A cluster data management method and device

Abstract

The embodiment of the present invention discloses a cluster data management method and device, which collects all data types, assigns category numbers to different types of data, assigns interval numbers to data in different databases, and establishes a matching number of transmission channels for the database according to the data popularity corresponding to the data type. In the embodiment, the category number and interval number are set in advance, and the data encoding of each piece of data is set in combination with the category number and interval number, so that the target data can be quickly matched according to the data request input by the target user, and the corresponding database is assigned to the target data. The management efficiency is higher, the user waiting time is greatly reduced, and the user experience is higher. Multiple transmission channels are established for databases with popular demand, which is more convenient for transmitting multiple copies of data to users at the same time.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and in particular to a cluster data management method and device. Background Art

[0002] A cluster is a high-performance computing system that connects multiple computers in a local area network or the Internet, and uses software and hardware to achieve resource sharing and task allocation to jointly complete a task. Clusters are mainly used in large-scale data processing, scientific computing, digital media processing and other fields, and can provide higher computing efficiency and larger data storage capacity. Using at least two or more database servers, a virtual single database logical image is formed, which can provide transparent data services to clients like a single database system.

[0003] Currently, it is often difficult to carry out timely linkage for cluster data management, and there is no more efficient transmission method for data types with high client demand, which reduces the user experience. Summary of the invention

[0004] In view of the above-mentioned defects, an embodiment of the present invention discloses a cluster data management method and device, which increase the transmission channel of high-demand data and improve transmission efficiency.

[0005] A first aspect of an embodiment of the present invention discloses a cluster data management method, comprising:

[0006] Collect all data types of data in each database, assign corresponding category numbers to each type of data, and assign corresponding interval numbers to each database, and form data codes for each piece of data based on the category numbers and interval numbers;

[0007] Calculate the data heat corresponding to different data types, and establish at least two transmission channels for databases whose data heat meets the conditions;

[0008] Receive a data request input by a target user, obtain target data according to the data request, and assign corresponding data codes according to the data type corresponding to the target data.

[0009] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the calculating of data heat corresponding to different data types includes:

[0010] Collect the number of downloads of each type of data within a certain preset period;

[0011] Calculate the download popularity of the data within any preset period according to the number of downloads within the preset period;

[0012] The average value of all download heats corresponding to any type of data is calculated to generate the data heat corresponding to the type of data.

[0013] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the step of establishing at least two transmission channels for a database whose data heat satisfies a condition includes:

[0014] Sort different types of data by popularity, and select the top N data types as hot data types;

[0015] It is determined whether the number of hot data types in any database is greater than a first threshold, and when the number is greater than the first threshold, at least two transmission channels are established for the database.

[0016] As an optional implementation manner, in the first aspect of the embodiment of the present invention, when the value is greater than the first threshold, at least two transmission channels are established for the database, including:

[0017] When the number of hot data types in the database is greater than a second threshold, three transmission channels are established for the database;

[0018] When the number of hot data types in the database is greater than the first threshold and less than the second threshold, two transmission channels are established for the database.

[0019] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the assigning corresponding data codes according to the data type corresponding to the target data includes:

[0020] Obtain all preliminary databases that match the data type, and calculate the evaluation value of each preliminary database;

[0021] A preliminary database with the highest current evaluation value is selected as a target database, and data encodings of data corresponding to the data type in the target database are obtained.

[0022] As an optional implementation manner, in the first aspect of the embodiment of the present invention, the calculating of the evaluation value of each preliminary selected database includes:

[0023] Obtaining the number of transmission channels of each preliminary selected database, and matching the corresponding first evaluation value according to the number of transmission channels;

[0024] Obtaining the number of times each primary selected database sends data within a set time range and calculating a success index for successful data sending, and generating a second evaluation value based on the number of times data is sent and the success index;

[0025] An evaluation value of the preliminary selection database is obtained according to the first evaluation value and the second evaluation value.

[0026] As an optional implementation manner, in the first aspect of the embodiment of the present invention, it also includes:

[0027] When the database corresponding to the allocated data code is occupied when the target data corresponding to the data code is sent, a new data code is allocated.

[0028] A second aspect of an embodiment of the present invention discloses a cluster data management device, including:

[0029] Type collection module: used to collect all data types of data in each database, assign corresponding category numbers to each type of data, and assign corresponding interval numbers to each database, and form data codes for each piece of data based on category numbers and interval numbers;

[0030] Heat calculation module: used to calculate the data heat corresponding to different data types, and establish at least two transmission channels for databases whose data heat meets the conditions;

[0031] Coding allocation module: used to receive data requests input by target users, obtain target data according to the data requests, and allocate corresponding data codes according to the data type corresponding to the target data.

[0032] As an optional implementation, in the second aspect of the embodiment of the present invention, the calculating of data heat corresponding to different data types includes:

[0033] Collect the number of downloads of each type of data within a certain preset period;

[0034] Calculate the download popularity of the data within any preset period according to the number of downloads within the preset period;

[0035] The average value of all download heats corresponding to any type of data is calculated to generate the data heat corresponding to the type of data.

[0036] As an optional implementation, in the second aspect of the embodiment of the present invention, the step of establishing at least two transmission channels for a database whose data heat satisfies a condition includes:

[0037] Sort different types of data by popularity, and select the top N data types as hot data types;

[0038] It is determined whether the number of hot data types in any database is greater than a first threshold, and when the number is greater than the first threshold, at least two transmission channels are established for the database.

[0039] As an optional implementation manner, in the second aspect of the embodiment of the present invention, when the value is greater than the first threshold, at least two transmission channels are established for the database, including:

[0040] When the number of hot data types in the database is greater than a second threshold, three transmission channels are established for the database;

[0041] When the number of hot data types in the database is greater than the first threshold and less than the second threshold, two transmission channels are established for the database.

[0042] As an optional implementation, in the second aspect of the embodiment of the present invention, the assigning corresponding data codes according to the data type corresponding to the target data includes:

[0043] Obtain all preliminary databases that match the data type, and calculate the evaluation value of each preliminary database;

[0044] A preliminary database with the highest current evaluation value is selected as a target database, and data encodings of data corresponding to the data type in the target database are obtained.

[0045] As an optional implementation manner, in the second aspect of the embodiment of the present invention, the calculating of the evaluation value of each preliminary selected database includes:

[0046] Obtaining the number of transmission channels of each preliminary selected database, and matching the corresponding first evaluation value according to the number of transmission channels;

[0047] Obtaining the number of times each primary selected database sends data within a set time range and calculating a success index for successful data sending, and generating a second evaluation value based on the number of times data is sent and the success index;

[0048] An evaluation value of the preliminary selection database is obtained according to the first evaluation value and the second evaluation value.

[0049] As an optional implementation manner, in the second aspect of the embodiment of the present invention, it also includes:

[0050] When the database corresponding to the allocated data code is occupied when the target data corresponding to the data code is sent, a new data code is allocated.

[0051] A third aspect of an embodiment of the present invention discloses an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the cluster data management method disclosed in the first aspect of the embodiment of the present invention.

[0052] A fourth aspect of an embodiment of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the cluster data management method disclosed in the first aspect of an embodiment of the present invention.

[0053] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0054] A cluster data management method disclosed in an embodiment of the present invention collects all data types, assigns category numbers to different types of data, assigns interval numbers to data in different databases, and establishes a matching number of transmission channels for the database according to the data popularity corresponding to the data type. In the embodiment, the category number and interval number are set in advance, and the data encoding of each piece of data is set in combination with the category number and the interval number, so that the target data can be quickly matched according to the data request input by the target user, and the corresponding database is assigned to the target data. The management efficiency is higher, the user waiting time is greatly reduced, and the user experience is higher. Multiple transmission channels are established for databases with popular demands, which is more convenient for transmitting multiple copies of data to users at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0056] Figure 1 It is a flow chart of a cluster data management method disclosed in an embodiment of the present invention;

[0057] Figure 2 It is a structural diagram of a cluster data management device provided by an embodiment of the present invention;

[0058] Figure 3 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] 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 only 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.

[0060] It should be noted that the terms "first", "second", "third", "fourth", etc. in the specification and claims of the present invention are used to distinguish different objects rather than to describe a specific order. The terms "including" and "having" in the embodiments of the present invention and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device including a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0061] The embodiment of the present invention discloses a cluster data management method, device, electronic device and storage medium. By collecting all data types, assigning category numbers to different types of data, assigning interval numbers to data in different databases, and establishing a matching number of transmission channels for the database according to the data popularity corresponding to the data type, the embodiment sets the category number and interval number in advance, and sets the data encoding of each piece of data in combination with the category number and interval number, and then can quickly match the target data according to the data request input by the target user, and assign the corresponding database to the target data, the management efficiency is higher, the user waiting time is greatly reduced, the user experience is higher, and multiple transmission channels are established for databases with popular demand, which is more convenient for transmitting multiple copies of data to users at the same time.

[0062] Embodiment 1

[0063] See also Figure 1 , Figure 1 It is a flow chart of a cluster data management method disclosed in an embodiment of the present invention. Among them, the execution subject of the method described in the embodiment of the present invention is an execution subject composed of software and / or hardware, and the execution subject can receive relevant information by wired or / and wireless means, and can send certain instructions. Of course, it can also have certain processing functions and storage functions. The execution subject can control multiple devices, such as a remote physical server or cloud server and related software, or it can be a local host or server and related software that performs related operations on a device placed somewhere. In some scenarios, multiple storage devices can also be controlled, and the storage devices can be placed in the same place or different places as the devices. For example Figure 1 As shown, the cluster data management method includes the following steps:

[0064] 101. Collect all data types of data in each database, assign a corresponding category number to each type of data, and a corresponding interval number to each database, and form a data code for each piece of data based on the category number and interval number.

[0065] In an embodiment, a cluster includes multiple databases, each of which stores multiple types of data, but different databases may store the same type of data, for example, data type 1 is stored in database A, and data type 1 is also stored in database B, or even the same data. The same category number is assigned to the same data type, and an interval number is assigned to the database, that is, the category number is used to identify the data of the same type, and the interval number is used to identify the database. For example, data 1 and data 2 are both of the same data type, so the category number of data 1 and data 2 is the same, but data 1 is stored in database A, and data 2 is stored in database B, so data 1 and data 2 have different interval numbers, so the data encoding of the two must be different.

[0066] 102. Calculate the data heat corresponding to different data types, and establish at least two transmission channels for databases whose data heat meets the conditions.

[0067] In the embodiment, data heat refers to the number of times requested by users to download. In the embodiment, calculating the data heat corresponding to different data types includes: collecting the number of downloads of each type of data within a plurality of preset periods; calculating the download heat of the data of this type within the preset period according to the number of downloads within any preset period; and averaging all the download heats corresponding to any type of data to generate the data heat corresponding to the data of this type.

[0068] In the embodiment, the data heat meets the conditions, that is, for the data stored in the database, the overall data heat meets the requirements. Specifically, different types of data are sorted according to the order of data heat from large to small, and the data types ranked in the top N are selected as hot data types; determine whether the number of hot data types in any database is greater than the first threshold, and when it is greater than the first threshold, establish at least two transmission channels for the database. N is a natural number, and N is not 0. The specific value of N can be set according to actual needs, for example, N=4.

[0069] The numerical value of the first threshold is also set according to actual needs, and the first threshold is greater than 0. Specifically, when the number of hot data types in the database is greater than the second threshold, three transmission channels are established for the database; when the number of hot data types in the database is greater than the first threshold and less than the second threshold, two transmission channels are established for the database.

[0070] 103. Receive a data request input by a target user, obtain target data according to the data request, and assign a corresponding data code according to a data type corresponding to the target data.

[0071] The target user is the user who accesses the system and makes data requests. The user needs to log in to the system, and then the user's account information can be obtained, the user's historical access needs can be understood, and the access preferences can be further understood, so that more personalized solutions can be provided in the future. The data request is the data that the target user wants to download.

[0072] In this step, the corresponding data code is assigned according to the data type corresponding to the target data, including: obtaining all the preliminary databases that match the data type, and calculating the evaluation value of each preliminary database; selecting the preliminary database with the highest current evaluation value as the target database, and obtaining the data code of the data corresponding to the data type in the target database. For example, the data request of the target user corresponds to data type a, specifically corresponding to data 1, that is, data 1 is data type a, and at this time, database 1 and database 2 both store data 1, then one of the databases is arranged to transmit data 1 to the target user, and the arranged database interval number is xx1, and the data code includes xx1 and the type number.

[0073] The embodiment calculates the evaluation value of each preliminary database, including: obtaining the number of transmission channels of each preliminary database, matching the corresponding first evaluation value according to the number of transmission channels; obtaining the number of times each preliminary database sends data within a set time range and calculating the success index of successfully sending data, generating a second evaluation value based on the number of times data is sent and the success index; obtaining the evaluation value of the preliminary database according to the first evaluation value and the second evaluation value. In the system, a matching table of the number of transmission channels and the first evaluation value has been set in advance, for example, the number of transmission channels 1 corresponds to 5 points, the number of transmission channels 2 corresponds to 8 points, and the number of transmission channels 3 corresponds to 10 points. The success index of successfully sending data is also the proportion of successful sending. For example, database 1 sends data 100 times, and 98 times are successfully received by the client, then the success index is 98%. The more times the number of transmissions is, the greater the demand for the database is, and the more popular it is. The higher the success index is, the more stable the transmission data is. Generally, the more times the number of transmissions is, the lower the success index is. Therefore, the second evaluation value is calculated by combining the number of transmissions and the success index. For example, for transmissions between 0 and 50 times, the success index of more than 99% is 5 points for the evaluation score, while the success index of less than 99% is 3 points. For transmissions between 200 and 300 times, the evaluation score of more than 99% is 10 points, and the success index between 98 and 99% is 8 points, and so on. The above are all examples, and can be set according to actual conditions. The evaluation score can also be the second evaluation value, and the number of transmissions can be scored again separately. The second evaluation value can also be the evaluation score plus the score of the number of transmissions. The evaluation value of the primary selection database obtained by the embodiment according to the first evaluation value and the second evaluation value is the first evaluation value plus the second evaluation value.

[0074] The embodiment may further include allocating a new data code when the database corresponding to the allocated data code is occupied when the target data corresponding to the data code is sent.

[0075] That is, for example, if the target user's data demand is data 1, it is allocated to database A. In fact, there are databases B and C that both store data 1. When the evaluation value is calculated for database allocation, database A is not occupied. For example, if the customer makes an appointment to download data at 10:00am, at this time, database A is occupied and other data is being transmitted. At this time, database B and database C are considered. The embodiment is flexibly mobilized in combination with the current actual situation, more personalized to meet user needs, and provide user data experience.

[0076] Embodiment 2

[0077] See also Figure 2 , Figure 2 Schematic diagram of the structure of a cluster data management device disclosed in an embodiment of the present invention. Figure 2 As shown, the cluster data management device may include: a type collection module 201, a heat calculation module 202 and a code allocation module 203, wherein the type collection module 201: is used to collect all data types of data in each database, assign a corresponding category number to each type of data, and assign a corresponding interval number to each database, and form a data code for each piece of data based on the category number and the interval number; the heat calculation module 202: is used to calculate the data heat corresponding to different data types, and establish at least two transmission channels for databases whose data heat meets the conditions; the code allocation module 203: is used to receive a data request input by a target user, obtain target data according to the data request, and allocate a corresponding data code according to the data type corresponding to the target data.

[0078] In the heat calculation module 202, the data heat corresponding to different data types is calculated, including: collecting the number of downloads of each type of data within several preset time periods; calculating the download heat of this type of data within any preset time period based on the number of downloads within the preset time period; and taking the average value based on all the download heats corresponding to any type of data to generate the data heat corresponding to this type of data.

[0079] Furthermore, at least two transmission channels are established for databases whose data heat meets the conditions, including: sorting different types of data according to the order of data heat from large to small, and selecting the data types ranked in the top N as hot data types; judging whether the number of hot data types in any database is greater than a first threshold, and establishing at least two transmission channels for the database when it is greater than the first threshold. When it is greater than the first threshold, at least two transmission channels are established for the database, including: when the number of hot data types in the database is greater than the second threshold, three transmission channels are established for the database; when the number of hot data types in the database is greater than the first threshold and less than the second threshold, two transmission channels are established for the database.

[0080] In the coding allocation module 203, corresponding data coding is allocated according to the data type corresponding to the target data, including: obtaining all preliminary databases that match the data type and calculating the evaluation value of each preliminary database; selecting the preliminary database with the highest current evaluation value as the target database, and obtaining the data coding of the data corresponding to the data type in the target database.

[0081] Furthermore, the above-mentioned calculation of the evaluation value of each preliminary database includes obtaining the number of transmission channels of each preliminary database, and matching the corresponding first evaluation value according to the number of transmission channels; obtaining the number of times each preliminary database sends data within a set time range and calculating the success index of successfully sending the data, and generating a second evaluation value based on the number of times the data is sent and the success index; and obtaining the evaluation value of the preliminary database according to the first evaluation value and the second evaluation value.

[0082] The embodiment may further include a reallocation module for allocating a new data code when the database corresponding to the allocated data code is occupied when the target data corresponding to the data code is sent.

[0083] Embodiment 3

[0084] See also Figure 3 , Figure 3 Schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention. The electronic device may be a computer, a server, etc. Of course, in certain circumstances, it may also be a smart device such as a mobile phone, a tablet computer, a monitoring terminal, and an image acquisition device with processing functions. Figure 3 As shown, the electronic device may include:

[0085] A memory 301 storing executable program codes;

[0086] a processor 302 coupled to the memory 301;

[0087] The processor 302 calls the executable program code stored in the memory 301 to execute part or all of the steps in the cluster data management method in the first embodiment.

[0088] An embodiment of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute part or all of the steps in the cluster data management method in the first embodiment.

[0089] The embodiment of the present invention further discloses a computer program product, wherein when the computer program product is run on a computer, the computer is enabled to execute part or all of the steps in the cluster data management method in the first embodiment.

[0090] An embodiment of the present invention further discloses an application publishing platform, wherein the application publishing platform is used to publish a computer program product, wherein when the computer program product runs on a computer, the computer executes part or all of the steps in the cluster data management method in embodiment one.

[0091] In various embodiments of the present invention, it should be understood that the size of the serial numbers of the processes does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0092] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, i.e., they may be located in one place or distributed over multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0093] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0094] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-accessible memory. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product, which is stored in a memory and includes several requests for a computer device (which can be a personal computer, a server or a network device, etc., specifically a processor in a computer device) to perform some or all of the steps of the method described in each embodiment of the present invention.

[0095] In the embodiments provided by the present invention, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.

[0096] A person of ordinary skill in the art can understand that some or all of the steps in the various methods of the embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0097] The cluster data management method, device, electronic device and storage medium disclosed in the embodiments of the present invention are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A cluster data management method, characterized in that: include: Collect all data types of data in each database, assign corresponding category numbers to each type of data, and assign corresponding interval numbers to each database, and form data codes for each piece of data based on the category numbers and interval numbers; Calculate the data heat corresponding to different data types, sort the data of different types according to the order of data heat from large to small, and select the data types ranked in the top N as hot data types; determine whether the number of hot data types in any database is greater than a first threshold, and if it is greater than the first threshold, establish at least two transmission channels for the database; Receive a data request input by a target user, obtain target data according to the data request, obtain all preliminary databases matching the data type, and obtain the number of transmission channels of each preliminary database, and match the corresponding first evaluation value according to the number of transmission channels; obtain the number of times each preliminary database sends data within a set time range and calculate the success index of successfully sending data, and generate a second evaluation value based on the number of times the data is sent and the success index; obtain the evaluation value of the preliminary database according to the first evaluation value and the second evaluation value; Selecting the primary database with the highest current evaluation value as the target database, and obtaining the data code of the data corresponding to the data type in the target database; When the database corresponding to the allocated data code is occupied when the target data corresponding to the data code is sent, a new data code is allocated.

2. The cluster data management method according to claim 1, characterized in that: The calculation of data heat corresponding to different data types includes: Collect the number of downloads of each type of data within a certain preset period; Calculate the download popularity of the data within any preset period according to the number of downloads within the preset period; The average value of all download heats corresponding to any type of data is calculated to generate the data heat corresponding to the type of data.

3. The cluster data management method according to claim 1, characterized in that: When the value is greater than the first threshold, at least two transmission channels are established for the database, including: When the number of hot data types in the database is greater than a second threshold, three transmission channels are established for the database; When the number of hot data types in the database is greater than the first threshold and less than the second threshold, two transmission channels are established for the database.

4. A cluster data management device, characterized in that: include: Type collection module: used to collect all data types of data in each database, assign corresponding category numbers to each type of data, and assign corresponding interval numbers to each database, and form data coding for each piece of data based on the category number and interval number; Heat calculation module: used to calculate the data heat corresponding to different data types, sort the data of different types according to the order of data heat from large to small, and select the data types ranked in the top N as hot data types; determine whether the number of hot data types in any database is greater than a first threshold, and if it is greater than the first threshold, establish at least two transmission channels for the database; Coding allocation module: used to receive a data request input by a target user, obtain target data according to the data request, obtain all preliminary databases matching the data type, and obtain the number of transmission channels of each preliminary database, and match the corresponding first evaluation value according to the number of transmission channels; obtain the number of times each preliminary database sends data within a set time range and calculate the success index of successfully sending data, and generate a second evaluation value based on the number of times the data is sent and the success index; obtain the evaluation value of the preliminary database according to the first evaluation value and the second evaluation value; Selecting the primary database with the highest current evaluation value as the target database, and obtaining the data code of the data corresponding to the data type in the target database; The reallocation module is used to allocate a new data code when the database corresponding to the allocated data code is occupied when the target data corresponding to the data code is sent.

5. An electronic device, characterized in that: include: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the cluster data management method according to any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program enables a computer to execute the cluster data management method according to any one of claims 1 to 3.

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