponding participating party execution script;

[0307] A second writing module 503, configured to execute a joint analysis execution script on the resource management platform and write the execution result of the joint analysis execution script into the model result table when detecting that each participating party has executed the corresponding participating party execution script.

[0308] Optionally, the server further includes a model editor; the device further includes:

[0309] A first obtaining module, configured to obtain model information from the model editor, where the model information includes:

[0310] Model setting information, where the model setting information includes a model number;

[0311] p pieces of participating party setting information corresponding to the p participating parties one by one, and the participating party setting information corresponding to each participating party includes a corresponding participating party number and a participating party execution script;

[0312] Joint analysis setting information, where the joint analysis setting information includes the joint analysis execution script;

[0313] The creation module is specifically configured to:

[0314] Create a model result table and p intermediate tables corresponding to the p participating parties one by one on the resource management platform according to the model information;

[0315] Among them, the names of the intermediate tables are determined based on the model number and the corresponding participant numbers; the name of the model result table is determined based on the model number.

[0316] Optionally, the model editor includes: a model setting area, p participant setting areas corresponding to the p participants one by one, and a joint analysis setting area;

[0317] The device further includes:

[0318] A first display module, configured to display in the model setting area: the model number and encryption / decryption information;

[0319] A second display module, configured to display in the participant setting area corresponding to each participant: the corresponding participant number, the corresponding original participant script, and the corresponding data to be encrypted;

[0320] A first generation module, configured to generate, according to the model number, the participant numbers corresponding to the participants, the original participant scripts corresponding to the participants, the data to be encrypted corresponding to the participants, and the encryption / decryption information, the participant execution scripts corresponding to the participants;

[0321] A third display module, configured to display in the joint analysis setting area: the original joint analysis script input by the target participant, where the target participant is the participant who initiates the joint analysis among the p participants;

[0322] A second generation module, configured to generate the joint analysis execution script according to the model number and the original joint analysis script, and display the joint analysis execution script in the joint analysis setting area.

[0323] Optionally, the first generation module includes:

[0324] A first generation unit, configured to generate a first name according to the model number and the participant number corresponding to the first participant, where the first name is the name of the intermediate table corresponding to the first participant, and the first participant is any one of the p participants;

[0325] A second generation unit, configured to generate a first field according to the encryption / decryption information and the fields to be encrypted;

[0326] A first rewriting unit, configured to rewrite the original participant script corresponding to the first participant according to a first rule to obtain the participant execution script corresponding to the first participant;

[0327] Among them, the first rule is: replacing the fields to be encrypted in the original script of the first participating party with the first field, and adding a second field to the original script of the first participating party, where the second field is used to represent that the script execution result is input into the table corresponding to the first name.

[0328] Optionally, the second generation module includes:

[0329] A third generation unit, configured to generate a second name according to the model number, where the second name is the name of the model result table;

[0330] A second rewriting unit, configured to rewrite the original joint analysis script according to a second rule to obtain the joint analysis execution script;

[0331] Among them, the second rule includes adding a third field to the original joint analysis script, where the third field is used to represent that the script execution result is input into the table corresponding to the second name.

[0332] Optionally, the device further includes:

[0333] A second generation module, configured to generate a joint model audit result according to the feature information of the model result table;

[0334] A display module, configured to display the joint model audit result on a target page;

[0335] Among them, the feature information includes at least one of the following: the total number of data included in the model result table, the intermediate tables associated with each data in the model result table, and the number of times each data in the model result table is read.

[0336] See Figure 6 , Figure 6 is the second structural diagram of the data processing device provided by the embodiment of the present application.

[0337] As Figure 6 shown, the data processing device 600 includes:

[0338] A second acquisition module 601, configured to acquire the execution script of the first participating party corresponding to the first participating party when the first participating party authorizes the joint analysis permission of at least one original table;

[0339] A first execution module 602, configured to execute the execution script of the first participating party to obtain first data;

[0340] A first sending module 603, configured to send the first data to a server, where the first data is written into a first intermediate table of the resource management platform of the server, and the first intermediate table corresponds to the first participating party.

[0341] Optionally, when the first participating party is the target participating party, where the target participating party is the participating party that initiates the joint analysis among p participating parties, and p is an integer greater than 1, the apparatus further includes:

[0342] A second sending module, configured to separately send a first request to at least one participating party, where the first request is used to request the joint analysis permission of at least one original table;

[0343] A second receiving module, configured to receive first replies separately sent by the at least one participating party, where the first replies are used to indicate whether the first request is passed;

[0344] The second obtaining module is specifically configured to:

[0345] When it is determined based on the first reply that the p participating parties respectively authorize the joint analysis permission of at least one original table, obtain the first participating party execution script corresponding to the first participating party.

[0346] Optionally, when the first participating party is not the target participating party, where the target participating party is the participating party that initiates the joint analysis among p participating parties, and p is an integer greater than 1, the apparatus further includes:

[0347] A third receiving module, configured to receive a first request sent by the target participating party, where the first request is for the joint analysis permission of at least one original table;

[0348] A third sending module, configured to send a first reply indicating that the first request is passed.

[0349] Optionally, when the first participating party is the target participating party, where the target participating party is the participating party that initiates the joint analysis among p participating parties, and p is an integer greater than 1, the apparatus further includes:

[0350] A first access module, configured to access a model editor of the server, where the model editor includes: a model setting area, p participating party setting areas corresponding to the p participating parties one by one, and a joint analysis setting area;

[0351] An input module, configured to input target information in the model editor;

[0352] Wherein, the target information includes:

[0353] Encryption and decryption information input in the model setting area;

[0354] Input in the participating party setting area corresponding to each participating party: the corresponding participating party original script and the corresponding data to be encrypted;

[0355] Entered in the conjoint analysis setting area: the conjoint analysis original script.

[0356] Optionally, the device further includes:

[0357] A second execution module, configured to:

[0358] Execute the first data reading execution script corresponding to the first participant, where the first data reading execution script is used to read data from the model result table of the server;

[0359] Write the execution result of the first data reading execution script into the participant result table corresponding to the first participant.

[0360] Optionally, the device further includes:

[0361] A second access module, configured to access a target page, where the target page includes a conjoint model audit result, and the conjoint model audit result is generated based on the feature information of the model result table, and the feature information includes at least one of the following: the total number of data included in the model result table, the intermediate tables associated with each data in the model result table, and the number of times each data in the model result table is read;

[0362] A determination module, configured to determine whether a preset conjoint analysis expected result is achieved according to the conjoint model audit result;

[0363] A fourth sending module, configured to send an indication message for indicating to close the conjoint analysis permission when the preset conjoint analysis expected result is not achieved.

[0364] The data processing device in the embodiments of the present application may be a device with an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiments of the present application.

[0365] The data processing device 500 provided in the embodiments of the present application can implement Figure 1 each process implemented by the data processing device in the method embodiment, and the data processing device 600 can implement Figure 3 each process implemented by the data processing device in the method embodiment. To avoid repetition, details are not described here again.

[0366] Optionally, as Figure 7 shown, the embodiments of the present application further provide a communication device 700, including a processor 701, a memory 702, a program or instruction stored on the memory 702 and executable on the processor 701, and when the program or instruction is executed by the processor 701, it implements the above Figure 1 or Figure 3The various processes of the method embodiments can achieve the same technical effects. To avoid repetition, they will not be elaborated here.

[0367] The embodiments of the present application further provide a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above data processing method embodiments are implemented, and the same technical effects can be achieved. To avoid repetition, they will not be elaborated here.

[0368] Among them, the processor is the processor in the communication device described in the above embodiments. The readable storage medium includes a computer-readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc, etc.

[0369] The embodiments of the present application further provide a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to execute a program or instruction to implement the various processes of the above data processing method embodiments, and the same technical effects can be achieved. To avoid repetition, they will not be elaborated.

[0370] It should be understood that the chip mentioned in the embodiments of the present application may also be referred to as a system-on-chip, a system chip, a chip system, or a system-on-chip, etc.

[0371] It should be noted that in this article, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including that element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in a reverse order according to the functions involved. For example, the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0372] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described example methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions for causing a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present application.

[0373] The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above specific implementation manners. The above specific implementation manners are merely illustrative rather than restrictive. Under the inspiration of the present application, those of ordinary skill in the art can also make many forms without departing from the purpose of the present application and the scope protected by the claims, and all of them belong to the protection scope of the present application.

Claims

1. A data processing method, executed by a server, characterized in that, The server is provided with a resource management platform; the method includes: When the joint analysis permissions of at least one original table are authorized by p participants respectively, if a first input is received, create a model result table and p intermediate tables corresponding to the p participants one by one in the resource management platform, where the first input is an input triggering joint analysis, the model result table only authorizes read permissions to the p participants, and each intermediate table only authorizes write permissions to its corresponding participant, and p is an integer greater than 1; Write data into the p intermediate tables, where the data written into the intermediate table corresponding to each participant is: the first data obtained by each participant by executing the corresponding participant execution script; When it is detected that each participant has executed the corresponding participant execution script, execute the joint analysis execution script in the resource management platform, and write the execution result of the joint analysis execution script into the model result table, where the joint analysis execution script is used to: obtain data from at least one of the p intermediate tables and write the obtained data into the model result table.

2. The method according to claim 1, characterized in that, The server further includes a model editor; before creating the model result table and p intermediate tables corresponding to the p participants one by one in the resource management platform, the method further includes: Obtain model information from the model editor, and the model information includes: Model setting information, and the model setting information includes a model number; p participant setting information corresponding to the p participants one by one, and the participant setting information corresponding to each participant includes: a participant number and a participant execution script; Joint analysis setting information, and the joint analysis setting information includes the joint analysis execution script; The creating the model result table and p intermediate tables corresponding to the p participants one by one in the resource management platform includes: Create a model result table and p intermediate tables corresponding to the p participants one by one in the resource management platform according to the model information; Among them, the name of each intermediate table is determined based on the model number and its corresponding participant number; the name of the model result table is determined based on the model number.

3. The method according to claim 2, characterized in that, The model editor includes: a model setting area, p participant setting areas corresponding to the p participants one by one, and a joint analysis setting area; Before obtaining the model information from the model editor, the method further includes: Display in the model setting area: the model number and encryption and decryption information; Display in the participant setting area corresponding to each participant: the corresponding participant number, the corresponding participant original script, and the corresponding data to be encrypted; Generate the participant execution script corresponding to each participant according to the model number, the participant number corresponding to each participant, the participant original script corresponding to each participant, the data to be encrypted corresponding to each participant, and the encryption and decryption information; Display in the joint analysis setting area: the joint analysis original script input by the target participant, and the target participant is the participant who initiates the joint analysis among the p participants; Generate the joint analysis execution script according to the model number and the original joint analysis script.

4. The method according to claim 3, characterized in that, Generating the execution script for each participating party according to the model number, the participating party number corresponding to each participating party, the original script of each participating party, the data to be encrypted corresponding to each participating party, and the encryption and decryption information includes: Generate a first name according to the model number and the participating party number corresponding to the first participating party, where the first name is the name of the intermediate table corresponding to the first participating party, and the first participating party is any one of the p participating parties; Generate a first field according to the encryption and decryption information and the fields to be encrypted corresponding to the first participating party; Rewrite the original script of the first participating party corresponding to the first participating party according to the first rule to obtain the execution script of the first participating party corresponding to the first participating party; Wherein, the first rule is: replace the fields to be encrypted in the original script of the first participating party with the first field, and add a second field to the original script of the first participating party, where the second field is used to represent inputting the script execution result into the table corresponding to the first name.

5. The method according to claim 3, characterized in that, The generating the joint analysis execution script according to the model number and the original joint analysis script includes: Generate a second name according to the model number, where the second name is the name of the model result table; Rewrite the original joint analysis script according to the second rule to obtain the joint analysis execution script; Wherein, the second rule includes adding a third field to the original joint analysis script, and the third field is used to represent inputting the script execution result into the table corresponding to the second name.

6. The method according to claim 1, characterized in that, After writing the execution result of the joint analysis execution script into the model result table, the method further includes: Generate an audit result of the joint model according to the characteristic information of the model result table; Display the audit result of the joint model on the target page; Wherein, the characteristic information includes at least one of the following: the total number of data included in the model result table, the intermediate tables associated with each data in the model result table, and the number of times each data in the model result table is read.

7. A data processing method, executed by a first participant, characterized in that, The method includes: When the first participating party authorizes the joint analysis permission of at least one original table, obtain the execution script of the first participating party corresponding to the first participating party; Execute the execution script of the first participating party to obtain first data; Send the first data to the server, and the first data is written into the first intermediate table of the resource management platform of the server, and the first intermediate table corresponds to the first participating party.

8. The method according to claim 7, wherein When the first participating party is the target participating party, and the target participating party is the participating party that initiates the joint analysis among the p participating parties, and p is an integer greater than 1, before obtaining the execution script of the first participating party corresponding to the first participating party, the method further includes: Send a first request to at least one participating party respectively, where the first request is used to request the joint analysis permission of at least one original table; Receive the first replies sent by the at least one participating party respectively, where the first reply is used to indicate whether the first request is passed; The obtaining of the first participant execution script corresponding to the first participant includes: When it is determined based on the first reply that each of the p participants authorizes the joint analysis permission for at least one original table, obtaining the first participant execution script corresponding to the first participant.

9. The method according to claim 7, wherein When the first participant is not the target participant, where the target participant is the participant who initiates the joint analysis among the p participants and p is an integer greater than 1, before obtaining the first participant execution script corresponding to the first participant, the method further includes: Receiving a first request sent by the target participant, where the first request is for the joint analysis permission for at least one original table; Sending a first reply for indicating approval of the first request.

10. The method according to claim 7, wherein When the first participant is the target participant, where the target participant is the participant who initiates the joint analysis among the p participants and p is an integer greater than 1, before obtaining the first participant execution script corresponding to the first participant, the method further includes: Accessing the model editor of the server, where the model editor includes: a model setting area, p participant setting areas corresponding to the p participants one by one, and a joint analysis setting area; Inputting target information in the model editor; Wherein, the target information includes: Encryption and decryption information input in the model setting area; Input in the participant setting area corresponding to each participant: the corresponding participant original script, and the corresponding data to be encrypted; Input in the joint analysis setting area: the joint analysis original script.

11. The method according to claim 7, wherein After sending the first data to the server, the method further includes: Executing the first data reading execution script corresponding to the first participant, where the first data reading execution script is used to read data from the model result table of the server; Writing the execution result of the first data reading execution script into the participant result table corresponding to the first participant.

12. The method according to claim 7, wherein After sending the first data to the server, the method further includes: Accessing a target page, where the target page includes a joint model audit result, and the joint model audit result is generated based on the feature information of the model result table of the server, and the feature information includes at least one of the following: the total number of data included in the model result table, the intermediate tables associated with each data in the model result table, and the number of times each data in the model result table is read; Determining whether the preset joint analysis expected result is achieved according to the joint model audit result; When the preset joint analysis expected result is not achieved, sending an indication information, where the indication information is used to indicate closing the joint analysis permission.

13. A data processing device, applied to a server, wherein The server includes a resource management platform; the device includes: A creation module, configured to, when the joint analysis permissions of at least one original table are authorized by p participants respectively, create a model result table and p intermediate tables corresponding to the p participants one by one in the resource management platform if a first input is received, where the first input is an input triggering the joint analysis, the model result table only authorizes read permissions to the p participants, and each intermediate table only authorizes write permissions to its corresponding participant, and p is an integer greater than 1; A first writing module, configured to write data into the p intermediate tables, where the data written into the intermediate table corresponding to each participant is: the first data obtained by each participant by executing the corresponding participant execution script; A second writing module, configured to, when it is detected that each participant has executed the corresponding participant execution script, execute a joint analysis execution script in the resource management platform and write the execution result of the joint analysis execution script into the model result table, where the joint analysis execution script is used to: obtain data from at least one of the p intermediate tables and write the obtained data into the model result table.

14. A data processing device, applied to a first party, wherein Comprising: A second obtaining module, configured to obtain the first participant execution script corresponding to the first participant when the first participant authorizes the joint analysis permissions of at least one original table; A first execution module, configured to execute the first participant execution script to obtain first data; A first sending module, configured to send the first data to a server, and the first data is written into a first intermediate table in the resource management platform of the server, and the first intermediate table corresponds to the first participant.

15. A communication device, characterized in that, Comprising a processor, a memory, and a program or instruction stored on the memory and executable on the processor, where when the program or instruction is executed by the processor, the steps of the data processing method according to any one of claims 1 to 6 are implemented; Or, the steps of the data processing method according to any one of claims 7 to 12.

16. A readable storage medium, characterized in that, A program or instruction is stored on the readable storage medium, and when the program or instruction is executed by a processor, the steps of the data processing method according to any one of claims 1 to 6 are implemented; Or, the steps of the data processing method according to any one of claims 7 to 12.

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