Remote heterogeneous data consistency maintenance method and device, electronic equipment and medium

Abstract

The embodiment of the invention discloses a remote heterogeneous data consistency maintenance method and device, electronic equipment and a medium. A specific embodiment of the method comprises the following steps: collecting different-place heterogeneous data; performing data standardization processing on the different-place heterogeneous data; performing coding storage and permission configuration operation on each piece of standardized remote heterogeneous data; the standardized remote heterogeneous data are encrypted and sent to a collaborator; carrying out the following consistency maintenance processing on the metadata stored in the service node corresponding to the preset service node identifier and the main data: obtaining the metadata and the main data as to-be-detected metadata and to-be-detected main data respectively; determining the different-place heterogeneous data corresponding to the preset service node identifier in the different-place heterogeneous data as target different-place heterogeneous data; performing consistency detection processing on the to-be-detected metadata and the to-be-detected master data; and updating the service node. According to the embodiment, the integrity and accuracy of the data after standardization processing are improved.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technology, and in particular to a method, device, electronic device, and medium for maintaining consistency of heterogeneous data in different locations. Background Art

[0002] With the popularization of technologies such as cloud computing and big data, distributed systems have become the mainstream of modern IT architecture. In distributed systems, data consistency is particularly important. Heterogeneous data consistency maintenance is a technology that performs standardized processing and consistency maintenance on data stored in business nodes (heterogeneous data in different locations). At present, when performing standardized processing and consistency maintenance on data stored in business nodes (heterogeneous data in different locations), the commonly used method is to directly perform standardized processing and consistency maintenance on data stored in business nodes (heterogeneous data in different locations).

[0003] However, when the above method is used to standardize and maintain the consistency of data stored in business nodes (heterogeneous data in different locations), the following technical problems often occur:

[0004] When the collected data (heterogeneous data in different locations) stored in the business nodes is directly standardized and maintained for consistency, the permissions of the standardized data are not set, which increases the risk of data leakage. At the same time, the data without permission settings is easy to be illegally modified or deleted, resulting in low integrity and accuracy of the standardized data.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the inventive concept and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the invention

[0006] The content of this disclosure is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this disclosure is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0007] Some embodiments of the present disclosure propose methods, devices, electronic devices and computer-readable media for maintaining consistency of heterogeneous data in different locations to solve one or more of the technical problems mentioned in the above background technology section.

[0008] In a first aspect, some embodiments of the present disclosure provide a method for maintaining consistency of heterogeneous data in different locations, the method comprising: collecting various heterogeneous data in different locations corresponding to various preset business node identifiers; performing data standardization processing on the above-mentioned various heterogeneous data in different locations to obtain various standardized heterogeneous data in different locations corresponding to the above-mentioned various preset business node identifiers, wherein each standardized heterogeneous data in the above-mentioned various standardized heterogeneous data in different locations includes standardized metadata, standardized master data, and standardized subject data; performing encoding storage and permission configuration operations on the above-mentioned various standardized heterogeneous data; in response to receiving an acquisition request message containing a preset business node identifier and a data encoding sent by a preset local client, encrypting and sending the standardized heterogeneous data corresponding to the above-mentioned data encoding to a collaborator corresponding to the above-mentioned preset business node identifier for use by the collaborator. The above-mentioned collaborator heterogeneously translates the above-mentioned standardized heterogeneous data to the above-mentioned preset local client; for each of the above-mentioned preset business node identifiers, the following consistency maintenance processing is performed on the metadata and master data stored in the business node corresponding to the above-mentioned preset business node identifier: in response to receiving the consistency maintenance request information sent by the above-mentioned business node, metadata and master data are obtained from the above-mentioned business node as metadata to be detected and master data to be detected respectively; the heterogeneous data corresponding to the above-mentioned preset business node identifier in the above-mentioned various heterogeneous data is determined as the target heterogeneous data; based on the above-mentioned target heterogeneous data, consistency detection processing is performed on the above-mentioned metadata to be detected and the above-mentioned master data to be detected to obtain consistency detection information; based on the above-mentioned consistency detection information, the above-mentioned business node is updated.

[0009] In a second aspect, some embodiments of the present disclosure provide a device for maintaining consistency of heterogeneous data in different locations, the device comprising: a collection unit, configured to collect various heterogeneous data corresponding to various preset business node identifiers; a data standardization processing unit, configured to perform data standardization processing on the above-mentioned various heterogeneous data to obtain various standardized heterogeneous data corresponding to the above-mentioned various preset business node identifiers, wherein each of the above-mentioned various standardized heterogeneous data includes standardized metadata, standardized master data, and standardized subject data; a storage unit, configured to encode, store and configure permissions for the above-mentioned various standardized heterogeneous data; a sending unit, configured to encrypt and send the standardized heterogeneous data corresponding to the above-mentioned data code to the above-mentioned preset business node identifier in response to receiving an acquisition request information containing a preset business node identifier and a data code sent by a preset local client. A collaborator corresponding to the node identifier is provided for the collaborator to heterogeneously translate the standardized heterogeneous data to the preset local client; a consistency maintenance processing unit is configured to perform the following consistency maintenance processing on the metadata and master data stored in the business node corresponding to the preset business node identifier for each of the preset business node identifiers: in response to receiving the consistency maintenance request information sent by the business node, obtain metadata and master data from the business node as metadata to be detected and master data to be detected respectively; determine the heterogeneous data corresponding to the preset business node identifier in the above-mentioned various heterogeneous data as target heterogeneous data; based on the target heterogeneous data, perform consistency detection processing on the metadata to be detected and the master data to be detected to obtain consistency detection information; based on the consistency detection information, update the business node.

[0010] In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation manner of the above-mentioned first aspect.

[0011] In a fourth aspect, some embodiments of the present disclosure provide a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner of the above-mentioned first aspect is implemented.

[0012] The above-mentioned embodiments of the present disclosure have the following beneficial effects: through the heterogeneous data consistency maintenance method of some embodiments of the present disclosure, the risk of data leakage is reduced and the integrity and accuracy of the data after standardization processing are improved. Specifically, the reason for the high risk of data leakage and the low integrity and accuracy of the data after standardization processing is that when the data (heterogeneous data) stored in the collected business node is directly standardized and maintained in consistency, the data after standardization processing is not set with permissions, which increases the risk of data leakage. At the same time, the data without permission setting is easily illegally modified or deleted, resulting in low integrity and accuracy of the data after standardization processing. Based on this, the heterogeneous data consistency maintenance method of some embodiments of the present disclosure first collects the heterogeneous data corresponding to each preset business node identifier. Thus, the heterogeneous data of each business node can be collected. Then, the above-mentioned heterogeneous data are subjected to data standardization processing to obtain the standardized heterogeneous data corresponding to the above-mentioned preset business node identifiers, wherein each standardized heterogeneous data in the above-mentioned standardized heterogeneous data includes standardized metadata, standardized master data, and standardized subject data. Thus, data standardization can be performed on each heterogeneous data to improve the uniqueness and consistency of each heterogeneous data. Afterwards, the above-mentioned standardized heterogeneous data are encoded, stored and configured with permissions. Thus, permissions can be configured for standardized heterogeneous data, reducing the risk of data leakage. At the same time, permissions are configured for standardized heterogeneous data, reducing the number of illegal modification or deletion of standardized heterogeneous data, and improving the integrity and accuracy of the data after standardization. Afterwards, in response to receiving the acquisition request information containing the preset business node identifier and data encoding sent by the preset local client, the standardized heterogeneous data corresponding to the above data encoding is encrypted and sent to the collaborator corresponding to the above preset business node identifier, so that the above collaborator can heterogeneously translate the above standardized heterogeneous data to the above preset local client. Thus, the collaborator can be used to realize the intercommunication between public and private networks, realize the free flow of information between the public network and the private network, and improve the security and stability of information transmission. Next, for each of the preset business node identifiers, the metadata and master data stored in the business node corresponding to the preset business node identifier are subjected to the following consistency maintenance processing: Step 1: In response to receiving the consistency maintenance request information sent by the business node, metadata and master data are obtained from the business node as metadata to be detected and master data to be detected, respectively. Thus, the metadata to be detected and master data to be detected stored by the business node can be obtained. Step 2: The heterogeneous data corresponding to the preset business node identifier in each of the heterogeneous data is determined as the target heterogeneous data.Thus, the target heterogeneous data for consistency detection of the metadata to be detected and the master data to be detected can be obtained. The third step is to perform consistency detection on the metadata to be detected and the master data to be detected based on the target heterogeneous data to obtain consistency detection information. Thus, consistency detection can be performed on the metadata to be detected and the master data to be detected. The fourth step is to update the business node based on the consistency detection information. Thus, the business node can be updated. Also, in the process of standardizing and maintaining the consistency of the data (heterogeneous data) stored in the business node, the permission configuration is performed on the standardized heterogeneous data, which reduces the risk of data leakage. At the same time, the permission configuration is performed on the standardized heterogeneous data, which reduces the number of illegal modification or deletion of the standardized heterogeneous data, and improves the integrity and accuracy of the standardized data. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0014] Figure 1 is a flow chart of some embodiments of the method for maintaining consistency of heterogeneous data in different locations according to the present disclosure;

[0015] Figure 2 It is a structural schematic diagram of some embodiments of the device for maintaining consistency of heterogeneous data in different locations according to the present disclosure;

[0016] Figure 3 It is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0017] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0018] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0019] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0020] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0021] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0022] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0023] Figure 1 The process 100 of some embodiments of the method for maintaining consistency of heterogeneous data in different locations according to the present disclosure is shown. The method for maintaining consistency of heterogeneous data in different locations includes the following steps:

[0024] Step 101: collect various heterogeneous data corresponding to various preset business node identifiers.

[0025] In some embodiments, the execution subject (e.g., server) of the method for maintaining consistency of heterogeneous data in different places can collect different heterogeneous data corresponding to each preset business node identifier through a wired connection mode or a wireless connection mode. In practice, the execution subject can collect different heterogeneous data from each business node corresponding to each preset business node identifier. Among them, each preset business node identifier in the preset business node identifier can represent the name of the business node. The business node can be a distributed node in a distributed business system (e.g., a distributed node server). The business system can be a system developed to meet business needs. Each of the different heterogeneous data in the different places includes metadata, master data, and subject data. The subject data can be a data set corresponding to business demand information. Among them, the business demand information includes demand information and data demand information. The demand information can represent the demand put forward by the business node corresponding to the target business node identifier to achieve business goals, optimize decision making, etc. The data demand information can include at least one data identifier. For example, the preset business demand information can be "demand information: financial institution risk management, data demand information: user credit data, market data, macroeconomic data". The at least one data identifier may be "user credit data, market data, macroeconomic data". The subject data may be a data set related to "financial institution risk management". For example, the data set may include but is not limited to user credit data, market data, and macroeconomic data.

[0026] It should be noted that the above-mentioned wireless connection methods may include but are not limited to 3G / 4G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods currently known or to be developed in the future.

[0027] Step 102, performing data standardization processing on each heterogeneous data in different locations to obtain each standardized heterogeneous data in different locations corresponding to each preset business node identifier.

[0028] In some embodiments, the execution subject may perform data standardization on the above-mentioned heterogeneous data to obtain the standardized heterogeneous data corresponding to the above-mentioned preset business node identifiers. Each standardized heterogeneous data in the above-mentioned heterogeneous data includes standardized metadata, standardized master data, and standardized subject data.

[0029] In some optional implementations of some embodiments, the execution subject may perform data standardization processing on the above-mentioned heterogeneous data through the following steps to obtain the standardized heterogeneous data corresponding to the above-mentioned preset business node identifiers:

[0030] In the first step, for each of the above-mentioned heterogeneous data, the following data standardization processing is performed:

[0031] The first sub-step is to determine the metadata included in the above-mentioned heterogeneous data as target metadata.

[0032] The second sub-step is to perform data standardization processing on the target metadata based on the preset metadata mapping table to obtain standardized metadata. The target metadata may include at least one field (data item to be mapped or converted). The preset metadata mapping table defines the correspondence between the field (i.e., the field of the target metadata) and the target field (i.e., the field of the standardized metadata). In practice, for each of the at least one field included in the target metadata, the execution subject may compare the field with each field in the preset metadata mapping table, and determine the field in the preset metadata mapping table that is the same as the field as the query field. Afterwards, the execution subject may determine the target field corresponding to the query field in the preset metadata mapping table as the field to be converted. Afterwards, the execution subject may update the field in the target metadata to the field to be converted to update the target metadata. Finally, the execution subject may determine the updated target metadata as the standardized metadata.

[0033] In the third sub-step, the master data included in the above-mentioned heterogeneous data is determined as the target master data. The above-mentioned target master data includes various business master data, wherein each of the above-mentioned business master data corresponds to category attribute information. The above-mentioned category attribute information can represent the information of the content attribute of the business master data. The above-mentioned business master data can be shared data between systems (for example, customer, supplier, account-related data).

[0034] The fourth sub-step is to perform unique cleaning processing on each business master data included in the target master data to obtain each cleaned business master data as the cleaned master data. In practice, the execution entity can perform unique cleaning processing on each business master data by using data deduplication technology to obtain each cleaned business master data as the cleaned master data.

[0035] The fifth sub-step is to standardize the various cleaning business master data included in the above cleaning master data to obtain various standardized cleaning business master data. In practice, the above-mentioned execution subject can standardize the above-mentioned various cleaning business master data through data conversion technology and data mapping technology to obtain various standardized cleaning business master data. Specifically, first, the above-mentioned execution subject can convert the specific data (such as date, character) contained in the above-mentioned various cleaning business master data into a unified format through data conversion technology (such as a script written using a data conversion tool or a programming language (such as Python)) to obtain various standardized cleaning business master data with unified data format. Afterwards, the above-mentioned execution subject can perform data conversion on the various standardized cleaning business master data after the data format is unified according to the preset mapping table representing the mapping relationship between the fields in the source data and the fields in the target data, through a data integration tool (such as Apache Nifi, Talend, etc.), to obtain various converted business data. Afterwards, the above-mentioned execution subject can determine each converted business data as each standardized cleaning business master data. As an example, each cleaning business master data can be "2024 / 11 / 15, customer name: A". After the data format is unified, each standardized cleaning service master data may be "2024-11-15, customer name: A". The mapping table may be "customer name-customer name", and each standardized cleaning service master data may be "2024-11-15, customer name: A". The above "A" may be the customer's name.

[0036] The sixth sub-step is to determine the above-mentioned standardized cleaning business master data as standardized master data.

[0037] In a seventh sub-step, a preset business node identifier corresponding to the above-mentioned heterogeneous data is determined as a target business node identifier.

[0038] The eighth sub-step is to obtain the business demand information corresponding to the target business node identifier. For example, the business demand information may be "demand information: financial institution risk management, data demand information: user credit data, market data, macroeconomic data". In practice, the execution entity may obtain the business demand information from the business node corresponding to the target business node identifier.

[0039] The ninth sub-step is to create a subject data structure corresponding to the above-mentioned business requirement information. In practice, first, the above-mentioned execution subject may determine the number of at least one data identifier included in the above-mentioned business requirement information as the target number. Afterwards, the above-mentioned execution subject may execute a creation task corresponding to the preset data structure creation information to create a target number of data structures (e.g., tables or columns) as the subject data structure. The above-mentioned preset data structure creation information may be a pre-written instruction for guiding the creation of a data structure.

[0040] The tenth sub-step is to store the subject data included in the above-mentioned heterogeneous data in the above-mentioned subject data structure to update the above-mentioned subject data structure.

[0041] The eleventh sub-step is to determine the updated subject data structure as the standardized subject data.

[0042] The twelfth sub-step is to determine the standardized metadata, the standardized master data, and the standardized subject data as standardized heterogeneous data corresponding to the target business node identifier.

[0043] Step 103, encoding storage and permission configuration operations are performed on each standardized heterogeneous data.

[0044] In some embodiments, the above-mentioned execution entity can perform encoding storage and permission configuration operations on the above-mentioned various standardized heterogeneous data.

[0045] In the process of adopting technical solutions to solve the problems mentioned in the background technology, the following problems are often accompanied:

[0046] Before performing permission configuration operations on standardized heterogeneous data, the standardized metadata, standardized master data, and standardized subject data included in the standardized heterogeneous data need to be stored for access and acquisition by the client. However, when the standardized metadata, standardized master data, and standardized subject data included in the standardized heterogeneous data are directly stored, since an index identifier for storing the data is not generated according to the characteristics of the data, when the client obtains the data (standardized metadata, standardized master data, or standardized subject data), it may be necessary to traverse all the stored standardized heterogeneous data, resulting in an increase in the waiting time for the client to obtain the data.

[0047] In the face of the above problems, the inventor decided to adopt the following solutions:

[0048] In some optional implementations of some embodiments, the execution subject may perform encoding storage and permission configuration operations on the standardized heterogeneous data in different locations through the following steps:

[0049] In the first step, for each standardized heterogeneous data in the above-mentioned standardized heterogeneous data, perform the following steps:

[0050] The first sub-step is to generate a metadata code corresponding to the standardized metadata included in the above-mentioned standardized heterogeneous data, and store the above-mentioned standardized metadata. The above-mentioned metadata code is an index identifier of the above-mentioned standardized metadata. In practice, the above-mentioned execution entity can use the URN (Uniform Resource Name) protocol to encode (identify) the metadata to obtain the metadata code. For example, the above-mentioned metadata can be "Book Title: Programming Basics, ISBN Number: 978-7-115-50000-1", "isbn" is used as the namespace identifier, and the URN protocol identifier "urn", the namespace identifier "isbn" and the specific ISBN number are combined to form a complete URN code. Then the metadata code can be "urn:isbn:978-7-115-50000-1".

[0051] The second sub-step is to obtain the preset metadata permission setting role information corresponding to the above-mentioned standardized metadata. In practice, the above-mentioned execution entity can obtain the preset metadata permission setting role information from a preset database. The above-mentioned preset metadata permission setting role information can be a list including various user roles (for example, administrator, ordinary user) and various permission setting information. Among them, each of the above-mentioned user roles corresponds one-to-one to each permission setting information in the above-mentioned permission setting information. Each permission setting information in the above-mentioned permission setting information includes permission type information (for example, operation permission) and permission content information (for example, addition, deletion, modification).

[0052] The third sub-step is to configure permissions for the standardized metadata based on the role permission setting information. In practice, the execution subject can configure permissions for the standardized metadata based on the role permission setting information through the role-based access control (RBAC) technology.

[0053] The fourth sub-step is to determine the standardized master data included in the above-mentioned standardized heterogeneous data as the standardized master data to be encoded.

[0054] The fifth sub-step is to determine each category attribute information corresponding to each business master data included in the above-mentioned standardized master data to be encoded. Among them, each business master data in the above-mentioned business master data corresponds one-to-one to each category attribute information in the above-mentioned category attribute information. The above-mentioned category attribute information includes each category attribute sub-information. Each category attribute sub-information in the above-mentioned category attribute sub-information can represent an attribute of the business master data. For example, the above-mentioned category attribute information can be "object: customer; type: individual customer; attribute: paid". The above-mentioned category attribute sub-information can be "type: individual customer".

[0055] The sixth sub-step is to classify and encode the above-mentioned business master data based on the above-mentioned category attribute information, obtain the business master data codes corresponding to the above-mentioned business master data, and store the above-mentioned business master data. Among them, each business master data code in the above-mentioned business master data codes is an index identifier of each business master data in the above-mentioned business master data. In practice, for each business master data in the above-mentioned business master data, the above-mentioned execution subject can perform the following classification and encoding processing: the first step is to determine the category attribute information of the above-mentioned business master data as the target category attribute information. The second step is that for each category attribute sub-information in the above-mentioned target category attribute information, the above-mentioned execution subject can determine the code corresponding to the above-mentioned category attribute sub-information in the preset coding table as the target code. The third step is that the above-mentioned execution subject can combine the obtained target codes in a preset arrangement order to obtain the business master data code corresponding to the above-mentioned business master data. Among them, the above-mentioned preset coding table can be a mapping table of category attribute sub-information to code. As an example, the above-mentioned target category attribute information can be "object: customer; type: individual customer; attribute: paid". The above-mentioned category attribute sub-information may be "type: individual customer", "object: customer" or "attribute: paid". The above-mentioned preset coding table may be expressed as "customer corresponds to K, individual customer corresponds to P, paid corresponds to A", and the above-mentioned business master data code may be KPA.

[0056] The seventh sub-step is to obtain the preset master data permission setting role information corresponding to the above-mentioned standardized master data. In practice, the above-mentioned execution entity can obtain the preset master data permission setting role information from a preset database. The above-mentioned preset master data permission setting role information can be a list containing various user roles (for example, administrators, ordinary users) and various permission setting information. Among them, each of the above-mentioned user roles corresponds one-to-one to each of the permission setting information in the above-mentioned permission setting information. Each of the above-mentioned permission setting information includes permission type information (for example, operation permission) and permission content information (for example, addition, deletion, modification).

[0057] In the eighth sub-step, based on the preset master data permission setting role information, permissions are configured for each stored business master data. In practice, the execution subject can configure permissions for each business master data based on the preset master data permission setting role information through role-based access control (RBAC) technology.

[0058] The ninth sub-step is to determine the standardized subject data included in the above-mentioned standardized heterogeneous data as the standardized subject data to be encoded.

[0059] The tenth sub-step is to determine the business demand information corresponding to the above-mentioned standardized subject data to be encoded.

[0060] The eleventh sub-step is to generate the subject data code corresponding to the above-mentioned standardized subject data to be encoded based on the above-mentioned business demand information, and store the above-mentioned standardized subject data to be encoded. The above-mentioned subject data code is the index identifier of the stored standardized subject data to be encoded. In practice, the above-mentioned execution subject can determine the demand information included in the above-mentioned business demand information as the target demand information. Then, the above-mentioned execution subject can query the code corresponding to the above-mentioned target demand information through the preset demand coding table as the subject data code corresponding to the above-mentioned standardized subject data to be encoded. The above-mentioned preset demand coding table can represent a table of the correspondence between demand information and coding. For example, the above-mentioned preset demand coding table can be expressed as "Financial institution risk management corresponds to J, and customer relationship maintenance corresponds to W". Then, when the business demand information of the standardized subject data to be encoded is "demand information: financial institution risk management, data demand information: user credit data, market data, macroeconomic data", the target demand information can be "financial institution risk management". The subject data code corresponding to the above-mentioned standardized subject data to be encoded can be "J".

[0061] The twelfth sub-step is to perform permission configuration processing on the stored standardized subject data to be coded. In practice, the above-mentioned execution subject can obtain the preset role permission setting list corresponding to the above-mentioned standardized subject data to be coded from the preset database. Afterwards, the above-mentioned execution subject can perform permission configuration processing on the standardized subject data to be coded based on the preset role permission setting list through role-based access control (RBAC, Role-Based AccessControl) technology. Among them, the above-mentioned preset role permission setting list is a list containing various user roles (for example, administrators, ordinary users) and various permission setting information. Among them, each of the above-mentioned user roles corresponds one-to-one to each permission setting information in the above-mentioned permission setting information. Each permission setting information in the above-mentioned permission setting information includes permission type information (for example, operation permission) and permission content information (for example, addition, deletion, modification).

[0062] The above technical solution and its related contents, as an inventive point of the embodiment of the present disclosure, solve the technical problem of "increased waiting time for the client to obtain data". The factors that lead to the increase of the waiting time for data acquisition are often as follows: when the standardized metadata, standardized master data, and standardized subject data included in the standardized heterogeneous data are directly stored, because the index identifier for storing the data is not generated according to the characteristics of the data, when the client obtains the data (standardized metadata, standardized master data, or standardized subject data), it may be necessary to traverse all the stored standardized heterogeneous data, resulting in an increase in the waiting time for the client to obtain the data. If the above factors are solved, the effect of reducing the waiting time for the client to obtain data can be achieved. In order to achieve this effect, first, for each standardized heterogeneous data in the above-mentioned standardized heterogeneous data, the following steps are performed: the first step is to generate a metadata code corresponding to the standardized metadata included in the above-mentioned standardized heterogeneous data, and store the above-mentioned standardized metadata, wherein the above-mentioned metadata code is an index identifier of the above-mentioned standardized metadata. Thus, the index identifier for storing the standardized metadata, i.e., the metadata code, can be generated. The second step is to obtain the preset metadata permission setting role information corresponding to the above-mentioned standardized metadata. Thus, the preset metadata permission setting role information for permission configuration of the standardized metadata can be obtained. The third step is to configure the permission of the standardized metadata based on the above role permission setting information. Thus, the permission configuration of the standardized metadata can be performed. The fourth step is to determine the standardized master data included in the above standardized heterogeneous data as the standardized master data to be encoded. The fifth step is to determine the various category attribute information corresponding to the various business master data included in the above standardized master data to be encoded, wherein each business master data in the above business master data corresponds to each category attribute information in the above category attribute information. Thus, each category attribute information for generating each index identifier of each business master data can be obtained. The sixth step is to classify and encode the above business master data based on the above category attribute information, obtain each business master data code corresponding to the above business master data, and store the above business master data, wherein each business master data code in the above business master data code is the index identifier of each business master data in the above business master data. Thus, each business master data can be stored and each business master data in each business master data has a corresponding index identifier. Step 7: Obtain the preset master data permission setting role information corresponding to the above-mentioned standardized master data. Thus, the preset master data permission setting role information can be obtained. Step 8: Based on the above-mentioned preset master data permission setting role information, perform permission configuration on each stored business master data. Thus, the permission configuration can be performed on each stored business master data. Step 9: Determine the standardized subject data included in the above-mentioned standardized heterogeneous data as the standardized subject data to be encoded.The tenth step is to determine the business demand information corresponding to the above-mentioned standardized subject data to be encoded. Thus, the business demand information for generating the index identifier of the standardized subject data to be encoded can be obtained. The eleventh step is to generate the subject data code corresponding to the above-mentioned standardized subject data to be encoded based on the above-mentioned business demand information, and store the above-mentioned standardized subject data to be encoded, wherein the above-mentioned subject data code is the index identifier of the stored standardized subject data to be encoded. Thus, the standardized subject data to be encoded can be stored with the subject data code as the index identifier of the standardized subject data to be encoded. The twelfth step is to perform permission configuration processing on the stored standardized subject data to be encoded. Thus, the permission configuration processing can be performed on the standardized subject data to be encoded. Also, before storing the standardized metadata, standardized master data, and standardized subject data included in the standardized heterogeneous data, the metadata code, each business master data code, and the subject data code are generated as the index identifiers for storing the standardized metadata, standardized master data, and standardized subject data respectively. The client can obtain the required standardized heterogeneous data in different places according to the index identifier, which reduces the traversal time and the waiting time for the client to obtain data.

[0063] Step 104, in response to receiving an acquisition request message containing a preset business node identifier and data encoding sent by a preset local client, encrypt the standardized heterogeneous data corresponding to the data encoding and send it to the collaborator corresponding to the preset business node identifier, so that the collaborator can heterogeneously translate the standardized heterogeneous data to the preset local client.

[0064] In some embodiments, in response to receiving an acquisition request message including a preset business node identifier and a data code sent by a preset local client, the above-mentioned execution subject encrypts and sends the standardized heterogeneous data corresponding to the above-mentioned data code to the collaborator corresponding to the above-mentioned preset business node identifier, so that the above-mentioned collaborator can heterogeneously translate the above-mentioned standardized heterogeneous data to the above-mentioned preset local client. Among them, the above-mentioned collaborator corresponds to the preset business node identifier one by one. The above-mentioned collaborator can be a component for coordinating data synchronization and exchange between different business nodes and preset local clients. In practice, the above-mentioned collaborator can send the encrypted standardized heterogeneous data to the above-mentioned preset local client. The above-mentioned preset local client can decrypt the encrypted standardized heterogeneous data to obtain standardized heterogeneous data. Afterwards, the above-mentioned preset local client can obtain the preset mapping table corresponding to the preset business node identifier from the preset database. Then, the above-mentioned preset local client can translate the standardized heterogeneous data into translated heterogeneous data according to the preset mapping table, and then store the translated heterogeneous data in the local preset file. As an example, the standardized heterogeneous data may be "2024-11-15, customer name: A", and the preset mapping table may translate the customer name into the customer name. The translated heterogeneous data may be "2024-11-15, customer name: A".

[0065] In some optional implementations of some embodiments, the execution subject may encrypt and send the standardized heterogeneous data corresponding to the data encoding to the collaborator corresponding to the preset service node identifier through the following steps:

[0066] The first step is to receive the handshake request information sent by the preset local client, wherein the handshake request information includes encrypted random number information and cipher suite list information, and the cipher suite list information includes each cipher suite information. The encrypted random number information may be an encrypted random number. The random number may be a random number generated by the preset local client. The preset local client may be a local device (such as a personal computer, a smart phone, etc.) for obtaining standardized heterogeneous data in different locations. Each cipher suite information in the above cipher suite information may represent a cipher suite.

[0067] The second step is to obtain pre-stored decryption algorithm information from a preset database, wherein the decryption algorithm information may represent a decryption algorithm (eg, an AES decryption algorithm).

[0068] The third step is to perform a decryption operation on the encrypted random number information according to the decryption algorithm information to obtain the decrypted random number information, wherein the decrypted random number information may be the decrypted random number information.

[0069] The fourth step is to generate random number information and obtain a preset cipher suite information sequence, wherein the preset cipher suite information in the preset cipher suite information sequence is arranged according to the preset priority information corresponding to the preset cipher suite information. In practice, the execution subject may generate a random number as the random number information through a random number generator. The preset priority information may represent the preset security level of the cipher suite corresponding to the preset cipher suite information. The execution subject may obtain the preset cipher suite information sequence from a preset database.

[0070] Step 5: Based on the above cipher suite information and the preset cipher suite information sequence, perform the following screening steps:

[0071] In the first sub-step, for the first preset cipher suite information in the preset cipher suite information sequence, the following steps are performed:

[0072] Sub-step one: in response to determining that among the cipher suite information there is cipher suite information that is the same as the preset cipher suite information, determining the cipher suite information as the filtered cipher suite information.

[0073] Sub-step 2: in response to determining that the cipher suite information does not contain the same cipher suite information as the preset cipher suite information, performing the following update steps:

[0074] Sub-step one: deleting the preset cipher suite information from the preset cipher suite information sequence to update the preset cipher suite information sequence.

[0075] Sub-step 2: executing the above screening step again according to the updated preset cipher suite information sequence.

[0076] Step 6: Send the random number information and the filtered cipher suite information to the preset local client.

[0077] Step 7: Generate session key information based on the above-mentioned filtered cipher suite information, the above-mentioned decrypted random number information, and the above-mentioned random number information. In practice, the above-mentioned execution subject may determine the cipher suite represented by the filtered cipher suite information as the filtered cipher suite. Afterwards, the above-mentioned execution subject may execute the key exchange algorithm in the filtered cipher suite, and generate a session key as the session key information based on the above-mentioned decrypted random number information and the above-mentioned random number information.

[0078] In the eighth step, based on the session key information, the standardized heterogeneous data is encrypted to obtain encrypted standardized heterogeneous data. The encrypted standardized heterogeneous data may be data obtained by encrypting the standardized heterogeneous data. In practice, the execution subject may execute a preset encryption algorithm (e.g., a symmetric encryption algorithm) and use the session key of the session key information to encrypt the standardized heterogeneous data to obtain encrypted standardized heterogeneous data.

[0079] The ninth step is to send the above-mentioned encrypted standardized heterogeneous data to the collaborator corresponding to the above-mentioned preset business node identifier, and delete the session key information.

[0080] The above technical solution and its related contents, as an inventive point of an embodiment of the present disclosure, solve the technical problem of "the security of standardized heterogeneous data in different places is low during transmission". The factors that lead to the low security of standardized heterogeneous data in different places during transmission are often as follows: when the standardized heterogeneous data in different places is directly encrypted using a fixed key, the risk of the long-term stored fixed key being stolen or leaked is high, and the attacker may obtain the fixed key by guessing, resulting in the security of the standardized heterogeneous data encrypted by the fixed key in the transmission process is still low. If the above factors are solved, the effect of improving the security of standardized heterogeneous data in different places during transmission can be achieved. In order to achieve this effect, first, the handshake request information sent by the preset local client is received, wherein the handshake request information includes the encrypted random number information and the cipher suite list information, and the cipher suite list information includes each cipher suite information. Then, the pre-stored decryption algorithm information is obtained from the preset database. Thus, the decryption algorithm information for decrypting the encrypted random number information can be obtained. Afterwards, according to the decryption algorithm information, the encrypted random number information is decrypted to obtain the decrypted random number information. Thus, the decrypted random number information of the session key information can be obtained. Then, random number information is generated, and a preset cipher suite information sequence is obtained, wherein the preset cipher suite information in the preset cipher suite information sequence is arranged according to the preset priority information corresponding to the preset cipher suite information. Thus, random number information for generating session key information can be obtained. Then, based on the above-mentioned cipher suite information and the preset cipher suite information sequence, the following screening steps are performed: First, for the first preset cipher suite information in the above-mentioned preset cipher suite information sequence, the following steps are performed: First sub-step, in response to determining that each cipher suite information has the same cipher suite information as the preset cipher suite information, the cipher suite information is determined as the screened cipher suite information. Thus, the screened cipher suite information representing the cipher suites supported by both the preset local client and the execution subject can be obtained. Second sub-step, in response to determining that each cipher suite information does not have the same cipher suite information as the preset cipher suite information, the following update steps are performed: First, the preset cipher suite information is deleted from the preset cipher suite information sequence to update the preset cipher suite information sequence. Second, according to the updated preset cipher suite information sequence, the above screening step is performed again. Afterwards, the above-mentioned random number information and the above-mentioned screened cipher suite information are sent to the above-mentioned preset local client. Thus, the random number information and the above-mentioned filtered cipher suite information can be sent to the above-mentioned preset local client. Then, based on the above-mentioned filtered cipher suite information, the above-mentioned decrypted random number information, and the above-mentioned random number information, the session key information is generated. Thus, the random and unpredictable session key information can be generated according to the decrypted random number information and the random number information.Since the session key information is dynamically generated based on two random number information (decrypted random number information, random number information) and the filtered cipher suite information, even if the previously generated session key information is leaked, it will not affect the security of the standardized heterogeneous data encryption, thereby improving the security of the standardized heterogeneous data during transmission. Afterwards, based on the above session key information, the above standardized heterogeneous data is encrypted to obtain encrypted standardized heterogeneous data. Thus, the standardized heterogeneous data can be encrypted using random and unpredictable session key information, thereby reducing the possibility that an attacker may obtain the key by guessing, thereby improving the security of the standardized heterogeneous data during transmission. Finally, the above encrypted standardized heterogeneous data is sent to the collaborator corresponding to the above preset business node identifier, and the session key information is deleted. Thus, the session key can be deleted to ensure that the key will not be misused or abused, thereby maintaining the security of the communication.

[0081] Step 105: For each preset service node identifier in each preset service node identifier, the following consistency maintenance process is performed on the metadata and master data stored in the service node corresponding to the preset service node identifier:

[0082] Step 1051 , in response to receiving the consistency maintenance request information sent by the service node, obtaining metadata and master data from the service node as metadata to be detected and master data to be detected respectively.

[0083] In some embodiments, the execution subject may, in response to receiving the consistency maintenance request information sent by the business node, obtain metadata and master data from the business node as metadata to be detected and master data to be detected, respectively. The consistency maintenance request information may be request information for performing consistency detection processing on the metadata and master data. The request information may be a message or an instruction.

[0084] Step 1052: determine the heterogeneous data corresponding to the preset business node identifier in each heterogeneous data as the target heterogeneous data.

[0085] In some embodiments, the execution subject may determine the heterogeneous data corresponding to the preset service node identifier among the various heterogeneous data as the target heterogeneous data.

[0086] Step 1053 , based on the target heterogeneous data in different locations, consistency detection processing is performed on the metadata to be detected and the master data to be detected to obtain consistency detection information.

[0087] In some embodiments, the execution subject may perform consistency detection processing on the metadata to be detected and the master data to be detected based on the target heterogeneous data in different locations to obtain consistency detection information.

[0088] In some optional implementations of some embodiments, the execution subject may perform consistency detection processing on the metadata to be detected and the master data to be detected based on the target heterogeneous data in different locations through the following steps to obtain consistency detection information:

[0089] In the first step, metadata included in the target heterogeneous data is determined as reference metadata.

[0090] In the second step, based on the reference metadata, metadata consistency detection processing is performed on the metadata to be detected to obtain metadata consistency detection information. In practice, the execution subject can compare each byte in the reference metadata with the byte corresponding to the byte in the metadata to be detected by byte-by-byte comparison. In response to determining that each byte in the reference metadata is the same as the byte corresponding to the byte in the metadata to be detected, the execution subject can determine the information representing metadata consistency as metadata consistency detection information. In response to determining that there is at least one byte in each byte in the reference metadata that is different from the byte in the metadata to be detected, the execution subject can determine the information representing metadata inconsistency as metadata consistency detection information. The metadata consistency detection information can be text information. Optionally, the execution subject can perform a hash operation on the reference metadata to obtain a first hash value. Then, the execution subject can perform a hash operation on the metadata to be detected to obtain a second hash value. Afterwards, the execution subject can compare the first hash value with the second hash value, and in response to determining that the first hash value is the same as the second hash value, the execution subject can determine the information representing metadata consistency as metadata consistency detection information. In response to determining that the first hash value is the same as the second hash value, the execution subject may determine the metadata inconsistency information as the metadata consistency detection information.

[0091] The third step is to determine the master data included in the above-mentioned target heterogeneous data as reference master data.

[0092] The fourth step is to perform master data consistency detection on the master data to be detected based on the reference master data to obtain master data consistency detection information. In practice, the execution subject can convert the reference master data and the master data to be detected into a first vector corresponding to the reference master data and a second vector corresponding to the master data to be detected, respectively, through word embedding technology. Afterwards, the execution subject can determine the similarity between the first vector and the second vector as the target similarity. In response to determining that the target similarity is a preset value (for example, 1), the execution subject can determine the information representing the consistency of the master data as the master data consistency detection information. In response to determining that the target similarity is less than the preset value, the execution subject can determine the information representing the inconsistency of the master data as the master data consistency detection information. Among them, the similarity can be cosine similarity.

[0093] In the fifth step, the metadata consistency detection information and the master data consistency detection information are determined as consistency detection information.

[0094] Step 1054: Update the service node based on the consistency detection information.

[0095] In some embodiments, the execution entity may update the service node based on the consistency detection information.

[0096] In some optional implementations of some embodiments, the execution subject may update the service node based on the consistency detection information through the following steps:

[0097] In the first step, in response to determining that the metadata consistency detection information included in the consistency detection information indicates that the metadata is inconsistent, the reference metadata is sent to the service node so that the service node updates the stored metadata to the reference metadata.

[0098] In the second step, in response to determining that the master data consistency detection information included in the consistency detection information indicates that the master data is inconsistent, the reference master data is sent to the business node so that the business node updates the stored master data to the reference master data.

[0099] Optionally, the above execution entity may further perform the following steps:

[0100] In the first step, in response to receiving a new metadata request message corresponding to a preset service node identifier sent by the coordinator, the preset metadata mapping table is determined as the preset metadata mapping table to be compared. The new metadata request message includes the new metadata and the target field corresponding to the new metadata.

[0101] In the second step, in response to determining that the newly added metadata included in the above-mentioned new metadata request information is different from the various metadata in the above-mentioned preset metadata mapping table to be compared, the above-mentioned newly added metadata and the target field are added to the above-mentioned preset metadata mapping table to update the preset metadata mapping table.

[0102] The above-mentioned embodiments of the present disclosure have the following beneficial effects: through the heterogeneous data consistency maintenance method of some embodiments of the present disclosure, the risk of data leakage is reduced and the integrity and accuracy of the data after standardization processing are improved. Specifically, the reason for the high risk of data leakage and the low integrity and accuracy of the data after standardization processing is that when the data (heterogeneous data) stored in the collected business node is directly standardized and maintained in consistency, the data after standardization processing is not set with permissions, which increases the risk of data leakage. At the same time, the data without permission setting is easily illegally modified or deleted, resulting in low integrity and accuracy of the data after standardization processing. Based on this, the heterogeneous data consistency maintenance method of some embodiments of the present disclosure first collects the heterogeneous data corresponding to each preset business node identifier. Thus, the heterogeneous data of each business node can be collected. Then, the above-mentioned heterogeneous data are subjected to data standardization processing to obtain the standardized heterogeneous data corresponding to the above-mentioned preset business node identifiers, wherein each standardized heterogeneous data in the above-mentioned standardized heterogeneous data includes standardized metadata, standardized master data, and standardized subject data. Thus, data standardization can be performed on each heterogeneous data to improve the uniqueness and consistency of each heterogeneous data. Afterwards, the above-mentioned standardized heterogeneous data are encoded, stored and configured with permissions. Thus, permissions can be configured for standardized heterogeneous data, reducing the risk of data leakage. At the same time, permissions are configured for standardized heterogeneous data, reducing the number of illegal modification or deletion of standardized heterogeneous data, and improving the integrity and accuracy of the data after standardization. Afterwards, in response to receiving the acquisition request information containing the preset business node identifier and data encoding sent by the preset local client, the standardized heterogeneous data corresponding to the above data encoding is encrypted and sent to the collaborator corresponding to the above preset business node identifier, so that the above collaborator can heterogeneously translate the above standardized heterogeneous data to the above preset local client. Thus, the collaborator can be used to realize the intercommunication between public and private networks, realize the free flow of information between the public network and the private network, and improve the security and stability of information transmission. Next, for each of the preset business node identifiers, the metadata and master data stored in the business node corresponding to the preset business node identifier are subjected to the following consistency maintenance processing: Step 1: In response to receiving the consistency maintenance request information sent by the business node, metadata and master data are obtained from the business node as metadata to be detected and master data to be detected, respectively. Thus, the metadata to be detected and master data to be detected stored by the business node can be obtained. Step 2: The heterogeneous data corresponding to the preset business node identifier in each of the heterogeneous data is determined as the target heterogeneous data.Thus, the target heterogeneous data for consistency detection of the metadata to be detected and the master data to be detected can be obtained. The third step is to perform consistency detection on the metadata to be detected and the master data to be detected based on the target heterogeneous data to obtain consistency detection information. Thus, consistency detection can be performed on the metadata to be detected and the master data to be detected. The fourth step is to update the business node based on the consistency detection information. Thus, the business node can be updated. Also, because in the process of standardizing and maintaining the consistency of the data (heterogeneous data) stored in the business node, the standardized heterogeneous data is configured with permissions, which reduces the risk of data leakage. At the same time, the standardized heterogeneous data is configured with permissions, which reduces the number of illegal modification or deletion of the standardized heterogeneous data, and improves the integrity and accuracy of the standardized data.

[0103] Further references Figure 2 As an implementation of the methods shown in the figures, the present disclosure provides some embodiments of a device for maintaining consistency of heterogeneous data in different locations. These device embodiments are similar to Figure 1 Corresponding to the method embodiments shown, the device can be specifically applied to various electronic devices.

[0104] like Figure 2As shown, some embodiments of the heterogeneous data consistency maintenance device 200 include: an acquisition unit 201, a generation unit 202, a processing unit 203, an input unit 204 and an input unit 205. The acquisition unit 201 is configured to acquire various heterogeneous data corresponding to various preset business node identifiers; the data standardization processing unit 202 is configured to perform data standardization processing on the above-mentioned various heterogeneous data to obtain various standardized heterogeneous data corresponding to the above-mentioned various preset business node identifiers, wherein each standardized heterogeneous data in the above-mentioned various standardized heterogeneous data includes standardized metadata, standardized master data, and standardized subject data; the storage unit 203 is configured to encode, store and configure permissions for the above-mentioned various standardized heterogeneous data; the sending unit 204 is configured to respond to receiving an acquisition request message containing a preset business node identifier and a data code sent by a preset local client, encrypt and send the standardized heterogeneous data corresponding to the above-mentioned data code to the collaborator corresponding to the above-mentioned preset business node identifier, so as to be transmitted to the above-mentioned The collaborator heterogeneously translates the above-mentioned standardized heterogeneous data to the above-mentioned preset local client; the consistency maintenance processing unit 205 is configured to perform the following consistency maintenance processing on the metadata and master data stored in the business node corresponding to the above-mentioned preset business node identifier for each preset business node identifier among the above-mentioned preset business node identifiers: in response to receiving the consistency maintenance request information sent by the above-mentioned business node, obtain metadata and master data from the above-mentioned business node as metadata to be detected and master data to be detected respectively; determine the heterogeneous data corresponding to the above-mentioned preset business node identifier in the above-mentioned various heterogeneous data as target heterogeneous data; based on the above-mentioned target heterogeneous data, perform consistency detection processing on the above-mentioned metadata to be detected and the above-mentioned master data to be detected to obtain consistency detection information; based on the above-mentioned consistency detection information, update the above-mentioned business node.

[0105] It is understood that the units described in the device 200 are similar to those described in the reference Figure 1 Therefore, the operations, features and beneficial effects described above for the method are also applicable to the device 200 and the units contained therein, and will not be described in detail here.

[0106] Reference below Figure 3 , which shows a structural schematic diagram of an electronic device 300 suitable for implementing some embodiments of the present disclosure. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0107] like Figure 3As shown, the electronic device 300 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0108] Typically, the following devices may be connected to the I / O interface 305: input devices 306 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 308 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 309. The communication devices 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 3 The electronic device 300 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 3 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0109] In particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from the network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the functions defined in the method of some embodiments of the present disclosure are executed.

[0110] It should be noted that the computer-readable medium recorded in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In some embodiments of the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device or device. In some embodiments of the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0111] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0112] The computer-readable medium may be contained in the electronic device; or it may exist independently without being installed in the electronic device. The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: collects various heterogeneous data corresponding to each preset business node identifier; performs data standardization processing on the above-mentioned various heterogeneous data to obtain various standardized heterogeneous data corresponding to the above-mentioned various preset business node identifiers, wherein each standardized heterogeneous data in the above-mentioned various standardized heterogeneous data includes standardized metadata, standardized master data, and standardized subject data; encodes, stores, and configures permissions for the above-mentioned various standardized heterogeneous data; and in response to receiving an acquisition request message containing a preset business node identifier and a data code sent by a preset local client, encrypts the standardized heterogeneous data corresponding to the above-mentioned data code and sends it to the collaborator corresponding to the above-mentioned preset business node identifier. , so that the above-mentioned collaborator can heterogeneously translate the above-mentioned standardized heterogeneous data to the above-mentioned preset local client; for each preset business node identifier among the above-mentioned preset business node identifiers, the metadata and master data stored in the business node corresponding to the above-mentioned preset business node identifier are subjected to the following consistency maintenance processing: in response to receiving the consistency maintenance request information sent by the above-mentioned business node, metadata and master data are obtained from the above-mentioned business node as metadata to be detected and master data to be detected respectively; the heterogeneous data corresponding to the above-mentioned preset business node identifier in the above-mentioned various heterogeneous data are determined as target heterogeneous data; based on the above-mentioned target heterogeneous data, consistency detection processing is performed on the above-mentioned metadata to be detected and the above-mentioned master data to be detected to obtain consistency detection information; based on the above-mentioned consistency detection information, the above-mentioned business node is updated.

[0113] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0114] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0115] The units described in some embodiments of the present disclosure may be implemented by software or by hardware. The described units may also be set in a processor, for example, it may be described as: a processor includes an acquisition unit, a generation unit, a processing unit, an input unit and an input unit. Among them, the names of these units do not constitute a limitation on the unit itself under certain circumstances. For example, the collection unit may also be described as "a unit for collecting various heterogeneous data corresponding to each preset business node identifier".

[0116] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0117] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of technical features, but should also cover other technical solutions formed by any combination of technical features or their equivalent features without departing from the inventive concept. For example, a technical solution formed by replacing the features with (but not limited to) the technical features with similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A method for maintaining consistency of heterogeneous data in different locations, comprising: Collecting various heterogeneous data corresponding to various preset business node identifiers; Performing data standardization processing on the various heterogeneous data to obtain various standardized heterogeneous data corresponding to the various preset business node identifiers, wherein each standardized heterogeneous data in the various standardized heterogeneous data includes standardized metadata, standardized master data, and standardized subject data; Performing encoding storage and permission configuration operations on each of the standardized heterogeneous data; In response to receiving an acquisition request message including a preset service node identifier and a data code sent by a preset local client, encrypting and sending the standardized heterogeneous data corresponding to the data code to a collaborator corresponding to the preset service node identifier, so that the collaborator can heterogeneously translate the standardized heterogeneous data to the preset local client; For each preset service node identifier among the preset service node identifiers, the following consistency maintenance process is performed on the metadata and master data stored in the service node corresponding to the preset service node identifier: In response to receiving the consistency maintenance request information sent by the service node, obtaining metadata and master data from the service node as metadata to be detected and master data to be detected respectively; Determine the heterogeneous data corresponding to the preset service node identifier among the various heterogeneous data as the target heterogeneous data; Based on the target heterogeneous data in different locations, performing consistency detection processing on the metadata to be detected and the master data to be detected to obtain consistency detection information; Based on the consistency detection information, the service node is updated.

2. The method according to claim 1, wherein: The method further comprises: In response to receiving a new metadata request message corresponding to a preset service node identifier sent by the coordinator, determining the preset metadata mapping table as the preset metadata mapping table to be compared, wherein the new metadata request message includes the new metadata and a target field corresponding to the new metadata; In response to determining that the newly added metadata included in the newly added metadata request information is different from each metadata in the preset metadata mapping table to be compared, the newly added metadata and the target field are added to the preset metadata mapping table to update the preset metadata mapping table.

3. The method according to claim 1, wherein: Each of the heterogeneous data in different locations includes metadata, master data, and subject data, and the data standardization processing is performed on the heterogeneous data in different locations to obtain each standardized heterogeneous data corresponding to each preset business node identifier, including: For each of the heterogeneous data in different locations, the following data standardization process is performed: Determining metadata included in the heterogeneous data in different locations as target metadata; Based on a preset metadata mapping table, performing data standardization processing on the target metadata to obtain standardized metadata; Determine the master data included in the heterogeneous data in different locations as target master data, wherein the target master data includes various business master data, wherein each business master data in the various business master data corresponds to category attribute information; Performing uniqueness cleaning processing on each business master data included in the target master data to obtain each cleaned business master data as the cleaned master data; Standardizing each cleaning service master data included in the cleaning master data to obtain each standardized cleaning service master data; Determine each of the standardized cleaning business master data as standardized master data; Determine a preset service node identifier corresponding to the heterogeneous data in different locations as a target service node identifier; Acquire the service requirement information corresponding to the target service node identifier; Creating a subject data structure corresponding to the business requirement information; Storing the subject data included in the heterogeneous data in the subject data structure to update the subject data structure; determining the updated subject data structure as the standardized subject data; The standardized metadata, the standardized master data, and the standardized subject data are determined as standardized heterogeneous data corresponding to the target business node identifier.

4. The method according to claim 1, wherein: The step of performing consistency detection processing on the metadata to be detected and the master data to be detected based on the target heterogeneous data in different locations to obtain consistency detection information includes: Determining metadata included in the target heterogeneous data in different locations as reference metadata; Based on the reference metadata, performing metadata consistency detection processing on the metadata to be detected to obtain metadata consistency detection information; Determining the master data included in the target heterogeneous data in different locations as reference master data; Based on the reference master data, performing master data consistency detection processing on the master data to be detected to obtain master data consistency detection information; The metadata consistency detection information and the master data consistency detection information are determined as consistency detection information.

5. The method according to claim 4, wherein: The updating process of the service node based on the consistency detection information includes: In response to determining that the metadata consistency detection information included in the consistency detection information indicates that the metadata is inconsistent, sending the reference metadata to the service node so that the service node updates the stored metadata to the reference metadata; In response to determining that the master data consistency detection information included in the consistency detection information indicates that the master data is inconsistent, the reference master data is sent to the service node so that the service node updates the stored master data to the reference master data.

6. A device for maintaining consistency of heterogeneous data in different locations, comprising: A collection unit is configured to collect various heterogeneous data corresponding to various preset business node identifiers; A data standardization processing unit is configured to perform data standardization processing on each of the heterogeneous data to obtain each standardized heterogeneous data corresponding to each of the preset business node identifiers, wherein each standardized heterogeneous data in each of the standardized heterogeneous data includes standardized metadata, standardized master data, and standardized subject data; A storage unit configured to perform encoding storage and permission configuration operations on each of the standardized heterogeneous data in different locations; A sending unit is configured to, in response to receiving an acquisition request message including a preset service node identifier and a data code sent by a preset local client, encrypt and send the standardized heterogeneous data corresponding to the data code to a collaborator corresponding to the preset service node identifier, so that the collaborator heterogeneously translates the standardized heterogeneous data to the preset local client; The consistency maintenance processing unit is configured to perform the following consistency maintenance processing on the metadata and master data stored in the business node corresponding to each preset business node identifier in the preset business node identifier: in response to receiving the consistency maintenance request information sent by the business node, obtain metadata and master data from the business node as metadata to be detected and master data to be detected respectively; determine the heterogeneous data corresponding to the preset business node identifier in the various heterogeneous data as target heterogeneous data; based on the target heterogeneous data, perform consistency detection processing on the metadata to be detected and the master data to be detected to obtain consistency detection information; based on the consistency detection information, update the business node.

7. An electronic device comprising: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 5.

8. A computer readable medium having a computer program stored thereon, wherein: When the program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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