Data structure-based data screening method, device, electronic equipment, and medium

Abstract

The present invention relates to the field of data analysis technology, and discloses a data screening method based on data structure, comprising: obtaining a plurality of pre-stored data storage tables, and obtaining the data type of the data in each data storage table; adding a fixed identifier to each data field in each data storage table according to the data type, to obtain a plurality of identifier storage tables; decoupling each identifier storage table through a preset data self-checking system, to obtain a plurality of decoupled data tables; receiving a data screening instruction, and performing a data compliance check on the data in each decoupled data table according to the data screening instruction. The present invention also proposes a data screening device, equipment, and storage medium based on a data structure. The present invention also relates to blockchain technology, and the fixed identifier can be stored in a blockchain node. The present invention can improve the accuracy of data screening.

Description

Technical Field

[0001] The present invention relates to the field of data analysis technology, and in particular to a data structure-based data screening method, device, electronic device and computer-readable storage medium. Background Art

[0002] With the development of network technology, data acquisition has become increasingly convenient, providing a breeding ground for criminals to obtain users' private data. Therefore, advanced countries have also attached increasing importance to data privacy security. Therefore, it has become a problem to safely store data according to legal requirements or company business development needs.

[0003] Existing data security storage systems often check whether the data is compliant before it is stored in the database. How to check the compliance of data that has already been stored in the database has become a difficult problem that needs to be solved urgently. Summary of the Invention

[0004] The present invention provides a data structure-based data screening method, device, electronic device and computer-readable storage medium, the main purpose of which is to improve the accuracy of data screening.

[0005] To achieve the above objectives, the present invention provides a data structure-based data screening method, comprising:

[0006] Acquire a plurality of pre-stored data storage tables, and acquire the data type of the data in each of the data storage tables;

[0007] Adding a fixed identifier to each data field in each data storage table according to the data type to obtain multiple identifier storage tables;

[0008] Decoupling each of the identification storage tables through a preset data self-checking system to obtain multiple decoupled data tables;

[0009] A data check instruction is received, and data compliance check is performed on the data in each of the decoupled data tables according to the data check instruction.

[0010] Optionally, performing data compliance checking on the data in each of the decoupled data tables according to the data checking instruction includes:

[0011] Establishing a troubleshooting task for checking the decoupled data table based on the data troubleshooting instruction;

[0012] Obtaining the scheduling node for data screening in each of the decoupled data tables;

[0013] In the scheduling node, data compliance checking is performed on the data in each of the decoupled data tables based on the checking task.

[0014] Optionally, obtaining the data type of the data in each data storage table includes:

[0015] Obtain the data to be checked in each of the data storage tables;

[0016] A preset data query table is obtained, and the data query table is searched according to the data to be checked in each data storage table to obtain the data type of the data to be checked.

[0017] Optionally, querying the data query table according to the data to be checked in each of the data storage tables to obtain the data type of the data to be checked includes:

[0018] Convert the data to be checked in each data storage table into text to obtain text data to be checked;

[0019] Acquire all corresponding data in the data query table, and convert all the corresponding data into text to obtain a plurality of corresponding text data;

[0020] The text data to be checked is compared with a plurality of corresponding text data, and the corresponding text data corresponding to the text data to be checked is found, thereby obtaining the data type of the data in the data storage table.

[0021] Optionally, before obtaining the plurality of pre-stored data storage tables, the method further includes:

[0022] Obtaining preset stored data and the encryption type of the stored data;

[0023] selecting a data encryption method for different types of stored data according to the encryption type of the stored data;

[0024] The stored data is encrypted according to the data encryption method to obtain the data to be checked, and the data to be checked is stored in a preset storage repository to obtain a database storing the data to be checked.

[0025] Optionally, the step of adding a fixed identifier to each data field in each data storage table according to the data type to obtain multiple identifier storage tables includes:

[0026] Using the encryption method as a fixed identifier for a data field in the data storage table;

[0027] According to the data type, a corresponding fixed identifier is added to each data field in each data storage table to construct an identifier storage table.

[0028] Optionally, the identification storage tables are decoupled by a preset data self-checking system to obtain a plurality of decoupled data tables, including:

[0029] Obtaining primary key data from each of the identification storage tables;

[0030] Extracting primary key data and primary key relationship data tables from each identification storage table;

[0031] The primary key data in each identification storage table is removed to obtain a plurality of decoupled data tables.

[0032] In order to solve the above problems, the present invention further provides a data structure-based data screening device, the device comprising:

[0033] A data table acquisition module is used to acquire a plurality of pre-stored data storage tables and obtain the data type of the data in each of the data storage tables;

[0034] An identification table construction module is used to add a fixed identification to each data field in each data storage table according to the data type, so as to obtain multiple identification storage tables;

[0035] An identification table decoupling module is used to decouple each of the identification storage tables through a preset data self-checking system to obtain multiple decoupled data tables;

[0036] The data checking module is used to receive data checking instructions and perform data compliance checking on the data in each of the decoupled data tables according to the data checking instructions.

[0037] In order to solve the above problem, the present invention further provides an electronic device, comprising:

[0038] at least one processor; and,

[0039] a memory communicatively connected to the at least one processor; wherein,

[0040] The memory stores a computer program that can be executed by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the data structure-based data screening method as described above.

[0041] In order to solve the above problems, the present invention also provides a computer-readable storage medium, including a data storage area and a program storage area, the data storage area stores created data, and the program storage area stores a computer program; wherein, when the computer program is executed by a processor, the data structure-based data screening method as described above is implemented.

[0042] In an embodiment of the present invention, multiple pre-stored data storage tables and the data types of the data in the data storage tables are obtained, and fixed identifiers are added to each data field in the data storage table according to the data type of the data to obtain multiple identifier storage tables, thereby distinguishing each field in the data storage table. Thereafter, the identifier storage table is decoupled through a preset data self-inspection system to obtain multiple decoupled data tables, and finally, a data check instruction is accepted, and data compliance check is performed on the data in the decoupled data table according to the data check instruction. By adding identifiers to the fields in the data storage table, each field is clearly distinguished, thereby improving the accuracy of the data compliance check. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A flowchart of a data structure-based data screening method provided by one embodiment of the present invention;

[0044] Figure 2 A schematic diagram of a module of a data structure-based data screening device provided by an embodiment of the present invention;

[0045] Figure 3 A schematic diagram of the internal structure of an electronic device for implementing a data structure-based data screening method provided by an embodiment of the present invention;

[0046] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0047] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0048] The embodiment of the present application provides a data screening method based on a data structure. The execution subject of the data screening method based on the data structure includes but is not limited to at least one of the electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. Among them, the server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms. In other words, the data screening method based on the data structure can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0049] Reference Figure 1FIG. 1 is a flow chart of a data structure-based data screening method according to an embodiment of the present invention. In this embodiment, the data structure-based data screening method includes:

[0050] S1. Acquire multiple pre-stored data storage tables, and acquire the data type of the data in each of the data storage tables.

[0051] In an embodiment of the present invention, the data storage table is a table in a preset database that stores the data to be checked, that is, the data to be checked is stored in the database in the form of a data table, wherein the database is the database to be checked, and the data stored in the database is the data to be checked.

[0052] In the embodiment of the present invention, the data to be checked is data in the database that needs to be checked, and data compliance can be achieved by checking the data to be checked.

[0053] For example, XXX Company needs to store user identity information data. Before storing the user identity information data in the company's database, checking the user identity information data can avoid storing data involving user privacy in the company's database, thereby causing legal violations.

[0054] Furthermore, the data type is a specific data type in the data storage table, and the data in the data storage table is distinguished by obtaining the data type.

[0055] In the embodiment of the present invention, obtaining the data type of the data in each data storage table includes:

[0056] Obtain the data to be checked in each of the data storage tables;

[0057] A preset data query table is obtained, and the data query table is searched according to the data to be checked in each data storage table to obtain the data type of the data to be checked.

[0058] In an embodiment of the present invention, the data query table has only two columns of data, one column of data is a primary key, storing the corresponding data of the data to be checked, and the other column of data is the data type of the corresponding data. The corresponding data can be the same data as the data to be checked.

[0059] Furthermore, the primary key is a unique identifier of the data query table, which is used to ensure the uniqueness of the corresponding data in the data query table and avoid different data types for the same data to be checked, resulting in data type acquisition errors.

[0060] Furthermore, querying the data query table according to the data to be checked in each of the data storage tables to obtain the data type of the data to be checked includes:

[0061] Convert the data to be checked in each data storage table into text to obtain text data to be checked;

[0062] Acquire all corresponding data in the data query table, and convert all the corresponding data into text to obtain a plurality of corresponding text data;

[0063] The text data to be checked is compared with a plurality of corresponding text data, and the corresponding text data corresponding to the text data to be checked is found, thereby obtaining the data type of the data in the data storage table.

[0064] In an embodiment of the present invention, the text data to be checked and the plurality of corresponding text data may be compared based on a text similarity algorithm. Specifically, the text similarity algorithm may be a string-based text similarity algorithm that compares the number of identical characters between the text data to be checked and each of the corresponding text data to determine the similarity between the text data to be checked and each of the corresponding text data.

[0065] In the embodiment of the present invention, before obtaining the plurality of pre-stored data storage tables, the method further includes:

[0066] Obtaining preset stored data and the encryption type of the stored data;

[0067] selecting a data encryption method for different types of stored data according to the encryption type of the stored data;

[0068] The stored data is encrypted according to the data encryption method to obtain the data to be checked, and the data to be checked is stored in a preset storage repository to obtain a database storing the data to be checked.

[0069] In the embodiment of the present invention, the preset storage data may be unprocessed user identity information data obtained from the user.

[0070] S2. Add a fixed identifier to each data field in each data storage table according to the data type to obtain multiple identifier storage tables.

[0071] In an embodiment of the present invention, the fixed identifier is a specific encrypted identifier, and the data to be checked in the data storage table can be distinguished and identified by the fixed identifier. After the data is sorted (for example, stored in other storage tables), the data to be checked can still be distinguished according to the fixed identifier.

[0072] In the embodiment of the present invention, the identification storage table is a storage table that adds a fixed identification to each data field according to the data type.

[0073] Furthermore, a fixed identifier is added to each data field in each data storage table according to the data type to obtain multiple identifier storage tables, including:

[0074] Using the encryption method as a fixed identifier for a data field in the data storage table;

[0075] According to the data type, a corresponding fixed identifier is added to each data field in each data storage table to construct an identifier storage table.

[0076] Furthermore, the encryption method is a symmetric encryption method, and the data in the identification storage table can be decrypted according to the decryption method corresponding to the encryption method, which can avoid the business code level from directly viewing the data in the identification storage table. The encryption method can be Aes encryption method, Sm4 encryption method, Md5 encryption method, etc.

[0077] In the embodiment of the present invention, the fixed identifier corresponding to each data field is the encryption method used when storing data in the data storage table.

[0078] For example, if the data storage table stores id name (name), pwd (password), and username (username), then the fixed identifier Sm4 will be used for the id name field, the fixed identifier Aes will be used for the pwd field, and the fixed identifier Md5 will be used for the username field.

[0079] S3. Decoupling each of the identification storage tables through a preset data self-checking system to obtain multiple decoupled data tables.

[0080] In an embodiment of the present invention, the data check instruction is an instruction for checking whether the data in the decoupled data table is compliant. The data check instruction can be an instruction for checking whether the data is compliant based on legal content, or it can be an instruction for checking data that does not meet business needs based on the company's business needs.

[0081] In an embodiment of the present invention, the data self-inspection system is a system that is independent of the business code and is used to check whether the data meets the requirements. The data self-inspection system can be used to view data and decouple the identification storage table. The data self-inspection system contains a visual configuration page for displaying the data.

[0082] In the embodiment of the present invention, the identification storage tables are decoupled by a preset data self-checking system to obtain a plurality of decoupled data tables, including:

[0083] Obtaining primary key data from each of the identification storage tables;

[0084] Extracting primary key data and primary key relationship data tables from each identification storage table;

[0085] The primary key data in each identification storage table is removed to obtain a plurality of decoupled data tables.

[0086] S4. Receive a data check instruction, and perform a data compliance check on the data in each of the decoupled data tables according to the data check instruction.

[0087] In the embodiment of the present invention, by performing data screening on the data in each of the decoupled data tables, the data in the decoupled data tables can meet the needs of target users, and the target users may be managers of the database.

[0088] In the embodiment of the present invention, performing data compliance checking on the data in each of the decoupled data tables according to the data checking instruction includes:

[0089] Establishing a troubleshooting task for checking the decoupled data table based on the data troubleshooting instruction;

[0090] Obtaining the scheduling node for data screening in each of the decoupled data tables;

[0091] In the scheduling node, data compliance checking is performed on the data in each of the decoupled data tables based on the checking task.

[0092] In an embodiment of the present invention, the check task is a task of checking data in each of the decoupled data tables. The scheduling node is a node that determines the location of data that needs to be checked in each of the decoupled data tables.

[0093] In an embodiment of the present invention, performing data compliance checks on the data in each of the decoupled data tables can achieve the purpose of managing major business risks, which generally includes ensuring that the data complies with applicable laws and regulations, industry guidelines and standards, company policies and procedures, etc.

[0094] In an embodiment of the present invention, multiple pre-stored data storage tables and the data types of the data in the data storage tables are obtained, and fixed identifiers are added to each data field in the data storage table according to the data type of the data to obtain multiple identifier storage tables, thereby distinguishing each field in the data storage table. Thereafter, the identifier storage table is decoupled through a preset data self-inspection system to obtain multiple decoupled data tables, and finally, a data check instruction is accepted, and data compliance check is performed on the data in the decoupled data table according to the data check instruction. By adding identifiers to the fields in the data storage table, each field is clearly distinguished, thereby improving the accuracy of the data compliance check.

[0095] like Figure 2 FIG. 1 is a schematic diagram of a module of a data structure-based data screening device according to the present invention.

[0096] The data structure-based data screening device 100 of the present invention can be installed in an electronic device. Depending on the functionality implemented, the data structure-based data screening device can include a data table acquisition module 101, an identification table construction module 102, an identification table decoupling module 103, and a data screening module 104. The modules described in the present invention, also referred to as units, refer to a series of computer program segments that can be executed by an electronic device processor and can perform a fixed function, and are stored in the memory of the electronic device.

[0097] In this embodiment, the functions of each module / unit are as follows:

[0098] The remaining data table acquisition module 101 is used to acquire multiple pre-stored data storage tables and acquire the data type of the data in each data storage table.

[0099] In an embodiment of the present invention, the data storage table is a table in a preset database that stores the data to be checked, that is, the data to be checked is stored in the database in the form of a data table, wherein the database is the database to be checked, and the data stored in the database is the data to be checked.

[0100] In the embodiment of the present invention, the data to be checked is data in the database that needs to be checked, and data compliance can be achieved by checking the data to be checked.

[0101] For example, XXX Company needs to store user identity information data. Before storing the user identity information data in the company's database, checking the user identity information data can avoid storing data involving user privacy in the company's database, thereby causing legal violations.

[0102] Furthermore, the data type is a specific data type in the data storage table, and the data in the data storage table is distinguished by obtaining the data type.

[0103] Furthermore, in another optional embodiment of the present invention, the data table acquisition module 101 specifically includes a data table acquisition unit and a data type acquisition unit.

[0104] The data table acquisition unit is used to acquire a plurality of pre-stored data storage tables.

[0105] The data type acquiring unit is used to acquire the data type of each data in the data storage table.

[0106] Furthermore, the data type acquisition unit is specifically used to:

[0107] Obtain the data to be checked in each of the data storage tables;

[0108] A preset data query table is obtained, and the data query table is searched according to the data to be checked in each data storage table to obtain the data type of the data to be checked.

[0109] In an embodiment of the present invention, the data query table has only two columns of data, one column of data is a primary key, storing the corresponding data of the data to be checked, and the other column of data is the data type of the corresponding data. The corresponding data can be the same data as the data to be checked.

[0110] Furthermore, the primary key is a unique identifier of the data query table, which is used to ensure the uniqueness of the corresponding data in the data query table and avoid different data types for the same data to be checked, resulting in data type acquisition errors.

[0111] Furthermore, the step of querying the data query table according to the data to be checked in each data storage table to obtain the data type of the data to be checked specifically includes:

[0112] Convert the data to be checked in each data storage table into text to obtain text data to be checked;

[0113] Acquire all corresponding data in the data query table, and convert all the corresponding data into text to obtain a plurality of corresponding text data;

[0114] The text data to be checked is compared with a plurality of corresponding text data, and the corresponding text data corresponding to the text data to be checked is found, thereby obtaining the data type of the data in the data storage table.

[0115] In an embodiment of the present invention, the text data to be checked and the plurality of corresponding text data may be compared based on a text similarity algorithm. Specifically, the text similarity algorithm may be a string-based text similarity algorithm that compares the number of identical characters between the text data to be checked and each of the corresponding text data to determine the similarity between the text data to be checked and each of the corresponding text data.

[0116] In the embodiment of the present invention, before the data table acquisition unit, the method further includes:

[0117] Obtaining preset stored data and the encryption type of the stored data;

[0118] selecting a data encryption method for different types of stored data according to the encryption type of the stored data;

[0119] The stored data is encrypted according to the data encryption method to obtain the data to be checked, and the data to be checked is stored in a preset storage repository to obtain a database storing the data to be checked.

[0120] In the embodiment of the present invention, the preset storage data may be unprocessed user identity information data obtained from the user.

[0121] The identification table construction module 102 is configured to add a fixed identification to each data field in each data storage table according to the data type, to obtain multiple identification storage tables.

[0122] In an embodiment of the present invention, the fixed identifier is a specific encrypted identifier, and the data to be checked in the data storage table can be distinguished and identified by the fixed identifier. After the data is sorted (for example, stored in other storage tables), the data to be checked can still be distinguished according to the fixed identifier.

[0123] In the embodiment of the present invention, the identification storage table is a storage table that adds a fixed identification to each data field according to the data type.

[0124] Furthermore, the identification table construction module 102 is specifically configured to:

[0125] Using the encryption method as a fixed identifier for a data field in the data storage table;

[0126] According to the data type, a corresponding fixed identifier is added to each data field in each data storage table to construct an identifier storage table.

[0127] Furthermore, the encryption method is a symmetric encryption method, and the data in the identification storage table can be decrypted according to the decryption method corresponding to the encryption method, which can avoid the business code level from directly viewing the data in the identification storage table. The encryption method can be Aes encryption method, Sm4 encryption method, Md5 encryption method, etc.

[0128] In the embodiment of the present invention, the fixed identifier corresponding to each data field is the encryption method used when storing data in the data storage table.

[0129] For example, if the data storage table stores id name (name), pwd (password), and username (username), then the fixed identifier Sm4 will be used for the id name field, the fixed identifier Aes will be used for the pwd field, and the fixed identifier Md5 will be used for the username field.

[0130] The decoupling module 103 is configured to decouple each of the identification storage tables through a preset data self-checking system to obtain a plurality of decoupled data tables.

[0131] In an embodiment of the present invention, the data check instruction is an instruction for checking whether the data in the decoupled data table is compliant. The data check instruction can be an instruction for checking whether the data is compliant based on legal content, or it can be an instruction for checking data that does not meet business needs based on the company's business needs.

[0132] In an embodiment of the present invention, the data self-inspection system is a system that is independent of the business code and is used to check whether the data meets the requirements. The data self-inspection system can be used to view data and decouple the identification storage table. The data self-inspection system contains a visual configuration page for displaying the data.

[0133] In the embodiment of the present invention, the decoupling module 103 is specifically configured to:

[0134] Obtaining primary key data from each of the identification storage tables;

[0135] Extracting primary key data and primary key relationship data tables from each identification storage table;

[0136] The primary key data in each identification storage table is removed to obtain a plurality of decoupled data tables.

[0137] The data checking module 104 is configured to receive a data checking instruction and perform a data compliance check on the data in each of the decoupled data tables according to the data checking instruction.

[0138] In the embodiment of the present invention, by performing data screening on the data in each of the decoupled data tables, the data in the decoupled data tables can meet the needs of target users, and the target users may be managers of the database.

[0139] In an embodiment of the present invention, the following operations can be performed to implement data compliance checking of the data in each of the decoupled data tables according to the data checking instruction:

[0140] Establishing a troubleshooting task for checking the decoupled data table based on the data troubleshooting instruction;

[0141] Obtaining the scheduling node for data screening in each of the decoupled data tables;

[0142] In the scheduling node, data compliance checking is performed on the data in each of the decoupled data tables based on the checking task.

[0143] In an embodiment of the present invention, the check task is a task of checking data in each of the decoupled data tables. The scheduling node is a node that determines the location of data that needs to be checked in each of the decoupled data tables.

[0144] In an embodiment of the present invention, performing data compliance checks on the data in each of the decoupled data tables can achieve the purpose of managing major business risks, which generally includes ensuring that the data complies with applicable laws and regulations, industry guidelines and standards, company policies and procedures, etc.

[0145] like Figure 3 FIG. 1 is a schematic diagram of the structure of an electronic device for implementing a data structure-based data screening method according to the present invention.

[0146] The electronic device may include a processor 10, a memory 11, a communication bus 12, and a communication interface 13. It may also include a computer program stored in the memory 11 and executable on the processor 10, such as a data structure-based data troubleshooting program.

[0147] In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and a combination of various control chips. The processor 10 is the control core (Control Unit) of the electronic device, connecting the various components of the entire electronic device using various interfaces and lines, and executing or executing programs or modules stored in the memory 11 (for example, executing a data structure-based data search program, etc.), as well as calling data stored in the memory 11, to execute various functions of the electronic device and process data.

[0148] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (for example, an SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of an electronic device, such as a mobile hard disk of the electronic device. In other embodiments, the memory 11 can also be an external storage device of an electronic device, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Furthermore, the memory 11 can also include both an internal storage unit of the electronic device and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device, such as the code of a data troubleshooting program based on a data structure, but can also be used to temporarily store data that has been output or is to be output.

[0149] The communication bus 12 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable communication between the memory 11 and at least one processor 10, etc.

[0150] The communication interface 13 is used for communication between the above-mentioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display (Display), an input unit (such as a keyboard (Keyboard)), optionally, the user interface may also be a standard wired interface, a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch device, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device and to display a visual user interface.

[0151] Figure 3 Only the electronic device with components is shown, and it can be understood by those skilled in the art that Figure 3 The structure shown does not limit the electronic device, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0152] For example, although not shown, the electronic device may further include a power source (such as a battery) for powering various components. Preferably, the power source may be logically connected to the at least one processor 10 via a power management device, thereby implementing functions such as charge management, discharge management, and power consumption management through the power management device. The power source may further include any components such as one or more DC or AC power sources, a recharging device, a power failure detection circuit, a power converter or inverter, a power status indicator, etc. The electronic device may further include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0153] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0154] The data structure-based data screening program stored in the memory 11 of the electronic device is a combination of multiple computer programs. When running in the processor 10, it can achieve the following:

[0155] Acquire a plurality of pre-stored data storage tables, and acquire the data type of the data in each of the data storage tables;

[0156] Adding a fixed identifier to each data field in each data storage table according to the data type to obtain multiple identifier storage tables;

[0157] Decoupling each of the identification storage tables through a preset data self-checking system to obtain multiple decoupled data tables;

[0158] A data check instruction is received, and data compliance check is performed on the data in each of the decoupled data tables according to the data check instruction.

[0159] Specifically, the specific implementation method of the processor 10 for the above computer program can refer to Figure 1 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0160] Furthermore, if the module / unit integrated into the electronic device is implemented as a software functional unit and sold or used as an independent product, it can be stored in a non-volatile computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0161] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program is executed by a processor of an electronic device, the computer program can implement:

[0162] Acquire a plurality of pre-stored data storage tables, and acquire the data type of the data in each of the data storage tables;

[0163] Adding a fixed identifier to each data field in each data storage table according to the data type to obtain multiple identifier storage tables;

[0164] Decoupling each of the identification storage tables through a preset data self-checking system to obtain multiple decoupled data tables;

[0165] A data check instruction is received, and data compliance check is performed on the data in each of the decoupled data tables according to the data check instruction.

[0166] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the module division is merely a logical function division, and other division methods may be used in actual implementation.

[0167] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of the modules may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0168] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional modules.

[0169] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0170] Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims rather than the foregoing description, and all changes that come within the meaning and range of equivalents of the claims are intended to be embraced therein. Any reference to a figure in a claim should not be construed as limiting the claim to which it relates.

[0171] Blockchain, as used in this article, refers to a novel application model for computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Blockchain is essentially a decentralized database, a series of data blocks generated using cryptographic methods. Each block contains information about a batch of online transactions, used to verify the validity of this information (to prevent counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, the platform product service layer, and the application service layer.

[0172] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.

[0173] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices recited in a system claim may also be implemented by a single unit or device through software or hardware. Second-order terms are used to indicate names and do not imply any particular order.

[0174] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A data screening method based on data structure, characterized in that: The method is applied to a client and includes: Obtaining preset storage data and an encryption type of the storage data, selecting a data encryption method for different types of the storage data according to the encryption type of the storage data, obtaining multiple data storage tables pre-stored in a database of data to be checked, and obtaining the data type of the data in each of the data storage tables; Adding a fixed identifier to each data field in each data storage table according to the data type to obtain a plurality of identifier storage tables, including: using the data encryption method as a fixed identifier for the data field in the data storage table, adding a corresponding fixed identifier to each data field in each data storage table according to the data type, and constructing an identifier storage table; Decoupling each of the identification storage tables through a preset data self-checking system to obtain a plurality of decoupled data tables, including: extracting primary key data from each of the identification storage tables, removing the primary key data from each of the identification storage tables, and obtaining the plurality of decoupled data tables; A data check instruction is received, and data compliance check is performed on the data in each of the decoupled data tables according to the data check instruction.

2. The data structure-based data screening method according to claim 1, characterized in that: The performing data compliance check on the data in each of the decoupled data tables according to the data check instruction includes: Establishing a troubleshooting task for checking the decoupled data table based on the data troubleshooting instruction; Obtaining a scheduling node for performing data checking on the data in each of the decoupled data tables; In the scheduling node, data compliance checking is performed on the data in each of the decoupled data tables based on the checking task.

3. The data structure-based data screening method according to claim 1, wherein: The obtaining of the data type of the data in each data storage table includes: Obtain the data to be checked in each of the data storage tables; A preset data query table is obtained, and the data query table is searched according to the data to be checked in each data storage table to obtain the data type of the data to be checked.

4. The data structure-based data screening method according to claim 3, characterized in that: The querying of the data query table according to the data to be checked in each data storage table to obtain the data type of the data to be checked includes: Convert the data to be checked in each data storage table into text to obtain text data to be checked; Acquire all corresponding data in the data query table, and convert all the corresponding data into text to obtain a plurality of corresponding text data; The text data to be checked is compared with a plurality of corresponding text data, and the corresponding text data corresponding to the text data to be checked is found, thereby obtaining the data type of the data in the data storage table.

5. The data structure-based data screening method according to claim 1, wherein: Before obtaining a plurality of data storage tables pre-stored in a database of data to be checked, the method further includes: The stored data is encrypted according to the data encryption method to obtain the data to be checked, and the data to be checked is stored in a preset storage repository to obtain a database storing the data to be checked.

6. A data structure-based data checking device, characterized in that: The device comprises: a data table acquisition module, configured to acquire preset stored data and an encryption type of the stored data, select a data encryption method for different types of stored data according to the encryption type of the stored data, acquire multiple data storage tables pre-stored in a database of data to be checked, and acquire the data type of the data in each data storage table; an identification table construction module, configured to add a fixed identification to each data field in each of the data storage tables according to the data type, to obtain a plurality of identification storage tables, including: using the data encryption method as a fixed identification for the data field in the data storage table, adding a corresponding fixed identification to each data field in each of the data storage tables according to the data type, and constructing an identification storage table; An identification table decoupling module is used to decouple each of the identification storage tables through a preset data self-checking system to obtain multiple decoupled data tables, including: extracting primary key data from each of the identification storage tables, removing the primary key data from each of the identification storage tables, and obtaining multiple decoupled data tables; The data checking module is used to receive data checking instructions and perform data compliance checking on the data in each of the decoupled data tables according to the data checking instructions.

7. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor to implement the data structure-based data screening method according to any one of claims 1 to 5.

8. A computer-readable storage medium comprising a data storage area and a program storage area, wherein the data storage area stores created data and the program storage area stores a computer program; When the computer program is executed by a processor, the data structure-based data screening method according to any one of claims 1 to 5 is implemented.

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