CN114564483A - Data structure-based data checking method and device, electronic equipment and medium - Google Patents
Data structure-based data checking method and device, electronic equipment and medium Download PDFInfo
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Abstract
The invention relates to the technical field of data analysis, and discloses a data checking method based on a data structure, which comprises the following steps: acquiring a plurality of pre-stored data storage tables and acquiring the data type of data in each data storage table; adding a fixed identifier for each data field in each data storage table according to the data type to obtain a plurality of identifier storage tables; decoupling each identification storage table through a preset data self-checking system to obtain a plurality of decoupling data tables; and receiving a data checking instruction, and performing data compliance checking on the data in each decoupling data table according to the data checking instruction. The invention also provides a data checking device, equipment and a storage medium based on the data structure. The invention also relates to a blockchain technology, and the fixed identification can be stored in a blockchain node. The invention can improve the accuracy of data checking.
Description
Technical Field
The present invention relates to the field of data analysis technologies, and in particular, to a data structure-based data checking method and apparatus, an electronic device, and a computer-readable storage medium.
Background
With the development of network technology, data acquisition is more and more convenient, and soil is provided for lawless persons to acquire private data of users, so that the privacy security of data is more and more emphasized in advanced countries, and the safe database dropping of data according to legal requirements or business development requirements of companies becomes a problem.
The existing data security database is usually to check whether the data is compliant when the data is not stored in the database, and how to perform the compliance check of the data stored in the database becomes a difficult problem to be solved urgently.
Disclosure of Invention
The invention provides a data checking method and device based on a data structure, electronic equipment and a computer readable storage medium, and mainly aims to improve the accuracy of data checking.
In order to achieve the above object, the present invention provides a data checking method based on a data structure, including:
acquiring a plurality of pre-stored data storage tables and acquiring the data type of data in each data storage table;
adding a fixed identifier for each data field in each data storage table according to the data type to obtain a plurality of identifier storage tables;
decoupling each identification storage table through a preset data self-checking system to obtain a plurality of decoupling data tables;
and receiving a data checking instruction, and performing data compliance checking on the data in each decoupling data table according to the data checking instruction.
Optionally, the performing data compliance investigation on the data in each decoupling data table according to the data investigation instruction includes:
establishing a checking task for checking the decoupling data table based on the data checking instruction;
acquiring scheduling nodes for data investigation in each decoupling data table;
and performing data compliance investigation on the data in each decoupling data table in the scheduling node based on the investigation task.
Optionally, the obtaining a data type of the data in each data storage table includes:
acquiring data to be checked in each data storage table;
and acquiring a preset data query table, and querying the data query table according to the data to be queried in each data storage table to obtain the data type of the data to be queried.
Optionally, the querying, according to the data to be checked in each data storage table, in the data query table to obtain the data type of the data to be checked, includes:
the data to be checked in each data storage table is subjected to textualization to obtain the text data to be checked;
acquiring all corresponding data in the data query table, and textualizing all the corresponding data to obtain a plurality of corresponding text data;
and comparing the text data to be checked with the plurality of corresponding text data, and finding the corresponding text data corresponding to the text data to be checked so as to obtain the data type of the data in the data storage table.
Optionally, before the obtaining of the plurality of pre-stored data storage tables, the method further includes:
acquiring preset storage data and an encryption type of the storage data;
selecting a data encryption method for the different types of the storage data according to the encryption type of the storage data;
and encrypting the stored data according to the data encryption method to obtain the data to be checked, and storing the data to be checked into a preset storage library to obtain a database for storing the data to be checked.
Optionally, the 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 includes:
using the encryption method as a fixed identifier of a data field in the data storage table;
and adding corresponding fixed identifications to each data field in each data storage table according to the data types to construct an identification storage table.
Optionally, the decoupling each identifier storage table by a preset data self-checking system to obtain a plurality of decoupling data tables, including:
acquiring primary key data in each identification storage table;
extracting the primary key data and the primary key relation data table in each identification storage table from each identification storage table;
and removing the main key data in each identification storage table to obtain a plurality of decoupling data tables.
In order to solve the above problem, the present invention further provides a data checking apparatus based on a data structure, the apparatus comprising:
the data table acquisition module is used for acquiring a plurality of pre-stored data storage tables and acquiring the data type of data in each data storage table;
the identification table building module is used for adding fixed identifications to each data field in each data storage table according to the data types to obtain a plurality of identification storage tables;
the identification table decoupling module is used for decoupling each identification storage table through a preset data self-checking system to obtain a plurality of decoupling data tables;
and the data checking module is used for receiving a data checking instruction and performing data compliance checking on the data in each decoupling data table according to the data checking instruction.
In order to solve the above problem, the present invention also provides an electronic device, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the data structure-based data querying method as described above.
In order to solve the above problem, the present invention further provides a computer-readable storage medium including a storage data area and a storage program area, the storage data area storing created data, the storage program area storing a computer program; wherein the computer program, when executed by a processor, implements a data structure based data querying method as described above.
In the embodiment of the invention, a plurality of pre-stored data storage tables and data types of data in the data storage tables are obtained, fixed identifiers are added to each data field in the data storage tables according to the data types of the data to obtain a plurality of identifier storage tables, each field in the data storage tables is distinguished, then the identifier storage tables are decoupled through a preset data self-checking system to obtain a plurality of decoupling data tables, finally a data checking instruction is received, data in the decoupling data tables are checked in a data compliance mode according to the data checking instruction, the fields in the data storage tables are clearly distinguished by adding the identifiers, and the accuracy of the data compliance checking is improved.
Drawings
Fig. 1 is a schematic flowchart of a data structure-based data checking method according to an embodiment of the present invention;
FIG. 2 is a block diagram of a data structure-based data checking apparatus according to an embodiment of the present invention;
fig. 3 is a schematic internal structural diagram of an electronic device implementing a data structure-based data checking method according to an embodiment of the present invention;
the implementation, functional features and advantages of the present invention will be further described with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment of the application provides a data checking method based on a data structure. The execution subject of the data checking method based on the data structure includes, but is not limited to, at least one of electronic devices, such as a server and a terminal, which can be configured to execute the method provided by the embodiments of the present application. The server may be an independent server, or may be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like. In other words, the data structure-based data checking method may be performed by software or hardware installed in a terminal device or a server device, and the software may be a block chain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
Fig. 1 is a schematic flow chart of a data structure-based data checking method according to an embodiment of the present invention. In this embodiment, the data checking method based on the data structure includes:
s1, acquiring a plurality of pre-stored data storage tables, and acquiring the data type of the data in each data storage table.
In the embodiment of the invention, the data storage table is a table for storing the data to be checked in a preset database, that is, the data to be checked is stored in the database in a data table form, wherein the database is the database to be checked, and the data stored in the database is the data to be checked.
In the embodiment of the invention, the data to be checked is the data which needs to be checked in the database, and the data can be in a standard way by checking the data to be checked.
For example, XXX company needs to store the identity information data of the user, and the checking of the identity information data of the user before storing the identity information data of the user in the database of the company can avoid storing data related to the privacy of the user in the database of the company, thereby causing legal violations.
Further, the data type is a specific data type in the data storage table, and the data in the data storage table is distinguished by acquiring the data type.
In an embodiment of the present invention, the obtaining a data type of data in each data storage table includes:
acquiring data to be checked in each data storage table;
and acquiring a preset data query table, and 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.
In the embodiment of the invention, the data query table only has two columns of data, one column of data is a main key and stores the corresponding data of the data to be checked, and the other column of data is the data type of the corresponding data. Wherein, the corresponding data may be the same data as the data to be checked.
Further, the primary key is a unique identifier of the data query table, and is used for ensuring the uniqueness of the corresponding data in the data query table and avoiding the occurrence of different data types on the same data to be checked, which results in the acquisition error of the data types.
Further, the querying in 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:
the data to be checked in each data storage table is subjected to textualization to obtain the text data to be checked;
acquiring all corresponding data in the data query table, and performing textualization on all the corresponding data to obtain a plurality of corresponding text data;
and comparing the text data to be checked with the plurality of corresponding text data, and finding the corresponding text data corresponding to the text data to be checked so as to obtain the data type of the data in the data storage table.
In the embodiment of the invention, the text data to be checked and the plurality of corresponding text data can be compared based on a text similarity algorithm. Specifically, the text similarity algorithm may be a character string-based text similarity algorithm, and the similarity between the text data to be checked and each corresponding text data is obtained by comparing the number of characters that are the same as the text data to be checked and each corresponding text data.
In this embodiment of the present invention, before acquiring a plurality of pre-stored data storage tables, the method further includes:
acquiring preset storage data and an encryption type of the storage data;
selecting a data encryption method for the different types of the storage data according to the encryption type of the storage data;
and encrypting the stored data according to the data encryption method to obtain the data to be checked, and storing the data to be checked into a preset storage library to obtain a database for storing the data to be checked.
In this embodiment of the present invention, the preset storage data may be unprocessed user identity information data obtained from a user.
And S2, adding fixed identifiers for each data field in each data storage table according to the data types to obtain a plurality of identifier storage tables.
In the 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 through the fixed identifier, and the data to be checked can still be distinguished according to the fixed identifier after the data is sorted (for example, stored in other storage tables).
In the embodiment of the present invention, the identifier storage table is a storage table that adds a fixed identifier to each data field according to the data type.
Further, the 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 includes:
using the encryption method as a fixed identifier of a data field in the data storage table;
and adding corresponding fixed identifications to each data field in each data storage table according to the data types to construct an identification storage table.
Furthermore, the encryption method is a symmetric encryption method, and the data in the identifier storage table can be decrypted according to a decryption method corresponding to the encryption method, so that the function of directly viewing the data in the identifier storage table at the level of avoiding the service code can be achieved. The encryption method may be an Aes encryption method, an Sm4 encryption method, an Md5 encryption method, or the like.
In the embodiment of the present invention, the fixed identifier corresponding to each data field is an encryption method for storing data in the data storage table.
For example, if id name pwd (password) username is stored in the data storage table, then Sm4 will be fixed for id name field, Aes will be fixed for pwd field, and Md5 will be fixed for username field.
And S3, decoupling each identification storage table through a preset data self-checking system to obtain a plurality of decoupling data tables.
In the embodiment of the invention, the data checking instruction is an instruction for checking whether the data in the decoupling data table are in compliance, and the data checking instruction can be an instruction for checking whether the data are in compliance according to legal content or an instruction for checking the data which do not meet the business requirements according to the business requirements of a company.
In the embodiment of the invention, the data self-checking system is a system which is separated from a service code and is used for checking whether data meet requirements or not, the data self-checking system can check the data and decouple the identification storage table, and a visual configuration page for displaying the data exists in the data self-checking system.
In the embodiment of the present invention, the decoupling each identifier storage table by a preset data self-checking system to obtain a plurality of decoupling data tables includes:
acquiring primary key data in each identification storage table;
extracting the primary key data and the primary key relation data table in each identification storage table from each identification storage table;
and removing the main key data in each identification storage table to obtain a plurality of decoupling data tables.
And S4, receiving a data checking instruction, and performing data compliance checking on the data in each decoupling data table according to the data checking instruction.
In the embodiment of the invention, the data in each decoupling data table can meet the requirements of target users by performing data checking on the data in each decoupling data table, and the target users can be managers of the database.
In an embodiment of the present invention, the performing data compliance investigation on the data in each decoupling data table according to the data investigation instruction includes:
establishing a checking task for checking the decoupling data table based on the data checking instruction;
acquiring scheduling nodes for data investigation in each decoupling data table;
and performing data compliance investigation on the data in each decoupling data table in the scheduling node based on the investigation task.
In the embodiment of the invention, the checking task is a task for checking data of each decoupling data table. The scheduling node is a node for determining the data position to be checked in each decoupling data table.
In the embodiment of the present invention, the purpose of managing the heavy business risk can be achieved by performing data compliance investigation on the data in each decoupling data table, and generally, the purpose may include that the data complies with applicable laws and regulations, industry standards and standards, company policies and procedures, and the like.
In the embodiment of the invention, a plurality of pre-stored data storage tables and data types of data in the data storage tables are obtained, fixed identifiers are added to each data field in the data storage tables according to the data types of the data to obtain a plurality of identifier storage tables, each field in the data storage tables is distinguished, then the identifier storage tables are decoupled through a preset data self-checking system to obtain a plurality of decoupling data tables, finally a data checking instruction is received, data in the decoupling data tables are checked in a data compliance mode according to the data checking instruction, the fields in the data storage tables are clearly distinguished by adding the identifiers, and the accuracy of the data compliance checking is improved.
Fig. 2 is a schematic block diagram of a data structure-based data checking apparatus according to the present invention.
The data structure-based data checking apparatus 100 of the present invention may be installed in an electronic device. According to the realized functions, the data checking device based on the data structure may include a data table obtaining module 101, an identification table constructing module 102, an identification table decoupling module 103, and a data checking module 104. The module of the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and that can perform a fixed function, and that are stored in a memory of the electronic device.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the remaining data table acquiring module 101 is configured to acquire a plurality of pre-stored data storage tables and acquire a data type of data in each data storage table.
In the embodiment of the invention, the data storage table is a table for storing the data to be checked in a preset database, that is, the data to be checked is stored in the database in a data table form, wherein the database is the database to be checked, and the data stored in the database is the data to be checked.
In the embodiment of the invention, the data to be checked is the data which needs to be checked in the database, and the data can be in a standard way by checking the data to be checked.
For example, XXX company needs to store the identity information data of the user, and the checking of the identity information data of the user before storing the identity information data of the user in the database of the company can avoid storing data related to the privacy of the user in the database of the company, thereby causing legal violations.
Further, the data type is a specific data type in the data storage table, and the data in the data storage table is distinguished by acquiring the data type.
Further, in another optional embodiment of the present invention, the data table obtaining module 101 specifically includes a data table obtaining unit and a data type obtaining unit.
The data table acquisition unit is used for acquiring a plurality of pre-stored data storage tables.
The data type obtaining unit is used for obtaining the data type of the data in each data storage table.
Further, the data type obtaining unit is specifically configured to:
acquiring data to be checked in each data storage table;
and acquiring a preset data query table, and 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.
In the embodiment of the invention, the data query table only has two columns of data, one column of data is a main key and stores the corresponding data of the data to be checked, and the other column of data is the data type of the corresponding data. Wherein, the corresponding data may be the same data as the data to be checked.
Further, the primary key is a unique identifier of the data query table, and is used for ensuring the uniqueness of the corresponding data in the data query table and avoiding the occurrence of different data types on the same data to be checked, which results in the acquisition error of the data types.
Further, the step of querying in 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:
the data to be checked in each data storage table is subjected to textualization to obtain the text data to be checked;
acquiring all corresponding data in the data query table, and performing textualization on all the corresponding data to obtain a plurality of corresponding text data;
and comparing the text data to be checked with the plurality of corresponding text data, and finding the corresponding text data corresponding to the text data to be checked so as to obtain the data type of the data in the data storage table.
In the embodiment of the invention, the text data to be checked and the plurality of corresponding text data can be compared based on a text similarity algorithm. Specifically, the text similarity algorithm may be a character string-based text similarity algorithm, and the similarity between the text data to be checked and each corresponding text data is obtained by comparing the number of characters that are the same as the text data to be checked and each corresponding text data.
In the embodiment of the present invention, before the data table obtaining unit, the method further includes:
acquiring preset storage data and an encryption type of the storage data;
selecting a data encryption method for the different types of the storage data according to the encryption type of the storage data;
and encrypting the stored data according to the data encryption method to obtain the data to be checked, and storing the data to be checked into a preset storage library to obtain a database for storing the data to be checked.
In this embodiment of the present invention, the preset storage data may be unprocessed user identity information data obtained from a user.
The identifier table constructing module 102 is configured to add a fixed identifier to each data field in each data storage table according to the data type, so as to obtain a plurality of identifier storage tables.
In the 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 through the fixed identifier, and the data to be checked can still be distinguished according to the fixed identifier after the data is sorted (for example, stored in other storage tables).
In the embodiment of the present invention, the identifier storage table is a storage table in which a fixed identifier is added to each data field according to the data type.
Further, the identification table constructing module 102 is specifically configured to:
using the encryption method as a fixed identifier of a data field in the data storage table;
and adding corresponding fixed identifications to each data field in each data storage table according to the data types to construct an identification storage table.
Furthermore, the encryption method is a symmetric encryption method, and the data in the identifier storage table can be decrypted according to a decryption method corresponding to the encryption method, so that the function of directly viewing the data in the identifier storage table at the level of avoiding the service code can be achieved. The encryption method may be an Aes encryption method, an Sm4 encryption method, an Md5 encryption method, or the like.
In the embodiment of the present invention, the fixed identifier corresponding to each data field is an encryption method for storing data in the data storage table.
For example, if id name pwd (password) username is stored in the data storage table, then Sm4 will be fixed for id name field, Aes will be fixed for pwd field, and Md5 will be fixed for username field.
The decoupling module 103 is configured to decouple each identifier storage table through a preset data self-checking system to obtain a plurality of decoupling data tables.
In the embodiment of the invention, the data checking instruction is an instruction for checking whether the data in the decoupling data table are in compliance, and the data checking instruction can be an instruction for checking whether the data are in compliance according to legal content or an instruction for checking the data which do not meet the business requirements according to the business requirements of a company.
In the embodiment of the invention, the data self-checking system is a system which is separated from a service code and is used for checking whether data meet requirements or not, the data self-checking system can check the data and decouple the identification storage table, wherein a visual configuration page for displaying the data exists in the data self-checking system.
In an embodiment of the present invention, the decoupling module 103 is specifically configured to:
acquiring primary key data in each identification storage table;
extracting the primary key data and the primary key relation data table in each identification storage table from each identification storage table;
and removing the main key data in each identification storage table to obtain a plurality of decoupling data tables.
The data checking module 104 is configured to receive a data checking instruction, and perform data compliance checking on data in each decoupling data table according to the data checking instruction.
In the embodiment of the invention, the data in each decoupling data table can meet the requirements of target users by performing data checking on the data in each decoupling data table, and the target users can be managers of the database.
In the embodiment of the present invention, the data in each decoupling data table may be subjected to data compliance investigation according to the data investigation instruction by:
establishing a checking task for checking the decoupling data table based on the data checking instruction;
acquiring scheduling nodes for data investigation in each decoupling data table;
and performing data compliance investigation on the data in each decoupling data table in the scheduling node based on the investigation task.
In the embodiment of the invention, the checking task is a task for checking data of each decoupling data table. The scheduling node is a node for determining the data position to be checked in each decoupling data table.
In the embodiment of the present invention, the purpose of managing the heavy business risk can be achieved by performing data compliance investigation on the data in each decoupling data table, and generally, the purpose may include that the data complies with applicable laws and regulations, industry standards and standards, company policies and procedures, and the like.
Fig. 3 is a schematic structural diagram of an electronic device implementing the data structure-based data checking method according to the present invention.
The electronic device may comprise a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may further comprise a computer program, such as a data structure based data checking program, stored in the memory 11 and executable on the processor 10.
In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same function or different functions, and includes one or more Central Processing Units (CPUs), a microprocessor, a digital Processing chip, a graphics processor, a combination of various control chips, and the like. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device by running or executing programs or modules (for example, executing a data structure-based data checking program, etc.) stored in the memory 11 and calling data stored in the memory 11.
The memory 11 includes at least one type of readable storage medium including flash memory, removable hard disks, multimedia cards, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disks, optical disks, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device, for example a removable hard disk of the electronic device. The memory 11 may also be an external storage device of the electronic device in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used not only to store application software installed in the electronic device and various types of data, such as codes of a data checking program based on a data structure, but also to temporarily store data that has been output or is to be output.
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 arranged to enable connection communication between the memory 11 and at least one processor 10 or the like.
The communication interface 13 is used for communication between the electronic device and other devices, and includes a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), which are typically 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), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable, among other things, for displaying information processed in the electronic device and for displaying a visualized user interface.
Fig. 3 shows only an electronic device having components, and those skilled in the art will appreciate that the structure shown in fig. 3 does not constitute a limitation of the electronic device, and may include fewer or more components than those shown, or some components may be combined, or a different arrangement of components.
For example, although not shown, the electronic device may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management and the like are realized through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.
The data structure-based data checking program stored in the memory 11 of the electronic device is a combination of a plurality of computer programs, and when running in the processor 10, can realize:
acquiring a plurality of pre-stored data storage tables and acquiring the data type of data in each data storage table;
adding a fixed identifier for each data field in each data storage table according to the data type to obtain a plurality of identifier storage tables;
decoupling each identification storage table through a preset data self-checking system to obtain a plurality of decoupling data tables;
and receiving a data checking instruction, and performing data compliance checking on the data in each decoupling data table according to the data checking instruction.
Specifically, the processor 10 may refer to the description of the relevant steps in the embodiment corresponding to fig. 1 for a specific implementation method of the computer program, which is not described herein again.
Further, the electronic device integrated module/unit, if implemented in the form of a software functional unit and sold or used as a separate product, may be stored in a non-volatile computer-readable storage medium. The computer readable storage medium may be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).
The present invention also provides a computer-readable storage medium storing a computer program which, when executed by a processor of an electronic device, implements:
acquiring a plurality of pre-stored data storage tables and acquiring the data type of data in each data storage table;
adding a fixed identifier for each data field in each data storage table according to the data type to obtain a plurality of identifier storage tables;
decoupling each identification storage table through a preset data self-checking system to obtain a plurality of decoupling data tables;
and receiving a data checking instruction, and performing data compliance checking on the data in each decoupling data table according to the data checking instruction.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a string of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, which is used for verifying the validity (anti-counterfeiting) of the information and generating a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
Furthermore, it will be obvious that the term "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A data checking method based on a data structure is applied to a client and comprises the following steps:
acquiring a plurality of pre-stored data storage tables and acquiring the data type of data in each data storage table;
adding a fixed identifier for each data field in each data storage table according to the data type to obtain a plurality of identifier storage tables;
decoupling each identification storage table through a preset data self-checking system to obtain a plurality of decoupling data tables;
and receiving a data checking instruction, and performing data compliance checking on the data in each decoupling data table according to the data checking instruction.
2. The data structure-based data checking method according to claim 1, wherein the performing data compliance checking on the data in each decoupling data table according to the data checking instruction comprises:
establishing a checking task for checking the decoupling data table based on the data checking instruction;
acquiring scheduling nodes for data investigation in each decoupling data table;
and performing data compliance investigation on the data in each decoupling data table in the scheduling node based on the investigation task.
3. The method for data structure-based data checking according to claim 1, wherein the obtaining the data type of the data in each data storage table comprises:
acquiring data to be checked in each data storage table;
and acquiring a preset data query table, and 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.
4. The data structure-based data query method according to claim 3, wherein the querying in the data query table according to the data to be queried in each data storage table to obtain the data type of the data to be queried comprises:
the data to be checked in each data storage table is subjected to textualization to obtain the text data to be checked;
acquiring all corresponding data in the data query table, and performing textualization on all the corresponding data to obtain a plurality of corresponding text data;
and comparing the text data to be checked with the plurality of corresponding text data, and finding the corresponding text data corresponding to the text data to be checked so as to obtain the data type of the data in the data storage table.
5. The data structure-based data inspection method of claim 1, wherein before the obtaining of the plurality of pre-stored data storage tables, the method further comprises:
acquiring preset storage data and an encryption type of the storage data;
selecting a data encryption method for the different types of the storage data according to the encryption type of the storage data;
and encrypting the stored data according to the data encryption method to obtain the data to be checked, and storing the data to be checked into a preset storage library to obtain a database for storing the data to be checked.
6. The data structure-based data checking method according to claim 1, wherein the 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 includes:
using the encryption method as a fixed identifier of a data field in the data storage table;
and adding corresponding fixed identifications to each data field in each data storage table according to the data types to construct an identification storage table.
7. The data structure-based data query method of claim 1, wherein the decoupling each of the identifier storage tables by a preset data self-query system to obtain a plurality of decoupled data tables comprises:
acquiring primary key data in each identification storage table;
extracting the primary key data and the primary key relation data table in each identification storage table from each identification storage table;
and removing the main key data in each identification storage table to obtain a plurality of decoupling data tables.
8. An apparatus for data structure-based data inspection, the apparatus comprising:
the data table acquisition module is used for acquiring a plurality of pre-stored data storage tables and acquiring the data type of data in each data storage table;
the identification table construction module is used for adding fixed identifications to each data field in each data storage table according to the data types to obtain a plurality of identification storage tables;
the identification table decoupling module is used for decoupling each identification storage table through a preset data self-checking system to obtain a plurality of decoupling data tables;
and the data checking module is used for receiving a data checking instruction and performing data compliance checking on the data in each decoupling data table according to the data checking instruction.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the data structure-based data querying method according to any one of claims 1 to 7.
10. A computer-readable storage medium includes a storage data area storing created data and a storage program area storing a computer program; wherein the computer program when executed by a processor implements the data structure based data scrubbing method of any one of claims 1 to 7.
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