Data management method, device, equipment and medium

Abstract

The present invention relates to a data management method, device, equipment and medium, and to the field of information technology. The method comprises: collecting data of each sub-object of a target object to obtain a total data set; disassembling the total data set to form microservice individuals of each sub-object; storing the microservice individuals of each sub-object in a preset storage system; if a data call request is received, obtaining the data called by the data call request from the microservice individual pointed to by the data call request. The present invention can shorten the delivery time of the requested data within the target object and improve the efficiency of collaborative analysis and collaborative processing of data between the sub-objects within the target object.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and in particular to a data management method, device, equipment and medium. Background Art

[0002] The rapid development of enterprise digital transformation has led to a rapid growth in data, and the sources and structures of enterprise data have become increasingly complex and diverse. According to IDC's survey data, 64.2ZB of data was created or copied in 2020. It is predicted that the compound annual growth rate (CAGR) of global data creation and replication will reach 23% during the forecast period of 2023-2025. More data is created every hour now than was created in a whole year 20 years ago. These massive amounts of data follow the distribution principle of the "80 / 20 rule", that is, the production data of key businesses only accounts for 20%, occupying the high-throughput, low-latency main storage system. The basic architectural model followed by the traditional enterprise data management architecture is a single architecture and single maintenance, but from a realistic perspective, there has never been an architectural model that is suitable for all business forms.

[0003] At present, there are many systems with strict performance requirements in enterprises that run on the monolithic architecture model. This monolithic architecture monolithic software design method makes the interaction between the components within the structure simple and the internal method calls are more efficient. It is suitable for small internal service networks or monolithic I / O data services. However, this traditional design method is not suitable for the collaborative management of data within large enterprises and multiple departments, because they usually use monolithic data storage, such as a SQL server with a single database containing many tables. This central database is used as a persistence engine for all data, and usually part of the application logic is unloaded to the SQL server in the form of queries using complex connections (even stored procedures). Therefore, the monolithic architecture monolithic software design method has major disadvantages both from the perspective of data maintenance and usage, and there are problems such as inefficiency in data development collaboration within large enterprises. Summary of the invention

[0004] The present invention provides a data management method, device, equipment and medium to solve the problem that the monolithic architecture integrated software design method in the prior art has major drawbacks in data maintenance and usage, and makes the internal data development collaboration of large enterprises inefficient.

[0005] In order to solve the above problems, the present invention adopts the following technical solutions:

[0006] In a first aspect, the present invention provides a data management method, the method comprising:

[0007] Collect data of each sub-object of the target object to obtain a total data set;

[0008] Decomposing the total data set to form microservice individuals of each sub-object;

[0009] Store the microservice individuals of each sub-object in the preset storage system;

[0010] If a data call request is received, the data called by the data call request is obtained from the microservice individual pointed to by the data call request.

[0011] A further technical solution is that the data of each sub-object of the target object is collected to obtain a total data set, including:

[0012] Collecting preset data fields in the data of each sub-object of the target object, wherein the data fields include a data processing method;

[0013] Identify each data field having a corresponding data relationship according to the data processing method to obtain an identified data field;

[0014] The identified data fields and the unidentified data fields are taken as a total data set.

[0015] A further technical solution is that the total data set is disassembled to form microservice individuals of each sub-object, including:

[0016] Receive the data requirements of each sub-object of the target object, and use the microservice technology stack to disassemble the total data set according to the data requirements of each sub-object to obtain multiple disassembled data;

[0017] A microservice individual of each sub-object is formed according to the disassembled data.

[0018] A further technical solution is that the data requirements include general functions and independent functions, and the total data set is disassembled using the microservice technology stack according to the data requirements of each sub-object to obtain multiple disassembled data, including:

[0019] Use the microservice technology stack to disassemble the total data set according to common functions and obtain the common fields shared by each sub-object;

[0020] Determine whether each sub-object needs to extend its functions after obtaining the common fields;

[0021] If it is necessary to extend the function, the microservice technology stack is used to disassemble the total data set according to the independent functions of each sub-object to obtain the non-common fields unique to each sub-object; wherein the common fields common to the sub-objects and the non-common fields unique to the sub-objects are the multiple disassembled data.

[0022] A further technical solution is that the preset storage system includes a storage system shared by each sub-object and a storage system unique to each sub-object, and storing the microservice individuals of each sub-object in the preset storage system includes:

[0023] The common fields common to the sub-objects are stored in a storage system shared by the sub-objects, and the non-common fields unique to the sub-objects are stored in a storage system unique to the sub-objects.

[0024] A further technical solution is that after storing the microservice individuals of each sub-object in a preset storage system, the method further includes:

[0025] Register the microservice individuals of each sub-object in the Nacos registration center to obtain registration information, which includes the data calling method, audit files and audit process;

[0026] If a data call request from a microservice individual is received, the data call method, audit file and audit process are displayed in the Nacos registration center, so that the microservice individual submits the data call request for review according to the data call method, the audit file and the audit process;

[0027] The Nacos registration center is used to review the data call request. If the review is passed, the microservice individual is allowed to make data calls.

[0028] A further technical solution is that if a data call request is received, the data called by the data call request is obtained from the microservice individual pointed to by the data call request, including:

[0029] If a data call request is received, a flow control test is performed on the data call request to obtain flow control test center data, wherein the flow control test center data includes a data load scenario and a data load degree;

[0030] A load balancing algorithm is matched according to the data load scenario and the data load degree, and data is called according to the load balancing algorithm.

[0031] In a second aspect, the present invention further provides a data management device, comprising a unit for executing the method as described in the first aspect.

[0032] In a third aspect, the present invention further provides an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0033] Memory, used to store computer programs;

[0034] The processor is used to implement the steps of the method described in the first aspect when executing the program stored in the memory.

[0035] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described in the first aspect.

[0036] The above technical solution provided by the present invention has the following advantages compared with the prior art:

[0037] In the present invention, after collecting the data of each sub-object of the target object to obtain a total data set, the total data set is disassembled to form microservice individuals of each sub-object, so that each independent, small, and well-encapsulated microservice individual can be formed to ensure the convenience of requesting data within the target object; then the microservice individual of each sub-object is stored in a preset storage system, which is conducive to data maintenance and use; if a data call request is received, the data called by the data call request is obtained from the microservice individual pointed to by the data call request, so that each request within the target object is to call data for each microservice individual. This design method shortens the delivery time of request data within the target object and improves the efficiency of collaborative analysis and collaborative processing of data between sub-objects within the target object. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0040] Figure 1 A flowchart of a data management method provided in Example 1 of the present invention;

[0041] Figure 2 A flowchart of a data management method provided in Embodiment 2 of the present invention;

[0042] Figure 3 A structural block diagram of a data management device provided in Embodiment 3 of the present invention;

[0043] Figure 4 A structural block diagram of a data management device provided in Embodiment 4 of the present invention;

[0044] Figure 5 is a load balancing flow chart in an embodiment of the present invention;

[0045] Figure 6 A flowchart of a data management method provided in Embodiment 5 of the present invention;

[0046] Figure 7 A schematic diagram of the structure of an electronic device provided in Example 6 of the present invention. DETAILED DESCRIPTION

[0047] In order to more fully understand the technical content of the present invention, the technical solution of the present invention is further introduced and illustrated in conjunction with specific embodiments below, but is not limited thereto.

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0050] It should also be understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0051] Example 1

[0052] like Figure 1 As shown, Figure 1 The flowchart of a data management method provided in Embodiment 1 of the present invention is shown in FIG. The method can be applied to an electronic device, wherein the electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus, and the present invention does not make any specific limitation on this. Specifically, Figure 1 As shown, the method includes the following steps S101-S104.

[0053] S101, collect data of each sub-object of the target object to obtain a total data set.

[0054] Specifically, when the target object is an enterprise, each sub-object of the target object is the internal departments of the enterprise. The data required by each department of the enterprise is different, so the data of each department of the enterprise needs to be collected first.

[0055] In one embodiment, collecting data of each sub-object of the target object to obtain a total data set includes:

[0056] Collecting preset data fields in the data of each sub-object of the target object, wherein the data fields include a data processing method;

[0057] Identify each data field having a corresponding data relationship according to the data processing method to obtain an identified data field;

[0058] The identified data fields and the unidentified data fields are taken as a total data set.

[0059] Specifically, the collected data is different from traditional data. Traditional data is large in volume and complex in content, while the data currently collected is mainly data fields, that is, preset data fields are collected. The preset data fields are set by the user. For example, the data of the Home Appliance Research Institute are mainly: product model, production time, material composition, etc., but detailed data under this field is not required. Only the names of these data fields, data processing methods, and data privacy permissions need to be collected. The data processing method means that some data may change dynamically with the change of certain data, such as inventory and shipments. The corresponding data relationship should be identified when collecting data. Data privacy permissions can be divided into public, private, and open to review, so that privacy permissions can be protected while designing the architecture.

[0060] S102: Decompose the total data set to form microservice individuals of each sub-object.

[0061] Specifically, after obtaining a relatively detailed data statistics sheet (ie, the total data set), the total data set is disassembled to form microservice individuals of each sub-object.

[0062] In one embodiment, the step of decomposing the total data set to form microservice entities of each sub-object includes:

[0063] Receive the data requirements of each sub-object of the target object, and use the microservice technology stack to disassemble the total data set according to the data requirements of each sub-object to obtain multiple disassembled data;

[0064] A microservice individual of each sub-object is formed according to the disassembled data.

[0065] Specifically, Spring Cloud and Spring Cloud Alibaba microservice technology stacks are used to disassemble the total data set according to the data needs of each department of the enterprise in accordance with the Dubbo protocol standard to obtain multiple disassembled data, and then microservice individuals of each department of the enterprise are formed based on the disassembled data.

[0066] In one embodiment, the data requirements include general functions and independent functions, and the total data set is disassembled using the microservice technology stack according to the data requirements of each sub-object to obtain multiple disassembled data, including:

[0067] Use the microservice technology stack to disassemble the total data set according to common functions and obtain the common fields shared by each sub-object;

[0068] Determine whether each sub-object needs to extend its functions after obtaining the common fields;

[0069] If it is necessary to extend the function, the microservice technology stack is used to disassemble the total data set according to the independent functions of each sub-object to obtain the non-common fields unique to each sub-object; wherein the common fields common to the sub-objects and the non-common fields unique to the sub-objects are the multiple disassembled data.

[0070] Specifically, the total data set is decomposed according to functions by utilizing the independent and modular characteristics of microservices. The decomposition ideas are as follows: data requirements are divided into general functions and independent functions. General functions are functions that all departments have, including but not limited to: login, production, and personnel production management information. These functions are available to all departments and are widely used, while the common fields common to all departments are set as required fields, and non-common fields are set as optional fields. In the process of being issued to each department for use, the optional fields can be freely selected for supplement. Independent functions are unique functions within each department, such as data maintenance and information maintenance in the big data center. For example, when it is determined that department A needs to extend and expand functions after obtaining the general fields, the microservice technology stack is used to decompose the total data set according to the independent functions in the data requirements of department A, and obtain the non-common fields unique to department A. These independent functions are developed separately according to the characteristics of data storage methods, data privacy permissions, data volume, etc., and their development process can be simply understood as a data storage model based on the cloud computing level.

[0071] S103, storing the microservice individuals of each sub-object in a preset storage system.

[0072] Specifically, the microservice individuals of each sub-object are stored in a preset storage system, thereby facilitating the maintenance and use of data.

[0073] In one embodiment, the preset storage system includes a storage system shared by each sub-object and a storage system unique to each sub-object, and storing the microservice individuals of each sub-object in the preset storage system includes:

[0074] The common fields common to the sub-objects are stored in a storage system shared by the sub-objects, and the non-common fields unique to the sub-objects are stored in a storage system unique to the sub-objects.

[0075] Specifically, the development department provides a common storage system (i.e., a storage system shared by all sub-objects) to store common fields common to all departments, thereby solving the problem of high resource consumption in the traditional enterprise data management architecture system. In contrast, the large amount of flooded data in the traditional enterprise data management architecture system not only requires unnecessary storage space, but also generates a large number of data islands, and too many redundant copies of the same data also affect system performance. The architecture in this application makes normal data access or data recovery workload faster; however, if some departments need to expand their own business, they can establish a unique storage system for the non-common fields unique to each department based on the storage system shared by all sub-objects, thereby having their own unique system at a relatively short cost and achieving unification.

[0076] Among them, the unique storage system of each sub-object is obtained by using the Spring Cloud microservice technology stack to decentralize the storage data structure and method similar to that of enterprise departments (decentralization is similar to heating at home, which can be centralized. Of course, some families will build their own central air-conditioning system for heating, which is decentralization). Ensure that each department has its own storage system. This system runs on the system of any basic cloud service provider. And it can be migrated and deployed between different service providers at will. That is, it maintains data security and is more convenient to use and maintain.

[0077] S104: If a data call request is received, the data called by the data call request is obtained from the microservice individual pointed to by the data call request.

[0078] Specifically, when a data call request is received, the data called by the data call request is obtained from the microservice entity pointed to by the data call request. For example, if department A requests to retrieve a certain data in department B, the data called by the data call request (i.e. a certain data) is obtained from the microservice entity pointed to by department A's data call request (i.e. department B).

[0079] In one embodiment, if a data call request is received, obtaining the data called by the data call request from the microservice entity pointed to by the data call request includes:

[0080] If a data call request is received, a flow control test is performed on the data call request to obtain flow control test center data, wherein the flow control test center data includes a data load scenario and a data load degree;

[0081] A load balancing algorithm is matched according to the data load scenario and the data load degree, and data is called according to the load balancing algorithm.

[0082] Specifically, when the amount of data is large and the calls between microservices are frequent, how to deal with it? First, use the Sentinel control to perform flow control detection and obtain the Sentinel flow control detection center data. Different scenarios and degrees of data load are obtained from the Sentinel flow control detection center data, and different load balancing algorithms are used to call data according to different scenarios and degrees of data load. Of course, in the step of disassembling the total data set to form the microservice individuals of each sub-object, permission isolation is used while encapsulating the data, such as blacklists and whitelists. Blacklists and whitelists are established in the permission configuration center of the Nacos registration center. The blacklist personnel stipulate that some data is inaccessible and the whitelist is accessible, thereby adopting the Nacos service hierarchical storage model, using environmental isolation to avoid departmental data permissions disorder and loss of control, and using load balancing algorithms to solve the problem of high resource consumption of enterprise data management architecture.

[0083] Load balancing mainly controls the flow of external requests to call the headquarters data or internal calls to the enterprise data. If a part of the data is called frequently, it will enter the monitoring queue. This not only ensures data security, but also allows the data source to be quickly found the next time it is called.

[0084] like Figure 5As shown, the load balancing process is as follows: Step 1, send a request: The requesting end sends a request based on the URL (data interface), and the receiving end is the load balancing client. Step 2, obtain the data information in the request URL received by the client: The balancing end obtains the data information in the request URL received by the load balancing client (such as data such as what department needs to be requested). Step 3, receive the request and make a call: The server, that is, the storage center receives the request and makes a call. Step 4: The server returns a data list (for example, the data list includes: localhost:8081, loclahost:8082). Step 5, return the data list and the detected traffic situation to the rule distribution center: The load balancing client receives the data list and returns the detected traffic situation to the rule distribution center. Step 6: The rule distribution center selects the appropriate algorithm and the service part in the data list (for example, select localhost:8081) based on the returned situation and returns the data.

[0085] Specifically, compared with the existing technology, the existing technology requires two operations on data, one is to export from the production environment, and the second is to import into the non-production environment, which is time-consuming and time-consuming. The import and export of data requires manual operation and cannot be completed automatically. In addition, manual transmission is required to complete the migration of data from the production environment to the test environment, which has a high labor cost.

[0086] The present application collects the data of each sub-object of the target object to obtain the total data set, then disassembles the total data set to form the microservice individuals of each sub-object, so that each independent small and well-encapsulated microservice individual can ensure the convenience of requesting data inside the target object; then the microservice individuals of each sub-object are stored in a preset storage system, which is conducive to the maintenance and use of data; if a data call request is received, the data called by the data call request is obtained from the microservice individual pointed to by the data call request, so that each request inside the target object is to call data for each microservice individual. This design method shortens the delivery time of the target object internal request data and improves the efficiency of data collaborative analysis and collaborative processing between the sub-objects inside the target object. And each independent small and well-encapsulated microservice individual is formed. The architecture of microservice technology can better balance the pressure problem between permission granularity and account management, better implement the security strategy based on user and permission separation, control the user's data use behavior at the minimum granularity, and prevent the occurrence of high-risk situations.

[0087] Example 2

[0088] See also Figure 2 , Figure 2The flowchart of a data management method provided in Example 2 of the present invention is shown in FIG. The data management method in Example 2 includes steps S201-S207, wherein steps S201-S204 are similar to steps S101-S104 in Example 1 above and are not described in detail here. Steps S205-S207 added in this embodiment are described in detail below.

[0089] S205, registering the microservice individuals of each sub-object in the Nacos registration center to obtain registration information, wherein the registration information includes a data calling method, an audit file, and an audit process.

[0090] S206: If a data call request from a microservice individual is received, the data call method, the audit file, and the audit process are displayed in the Nacos registration center, so that the microservice individual submits the data call request for review according to the data call method, the audit file, and the audit process.

[0091] S207, using the Nacos registration center to review the data call request, if the review is passed, the microservice individual is allowed to make data calls.

[0092] Specifically, after all the data systems developed and stored according to functional classification are established, there is a problem: how to manage the independent data systems in an orderly and unified manner? A key technology is adopted - Nacos Registration Center. A single data system is registered in the Nacos Registration Center, that is, the microservice individuals of each sub-object are registered in the Nacos Registration Center, so that management and maintenance personnel can directly view the running status and data permissions of the microservice system in the Nacos Registration Center. When a microservice wants to call the data interface of another microservice during development or production, it can directly view the data calling method, audit files, and audit process in the registration center. After the submission and audit are successful, the data packaged by another microservice can be directly called.

[0093] Example 3

[0094] like Figure 3 As shown, an embodiment of the present invention further provides a data management device 400 , which includes a first collection unit 401 , a first disassembly unit 402 , a first storage unit 403 , and a first acquisition unit 404 .

[0095] The first collecting unit 401 is used to collect data of each sub-object of the target object to obtain a total data set;

[0096] A first disassembling unit 402 is used to disassemble the total data set to form microservice individuals of each sub-object;

[0097] The first storage unit 403 is used to store the microservice individual of each sub-object in a preset storage system;

[0098] The first acquisition unit 404 is configured to, upon receiving a data call request, acquire the data called by the data call request from the microservice entity pointed to by the data call request;

[0099] In one embodiment, collecting data of each sub-object of the target object to obtain a total data set includes:

[0100] Collecting preset data fields in the data of each sub-object of the target object, wherein the data fields include a data processing method;

[0101] Identify each data field having a corresponding data relationship according to the data processing method to obtain an identified data field;

[0102] The identified data fields and the unidentified data fields are taken as a total data set.

[0103] In one embodiment, the step of decomposing the total data set to form microservice entities of each sub-object includes:

[0104] Receive the data requirements of each sub-object of the target object, and use the microservice technology stack to disassemble the total data set according to the data requirements of each sub-object to obtain multiple disassembled data;

[0105] A microservice individual of each sub-object is formed according to the disassembled data.

[0106] In one embodiment, the data requirements include general functions and independent functions, and the total data set is disassembled using the microservice technology stack according to the data requirements of each sub-object to obtain multiple disassembled data, including:

[0107] Use the microservice technology stack to disassemble the total data set according to common functions and obtain the common fields shared by each sub-object;

[0108] Determine whether each sub-object needs to extend its functions after obtaining the common fields;

[0109] If it is necessary to extend the function, the microservice technology stack is used to disassemble the total data set according to the independent functions of each sub-object to obtain the non-common fields unique to each sub-object; wherein the common fields common to the sub-objects and the non-common fields unique to the sub-objects are the multiple disassembled data.

[0110] In one embodiment, the preset storage system includes a storage system shared by each sub-object and a storage system unique to each sub-object, and storing the microservice individuals of each sub-object in the preset storage system includes:

[0111] The common fields common to the sub-objects are stored in a storage system shared by the sub-objects, and the non-common fields unique to the sub-objects are stored in a storage system unique to the sub-objects.

[0112] In one embodiment, if a data call request is received, obtaining the data called by the data call request from the microservice entity pointed to by the data call request includes:

[0113] If a data call request is received, a flow control test is performed on the data call request to obtain flow control test center data, wherein the flow control test center data includes a data load scenario and a data load degree;

[0114] A load balancing algorithm is matched according to the data load scenario and the data load degree, and data is called according to the load balancing algorithm.

[0115] Example 4

[0116] like Figure 4 As shown, the embodiment of the present invention further provides a data management device 400 , which differs from the data management device 400 proposed in Embodiment 3 in that it further includes: a first registration unit 405 , a first display unit 406 , and a first review unit 407 .

[0117] The first registration unit 405 is used to register the microservice individual of each sub-object in the Nacos registration center to obtain registration information, which includes the data calling method, audit file and audit process;

[0118] The first display unit 406 is used to display the data calling method, audit file and audit process in the Nacos registration center if a data calling request of a microservice individual is received, so that the microservice individual submits the data calling request for review according to the data calling method, the audit file and the audit process;

[0119] The first review unit 407 is used to review the data call request using the Nacos registration center, and if the review is passed, the microservice individual is allowed to make data calls.

[0120] Example 5

[0121] like Figure 6As shown, Embodiment 5 of the present invention is a flowchart of a data management method provided when the target object is an enterprise and each sub-object of the target object is a department within the enterprise. The method can be applied to an electronic device, the electronic device includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus, which is not specifically limited by the present invention. Specifically, Figure 6 As shown, the method includes the following steps S301-S306.

[0122] S301, collect data from various departments within the enterprise.

[0123] S302, design a basic storage system based on the common parts of data of various departments within the enterprise.

[0124] S303, determining whether each department needs to extend the storage after obtaining the basic storage.

[0125] S304: If storage extension is required, storage is developed according to the needs of each department.

[0126] S305, establish cloud service and cloud computing on the server.

[0127] S306, each microservice publishes a request interface document to call data.

[0128] Example 6

[0129] like Figure 7 As shown, an embodiment of the present invention further provides an electronic device, including a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other through the communication bus 114.

[0130] Memory 113, used for storing computer programs;

[0131] The processor 111 is used to execute the program stored in the memory 113 to implement the data management method provided in the above embodiment.

[0132] The embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by the processor 111, the steps of the data management method provided in the above embodiment are implemented.

[0133] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0134] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A data management method, characterized in that: The method comprises: Collect data of each sub-object of the target object to obtain a total data set; Decomposing the total data set to form microservice individuals of each sub-object; Store the microservice individuals of each sub-object in the preset storage system; If a data call request is received, the data called by the data call request is obtained from the microservice individual pointed to by the data call request; The step of disassembling the total data set to form microservice individuals of each sub-object includes: Receive the data requirements of each sub-object of the target object, and use the microservice technology stack to disassemble the total data set according to the data requirements of each sub-object to obtain multiple disassembled data; Forming microservice individuals of each sub-object according to the disassembled data; The data requirements include general functions and independent functions. The total data set is disassembled using the microservice technology stack according to the data requirements of each sub-object to obtain multiple disassembled data, including: Use the microservice technology stack to disassemble the total data set according to common functions and obtain the common fields shared by each sub-object; Determine whether each sub-object needs to extend its functions after obtaining the common fields; If it is necessary to extend the function, the microservice technology stack is used to disassemble the total data set according to the independent functions of each sub-object to obtain the non-common fields unique to each sub-object; wherein the common fields common to the sub-objects and the non-common fields unique to the sub-objects are the multiple disassembled data.

2. The data management method according to claim 1, characterized in that: The data of each sub-object of the target object is collected to obtain a total data set, including: Collecting preset data fields in the data of each sub-object of the target object, wherein the data fields include a data processing method; Identify each data field having a corresponding data relationship according to the data processing method to obtain an identified data field; The identified data fields and the unidentified data fields are taken as a total data set.

3. The data management method according to claim 1, characterized in that: The preset storage system includes a storage system shared by each sub-object and a storage system unique to each sub-object. The storing of the microservice individuals of each sub-object in the preset storage system includes: The common fields common to the sub-objects are stored in a storage system shared by the sub-objects, and the non-common fields unique to the sub-objects are stored in a storage system unique to the sub-objects.

4. The data management method according to claim 1, characterized in that: After storing the microservice individuals of each sub-object in a preset storage system, the method further includes: Register the microservice individuals of each sub-object in the Nacos registration center to obtain registration information, which includes the data calling method, audit files and audit process; If a data call request from a microservice individual is received, the data call method, audit file and audit process are displayed in the Nacos registration center, so that the microservice individual submits the data call request for review according to the data call method, the audit file and the audit process; The Nacos registration center is used to review the data call request. If the review is passed, the microservice individual is allowed to make data calls.

5. The data management method according to claim 1, characterized in that: If a data call request is received, obtaining the data called by the data call request from the microservice individual pointed to by the data call request includes: If a data call request is received, a flow control test is performed on the data call request to obtain flow control test center data, wherein the flow control test center data includes a data load scenario and a data load degree; A load balancing algorithm is matched according to the data load scenario and the data load degree, and data is called according to the load balancing algorithm.

6. A data management device, characterized in that: The method comprises a unit for executing the method according to any one of claims 1 to 5.

7. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, for implementing the steps of the method described in any one of claims 1 to 5 when executing a program stored in a memory.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

Images