CN114706680A

CN114706680A - Data processing method and device and computer equipment

Info

Publication number: CN114706680A
Application number: CN202210329986.1A
Authority: CN
Inventors: 陈海涛; 陆明; 聂志远
Original assignee: Lenovo Beijing Ltd
Current assignee: Lenovo Beijing Ltd
Priority date: 2022-03-31
Filing date: 2022-03-31
Publication date: 2022-07-05

Abstract

The application discloses a data processing method, a data processing device and computer equipment, wherein the computer equipment responds to a strategy configuration request and can automatically obtain target information at least containing storage framework information, so that a candidate strategy and parameter values at least containing the storage framework information under the candidate strategy, namely candidate parameters under the candidate strategy, are obtained based on the target information and preset constraint conditions, then the target strategy conforming to the strategy configuration request is automatically determined based on the evaluation parameters and the candidate parameters of the candidate strategy, the target parameters and the evaluation parameters under the target strategy are output without manually and continuously selecting an information parameter combination, the corresponding evaluation parameters are calculated, the processing efficiency, the reliability and the resource utilization rate are improved, and the obtained target strategy is ensured to meet the strategy configuration request.

Description

Data processing method and device and computer equipment

Technical Field

The present application relates to the field of communications technologies, and in particular, to a data processing method and apparatus, and a computer device.

Background

In the planning and configuration process of the system architecture, such as a cloud storage architecture, there are often many configuration influencing factors on the system architecture, and a designer needs to continuously adjust configuration contents of the influencing factors to meet configuration requirements of the system architecture, so that time and labor are wasted, configuration efficiency of the system architecture is reduced, and optimal performance of the manually configured system architecture cannot be guaranteed.

Disclosure of Invention

In view of the above, the present application provides a data processing method, including:

responding to the strategy configuration request to obtain target information; the target information at least comprises storage architecture information;

obtaining a candidate strategy and candidate parameters under the candidate strategy based on the target information and a preset constraint condition; the candidate parameters comprise parameter values corresponding to the storage architecture information;

and outputting a target strategy which accords with the strategy configuration request and a target parameter and an evaluation parameter under the target strategy based on the evaluation parameter of the candidate strategy and the candidate parameter.

Optionally, the outputting a target policy according with the policy configuration request based on the evaluation parameter of the candidate policy and the candidate parameter, and the outputting a target parameter and an evaluation parameter under the target policy includes:

according to the evaluation parameters of the candidate strategies, sequencing the obtained candidate strategies to obtain a strategy sequencing result aiming at the evaluation parameters;

and outputting a target strategy which accords with the strategy configuration request, and target parameters and evaluation parameters under the target strategy based on the strategy sorting result.

Optionally, the sorting the obtained multiple candidate policies according to the evaluation parameters of the candidate policies includes:

determining at least one evaluation parameter that each of the candidate policies has based on the business application requirements indicated by the policy configuration request;

ranking a plurality of the candidate policies based on the at least one evaluation parameter.

obtaining the sorting priority of various evaluation parameters of the candidate strategies, and sorting the candidate strategies according to the sorting priority; or the like, or, alternatively,

obtaining respective ranking weights of multiple evaluation parameters of the candidate strategies, and ranking the candidate strategies according to the multiple evaluation parameters and the corresponding ranking weights; or the like, or, alternatively,

and obtaining a target evaluation parameter of the candidate strategies, which accords with the strategy configuration request, and sequencing the candidate strategies according to the target evaluation parameter.

Optionally, the outputting the target policy according with the policy configuration request, and the target parameter and the evaluation parameter under the target policy based on the policy sorting result includes:

displaying the strategy sorting result on an output strategy configuration interface;

responding to the adjustment operation of the candidate parameters under each candidate strategy in the strategy sorting result to obtain the evaluation parameters of the adjusted candidate strategies;

and responding to the selection operation of the candidate strategy based on the evaluation parameter, and outputting the selected target strategy, and the target parameter and the evaluation parameter under the target strategy.

Optionally, the obtaining a candidate policy and candidate parameters under the candidate policy based on the target information and a preset constraint condition includes:

acquiring a parameter value range of equipment corresponding to the target information based on the service configuration requirement of the equipment corresponding to the target information;

obtaining a candidate strategy and candidate parameters under the candidate strategy according to a preset constraint condition and the parameter value range; the candidate parameters comprise parameter values of different storage architecture devices;

if a corresponding parameter adjustment step length is configured for the parameter value range, the candidate policy and the candidate parameters of each storage architecture device under the candidate policy are obtained according to a preset constraint condition and the parameter value range, including:

and extracting parameter values from the corresponding parameter value ranges according to the parameter adjustment step length, and obtaining candidate strategies and candidate parameters of each storage framework device under the candidate strategies based on the extracted parameter values and preset constraint conditions.

Optionally, the obtaining a candidate policy and candidate parameters of each storage architecture device under the candidate policy according to a preset constraint condition and the parameter value range includes:

calling a strategy configuration model aiming at the target information; the strategy configuration model is constructed based on preset constraint conditions;

and inputting the target information and the parameter value range into the strategy configuration model to obtain candidate strategies meeting the preset constraint conditions and candidate parameters under the candidate strategies.

Optionally, the responding to the policy configuration request to obtain the target information includes:

responding to the strategy configuration request, and determining the type of the storage architecture to be configured;

and at least obtaining storage architecture information based on the storage architecture type and the request content of the policy configuration request.

The present application further provides a data processing apparatus, comprising:

the target information obtaining module is used for responding to the strategy configuration request and obtaining target information; the target information at least comprises storage architecture information;

the strategy configuration module is used for obtaining a candidate strategy and candidate parameters under the candidate strategy based on the target information and preset constraint conditions; the candidate parameters comprise parameter values corresponding to the storage architecture information;

and the output module is used for outputting a target strategy which accords with the strategy configuration request and a target parameter and an evaluation parameter under the target strategy based on the evaluation parameter of the candidate strategy and the candidate parameter.

The present application further provides a computer device, comprising: at least one memory and at least one processor, wherein:

the memory is used for storing programs for realizing the data processing method;

the processor is used for loading and executing the program stored in the memory to realize the data processing method.

According to the technical scheme, the computer equipment can automatically obtain target information at least containing storage architecture information in response to the strategy configuration request, so that the candidate strategy and the parameter value at least containing the storage architecture information under the candidate strategy, namely each candidate parameter under the candidate strategy, are obtained based on the target information and the preset constraint condition, the target strategy meeting the strategy configuration request is automatically determined based on the evaluation parameter and the candidate parameter of the candidate strategy, the target parameter and the evaluation parameter under the target strategy are output, information parameter combinations are not required to be selected manually, the corresponding evaluation parameters are calculated, the processing efficiency, the reliability and the resource utilization rate are improved, and the obtained target strategy is ensured to meet the strategy configuration request.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.

Fig. 1 is a schematic flow chart of an alternative example of a data processing method proposed in the present application;

FIG. 2 is a schematic flow chart diagram of yet another alternative example of the data processing method proposed in the present application;

fig. 3a is a schematic structural diagram of an example of a storage structure constructed in the data processing method proposed in the present application;

fig. 3b is a schematic structural diagram of another example of a storage structure constructed in the data processing method proposed in the present application;

FIG. 4 is a schematic flow chart diagram of yet another alternative example of the data processing method presented in the present application;

fig. 5 is a schematic diagram of processing results of multiple candidate strategies obtained in the data processing method provided by the present application;

FIG. 6 is a schematic flow chart diagram of yet another alternative example of the data processing method presented in the present application;

fig. 7 is a schematic structural diagram of an alternative example of the data processing apparatus proposed in the present application;

fig. 8 is a schematic structural diagram of still another alternative example of the data processing apparatus proposed in the present application;

fig. 9 is a schematic hardware configuration diagram of an alternative example of a computer device suitable for the data processing method proposed in the present application;

fig. 10 is a hardware configuration diagram of still another alternative example of a computer device suitable for the data processing method proposed in the present application.

Detailed Description

In view of the technical problems described in the background section, the embodiments of the present application use an example of planning configurations of system architectures such as storage architectures to illustrate how to automatically, quickly, and accurately determine a target policy constituting an architecture composition and configuration parameters thereof to meet business configuration requirements.

For example, in the device capacity planning process of the Storage architecture, the influencing factors may include parameters such as a resell ratio parameter of the Storage capacity, a number of volumes supported by an SVC (Storage Area Network) group, a number of virtual machines allocated on each physical host, a number of copies of a production Storage device, and the like, values of each parameter are changed and are not fixed values, and in the process of allocating different Storage devices to each SVC group, it is necessary to satisfy a certain condition, for example, n production Storage devices and n/2 non-production Storage devices need to be allocated to a plurality of SVC groups, a sum of the number of volumes occupied by the allocated Storage device capacity cannot exceed the number of currently set SVC volumes, and different parameter combinations configured by multiple influencing factors are required, so that the obtained Storage architecture has balanced performance of each device, and the obtained Storage architecture has balanced performance, Cost optimization, maintenance convenience and other constraint targets.

Based on the above requirements in different aspects, selection of the component devices of the storage structure and the configuration parameters thereof is very difficult, and if a designer performs selection calculation in a manual configuration manner, it often takes a lot of time to continuously select calculation in combination with the accumulated technical experience, and it is not yet guaranteed that the selected combination is an optimal solution. In order to solve the technical problem, the present application proposes that more influencing factors of the system architecture can be converted into key information, and then, the candidate strategies possibly meeting the service requirements and the corresponding candidate parameters can be automatically recommended by combining the preset constraint conditions aiming at the system architecture, such as recommended parameter values corresponding to various system architecture information, determining evaluation parameters of each candidate strategy, therefore, the target strategy meeting the actual strategy configuration requirements (such as equipment configuration requirements and the like aiming at the system architecture determined based on business requirements) and the corresponding target parameters and evaluation parameters are automatically determined based on the evaluation parameters and the candidate parameters, a designer does not need to manually select calculation, the computer equipment can automatically and accurately determine the optimal parameter combination aiming at the system architecture according to the data processing method, and the data processing efficiency and accuracy are greatly improved.

In practical application, the target policy, the target parameters thereof and the evaluation parameters determined above may be sent to an operation and maintenance worker, so that the operation and maintenance worker may further adjust each target parameter in the target policy according to actual requirements, such as service configuration requirements, in combination with the evaluation parameters, to implement personalized policy configuration and meet different service requirements, and the implementation process may refer to, but is not limited to, descriptions of corresponding parts of the following embodiments, which is not described in detail herein.

The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments, and the embodiments and features in the embodiments in the present application can be combined with each other without conflict. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

Referring to fig. 1, a schematic flow chart of an optional example of the data processing method provided by the present application is shown, in an actual application, the data processing method may be executed by a computer device such as a terminal or a server, or may be configured by the terminal and the server, and the execution of the data processing method provided by the present application may be determined according to requirements of an actual application scenario. As shown in fig. 1, the data processing method proposed in the present application may include, but is not limited to, the following steps:

step S11, responding to the strategy configuration request to obtain the target information;

according to the service requirement, under the condition of configuring information such as composition and configuration parameters of a corresponding system architecture, a configuration platform of the system architecture can be logged in, a policy configuration function button for a target architecture (such as any system architecture) is triggered, a corresponding policy configuration request is generated, and then, a computer device can respond to the policy configuration request to obtain target information required for configuring a target policy of the target architecture.

In this embodiment of the present application, the system architecture may be a storage architecture constituting a storage system, and therefore, the target information obtained by the computer device may at least include storage architecture information, such as device information, configuration information, and parameters of a communication connection manner of each component device constituting the storage architecture.

In addition, the generation manner of the policy configuration request includes, but is not limited to, the implementation method described above; optionally, in executing the service application by the computer device, the executed service needs to invoke a corresponding system architecture to meet a service requirement based on the system architecture, in this case, whether a target architecture required by the service exists or not may be detected first, and if so, the target architecture may be directly invoked; and if the target architecture does not exist, the target architecture required by the service needs to be configured online, and a policy configuration request aiming at the target architecture required by the service is generated, so that the computer equipment responds to the policy configuration request to obtain corresponding target information and the like. It is understood that the target information obtained for different target architectures often has different content, and this application is not described in detail here by way of example.

Step S12, obtaining a candidate strategy and candidate parameters under the candidate strategy based on the target information and preset constraint conditions;

in the embodiment of the present application, the preset constraint condition may represent respective requirements in various aspects of the configured policy, such as overall performance, cost, and maintenance convenience requirements of the configured policy, and performance of each component device of the configured policy, configuration constraints (such as number of interfaces, types of interfaces, communication requirements, and the like) of the device type to which the component device belongs, and may even include service configuration requirements, and the like.

For example, taking the policy of configuring the storage fabric as an example, if the storage fabric can be composed of an SVC controller and at least one core switch communicatively connected to the SVC controller, each core switch can be communicatively connected to at least one edge switch, so that a computer node such as a physical host can access the edge switch or the core switch to meet data processing requirements. For such a storage structure, the preset constraint condition may include a first constraint condition for limiting connection between the storage device and the switch, a second constraint condition for limiting connection between the physical host and the switch, and the content of each constraint condition may be determined based on information such as the number of switches, the model, the number of hosts, the number of storage devices, the number of SVCs, and the number of SVC volumes, in combination with the above analysis, which is not limited in this application.

Optionally, the preset constraint condition is configured according to the constraint type, which may include, but is not limited to, a storage constraint condition, a switch constraint condition, a cost constraint condition, a connection mode constraint condition, and the like, and the content of each constraint condition included in the preset constraint condition may be determined according to various requirements, such as the type of the storage architecture and the service configuration requirement thereof, and the embodiment of the present application is not described in detail herein.

In combination with the above description of the preset constraint condition, the computer device may perform value combination on each piece of storage architecture information included in the target information, and after a logically unreasonable combination is proposed, may further perform screening on the obtained multiple combinations according to the constraint content included in the preset constraint condition, to preliminarily obtain at least one candidate policy that meets the preset constraint condition, and candidate parameters corresponding to the candidate policy, such as parameter values corresponding to each piece of storage architecture information, and the like.

In some embodiments, the present application may combine the value parameters of each storage structure information included in the target information by using cartesian product operation, to obtain respective corresponding policies for multiple combinations to be screened, select a suitable optimization algorithm, filter parameter combinations that do not meet preset constraint conditions from the multiple parameter combinations obtained by combining, to obtain policies corresponding to different parameter combinations that meet preset constraint conditions, such as parameter values of each device that configures the storage structure and storage architecture, and even determine corresponding evaluation parameters of performance, cost, maintainability, and the like, so as to further screen the obtained multiple parameter combinations in the following process, to obtain candidate policies or target policies, and the like, which does not describe in detail in the implementation process.

Optionally, for the screening implementation process of the candidate policies, a policy configuration model constructed in advance based on preset constraint conditions may be called, the obtained target information is directly input into the policy configuration model, and information such as at least one candidate policy recommended for the policy configuration request and candidate parameters thereof is output. Compared with the processing mode based on the preset constraint conditions and on-line analysis on the target information to obtain the candidate strategies and the corresponding candidate parameters, the processing mode of directly calling the strategy configuration model to recommend the candidate strategies improves the processing efficiency and accuracy.

It should be noted that, regarding how to preliminarily determine, by the computer device, at least one candidate policy that may meet the policy configuration request and an implementation method of candidate parameters under the candidate policy based on the target information and the preset constraint condition, including but not limited to the description of the above embodiment, the implementation method may be determined in combination with the application scenario requirement, and the application is not described in detail.

In combination with the above description of the target information, for the candidate parameter under each candidate policy, at least a parameter value corresponding to the storage architecture information, such as a value parameter of each piece of device information constituting the storage structure, may be included, and a content included in the candidate parameter may be determined according to a content of the target information.

And step S13, outputting the target strategy according with the strategy configuration request and the target parameter and the evaluation parameter under the target strategy based on the evaluation parameter and the candidate parameter of the candidate strategy.

The evaluation parameter of each candidate policy may be obtained in the process of determining the candidate policy, or the evaluation parameter of each candidate policy may be determined according to a preset policy evaluation requirement after determining the candidate policy.

For example, the policy evaluation parameter may include, but is not limited to, a parameter value obtained by evaluating at least one element of performance, cost, maintainability, and the like of the policy, and the evaluation process may determine an element type for evaluating the policy based on a service configuration requirement included in the policy configuration request, so that the content of the evaluation parameter of the obtained candidate policy may be different or the same for different service configuration requirements, thereby achieving flexibility of policy evaluation and ensuring that the obtained target policy reliably and accurately meets the service requirement.

Therefore, in the embodiment of the present application, after obtaining each candidate policy, candidate parameter thereof, and evaluation parameter which may meet the policy configuration request, the obtained multiple candidate policies may be further screened according to request contents, such as service configuration requirements, included in the policy configuration request, and evaluation parameters of each candidate policy, so as to more accurately determine a target policy meeting the policy configuration request; or the candidate parameters under the existing candidate strategy are adaptively adjusted to obtain the target strategy which accords with the strategy configuration request, and the like.

Under the condition that computer equipment for executing the data processing method provided by the application is a server, the server can send the obtained target strategy meeting the strategy configuration request, and information such as target parameters and evaluation parameters under the target strategy to a terminal of an operation and maintenance worker for output, so that the operation and maintenance worker can further adjust the information according to actual business requirements or execute the target strategy and build a corresponding storage framework and the like after seeing the information content output by the terminal visually.

Based on this, if the computer device executing the data processing method is a terminal, it may output the obtained target policy meeting the policy configuration request, and the information such as the target parameters and the evaluation parameters under the target policy, according to the corresponding output mode through the output component such as the display screen or the voice player, and then the terminal user may perform information adjustment and/or building of the storage architecture according to the output information content and the method described above. Of course, if the terminal user does not have the adjustment authority of the information or does not set up the storage architecture, the terminal may also send the obtained information to the terminal of the corresponding operation and maintenance person to notify the operation and maintenance person to perform information adjustment and/or set up the storage architecture, so as to obtain the storage architecture meeting the actual business requirements.

It can be seen that, in different application scenarios, the computer device outputs the target policy meeting the policy configuration request, and the implementation manners of the target parameter and the evaluation parameter under the target policy may be different, including but not limited to the above listed output implementation methods, as the case may be.

In summary, in the embodiment of the present application, a computer device, in response to a policy configuration request, may automatically obtain target information at least including storage architecture information, so as to obtain a candidate policy and a parameter value at least including corresponding to each storage architecture information under the candidate policy, that is, each candidate parameter under the candidate policy, based on the target information and a preset constraint condition, and then automatically determine a target policy meeting the policy configuration request, and output the target parameter and the evaluation parameter under the target policy, without manually and continuously selecting an information parameter combination, to calculate a corresponding evaluation parameter, thereby improving processing efficiency, reliability, and resource utilization rate, and ensuring that the obtained target policy meets the policy configuration request.

Referring to fig. 2, which is a schematic flow chart of yet another optional example of the data processing method proposed in the present application, the present embodiment may be a description of an optional detailed implementation method of the data processing method proposed above, but is not limited to the detailed implementation method described in the present embodiment. As shown in fig. 2, the data processing method described in this embodiment may include:

step S21, responding to the strategy configuration request to obtain the target information;

for the implementation method of step S21, reference may be made to the description of the corresponding parts in the foregoing embodiments, and details of this embodiment are not repeated herein. The target information obtained by the computer device may include at least storage architecture information, and the storage architecture information may include, but is not limited to, information that affects storage capacity, such as a storage capacity over-sell ratio, an SVC group support volume number, a model and number of switches (e.g., storage switches such as core switches and edge switches), a number of physical hosts, a number of virtual hosts allocated per physical host, and an over-sell ratio, when it is required to construct an example of the storage architecture shown in fig. 3a, and the present application does not limit the composition of the storage architecture of the type shown in fig. 3 a.

Optionally, in a schematic structural diagram of another example of a storage structure shown in fig. 3b, the storage structure information may include information that affects storage capacity, such as a model and communication configuration parameters of a network switch, a number of physical hosts, a number of virtual hosts allocated on each physical host, and a resell ratio, and may be determined according to a type of a component device of the storage structure of the type and an application requirement thereof, where the application does not limit target information content of storage structures of different types.

In still other embodiments provided by the present application, the target information may be key storage architecture information that affects storage architecture capacity, in order to accurately and comprehensively determine the target information, a requirement that the production storage capacity needs to meet may be determined according to an actual service scenario of a user, storage capacity evaluation contents such as storage capacity size that needs to be stored for production, number of copies that need to be delivered for different levels of storage resources, production-to-non-production proportional relationship, and number of occupied volumes may be further configured according to a policy, and corresponding target information is extracted from the request contents of the request, but is not limited to the target information obtaining method described in this embodiment.

Step S22, acquiring a parameter value range of the equipment corresponding to the target information based on the service configuration requirement of the equipment corresponding to the target information;

for the case of a large amount of obtained target information, if an enumeration method is used to obtain each value-taking parameter combination of different target information, the number of the obtained combinations is often very large because the parameter value range of each target information is not constrained, and many combinations are not reasonable and/or are not suitable for the combination required by service configuration, and the candidate policy can be determined by using the remaining combinations if the combinations are screened out.

It can be seen that the parameter value range corresponding to each target information directly affects the number of parameter combinations of different target information, and in order to reduce the time and resources spent on acquiring and screening such combinations, the present application proposes to determine the parameter value ranges of devices corresponding to corresponding target information in advance based on service configuration requirements, such as the number of volumes supported by each set of SVC, the number of physical hosts required, the respective parameter value ranges of cloud platform CPU/memory/storage device over-sell ratios, and the like. For different service configuration requirements, parameter value ranges of devices corresponding to the same kind of target information may be the same or different, and may be determined according to circumstances.

In this embodiment of the present application, the service configuration requirement may include a content of a requirement for a device corresponding to each piece of target information, or may also include a content of a requirement for the entire target information (that is, a requirement for the entire architecture configuration), and the like. In practical applications, the computer device may determine the parameter value range of the device according to the service configuration requirement of the device corresponding to each target information, and compared with a processing method for determining the parameter value ranges of the devices corresponding to all the target information according to one service configuration requirement, the processing method for obtaining the parameter value ranges in a targeted manner described in step S22 improves the reliability and accuracy of the parameter value ranges, and is beneficial to accurately obtaining candidate policies that may meet the policy configuration requirement, but is not limited to the processing method described in this embodiment.

Step S23, obtaining a candidate strategy and candidate parameters under the candidate strategy according to preset constraint conditions and parameter value ranges;

after obtaining the parameter value range of the device corresponding to each target information, when determining the parameter combination of each target information, a parameter may be extracted from the parameter value range of the corresponding device, and the parameter combination may form a parameter combination with the extracted parameters of other devices, and then, the obtained parameter combinations may be analyzed according to the preset constraint condition, so as to obtain a candidate policy that may meet the policy configuration request, and with regard to the content of the preset constraint condition, and how to obtain the implementation process of the candidate policy based on the preset constraint condition, reference may be made to the description of the corresponding part of the above embodiment, which is not described herein again.

In the process of obtaining the candidate strategy, a cartesian product operation mode can be adopted to perform value combination on the parameter value ranges of the devices corresponding to the target information to obtain various parameter combinations, and then the parameter combinations which do not meet the preset constraint condition are filtered. Illustratively, if the value of the over-sell ratio parameter is too large, not only the cost is not necessarily saved, but also the risk of reducing the performance and the stability is brought; when the value is taken near the boundary of the parameter value range, the parameters can be properly adjusted to reduce the number of key equipment purchases, reduce the overall cost, reduce the adverse effect on the performance and the like.

In some embodiments provided in the present application, if a corresponding parameter adjustment step is configured for each parameter value range, in the execution process of step S23, when extracting parameters from each parameter value range, a parameter value may be extracted from the corresponding parameter value range according to a preconfigured parameter adjustment step, and then a candidate policy and candidate parameters of each storage architecture device under the candidate policy are obtained based on the extracted parameter value and a preset constraint condition. The parameter adjustment step lengths in different parameter value ranges can be the same or different, and the numerical value of the parameter adjustment step length is not limited in the application.

For example, if the over-sell ratio of a single cloud computing host (i.e., physical host) can be defined as from 1 host running 20 virtual machines to 70 virtual machines, the number of virtual machines running on each physical host is increased every 5 virtual machines at intervals, but the over-sell ratio is not limited to the parameter value range of 20-70 machines for the information of the number of virtual machines running on each physical host given in this embodiment, and the parameter adjustment step size of 5 machines corresponding to the parameter value range. In practical application, a feasible solution interval can be selected on the basis, and the parameter adjustment step length is further updated to 2 or 1 in the interval range, so that a possible over-sell ratio parameter optimization result is further calculated. For parameter value ranges of other types of target information, parameter adjustment step length values of extracted parameters and optimization implementation processes thereof are similar, which is not described in detail herein.

Therefore, still taking the storage architecture shown in fig. 3a as an example, as shown in the various candidate policy diagrams shown in fig. 4, that is, for the various device capacity planning schemes of the storage architecture shown in fig. 3a, the supported capacity range may be from 18000 to 30000, the number of volumes supported by each SVC is determined, the recommended value of each parameter, for example, when the maximum supported volume number is 26000, the recommended parameter is 6500 volumes supported by each SVC, and the number of virtual hosts (VMs) operated by each physical host is 60.

It should be understood that, for the device information related to the number contained in the target information, the extracted corresponding parameter value is an integer, and the corresponding parameter adjustment step size is a positive integer; for other information that is not related to the number, the extracted parameter value may be an integer or may carry a decimal number, as the case may be.

Step S24, according to the evaluation parameters of the candidate strategies, sequencing the obtained multiple candidate strategies to obtain the strategy sequencing results aiming at the evaluation parameters;

and step S25, outputting the target strategy according with the strategy configuration request and the target parameter and the evaluation parameter under the target strategy based on the strategy sorting result.

According to the method, but not limited to the method described above, each parameter combination is optimized and adjusted based on at least one constraint target, and after a plurality of candidate policies that may satisfy policy configuration requests are obtained, evaluation parameters of each candidate policy may be determined, so that each candidate policy is ranked according to the evaluation parameters to obtain corresponding policy ranking results, thereby characterizing the merits of the candidate policies considered from the aspect of the evaluation parameters. It should be noted that the present application does not limit the implementation method of the sorting of step S24.

In some embodiments, in the process of ranking a plurality of candidate policies based on a plurality of evaluation parameters, the influence of the plurality of evaluation parameters on the target policy may be determined based on the policy configuration request obtained by the computer device this time, so as to obtain the ranking priority or the ranking weight of the corresponding evaluation parameter, and then the ranking of the plurality of candidate policies is implemented in combination with the ranking priority or the ranking weight of the evaluation parameter. In still other embodiments, the policy configuration request may also be based on one target evaluation parameter concerned by the policy configuration request, so that the obtained multiple candidate policies are ranked according to the one target evaluation parameter, and the like, which may be determined according to business application requirements, and details of examples are not described in this application. It will be appreciated that the resulting policy ordering results for the plurality of candidate policies may be different for different orderings depending on the content.

Then, the computer device may directly sort the target policies meeting the policy configuration request from the obtained candidate policies according to the obtained policy sorting result, for example, sort a plurality of candidate policies according to the merits, extract the top N (i.e., an integer greater than 1) or the first ranked candidate policies from the candidate policies as the target policies, and output the determined target policies and the target parameters and evaluation parameters under the target policies according to, but not limited to, the method described above.

In summary, in the embodiment of the present application, after the computer device responds to the policy configuration request and obtains the corresponding target information, the parameter value range of the device corresponding to each target information may be determined based on the service configuration request, then the automatic optimization analysis is performed according to the preset constraint condition and the parameter value range, so as to obtain the candidate policies and the candidate parameters thereof that may satisfy the policy configuration request, and the multiple candidate policies are automatically sorted according to the evaluation parameters of each candidate policy, thereby quickly and accurately determining the target policy that meets the policy configuration request based on the obtained policy sorting result, outputting the target policy, the target parameters thereof, and the evaluation parameters thereof, so that the operation and maintenance staff may further optimize the target policy based on the obtained policy sorting result, obtain the storage architecture design that meets the service configuration request and the configuration information thereof, and select the parameter combination manually, and the processing mode of the target strategy is determined, so that the processing efficiency, the reliability and the resource utilization rate are greatly improved.

Referring to fig. 5, which is a schematic flow chart of yet another optional example of the data processing method proposed in the present application, this embodiment may be a description of yet another optional detailed implementation method of the data processing method proposed above, and as shown in fig. 5, the method may include:

step S51, responding the strategy configuration request, and determining the type of the storage architecture to be configured;

step S52, based on the storage structure type and the request content of the strategy configuration request, at least obtaining the storage structure information to form the target information;

step S53, acquiring a parameter value range of the equipment corresponding to the target information based on the service configuration requirement of the equipment corresponding to the target information;

regarding the implementation process of step S51-step S53, reference may be made to the description of the corresponding parts of the above embodiments, which are not described in detail here. The storage architecture types may include, but are not limited to, the storage architectures shown in fig. 3a and fig. 3b, and it is to be noted that the policy configuration request includes, but is not limited to, a policy configuration request for the storage architecture, and may also include policy configuration requests for other types of system architectures, and for a target policy obtaining method for other types of system architectures, the method is similar to the target policy obtaining method for the storage architecture described in the embodiment of the present application, and details of the present application are not described in detail by way of example.

Step S54, calling a strategy configuration model aiming at the target information;

in this embodiment of the present application, if the target information includes storage architecture information, the present application may determine a preset constraint condition for the storage architecture information according to, but not limited to, the method described above, so as to construct a policy configuration model for a corresponding type of storage architecture based on the preset constraint condition, and store at least one of the constructed policy configuration models for storage. In this way, when the computer device responds to the policy configuration request, the policy configuration model corresponding to the storage structure type of the request configuration can be directly called from the pre-stored policy configuration models, the policy configuration model does not need to be built on line, the time spent on building the policy configuration model on line and the consumed resources are saved, and the data processing efficiency is improved.

It should be noted that, the present application is not limited to the implementation method for constructing the policy configuration model of different types of system architectures (e.g., different types of storage architectures), and the storage method thereof, and may be determined according to the circumstances. Because preset constraint conditions of different types of system architectures may be different, and the constructed policy configuration models are also different, the policy configuration models are constructed and called in a targeted manner to determine the processing mode of the candidate policy meeting the policy configuration request, so that the policy optimization efficiency and reliability are improved.

Step S55, inputting the target information and the parameter value range into a strategy configuration model to obtain a candidate strategy which accords with a preset constraint condition and a candidate parameter which at least comprises a candidate storage architecture parameter under the candidate strategy;

in the embodiment of the application, the obtained storage architecture information and the parameter value range corresponding to the storage architecture information can be input into the called strategy configuration model to perform parameter combination optimization processing, so as to obtain a candidate strategy which possibly meets the preset constraint condition. The implementation process of the parameter combination optimization process is not described in detail in this application.

In still other embodiments, the obtaining process of the parameter value range described in step S53 may also be integrated into the policy configuration model, so that only the obtained target information needs to be input into the policy configuration model corresponding to the service configuration requirement for processing, and a candidate policy that may meet the policy configuration request and information such as a candidate parameter and an evaluation parameter corresponding to the candidate policy are obtained, which is not described in detail herein.

Illustratively, with reference to the storage architecture type shown in fig. 3a and the flow diagram of an optional application scenario of the data processing method shown in fig. 6, an operation and maintenance worker may predict the storage capacity of the storage architecture, determine a production storage capacity and a non-production storage capacity, determine an SVC scale according to a service configuration requirement, extract key storage architecture information according to the predicted storage capacity, obtain target information for the service configuration requirement, where the obtained target information may include storage architecture information such as a storage capacity over-sell ratio, an SVC group support volume number, and a virtual host over-sell ratio allocated to each physical host, input the information into a pre-constructed policy configuration model to perform parameter combination optimization analysis, and output at least one candidate policy and recommended parameter values of each information corresponding to the candidate policy, that is, candidate parameters.

Step S56, determining at least one evaluation parameter of each candidate strategy based on the service application requirement indicated by the strategy configuration request;

step S57, based on the at least one evaluation parameter, ranking a plurality of candidate strategies to obtain corresponding strategy ranking results;

in combination with the description of the corresponding part of the above embodiment, for different service application requirements of different contents, the types and the numbers of the determined evaluation parameters for candidate policy ordering may be different, for example, a certain service only needs to pay attention to any evaluation standard such as cost, performance, maintainability, or the like of a planning policy of a storage structure, and the evaluation parameters corresponding to each candidate policy may be calculated according to the evaluation standard.

If the policy configuration model outputs one candidate policy, the target policy may be directly output, or the candidate parameters of the candidate policy are adjusted to obtain the target policy, and the like, which is not described in detail in the application of the present invention.

If various evaluation parameters of the candidate strategies are determined, in the implementation process of sequencing the candidate strategies based on the various evaluation parameters, the sequencing priorities of the various evaluation parameters of the candidate strategies can be obtained, and the candidate strategies are sequenced according to the sequencing priorities; or, obtaining respective ranking weights of multiple evaluation parameters of the candidate strategies, and ranking the multiple candidate strategies according to the multiple evaluation parameters and the corresponding ranking weights (namely, performing weighted summation on the multiple evaluation parameters); or, obtaining a target evaluation parameter of the candidate policies, which meets the policy configuration request, and sorting the multiple candidate policies according to the target evaluation parameter. The present application does not limit the implementation method of the candidate policy ranking included in step S57, and may be determined as the case may be.

Step S58, displaying the strategy sorting result on the output strategy configuration interface;

in the embodiment of the present application, if a computer device executing a data processing method is a terminal, as shown in an application scenario shown in fig. 6, a policy configuration interface output by the terminal may display policy ranking results of a plurality of candidate policies obtained, where the policy ranking results may include a ranking order of the plurality of candidate policies, and candidate parameters, evaluation parameters, and the like corresponding to each candidate policy, and the application does not limit content of the policy ranking results and an output manner thereof.

It can be understood that, if the computer device executing the data processing method is a server, the server may send the obtained policy sorting result to the terminal, and the policy configuration interface output by the terminal displays the policy sorting result, and then the terminal executes the following steps. The embodiment of the present application takes an application scenario in which a computer device is a terminal as an example for explanation.

Step S59, responding to the adjustment operation of the candidate parameters under each candidate strategy in the strategy ordering result, and obtaining the evaluation parameters of the adjusted candidate strategy;

step S510, responding to the selection operation of the candidate policy based on the evaluation parameter, outputting the selected target policy, and the target parameter and the evaluation parameter under the target policy.

And the operation and maintenance personnel of the storage framework watch the displayed strategy sorting result content, can directly select the required candidate strategy as the target strategy, and marks the candidate parameter of the selected candidate strategy as the target parameter. Of course, if all the candidate policies in the displayed policy sorting result do not meet the service configuration requirement of the policy configuration request, the candidate parameters of the candidate policies may be adjusted according to the policy sorting result, the adjusted candidate policies are obtained again, and then the evaluation parameters of the adjusted candidate policies are recalculated. The method for adjusting the candidate parameters is not limited.

Optionally, the present application may trigger the candidate policy to be adjusted to perform an editing state, so that each candidate parameter corresponding to the candidate policy enters an editable state, which is convenient for operation and maintenance personnel to directly edit and adjust each candidate parameter, and the terminal may respond to an adjustment operation on any candidate parameter of any candidate policy to obtain an evaluation parameter of the adjusted candidate policy, but is not limited to the implementation method described in this embodiment.

Then, the operation and maintenance personnel can select the adjusted candidate policy based on the evaluation parameter of the adjusted candidate policy, namely, select a target policy meeting the service configuration requirement, determine the selected target policy, and output the target policy and the corresponding target parameter and evaluation parameter thereof, so that the construction of the storage architecture can be completed subsequently, and the service application requirement can be met.

Therefore, the embodiment of the application can quickly and reliably obtain the candidate strategies which possibly meet the strategy configuration request, and after each candidate parameter and evaluation parameter under each candidate strategy based on the pre-constructed strategy configuration model, sequence the multiple candidate strategies, and push the strategy sequencing result to the operation and maintenance personnel for further screening and adjustment to obtain the target strategy meeting the service configuration requirement, and the target parameter and evaluation parameter thereof.

Referring to fig. 7, a schematic diagram of an alternative example of the data processing apparatus proposed in the present application may include:

a target information obtaining module 71, configured to respond to the policy configuration request and obtain target information; the target information at least comprises storage architecture information;

a policy configuration module 72, configured to obtain a candidate policy and candidate parameters under the candidate policy based on the target information and a preset constraint condition; the candidate parameters comprise parameter values corresponding to the storage architecture information;

and the output module 73 is configured to output a target policy according with the policy configuration request, and a target parameter and an evaluation parameter under the target policy, based on the evaluation parameter of the candidate policy and the candidate parameter.

In some embodiments, as shown in fig. 8, the output module 73 may include:

a candidate policy sorting unit 731, configured to sort, according to an evaluation parameter of the candidate policy, the obtained multiple candidate policies, and obtain a policy sorting result for the evaluation parameter;

an output unit 732, configured to output, based on the policy sorting result, a target policy that meets the policy configuration request, and a target parameter and an evaluation parameter under the target policy.

In one possible implementation, the candidate policy ranking unit 731 may include:

an evaluation parameter determination unit, configured to determine at least one evaluation parameter that each of the candidate policies has based on a service application requirement indicated by the policy configuration request;

a first ordering unit configured to order the plurality of candidate policies based on the at least one evaluation parameter.

In another possible implementation manner, the candidate policy ranking unit 731 may also include:

a ranking priority obtaining unit, configured to obtain ranking priorities of multiple evaluation parameters of the candidate policy;

a second sorting unit, configured to sort the plurality of candidate policies according to the sorting priority;

in yet another possible implementation manner, the candidate policy ranking unit 731 may also include:

a ranking weight obtaining unit, configured to obtain ranking weights of the various evaluation parameters of the candidate policy;

a third sorting unit, configured to sort the candidate policies according to the multiple evaluation parameters and the corresponding sorting weights;

a target evaluation parameter obtaining unit, configured to obtain a target evaluation parameter of the candidate policy that meets the policy configuration request;

and the fourth sorting unit is used for sorting the candidate strategies according to the target evaluation parameters.

Based on the description of the above embodiments, the output unit 732 may include:

the strategy sorting result output unit is used for displaying the strategy sorting result on an output strategy configuration interface;

the parameter adjusting unit is used for responding to the adjustment operation of the candidate parameters under each candidate strategy in the strategy sorting result to obtain the evaluation parameters of the adjusted candidate strategies;

and the target strategy output unit is used for responding to the selection operation of the candidate strategy based on the evaluation parameter and outputting the selected target strategy, the target parameter and the evaluation parameter under the target strategy.

Based on the above description of the embodiments, as shown in fig. 8, the policy configuration module 72 may include:

a parameter value range obtaining unit 721, configured to obtain a parameter value range of the device corresponding to the target information based on a service configuration requirement of the device corresponding to the target information;

a first obtaining unit 722, configured to obtain a candidate policy and a candidate parameter under the candidate policy according to a preset constraint condition and the parameter value range; the candidate parameters comprise parameter values of different storage architecture devices;

if a corresponding parameter adjustment step size is configured for the parameter value range, the first obtaining unit 722 may include or may include:

a parameter adjustment step length determining unit, configured to determine that each parameter value range is configured with a corresponding parameter adjustment step length;

the parameter extraction unit is used for extracting parameter values from the value range corresponding to the parameters according to the parameter adjustment step length;

and the second obtaining unit is used for obtaining the candidate strategies and the candidate parameters of the storage framework equipment under the candidate strategies based on the extracted parameter values and preset constraint conditions.

Optionally, the first obtaining unit 722 may also include:

a policy configuration model calling unit, configured to call a policy configuration model for the target information; the strategy configuration model is constructed based on preset constraint conditions;

and the third obtaining unit is used for inputting the target information and the parameter value range into the strategy configuration model to obtain a candidate strategy meeting the preset constraint condition and a candidate parameter under the candidate strategy.

In still other embodiments, in combination with the description of the above embodiments, as shown in fig. 8, the above target information obtaining module 71 may include:

a storage architecture type determining unit 711, configured to respond to the policy configuration request, and determine a storage architecture type to be configured;

a storage architecture information obtaining unit 712, configured to obtain at least storage architecture information based on the storage architecture type and the request content of the policy configuration request.

It should be noted that, various modules, units, and the like in the embodiments of the foregoing apparatuses may be stored in the memory as program modules, and the processor executes the program modules stored in the memory to implement corresponding functions, and for the functions implemented by the program modules and their combinations and the achieved technical effects, reference may be made to the description of corresponding parts in the embodiments of the foregoing methods, which is not described in detail in this embodiment.

The present application also provides a computer-readable storage medium, on which a computer program can be stored, which can be called and loaded by a processor to implement the steps of the data processing method described in the above embodiments.

Referring to fig. 9, a schematic diagram of a hardware structure of an alternative example of a computer device suitable for the data processing method proposed in the present application, the computer device may be a terminal or a server with certain data processing capability, and the terminal may include, but is not limited to, a desktop computer, a smart medical device, a smart transportation device, a robot, etc.; the server can be an independent physical server, can also be a server cluster formed by a plurality of physical servers, can also be a cloud server capable of realizing cloud computing and the like, can be connected with the terminal through a wired communication network or a wireless communication network, meets the data communication requirement between the server and the terminal, and can determine the type of the computer equipment according to the application scene requirement.

In the embodiment of the present application, a computer device is exemplified as a server, and as shown in fig. 9, the computer device may include: at least one memory 91 and at least one processor 92, wherein:

the memory 91 may be used to store a program for implementing the data processing method described in the above-described method embodiments; the processor 92 may load and execute the program stored in the memory to implement the steps of the data processing method described in the above corresponding method embodiment, and the specific implementation process may refer to the description of the corresponding parts in the above embodiment, which is not described again.

In practical applications, the memory 91 and the processor 92 may be connected to a communication bus, and data interaction between each other and other structural components of the computer device is achieved through the communication bus, which may be determined according to practical requirements, and is not described in detail in this application.

In the embodiment of the present application, the memory 91 may include a high-speed random access memory, and may further include a nonvolatile memory, such as at least one magnetic disk storage device or other volatile solid-state storage devices. The processor 92 may be a Central Processing Unit (CPU), an application-specific integrated circuit (ASIC), a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device. The structures and the models of the memory 91 and the processor 92 are not limited in the present application, and can be flexibly adjusted according to actual requirements.

It should be understood that the structure of the computer device shown in fig. 9 does not constitute a limitation to the computer device in the embodiment of the present application, and in practical applications, the computer device may include more or less components than those shown in fig. 9, or may combine some components, such as a communication interface of at least one communication module, various sensors, a database, and the like, which are not listed herein.

In addition, in the case that the computer device is a terminal, as shown in fig. 10, the terminal may further include at least one input component such as a touch sensing unit that senses a touch event on the touch display panel, a keyboard, a mouse, a camera, a microphone, and the like; at least one output component such as a display, speaker, vibration mechanism, light, etc.; an antenna; a sensor module; for example, the power module and the like, fig. 10 does not show the listed input components and output components, and the hardware structure can be determined according to the type of the terminal and the functional requirements thereof, which is not listed herein.

Finally, it should be noted that in the description of the embodiments of the present application, "/" indicates an OR meaning, for example, A/B may indicate A or B; "and/or" herein is merely an association describing an associated object, and means that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of the present application, "a plurality" means two or more than two.

Reference herein to terms such as "first," "second," or the like, is used for descriptive purposes only and to distinguish one operation, element, or module from another operation, element, or module without necessarily requiring or implying any actual such relationship or order between such elements, operations, or modules. And are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated, whereby a feature defined as "first" or "second" may explicitly or implicitly include one or more of such features.

In addition, in the present specification, the embodiments are described in a progressive or parallel manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments may be referred to each other. The device and the computer equipment disclosed by the embodiment correspond to the method disclosed by the embodiment, so that the description is relatively simple, and the relevant points can be referred to the method part for description.

Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the components and steps of the various examples have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method of data processing, comprising:

2. The method of claim 1, the outputting a target policy that meets the policy configuration request based on the evaluation parameter of the candidate policy and the candidate parameter, and a target parameter and an evaluation parameter under the target policy, comprising:

3. The method of claim 2, wherein said ranking the obtained plurality of candidate policies according to their evaluation parameters comprises:

4. The method of claim 2, wherein said ranking the obtained plurality of candidate policies according to their evaluation parameters comprises:

5. The method according to any one of claims 2-4, wherein outputting a target policy according with the policy configuration request and target parameters and evaluation parameters under the target policy based on the policy ranking result comprises:

6. The method according to any one of claims 1 to 4, wherein the obtaining of the candidate policy and the candidate parameter under the candidate policy based on the target information and a preset constraint condition comprises:

acquiring a parameter value range of the equipment corresponding to the target information based on the service configuration requirement of the equipment corresponding to the target information;

and extracting parameter values from the parameter value range according to the parameter adjustment step length, and obtaining a candidate strategy and candidate parameters of each storage framework device under the candidate strategy based on the extracted parameter values and preset constraint conditions.

7. The method according to claim 6, wherein the obtaining a candidate policy and candidate parameters of each storage architecture device under the candidate policy according to a preset constraint condition and the parameter value range includes:

8. The method of any of claims 1-4, wherein obtaining target information in response to a policy configuration request, comprises:

9. A data processing apparatus comprising:

10. A computer device, comprising: at least one memory and at least one processor, wherein:

the memory for storing a program for implementing the data processing method according to any one of claims 1 to 8;

the processor is used for loading and executing the program stored in the memory and realizing the data processing method of any one of claims 1 to 8.