Computing power resource scheduling method and related device

Abstract

The invention discloses a computing power resource scheduling method and a related device, relates to the technical field of IT (Information Technology), and aims at presetting a corresponding relationship between a scheduling algorithm identifier and computing power resource data and realizing configuration of a scheduling algorithm. Obtaining a to-be-deployed business program; obtaining a target scheduling algorithm identifier corresponding to the to-be-deployed business program; searching target computing power resource data corresponding to the target scheduling algorithm identifier from a preset corresponding relationship between the scheduling algorithm identifier and the computing power resource data; based on the scheduling algorithm with the target scheduling algorithm identifier and the target computing power resource data, the resource demand and the available computing power resource of the business program, namely the target server, can be accurately matched. According to the method, codes do not need to be modified, and different service scene requirements and scene changes can be adapted only by configuring different scheduling algorithm identifiers, so that the flexibility is greatly improved; therefore, the purpose of more flexible and efficient computing power resource scheduling is achieved.

Description

Technical Field

[0001] The present application relates to the field of IT technology, and in particular to a computing resource scheduling method and related devices. Background Art

[0002] In the computing resource scheduling method, hard coding is usually used to support computing resource types and scheduling algorithms. For example, if a new scheduling algorithm is introduced, a new scheduling algorithm needs to be written. As business scenarios develop and market demand changes, scheduling algorithms may continue to increase and update. If each increase or update of the scheduling algorithm needs to be implemented through hard coding, the amount of code in the computing resource scheduling method will expand dramatically, and the complexity of the code will continue to increase, making it difficult to manage and maintain.

[0003] Therefore, there is an urgent need for a more flexible and efficient computing resource scheduling method to better meet the needs of business scenario development. Summary of the invention

[0004] In view of the above problems, the present application provides a computing resource scheduling method and related devices to achieve a more flexible and efficient computing resource scheduling. The specific scheme is as follows: The first aspect of the present application provides a computing resource scheduling method, comprising: Obtain the business program to be deployed; Obtain the target scheduling algorithm identifier corresponding to the business program to be deployed; From the correspondence between the preset scheduling algorithm identifier and the computing power resource data, searching for the target computing power resource data corresponding to the target scheduling algorithm identifier; Based on the scheduling algorithm having the target scheduling algorithm identifier and the target computing resource data, a target server for deploying the business program is determined.

[0005] In a possible implementation, a method for constructing a corresponding relationship between the target scheduling algorithm identifier and the target computing power resource data includes: In response to the operation of setting the computing power resource data of the target scheduling algorithm, controlling the display of the scheduling algorithm configuration interface; Determine a data model table through the scheduling algorithm configuration interface, wherein the data model table includes a first field set corresponding to a plurality of servers respectively, and the first field set includes a plurality of fields and computing power resource values ​​corresponding to the plurality of fields respectively; Determining a target field from a plurality of fields included in the data model table through the scheduling algorithm configuration interface; Determining the filtering condition of the target field through the scheduling algorithm configuration interface; Determine that a second field set corresponding to at least one server in the data model table is computing power resource data identified by the target scheduling algorithm, and the second field set includes computing power resource values ​​of the target field that meet the filtering conditions.

[0006] In a possible implementation, after obtaining the service program to be deployed, the following is further included: Acquire target scheduling resources required by the business program; Accordingly, the step of determining the target server for deploying the business program based on the scheduling algorithm having the target scheduling algorithm identifier and the target computing power resource data includes: Acquire multiple candidate servers based on the scheduling algorithm having the target scheduling algorithm identifier and the target computing power resource data; A target server that meets the target scheduling resources is determined from the plurality of candidate servers.

[0007] In a possible implementation, the number of the target fields is multiple, and the step of determining the target server for deploying the business program based on the scheduling algorithm having the target scheduling algorithm identifier and the target computing power resource data includes: Acquire multiple candidate servers based on the scheduling algorithm having the target scheduling algorithm identifier and the target computing power resource data; Obtaining preset weights corresponding to the plurality of target fields respectively; For each of the candidate servers, determine the sum of the products of the preset weights corresponding to the plurality of target fields and the computing power resource values ​​of the corresponding target fields as the scheduling level of the candidate server; Based on the scheduling levels respectively corresponding to the plurality of candidate servers, a target server for deploying the business program is determined from the plurality of candidate servers.

[0008] In a possible implementation, the method for obtaining the data model table includes: Creating the data model table; Obtain candidate field sets from multiple data tables respectively, wherein the candidate field sets include computing power resource values ​​corresponding to the multiple candidate fields respectively; Constructing association relationships between candidate field sets corresponding to the plurality of data tables; Inserting the plurality of candidate field sets having associated relationships into the data model table.

[0009] A second aspect of the present application provides a computing resource scheduling device, including: A first acquisition module is used to acquire the business program to be deployed; The second acquisition module is used to obtain the target scheduling algorithm identifier corresponding to the business program to be deployed; A search module, used to search for target computing resource data corresponding to the target scheduling algorithm identifier from the correspondence between the preset scheduling algorithm identifier and the computing resource data; A first determination module is used to determine a target server for deploying the business program based on a scheduling algorithm having the target scheduling algorithm identifier and the target computing power resource data.

[0010] In a possible implementation, the method further includes: A control display module, configured to control and display a scheduling algorithm configuration interface in response to an operation of setting computing power resource data of the target scheduling algorithm; A second determination module is used to determine a data model table through the scheduling algorithm configuration interface, wherein the data model table includes a first field set corresponding to a plurality of servers respectively, and the first field set includes a plurality of fields and computing power resource values ​​corresponding to the plurality of fields respectively; A third determination module, used to determine a target field from a plurality of fields included in the data model table through the scheduling algorithm configuration interface; A fourth determination module, used to determine the filtering condition of the target field through the scheduling algorithm configuration interface; The fifth determination module is used to determine that the second field set corresponding to at least one server in the data model table is the computing power resource data identified by the target scheduling algorithm, and the second field set includes the computing power resource value of the target field that meets the filtering condition.

[0011] The third aspect of the present application provides a computer program product, including computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements the computing resource scheduling method of the above-mentioned first aspect or any implementation method of the first aspect.

[0012] A fourth aspect of the present application provides an electronic device, comprising at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is used to execute the computer program so that the electronic device can implement the computing resource scheduling method of the above-mentioned first aspect or any implementation method of the first aspect.

[0013] A fifth aspect of the present application provides a computer storage medium, which carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement the computing resource scheduling method of the above-mentioned first aspect or any implementation of the first aspect.

[0014] By means of the above technical scheme, the present application provides a method for scheduling computing resources, presetting the correspondence between the scheduling algorithm identifier and the computing resource data, and realizing the configuration of the scheduling algorithm. Obtain the business program to be deployed; obtain the target scheduling algorithm identifier corresponding to the business program to be deployed; from the correspondence between the preset scheduling algorithm identifier and the computing resource data, find the target computing resource data corresponding to the target scheduling algorithm identifier; based on the scheduling algorithm with the target scheduling algorithm identifier and the target computing resource data, the resource requirements of the business program can be accurately matched with the available computing resources, that is, the target server. This application does not need to modify the code, but only needs to configure different scheduling algorithm identifiers to adapt to different business scenario requirements and scenario changes, greatly improving flexibility; when the business scenario requirements change or need to support new business programs, the corresponding scheduling algorithm can be quickly configured without complex code development and testing. For example, when a new business program is added, it only needs to configure a suitable scheduling algorithm identifier for it to quickly realize scheduling support, shorten the business launch time, and improve the market response speed of the enterprise. Thereby achieving the purpose of more flexible and efficient computing resource scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] 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 the originals and elements are not necessarily drawn to scale.

[0016] Figure 1 A schematic diagram of a system architecture provided for this application; Figure 2 A schematic diagram of an optional hardware structure of a terminal provided in this application; Figure 3 A schematic diagram of the structure of a resource configuration server 200 provided in this application; Figure 4 A flowchart of a computing resource scheduling method provided in this application; Figure 5 A schematic diagram of an implementation method of a scheduling algorithm configuration interface provided in this application; Figure 6 A schematic diagram of the complex pattern of filtering conditions provided for this application; Figure 7 A schematic diagram of an implementation method of the weight setting interface provided in this application; Figure 8 A schematic diagram of setting the weight of a target field through a complex mode provided for this application; Fig. 9 A schematic diagram of a list management interface provided for this application; Fig.10 A schematic diagram of a new variable interface provided for this application; Fig.11 A schematic diagram of the interface for setting output parameters provided by this application; Fig.12 A schematic diagram of a new variable interface for output parameters provided in this application; Fig.13 A schematic diagram of the structure of the computing power scheduling system provided for this application; Fig.14 A schematic diagram of the structure of a computing resource scheduling device provided in this application; Fig.15 A schematic diagram of the structure of the electronic device provided in this application. DETAILED DESCRIPTION

[0017] The following describes the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. The terms used in the implementation method section of the present application are only used to explain the specific embodiments of the present application, and are not intended to limit the present application.

[0018] The embodiments of the present application are described below in conjunction with the accompanying drawings. Those skilled in the art will appreciate that, with the development of technology and the emergence of new scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0019] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and need not be used to describe a specific order or sequential order. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances, which is only to describe the distinction mode adopted by the objects of the same attributes when describing in the embodiments of the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, so that the process, method, system, product or equipment comprising a series of units need not be limited to those units, but may include other units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0020] The present invention provides a more flexible, efficient and scalable computing power scheduling method, which can quickly adapt to the increase or update of computing power resource types and scheduling algorithms in a configurable manner, thereby better meeting the needs of business scenario development.

[0021] The following is an explanation in combination with the system architecture, method and related devices.

[0022] See also Figure 1 , Figure 1A schematic diagram of a system architecture is shown. The system may include a user terminal 100, a resource configuration server 200, an operation and maintenance terminal 300, and multiple hosts 400. The resource configuration server 200 may include one or more servers ( Figure 1 In the example of including one server), the resource configuration server 200 can provide the method provided in the embodiment of the present application for one or more user terminals or operation and maintenance terminals.

[0023] Exemplarily, the user terminal 100 may be a terminal used by an enterprise user. An application or a webpage may be installed on the user terminal 100, and the application and the webpage may provide an interface. The user terminal 100 may receive relevant parameters input by the enterprise user on the interface, such as the business program to be deployed, and send the parameters to the resource configuration server 200. The resource configuration server 200 may obtain processing results based on the received parameters, such as the identification of the host for deploying the business program, and return the processing results to the user terminal 100.

[0024] Exemplarily, the resource configuration server 200 is connected to multiple hosts 400 respectively, and can obtain and store the computing resource status of the multiple hosts 400 in real time.

[0025] The operation and maintenance terminal 300 may be a terminal used by the operation and maintenance personnel. The operation and maintenance terminal 300 may be installed with an application or a webpage, and the application and the webpage may provide an interface. The operation and maintenance terminal 300 may receive relevant parameters input by the operation and maintenance personnel on the interface, for example, create a data model table or construct a corresponding relationship between a scheduling algorithm identifier and computing power resource data, and send the above parameters to the resource configuration server 200. The resource configuration server 200 may obtain a processing result based on the received parameters, for example, the corresponding relationship is successfully constructed, and return the processing result to the operation and maintenance terminal 300.

[0026] Exemplarily, a host may be a server or a server cluster.

[0027] Next describe Figure 1 The product form of the user terminal 100 or the operation and maintenance terminal 300 (hereinafter collectively referred to as the terminal); The terminal in the embodiment of the present application can be a mobile phone, a tablet computer, a wearable device, a vehicle-mounted device, an augmented reality (AR) / virtual reality (VR) device, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), etc., and the embodiment of the present application does not impose any restrictions on this.

[0028] Figure 2 An optional hardware structure diagram of a terminal is shown.

[0029] refer to Figure 2 As shown, the terminal may include a radio frequency unit 110, a memory 120, an input unit 130, a display unit 140, a camera 150 (optional), an audio circuit 160 (optional), a speaker 161 (optional), a microphone 162 (optional), an earphone jack 163 (optional), a processor 170, an external interface 180, a power supply 190 and other components. Those skilled in the art will appreciate that Figure 2 This is merely an example of a terminal and does not constitute a limitation on the terminal. The terminal may include more or fewer components than shown in the figure, or a combination of certain components, or different components.

[0030] The input unit 130 can be used to receive input digital or character information, and generate key signal input related to the user settings and function control of the terminal. Specifically, the input unit 130 may include a touch screen 131 (optional) and / or other input devices 132. The touch screen 131 can collect the user's touch operations on or near it (such as the user's operation on or near the touch screen using any suitable object such as fingers, joints, stylus, etc.), and drive the corresponding connection device according to a pre-set program. The touch screen can detect the user's touch action on the touch screen, convert the touch action into a touch signal and send it to the processor 170, and can receive and execute the command sent by the processor 170; the touch signal at least includes the touch point coordinate information. The touch screen 131 can provide an input interface and an output interface between the terminal and the user. In addition, the touch screen can be implemented using multiple types such as resistive, capacitive, infrared and surface acoustic wave. In addition to the touch screen 131, the input unit 130 can also include other input devices. Specifically, other input devices 132 may include, but are not limited to, one or more of a physical keyboard, function keys (such as a volume control key, a switch key, etc.), a trackball, a mouse, a joystick, and the like.

[0031] Among them, the input device 132 can receive input data and the like.

[0032] The display unit 140 can be used to display information input by the user or information provided to the user, various menus of the terminal, interactive interfaces, file display and / or playback of any multimedia file. In the embodiment of the present application, the display unit 140 can be used to display interfaces, processing results, etc.

[0033] The memory 120 can be used to store instructions and data. The memory 120 can mainly include an instruction storage area and a data storage area. The data storage area can store various data, such as multimedia files, texts, etc.; the instruction storage area can store software units such as operating systems, applications, instructions required for at least one function, or their subsets and extensions. It can also include a non-volatile random access memory; provide the processor 170 with hardware, software and data resources including management of computing and processing equipment, and support control software and applications. It is also used for the storage of multimedia files, and the storage of running programs and applications.

[0034] The processor 170 is the control center of the terminal. It uses various interfaces and lines to connect various parts of the entire terminal. By running or executing instructions stored in the memory 120 and calling data stored in the memory 120, it executes various functions of the terminal and processes data, thereby controlling the terminal device as a whole. Optionally, the processor 170 may include one or more processing units; preferably, the processor 170 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface and application program, and the modem processor mainly processes wireless communication. It is understandable that the above-mentioned modem processor may not be integrated into the processor 170. In some embodiments, the processor and the memory may be implemented on a single chip, and in some embodiments, they may also be implemented separately on separate chips. The processor 170 may also be used to generate corresponding operation control signals, send them to corresponding components of the computing and processing device, read and process data in the software, especially read and process data and programs in the memory 120, so that each functional module therein performs corresponding functions, thereby controlling the corresponding components to act according to the requirements of the instructions.

[0035] The radio frequency unit 110 (optional) can be used for receiving and sending information or receiving and sending signals during a call, for example, after receiving the downlink information of the base station, it is sent to the processor 170 for processing; in addition, the designed uplink data is sent to the base station. Generally, the RF circuit includes but is not limited to an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier (Low Noise Amplifier, LNA), a duplexer, etc. In addition, the radio frequency unit 110 can also communicate with network devices and other devices through wireless communication. The wireless communication can use any communication standard or protocol, including but not limited to Global System of Mobile communication (Global System of Mobile communication, GSM), General Packet Radio Service (General Packet Radio Service, GPRS), Code Division Multiple Access (Code Division Multiple Access, CDMA), Wideband Code Division Multiple Access (Wideband Code Division Multiple Access, WCDMA), Long Term Evolution (Long Term Evolution, LTE), email, Short Messaging Service (SMS), etc.

[0036] In this embodiment of the present application, the radio frequency unit 110 can send data to the resource configuration server 200 and receive the processing result sent by the resource configuration server 200.

[0037] It should be understood that the radio frequency unit 110 is optional and can be replaced by other communication interfaces, such as a network port.

[0038] The terminal also includes a power supply 190 (such as a battery) for supplying power to various components. Preferably, the power supply can be logically connected to the processor 170 through a power management system, so that the power management system can manage charging, discharging, power consumption and other functions.

[0039] The terminal also includes an external interface 180, which may be a standard Micro USB interface or a multi-pin connector, and may be used to connect the terminal to communicate with other devices, or to connect a charger to charge the terminal.

[0040] Although not shown, the terminal may also include a flashlight, a wireless fidelity (WiFi) module, a Bluetooth module, sensors with different functions, etc., which will not be described in detail here. Some or all of the methods described below may be applied in the following embodiments. Figure 2 in the terminal shown.

[0041] Next describe Figure 1 The product form of the resource configuration server 200; Figure 3 A schematic diagram of the structure of a resource configuration server 200 is provided, such as Figure 3 As shown, the resource configuration server 200 includes a bus 201, a processor 202, a communication interface 203 and a memory 204. The processor 202, the memory 204 and the communication interface 203 communicate with each other via the bus 201.

[0042] The bus 201 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0043] The processor 202 may be any one or more of a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0044] The memory 204 may include a volatile memory, such as a random access memory (RAM). The memory 204 may also include a non-volatile memory, such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD), or a solid state drive (SSD).

[0045] Among them, the memory 204 can be used to store software codes related to the computing power resource scheduling method, the processor 202 can execute the steps of the computing power resource scheduling method of the chip, and can also schedule other units to achieve corresponding functions.

[0046] It should be understood that the above-mentioned terminal and resource configuration server 200 can be centralized or distributed devices, and the processors in the above-mentioned terminal and resource configuration server 200 (such as processor 170 and processor 202) can be hardware circuits (such as application specific integrated circuit (ASIC), field-programmable gate array (FPGA), general-purpose processor, digital signal processor (DSP), microprocessor or microcontroller, etc.), or a combination of these hardware circuits. For example, the processor can be a hardware system with an instruction execution function, such as a CPU, DSP, etc., or a hardware system without an instruction execution function, such as an ASIC, FPGA, etc., or a combination of the above-mentioned hardware systems without an instruction execution function and hardware systems with an instruction execution function.

[0047] Reference Figure 4 , Figure 4 A flowchart of a computing resource scheduling method provided in an embodiment of the present application is shown in FIG. Figure 4 As shown, a computing resource scheduling method provided in an embodiment of the present application may include steps S401 to S404, and these steps are described in detail below.

[0048] Step S401: Obtain the service program to be deployed.

[0049] For example, in the computing resource scheduling system, a business program refers to an application or service that needs to be deployed and run on a server. These business programs are usually software developed to meet specific business needs. They can be various types of applications, such as website services, data analysis tools, machine learning models, video processing programs, etc.

[0050] For example, a business program is a software program developed to implement a specific business function. It can be an independent application or a complex system composed of multiple components or modules.

[0051] It is understandable that business procedures are closely related to the business processes and needs of enterprises, and their functions and performance directly affect the operational efficiency and quality of the business. For example, the business procedures of an e-commerce platform may include functional modules such as product display, order processing, and payment settlement, which together support the business operations of the e-commerce platform.

[0052] Business programs consume certain computing resources during operation, such as CPU (Central Processing Unit), memory, storage, network bandwidth, etc. Different business programs may have different requirements for computing resources. For example, computationally intensive machine learning models may require a large amount of CPU or GPU resources, while data storage-based business programs may require a large storage space.

[0053] Exemplarily, an enterprise user may input a business program to be deployed through a user interface displayed on a user terminal.

[0054] Step S402: Obtain the target scheduling algorithm identifier corresponding to the business program to be deployed.

[0055] Step S403: searching for the target computing resource data corresponding to the target scheduling algorithm identifier from the correspondence between the preset scheduling algorithm identifier and the computing resource data.

[0056] Exemplarily, a scheduling algorithm has a unique scheduling algorithm identifier.

[0057] It is understandable that the operation and maintenance personnel set the "correspondence between the scheduling algorithm identifier and the computing power resource data" through the operation and maintenance terminal, so enterprise users can select one or more target scheduling algorithm identifiers from multiple scheduling algorithm identifiers through the user interface displayed on the user terminal.

[0058] The scheduling algorithm is the specific calculation method and logic for implementing the scheduling strategy, which determines how to select and allocate hosts based on computing resource data.

[0059] In the embodiment of the present application, the selected host is referred to as the target server.

[0060] Exemplarily, the scheduling algorithm includes, but is not limited to: one or more of a greedy algorithm, a weighted polling algorithm, and a delay minimization algorithm.

[0061] Exemplarily, the scheduling strategy is used to guide how to select and allocate hosts according to business scenario requirements and computing resource data. Exemplarily, the scheduling strategy includes, but is not limited to: one or more of the proximity priority scheduling strategy, resource idle priority scheduling strategy, cost priority scheduling strategy, and high availability scheduling strategy.

[0062] Exemplarily, multiple scheduling algorithms are preset by operation and maintenance personnel.

[0063] Exemplarily, the correspondence between the scheduling algorithm identifier and the computing power resource data provides a clear mapping for scheduling decisions and simplifies the decision-making process. There is no need to perform complex logical judgments and resource searches. It is only necessary to quickly find the corresponding target computing power resource data according to the target scheduling algorithm identifier, and then apply the target scheduling algorithm and target computing power resource data to determine the target server, thereby improving the efficiency of scheduling decisions. This method reduces the human intervention link and reduces scheduling errors and unreasonable resource allocation caused by human operational errors. The scheduling process is more automated and intelligent, which improves the stability and reliability of the computing power scheduling method and reduces the workload of operation and maintenance personnel.

[0064] The following is an explanation of the process of obtaining computing power resource data.

[0065] Exemplarily, a computing power resource collection configuration may be set, and the computing power resource collection configuration mainly includes the following parameters: collection task type, request parameters, response configuration, field mapping relationship, associated data table, and timing configuration.

[0066] Exemplarily, the types of collection tasks include, but are not limited to: HTTP (Hypertext Transfer Protocol) and SQL.

[0067] The following uses HTTP as an example to explain other parameters.

[0068] HTTP request parameters include URL (Uniform Resource Locator) and request header (indicating the type of data sent by the terminal).

[0069] HTTP response Schema configuration includes configuring the format of HTTP response messages (so that the terminal can correctly parse the data returned by the server).

[0070] The field mapping relationship includes configuring the mapping relationship between the HTTP response message fields and the database table fields so that after the data is collected, it can be correctly stored in the database.

[0071] The associated data table includes configuring the name of the data table to which the response result data is saved.

[0072] Scheduled configuration includes support for configuring scheduled plans through cron expressions.

[0073] Step S404: Determine a target server for deploying the business program based on the scheduling algorithm having the target scheduling algorithm identifier and the target computing resource data.

[0074] For example, the scheduling algorithm with the target scheduling algorithm identifier and the target computing resource data can be loaded and stored in the database; if the database is detected to be updated, it is automatically loaded into the memory, so that the target server can be determined based on the updated "scheduling algorithm with the target scheduling algorithm identifier and the target computing resource data". There is no need to write the scheduling algorithm into the code in a hard-coded manner.

[0075] It is understandable that as business scenarios develop and computing resource types increase, the system's scheduling capabilities can be expanded by adding new scheduling algorithm identifiers and corresponding computing resource data without making large-scale changes to the system architecture. This modular expansion approach enables the system to flexibly adapt to future business growth and technological development.

[0076] The embodiment of the present application provides a computing power resource scheduling method, which pre-sets the correspondence between the scheduling algorithm identifier and the computing power resource data, and realizes the configuration of the scheduling algorithm. Obtain the business program to be deployed; obtain the target scheduling algorithm identifier corresponding to the business program to be deployed; from the correspondence between the preset scheduling algorithm identifier and the computing power resource data, find the target computing power resource data corresponding to the target scheduling algorithm identifier; based on the scheduling algorithm with the target scheduling algorithm identifier and the target computing power resource data, it is enough to accurately match the resource requirements of the business program with the available computing power resources, that is, the target server. This application does not need to modify the code, but only needs to configure different scheduling algorithm identifiers to adapt to different business scenario requirements and scenario changes, which greatly improves flexibility; when the business scenario requirements change or need to support new business programs, the corresponding scheduling algorithm can be quickly configured without complex code development and testing. For example, when a new business program is added, it only needs to configure a suitable scheduling algorithm identifier for it to quickly implement scheduling support, shorten the business launch time, and improve the market response speed of the enterprise. Thereby achieving the purpose of more flexible and efficient computing power resource scheduling.

[0077] The following is a description of the method for constructing a corresponding relationship between a standard scheduling algorithm identifier and target computing power resource data. The method includes the following steps A1 to A5.

[0078] Step A1: In response to the operation of setting the computing power resource data of the target scheduling algorithm, control the display of the scheduling algorithm configuration interface.

[0079] Exemplarily, the “operation” in step A1 may be a key operation, a voice operation, or a preset gesture operation.

[0080] Exemplarily, the "operation" in step A1 can be performed when a certain scheduling algorithm AA is selected, so the computing power resource data configured through the scheduling algorithm configuration interface is the computing power resource data of the scheduling algorithm AA.

[0081] Step A2: Determine a data model table through the scheduling algorithm configuration interface, wherein the data model table includes a first field set corresponding to a plurality of servers respectively, and the first field set includes a plurality of fields and computing power resource values ​​corresponding to the plurality of fields respectively.

[0082] Exemplarily, the multiple fields of the first field set include, but are not limited to: server_id (unique identifier of the host), cpu_total (total CPU amount of the host), cpu_remaining (remaining CPU resources of the host), memory_total (total memory amount of the host), memory_remaining (remaining memory resources of the host), gpu_total (total GPU amount of the host), gpu_remaining (remaining GPU resources of the host), storage_total (total storage amount of the host), storage_remaining (remaining storage resources of the host), network_bandwidth (network bandwidth of the host), network_latency (network latency of the host), location (geographic location of the host), availability_zone (availability zone of the host), cost_per_hour (cost per hour of the host).

[0083] Exemplarily, each row in the data model table is a first field set of a server, ie, a host.

[0084] Exemplarily, the computing power resource value is the field value of the field, and the computing power resource value is obtained by the resource configuration server 200 from the host in real time.

[0085] like Figure 5 , which is a schematic diagram of an implementation method of the scheduling algorithm configuration interface provided in an embodiment of the present application.

[0086] For example, it can be done by Figure 5 Select or enter the data model table from the drop-down box of "Associated Model".

[0087] For example, it can be done by Figure 5 The "Query Field" in determines the target field.

[0088] For example, it can be done by Figure 5 The "Filter method" in determines the scope of the target field.

[0089] Step A3: Determine a target field from a plurality of fields included in the data model table through the scheduling algorithm configuration interface.

[0090] It is understandable that the data used by the target scheduling algorithm in determining the target server is part or all of the data in the data model table. If it is all the data in the data model table, the target field includes all the fields in the data model table; if it is part of the data in the data model table, then Figure 5 In the drop-down box of "Query Field", select the corresponding field. In the embodiment of the present application, the selected field is referred to as the target field.

[0091] Step A4: Determine the filtering condition of the target field through the scheduling algorithm configuration interface.

[0092] Assume that the fields in the data model table are: CVSS (Common Vulnerability Scoring System), attributes, business group, operating system, server_id, cpu_total, cpu_remaining, memory_total, memory_remaining, gpu_total, gpu_remaining, storage_total, storage_remaining, network_bandwidth, network_latency, location, availability_zone, cost_per_hour. For example, a business group refers to an organization divided according to business scenario requirements, functional modules, or business processes. Hosts belonging to the same business group usually have the same resources and permissions. Attributes refer to the characteristics, features, and description information of a host. CVSS refers to existing vulnerabilities in a host.

[0093] Assume that the target fields are CVSS, host attributes, business groups, and the number of host operating systems. Figure 5 As shown, it can be Figure 5 In the simple mode of the filtering method shown in , the target field is determined in "Select Attributes", and the filtering condition for each target field is determined based on "Operator" and "Value".

[0094] Combination Figure 5It can be seen that the "selection attribute", "operator" and "value" can be configured to obtain the filtering condition of the target field. For example, if the "selection attribute" is configured as the target field "podCode", the "operator" is configured as "=" and the "value" is configured as "1", then the filtering condition is "podCode=1" so as to obtain data that meets the filtering condition from the data model table. Exemplarily, multiple "selection attributes", multiple "operators" and multiple "values" can be configured, that is, multiple filtering conditions can be set, and multiple filtering conditions can be connected in AND mode. In addition, variables can be used in the "selection attribute". The specific variables that can be used are defined in the variable management. For example, when using variables that are not defined in the variable configuration, an error prompt is required.

[0095] For example, the "complex mode" in the "filter mode" means that the range of the target field can be determined by an SQL statement, such as Figure 6 The figure is a schematic diagram of a complex pattern of filtering conditions provided in an embodiment of the present application.

[0096] like Figure 6 As shown, the input box corresponding to the "Filter Expression" contains the SQL statement used to determine the range of the target field.

[0097] For example, you can use SQL statement expressions to write filtering conditions, and you can also use variables in the expressions. The specific variables that can be used are defined in variable management. For example, when using variables that are not defined in the variable configuration, you need to prompt an error.

[0098] Combination Figure 5 and Figure 6 It can be seen that the method of setting filtering conditions supports simple mode and complex mode.

[0099] Step A5: Determine that the second field set corresponding to at least one server in the data model table is the computing power resource data identified by the target scheduling algorithm, and the second field set includes the computing power resource value of the target field that meets the filtering condition.

[0100] In actual applications, the structure of the data model table may change with business development and technology updates, such as adding new fields or adjusting field names. By configuring the field correspondence, you don't need to modify the structure of the model data table or related code. You only need to update the configuration to adapt to the changes, thereby maintaining the stability and continuity of the system.

[0101] It is understandable that there may be multiple data model tables. The following describes the process of obtaining each data model table. The process includes the following steps B1 to B4.

[0102] Step B1: Create the data model table.

[0103] For example, a data model table may be created using a SQL (Structured Query Language) statement. If the name of the data model table is "data_model_table", the SQL statement for creating the data model table is: CREATE TABLE data_model_table.

[0104] Step B2: Obtain candidate field sets from multiple data tables respectively, wherein the candidate field sets include computing power resource values ​​corresponding to the multiple candidate fields respectively.

[0105] Exemplarily, the data in the data model table may be formed from data in one or more data tables. For example, part or all of the data in the "multiple data tables" mentioned in step B2 forms the data in the data model table.

[0106] For example, if the data model table is a recommendation information table, the "multiple data tables" in step B2 include, but are not limited to: a data table including user behavior data, and a data table including product information.

[0107] Exemplarily, step B2 constructs a relationship between the candidate fields in the data model table and the data table.

[0108] For example, a select statement may be used to select a candidate field set from multiple data tables. Assume that the multiple data tables are: data table a, data table b, and data table c. Assume that it is necessary to obtain candidate field x from data table a, candidate field y from data table b, and candidate field x from data table c. Then the select statement is: select data table ax, data table by, data table cx.

[0109] Exemplarily, the candidate field may be one or more.

[0110] Exemplarily, the data sources of different data tables may be the same or different.

[0111] Step B3: construct association relationships between candidate field sets corresponding to the plurality of data tables.

[0112] It is understandable that the fields between multiple data tables have a corresponding relationship. For example, the candidate field sets corresponding to the multiple data tables can be associated by Join. The following example illustrates the use of INNER Join operation to connect data table a and data table b based on the common field x, ensuring that only records with matching field x in data table a and data table b are selected. The statement is: data table a INNER JOIN data table b ON data table ax = data table bx.

[0113] It is understandable that when multiple data tables are involved, these candidate field sets need to be associated in some way so that complete data can be obtained from data tables of multiple different data sources. A common method is the Join operation in the database, which can connect two data tables based on one or more common fields. For example, the user information table and the user transaction table can be connected through the user ID field.

[0114] Step B4: inserting the plurality of candidate field sets having association relationships into the data model table.

[0115] Exemplarily, the Insert into statement can be used to insert the multiple candidate field sets with associated relationships into the data model table. Still taking the above as an example, the insert statement is: Insert into data model table select data table ax, data table by, data table cx from data table a INNER JOIN data table b ON data table ax = data table bx.

[0116] It is understandable that after obtaining the business program to be deployed, it also includes: obtaining the target scheduling resources required by the business program. Correspondingly, the step of determining the target server for deploying the business program based on the scheduling algorithm with the target scheduling algorithm identifier and the target computing power resource data includes: obtaining multiple candidate servers based on the scheduling algorithm with the target scheduling algorithm identifier and the target computing power resource data; determining the target server that meets the target scheduling resources from the multiple candidate servers.

[0117] Exemplarily, the target scheduling resources include, but are not limited to: number of CPU cores, CPU frequency, and memory capacity and speed.

[0118] Correspondingly, the number of the target fields is multiple, and the step of determining the target server for deploying the business program based on the scheduling algorithm having the target scheduling algorithm identifier and the target computing resource data includes the following steps C1 to C4.

[0119] Step C1: Based on the scheduling algorithm having the target scheduling algorithm identifier and the target computing power resource data, a plurality of candidate servers are obtained.

[0120] Step C2: Obtain preset weights corresponding to the plurality of target fields respectively.

[0121] Exemplarily, a method for setting preset weights corresponding to a plurality of target fields may include the following steps C21 to C22.

[0122] Step C21: In response to the weight setting operation, a weight setting interface is displayed.

[0123] Step C22: Set the preset weights corresponding to the respective target fields through the weight setting interface.

[0124] like Figure 7 , which is a schematic diagram of an implementation method of the weight setting interface provided in an embodiment of the present application.

[0125] like Figure 7 As shown in the figure, the operation and maintenance personnel can set the weight of each target field through the "Simple Mode" and "Complex Mode" in the "Sorting Mode". Figure 7 In the simple mode, select the target field for which you want to set the weight in "Weight Attribute", and then write the weight of the target field in "Weight".

[0126] like Figure 8 As shown, it is a schematic diagram of setting the weight of the target field through a complex mode provided in an embodiment of the present application.

[0127] Figure 8 Use the expression method to write the sort expression. Variables can also be used in the expression. The specific variables that can be used are defined in the variable management. If a variable that is not defined in the variable configuration is used, an error message will be prompted.

[0128] Combination Figure 7 and Figure 8 As shown, the candidate servers (ie, candidate hosts) are sorted by the weights of the target fields in the “sort method”.

[0129] For example, the above mentioned variables can be managed through the interface, and these variables can be used in filtering conditions or sorting methods. Fig. 9 The list management interface shown manages each variable, such as adding variables, deleting variables, or viewing variables. Fig. 9 The "New" button can display Fig.10 The new variable interface is shown. This can achieve the purpose of adding new variables.

[0130] Understandably, Fig.10 The variable name shown in is the unique identifier of the variable.

[0131] Step C3: For each of the candidate servers, determine the sum of the products of the preset weights corresponding to the multiple target fields and the computing power resource values ​​of the corresponding target fields, which is the scheduling level of the candidate server.

[0132] Exemplarily, the score of each target field = computing power resource value × preset weight. The scheduling level of a candidate server = the sum of the scores of each target field.

[0133] Step C4: Based on the scheduling levels respectively corresponding to the plurality of candidate servers, determine a target server for deploying the business program from the plurality of candidate servers.

[0134] It is understandable that, after determining the target server, the embodiment of the present application can output the identifier of the target server and can also output other parameters. The embodiment of the present application can set the output parameters, such as Fig.11 , which is a schematic diagram of an interface for setting output parameters provided in an embodiment of the present application.

[0135] It is understandable that based on Fig.11 The configured output parameters determine the results that need to be output.

[0136] Understandably, if you click Fig.11 The "New" button in Fig.12 The new variable interface is shown.

[0137] like Fig.12 As shown in the figure, enter the variable name in the "Select variable" input box.

[0138] Computing power scheduling systems are widely used in the field of IT technology. Business operations require computing power resources, which are diverse, including IaaS (Infrastructure as a Service) computing power resources, PaaS (Platform as a Service) computing power resources, and SaaS (Software as a Service) computing power resources. At the same time, there are also various resource selection strategies when the business is running, such as proximity priority and surplus priority. Therefore, a computing power scheduling system is needed to support these business needs, that is, to select appropriate computing power resources according to the business resource requirements and selection strategies to meet business needs and improve the utilization of computing power resources. Fig.13 , which is a schematic diagram of the structure of the computing power scheduling system provided in an embodiment of the present application.

[0139] The computing power perception module is used to obtain computing power resource data based on the computing power resource collection configuration, and explode it into a data table used to store computing power resources.

[0140] Exemplarily, computing resource data includes, but is not limited to: host quota data (such as total CPU usage, CPU margin), host specification data (i.e., resource specifications that can be selected when creating a virtual machine, such as 1C2G), etc.

[0141] For example, the computing power perception module can obtain available computing power resource data through regular synchronization or events, and save the collected computing power resource data according to the corresponding data model table. The computing power decision module needs to use this data when making decisions. The model management module is used to obtain computing power resource data based on the computing power model configuration and generate computing power model data, namely the data model table.

[0142] The business portal module is located in the enterprise user's terminal and is used to call the scheduling decision module interface, obtain the target server, and the business program and target scheduling algorithm identifier that need to be passed in.

[0143] Scheduling decision module: used to generate decision results, i.e. target servers, based on resource requirements, scheduling strategies, and computing power model data.

[0144] In summary, the computing power scheduling system provided by the embodiment of the present invention can support new business scenarios through configuration methods, such as new business needs, such as the need to support scheduling by GPU resources, or support new scheduling algorithms, such as location priority scheduling, dynamic weight scheduling, and other scheduling algorithms.

[0145] The above introduces a computing power resource scheduling method provided by an embodiment of the present application, and the following will introduce a device for executing the above computing power resource scheduling method.

[0146] See also Fig.14 , Fig.14 A schematic diagram of the structure of a computing resource scheduling device provided in an embodiment of the present application. Fig.14 As shown, the computing resource scheduling device includes: The first acquisition module 1401 is used to acquire the service program to be deployed; The second acquisition module 1402 is used to acquire a target scheduling algorithm identifier corresponding to the business program to be deployed; A search module 1403 is used to search for target computing resource data corresponding to the target scheduling algorithm identifier from the correspondence between the preset scheduling algorithm identifier and the computing resource data; The first determination module 1404 is used to determine the target server for deploying the business program based on the scheduling algorithm with the target scheduling algorithm identifier and the target computing resource data.

[0147] In an optional implementation, the method further includes: A control display module, configured to control and display a scheduling algorithm configuration interface in response to an operation of setting computing power resource data of the target scheduling algorithm; A second determination module is used to determine a data model table through the scheduling algorithm configuration interface, wherein the data model table includes a first field set corresponding to a plurality of servers respectively, and the first field set includes a plurality of fields and computing power resource values ​​corresponding to the plurality of fields respectively; A third determination module, used to determine a target field from a plurality of fields included in the data model table through the scheduling algorithm configuration interface; A fourth determination module, used to determine the filtering condition of the target field through the scheduling algorithm configuration interface; The fifth determination module is used to determine that the second field set corresponding to at least one server in the data model table is the computing power resource data identified by the target scheduling algorithm, and the second field set includes the computing power resource value of the target field that meets the filtering condition.

[0148] In an optional implementation, the method further includes: A third acquisition module is used to acquire the target scheduling resources required by the business program; Accordingly, the first determining module includes: A first acquisition unit, configured to acquire a plurality of candidate servers based on a scheduling algorithm having the target scheduling algorithm identifier and the target computing power resource data; The second acquisition unit is used to determine a target server that meets the target scheduling resources from the multiple candidate servers.

[0149] In an optional implementation, the number of the target fields is multiple, and the first determining module includes: A third acquisition unit, configured to acquire a plurality of candidate servers based on the scheduling algorithm having the target scheduling algorithm identifier and the target computing power resource data; A fourth acquisition unit, used to acquire preset weights corresponding to the plurality of target fields respectively; A first determining unit is used to determine, for each of the candidate servers, a sum of products of preset weights corresponding to the plurality of target fields and computing power resource values ​​of the corresponding target fields as the scheduling level of the candidate server; The second determining unit is configured to determine a target server for deploying the business program from a plurality of the candidate servers based on the scheduling levels respectively corresponding to the plurality of the candidate servers.

[0150] In an optional implementation, the method further includes: A creation module, used for creating the data model table; A fourth acquisition module is used to respectively acquire candidate field sets from multiple data tables, wherein the candidate field sets include computing power resource values ​​corresponding to the multiple candidate fields respectively; A construction module, used to construct association relationships between candidate field sets corresponding to a plurality of the data tables; An inserting module is used to insert the plurality of candidate field sets having associated relationships into the data model table.

[0151] The present application also provides an electronic device in an embodiment. Fig.15 As shown, it shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present application. The electronic device in the embodiments of the present application may include but is not limited to fixed user terminals such as mobile phones, notebook computers, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, etc. Fig.15 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0152] like Fig.15 As shown, the electronic device may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 1501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1502 or a program loaded from a storage device 1508 to a random access memory (RAM) 1503. When the electronic device is powered on, various programs and data required for the operation of the electronic device are also stored in the RAM 1503. The processing device 1501, the ROM 1502, and the RAM 1503 are connected to each other via a bus 1504. An input / output (I / O) interface 1505 is also connected to the bus 1504.

[0153] Typically, the following devices may be connected to the I / O interface 1505: an input device 1506 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 1507 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 1508 including, for example, a memory card, a hard disk, etc.; and a communication device 1509. The communication device 1509 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although Fig.15 An electronic device having various devices is shown, 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.

[0154] An embodiment of the present application also provides a computer program product, including computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements any computing resource scheduling method provided in the embodiment of the present application.

[0155] A computer-readable storage medium is also provided in an embodiment of the present application. The storage medium carries one or more computer programs. When one or more computer programs are executed by an electronic device, the electronic device can implement any computing resource scheduling method provided in an embodiment of the present application.

[0156] It should also be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the drawings of the device embodiments provided by the present application, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines.

[0157] Through the description of the above implementation mode, the technicians in the field can clearly understand that the present application can be implemented by means of software plus necessary general hardware, and of course, it can also be implemented by special hardware including special integrated circuits, special CPUs, special memories, special components, etc. In general, all functions completed by computer programs can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be various, such as analog circuits, digital circuits or special circuits. However, for the present application, software program implementation is a better implementation mode in more cases. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a readable storage medium, such as a computer floppy disk, a U disk, a mobile hard disk, a ROM, a RAM, a disk or an optical disk, etc., including a number of instructions to enable a computer device (which can be a personal computer, a training device, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0158] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product.

[0159] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, a computer, a training device, or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, training device, or data center. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device, a data center, etc. that includes one or more available media integrations. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)), etc.

Claims

1. A computing resource scheduling method, characterized in that: include: Obtain the business program to be deployed; Obtain the target scheduling algorithm identifier corresponding to the business program to be deployed; From the correspondence between the preset scheduling algorithm identifier and the computing power resource data, searching for the target computing power resource data corresponding to the target scheduling algorithm identifier; Determining a target server for deploying the business program based on a scheduling algorithm having the target scheduling algorithm identifier and the target computing power resource data; The method for constructing the corresponding relationship between the target scheduling algorithm identifier and the target computing power resource data includes: In response to an operation of setting computing power resource data of a target scheduling algorithm, controlling display of a scheduling algorithm configuration interface; Determine a data model table through the scheduling algorithm configuration interface, wherein the data model table includes a first field set corresponding to a plurality of servers respectively, and the first field set includes a plurality of fields and computing power resource values ​​corresponding to the plurality of fields respectively; Determining a target field from a plurality of fields included in the data model table through the scheduling algorithm configuration interface; Determining the filtering condition of the target field through the scheduling algorithm configuration interface; Determine that a second field set corresponding to at least one server in the data model table is computing power resource data identified by the target scheduling algorithm, and the second field set includes computing power resource values ​​of the target field that meet the filtering conditions.

2. The computing resource scheduling method according to claim 1, characterized in that: After obtaining the business program to be deployed, it also includes: Acquire target scheduling resources required by the business program; Accordingly, determining the target server for deploying the business program based on the scheduling algorithm having the target scheduling algorithm identifier and the target computing power resource data includes: Acquire multiple candidate servers based on the scheduling algorithm having the target scheduling algorithm identifier and the target computing power resource data; A target server that meets the target scheduling resources is determined from the plurality of candidate servers.

3. The computing resource scheduling method according to claim 2, characterized in that: The number of the target fields is multiple, and the determining the target server for deploying the business program based on the scheduling algorithm having the target scheduling algorithm identifier and the target computing power resource data includes: Acquire multiple candidate servers based on the scheduling algorithm having the target scheduling algorithm identifier and the target computing power resource data; Obtaining preset weights corresponding to the plurality of target fields respectively; For each of the candidate servers, determine the sum of the products of the preset weights corresponding to the plurality of target fields and the computing power resource values ​​of the corresponding target fields as the scheduling level of the candidate server; Based on the scheduling levels respectively corresponding to the plurality of candidate servers, a target server for deploying the business program is determined from the plurality of candidate servers.

4. The computing resource scheduling method according to claim 2, characterized in that: The method for obtaining the data model table includes: Creating the data model table; Obtain candidate field sets from multiple data tables respectively, wherein the candidate field sets include computing power resource values ​​corresponding to the multiple candidate fields respectively; Constructing association relationships between candidate field sets corresponding to the plurality of data tables; Inserting the plurality of candidate field sets having associated relationships into the data model table.

5. A computing resource scheduling device, characterized in that: include: A first acquisition module is used to acquire the business program to be deployed; The second acquisition module is used to obtain the target scheduling algorithm identifier corresponding to the business program to be deployed; A search module, used to search for target computing resource data corresponding to the target scheduling algorithm identifier from the correspondence between the preset scheduling algorithm identifier and the computing resource data; A first determination module is used to determine a target server for deploying the business program based on a scheduling algorithm having the target scheduling algorithm identifier and the target computing power resource data; A control display module, used for controlling and displaying a scheduling algorithm configuration interface in response to an operation of setting computing power resource data of a target scheduling algorithm; A second determination module is used to determine a data model table through the scheduling algorithm configuration interface, wherein the data model table includes a first field set corresponding to a plurality of servers respectively, and the first field set includes a plurality of fields and computing power resource values ​​corresponding to the plurality of fields respectively; A third determination module, used to determine a target field from a plurality of fields included in the data model table through the scheduling algorithm configuration interface; A fourth determination module, used to determine the filtering condition of the target field through the scheduling algorithm configuration interface; The fifth determination module is used to determine that the second field set corresponding to at least one server in the data model table is the computing power resource data identified by the target scheduling algorithm, and the second field set includes the computing power resource value of the target field that meets the filtering condition.

6. A computer program product, characterized in that It includes computer-readable instructions, and when the computer-readable instructions are executed on an electronic device, the electronic device implements the computing resource scheduling method as described in any one of claims 1 to 4.

7. An electronic device, characterized in that: The method comprises at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is used to execute the computer program so that the electronic device can implement the computing resource scheduling method as described in any one of claims 1 to 4.

8. A computer storage medium, characterized in that: The storage medium carries one or more computer programs, and when the one or more computer programs are executed by an electronic device, the electronic device can implement the computing resource scheduling method as described in any one of claims 1 to 4.

Images