Data storage resource processing method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of computers, and discloses a data storage resource processing method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining feature information of a service request sent by a server to a data storage system and a current service mode of the server; constructing a data model of the service request according to the feature information; determining a target data storage strategy corresponding to the service request according to the data model and a current service mode of the server; and based on the target data storage strategy, allocating storage resources to the service request to store to-be-stored data of the service request to a data storage system. According to the method provided by the scheme, the storage resources are allocated according to the service request characteristics of the server side and the current service mode, and the storage resource allocation result is ensured to be matched with the actual application scene of the server side, so that the performance of the data storage system is improved, and a foundation is laid for improving the front-end service response rate of the server side.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a data storage resource processing method, device, electronic device and storage medium. Background Art

[0002] At present, with the development of computer technology, the amount of data to be stored generated by computer services is increasing explosively, so the performance requirements of data storage systems are getting higher and higher.

[0003] In the related art, data is usually stored in a data storage system according to a fixed data storage strategy. For example, the data storage strategy is determined according to the source address of the data to be stored.

[0004] However, when the application scenario of computer services changes, if a fixed data storage strategy is still used for data storage, the performance of the data storage system will be reduced, and the computer services will not be able to respond to front-end business in a timely manner. Summary of the invention

[0005] The present application provides a data storage resource processing method, device, electronic device and storage medium to solve the defects of related technologies that reduce the performance of data storage systems, resulting in computer services being unable to respond to front-end services in a timely manner.

[0006] The first aspect of the present application provides a data storage resource processing method, comprising:

[0007] Acquire characteristic information of a service request sent by a server to a data storage system and a current service mode of the server;

[0008] Constructing a data model of the business request according to the characteristic information;

[0009] Determining a target data storage strategy corresponding to the business request according to the data model and the current business mode of the server;

[0010] Based on the target data storage policy, storage resources are allocated to the business request to store the data to be stored in the business request in the data storage system.

[0011] In an optional implementation, constructing the data model of the service request according to the characteristic information includes:

[0012] Determining several characteristic indicators of the service request according to the characteristic information;

[0013] A data model of the business request is constructed according to a preset data structure of the data model and the plurality of characteristic indicators.

[0014] In an optional implementation manner, determining the target data storage strategy corresponding to the business request according to the data model and the current business mode of the server includes:

[0015] According to the current business mode of the server, determining whether the data model needs to be adjusted in parameters;

[0016] In the case where it is determined that the data model needs to be adjusted in parameters, determining the performance of the data storage system for different types of business requests according to the backend disk array storage medium of the data storage system;

[0017] Determining a parameter adjustment strategy for the data model according to the performance of the data storage system for different types of business requests;

[0018] According to the parameter adjustment strategy of the data model, the parameters of the data model are adjusted to obtain an optimized data model;

[0019] Matching the optimized data model with a standard data model in a preset database to obtain a data model matching result;

[0020] Determining a target data storage strategy corresponding to the business request according to the data model matching result;

[0021] The service mode of the server is divided into at least two types: a normal mode and a high availability mode. When the current service mode of the server is the high availability mode, it is determined that the data model needs to be adjusted in parameters.

[0022] In an optional embodiment, the method further includes:

[0023] When the current service mode of the server is a normal mode, determining that the data model does not need parameter adjustment;

[0024] Directly matching the data model with a standard data model in a preset database to obtain a data model matching result;

[0025] A target data storage strategy corresponding to the business request is determined according to the data model matching result.

[0026] In an optional implementation, adjusting the parameters of the data model according to the parameter adjustment strategy of the data model to obtain an optimized data model includes:

[0027] Determining a weight adjustment coefficient of each parameter in the data model according to a parameter adjustment strategy of the data model;

[0028] According to the weight adjustment coefficient of each parameter in the data model, the parameters of the data model are adjusted to obtain an optimized data model;

[0029] The parameters in the data model include characteristic indicators of the business request.

[0030] In an optional implementation, allocating storage resources to the business request based on the target data storage policy to store the data to be stored of the business request in the data storage system includes:

[0031] Binding a processor core for the service request in the data storage system according to the target data storage policy;

[0032] Responding to the service request based on the processor core to store the to-be-stored data of the service request in the data storage system;

[0033] Wherein, the storage resource includes a processor core.

[0034] In an optional embodiment, the method further includes:

[0035] Determining changes in the service request of the server according to the data model of the service request;

[0036] According to changes in the service requests of the server, the sampling rate of the service requests of the server is adjusted.

[0037] A second aspect of the present application provides a data storage resource processing device, comprising:

[0038] An acquisition module, used to acquire characteristic information of a service request sent by a server to a data storage system and a current service mode of the server;

[0039] A construction module, used to construct a data model of the business request according to the characteristic information;

[0040] A determination module, used to determine a target data storage strategy corresponding to the business request according to the data model and the current business mode of the server;

[0041] A processing module is used to allocate storage resources to the business request based on the target data storage policy, so as to store the data to be stored of the business request in the data storage system.

[0042] In an optional implementation, the building block is specifically used to:

[0043] Determining several characteristic indicators of the service request according to the characteristic information;

[0044] A data model of the business request is constructed according to a preset data structure of the data model and the plurality of characteristic indicators.

[0045] In an optional implementation manner, the determining module is specifically configured to:

[0046] According to the current business mode of the server, determining whether the data model needs to be adjusted in parameters;

[0047] In the case where it is determined that the data model needs to be adjusted in parameters, determining the performance of the data storage system for different types of business requests according to the backend disk array storage medium of the data storage system;

[0048] Determining a parameter adjustment strategy for the data model according to the performance of the data storage system for different types of business requests;

[0049] According to the parameter adjustment strategy of the data model, the parameters of the data model are adjusted to obtain an optimized data model;

[0050] Matching the optimized data model with a standard data model in a preset database to obtain a data model matching result;

[0051] Determining a target data storage strategy corresponding to the business request according to the data model matching result;

[0052] The service mode of the server is divided into at least two types: a normal mode and a high availability mode. When the current service mode of the server is the high availability mode, it is determined that the data model needs to be adjusted in parameters.

[0053] In an optional implementation manner, the determining module is further configured to:

[0054] When the current service mode of the server is a normal mode, determining that the data model does not need parameter adjustment;

[0055] Directly matching the data model with a standard data model in a preset database to obtain a data model matching result;

[0056] A target data storage strategy corresponding to the business request is determined according to the data model matching result.

[0057] In an optional implementation manner, the determining module is specifically configured to:

[0058] Determining a weight adjustment coefficient of each parameter in the data model according to a parameter adjustment strategy of the data model;

[0059] According to the weight adjustment coefficient of each parameter in the data model, the parameters of the data model are adjusted to obtain an optimized data model;

[0060] The parameters in the data model include characteristic indicators of the business request.

[0061] In an optional implementation, the processing module is specifically used to:

[0062] Binding a processor core for the service request in the data storage system according to the target data storage policy;

[0063] Responding to the service request based on the processor core to store the to-be-stored data of the service request in the data storage system;

[0064] Wherein, the storage resource includes a processor core.

[0065] In an optional embodiment, the device further comprises:

[0066] The sampling rate adjustment module is used to determine the change of the service request of the server according to the data model of the service request; and adjust the sampling rate of the service request of the server according to the change of the service request of the server.

[0067] A third aspect of the present application provides an electronic device, comprising: at least one processor and a memory;

[0068] The memory stores computer-executable instructions;

[0069] The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor performs the method described in the first aspect and various possible designs of the first aspect.

[0070] A fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions. When a processor executes the computer-executable instructions, the method described in the first aspect and various possible designs of the first aspect are implemented.

[0071] A fifth aspect of the present application provides a computer program product, including computer instructions, which are used to enable a computer to execute the method described in the first aspect and various possible designs of the first aspect.

[0072] The technical solution of this application has the following advantages:

[0073] The present application provides a data storage resource processing method, device, electronic device and storage medium, the method comprising: obtaining characteristic information of a business request sent by a server to a data storage system and the current business mode of the server; constructing a data model of the business request based on the characteristic information; determining the target data storage strategy corresponding to the business request based on the data model and the current business mode of the server; allocating storage resources to the business request based on the target data storage strategy to store the data to be stored in the business request to the data storage system. The method provided by the above scheme improves the performance of the data storage system by allocating storage resources based on the business request characteristics and the current business mode of the server, ensuring that the storage resource allocation result matches the actual application scenario of the server, and laying a foundation for improving the front-end business response rate of the server. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the following is a brief introduction to the drawings required for use in the embodiments or the related technical descriptions. Obviously, the drawings described below are some embodiments of the present application, and a person skilled in the art can also obtain other drawings based on these drawings.

[0075] Figure 1 This is a schematic diagram of the structure of the data storage resource processing system on which the embodiment of the present application is based;

[0076] Figure 2 A schematic diagram of a process flow of a data storage resource processing method provided in an embodiment of the present application;

[0077] Figure 3 A structural diagram of a data storage resource processing device provided in an embodiment of the present application;

[0078] Figure 4 A schematic diagram of the structure of another data storage resource processing device provided in an embodiment of the present application;

[0079] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0080] The above drawings have shown clear embodiments of the present application, which will be described in more detail below. These drawings and text descriptions are not intended to limit the scope of the present disclosure in any way, but to illustrate the concepts of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0081] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0082] In addition, the terms "first", "second", etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. In the description of the following embodiments, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0083] In the related technologies, with the rapid development of information technology, the amount of data has exploded, and the demands on data storage systems, especially high-end centralized storage, have become increasingly high. Existing centralized storage systems usually adopt fixed storage strategies when facing different types of IO requests (size / read / write / random, sequential), which leads to the inability to effectively guarantee and improve the performance in different application scenarios, especially when the business model (data model) changes. Therefore, it is particularly important to develop a storage policy management module that can adaptively adjust according to the characteristics of IO requests. Currently, there is no independent module in the industry to predict this changing data model and adaptively adjust the storage strategy. In some extreme scenarios, it is easy to cause the cluster to be unable to respond to the front-end business in a timely manner, thereby affecting the availability of the entire system.

[0084] In response to the above problems, the embodiments of the present application provide a data storage resource processing method, device, electronic device and storage medium, the method comprising: obtaining characteristic information of a business request sent by a server to a data storage system and the current business mode of the server; constructing a data model of the business request based on the characteristic information; determining the target data storage strategy corresponding to the business request based on the data model and the current business mode of the server; allocating storage resources to the business request based on the target data storage strategy to store the data to be stored in the business request to the data storage system. The method provided by the above scheme improves the performance of the data storage system by allocating storage resources based on the business request characteristics and the current business mode of the server, ensuring that the storage resource allocation result matches the actual application scenario of the server, and laying a foundation for improving the front-end business response rate of the server.

[0085] The following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0086] First, the structure of the data storage resource processing system on which this application is based is described:

[0087] The data storage resource processing method, device, electronic device and storage medium provided in the embodiments of the present application are suitable for allocating storage resources for service requests when a service end sends a service request to a data storage system to store I / O data. Figure 1 As shown, it is a structural diagram of the data storage resource processing system based on the embodiment of the present application, which mainly includes a data storage resource processing device, a server and a data storage system. The data storage resource processing device is used to collect and analyze the business requests sent by the server to the data storage system, and allocate storage resources to the business requests according to the analysis results, so as to ensure that the storage resource allocation results match the actual application scenarios of the server, thereby improving the performance of the data storage system.

[0088] The embodiment of the present application provides a data storage resource processing method, which is used to allocate storage resources for a service request when a service request is sent by a server to a data storage system to store I / O data. The execution subject of the embodiment of the present application is an electronic device, such as a server, a desktop computer, a laptop computer, a tablet computer, and other electronic devices that can be used for data storage resource processing.

[0089] like Figure 2 As shown, it is a flow chart of a data storage resource processing method provided in an embodiment of the present application, and the method includes:

[0090] Step 201: Acquire characteristic information of a service request sent by a server to a data storage system and a current service mode of the server.

[0091] The characteristic information of the service request includes at least the size, read / write type and read / write mode of the service request, and the current service mode of the server includes at least the normal mode and the high availability mode.

[0092] Step 202: construct a data model of the business request based on the characteristic information.

[0093] Specifically, the data model of the business request can be obtained by regularizing the feature information.

[0094] Specifically, in one embodiment, several characteristic indicators of the service request may be determined according to the characteristic information; and a data model of the service request may be constructed according to a preset data structure of the data model and the several characteristic indicators.

[0095] The characteristic indicators of the service request include the size of the service request, the read / write type, and the value of the read / write mode.

[0096] Specifically, several characteristic indicators of the business request can be processed in a regularized manner according to the preset data structure of the data model, so as to record several characteristic indicators in the format required by the preset data structure and obtain the data model of the business request for matching with the standard data model.

[0097] Step 203: Determine the target data storage strategy corresponding to the business request based on the data model and the current business mode of the server.

[0098] Specifically, by analyzing the data model and the current business model of the server, the actual current business scenario of the server is determined, and then the target data storage strategy that meets its actual business scenario is determined.

[0099] Step 204 : Allocate storage resources to the business request based on the target data storage policy, so as to store the data to be stored in the business request into the data storage system.

[0100] The target data storage strategy includes a storage resource allocation strategy of a data storage system, and the storage resources of the data storage system include processor computing resources.

[0101] On the basis of the above embodiments, since the server has different performance requirements for data storage in different business modes, the performance requirements for data storage in the high availability mode are relatively high. Therefore, in order to further ensure the reliability of the result of determining the target data storage strategy, as an implementable method, in one embodiment, according to the data model and the current business mode of the server, the target data storage strategy corresponding to the business request is determined, including:

[0102] Step 2031, judging whether the data model needs to be adjusted in parameters according to the current business mode of the server;

[0103] Step 2032: when it is determined that the data model needs to be adjusted in parameters, the performance of the data storage system for different types of business requests is determined according to the backend disk array storage medium of the data storage system;

[0104] Step 2033, determining a parameter adjustment strategy for the data model according to the performance of the data storage system for different types of business requests;

[0105] Step 2034, adjusting the parameters of the data model according to the parameter adjustment strategy of the data model to obtain an optimized data model;

[0106] Step 2035, matching the optimized data model with the standard data model in the preset database to obtain a data model matching result;

[0107] Step 2036: Determine the target data storage strategy corresponding to the business request based on the data model matching result.

[0108] The service mode of the server is divided into at least two types: a normal mode and a high availability mode. When the current service mode of the server is a high availability mode, it is determined that the data model needs to be adjusted in parameters.

[0109] It should be noted that the server has high requirements for business continuity in high availability mode. Therefore, by further optimizing the data model in high availability mode, it is ensured that the final target data storage strategy can improve the business continuity of the server.

[0110] Accordingly, in one embodiment, when the current business mode of the server is the normal mode, it can be determined that the data model does not need to adjust parameters; the data model is directly matched with the standard data model in the preset database to obtain a data model matching result; and based on the data model matching result, the target data storage strategy corresponding to the business request is determined.

[0111] Specifically, the data model constructed in the embodiment of the present application can be matched with the parameters in the standard data model in the preset database, and the model type of the matching standard data model can be used as the model type of the data model, and then the data storage strategy corresponding to the model type can be used as the target data storage strategy.

[0112] Among them, the parameters of the data model are the values ​​of the characteristic indicators of the business request. For any parameter, if the value of the parameter in the data model constructed in the embodiment of the present application is the same as its value in a standard data model or the difference is within a preset matching range, then it is determined that the standard data model matches the data model constructed in the embodiment of the present application in terms of the parameter; if all parameters of a standard data model match the parameters of the data model constructed in the embodiment of the present application, then it is determined that the standard data model matches the data model constructed in the embodiment of the present application.

[0113] Specifically, in one embodiment, if there is no matching standard data model in the preset database, the historical business requests of the server can be analyzed and mined to determine the business request patterns and rules of the server, thereby providing a reference for the formulation of data storage strategies.

[0114] Specifically, historical business requests can be clustered to find similarities and patterns in business requests. For example, requests can be grouped according to features such as request size, read / write type, and request order, and then the request group of the currently collected business requests can be determined. Finally, the data storage strategy with the most usage in the request group can be used as the target data storage strategy.

[0115] Specifically, in one embodiment, historical business requests can also be used to predict future trends and behaviors. By analyzing past business requests and data storage conditions, a prediction model is established to predict future request patterns and data volumes, and then the target data storage strategy corresponding to the current business request is determined based on the prediction results.

[0116] Specifically, in one embodiment, the weight adjustment coefficient of each parameter in the data model can be determined according to the parameter adjustment strategy of the data model; the parameters of the data model are adjusted according to the weight adjustment coefficient of each parameter in the data model to obtain an optimized data model.

[0117] The parameters in the data model include characteristic indicators of the business request.

[0118] It should be noted that the back-end disk array storage medium of the data storage system includes at least hard disks, mechanical hard disks (HHD) and solid state disks (SSD). For HDD, the weight of random sequential requests (read-write mode) is higher than that of SSD, because HDD has poor performance when processing random business requests and requires more resources to optimize. For SSD, the weight of read-write type requests is higher than that of HDD, because SSD is faster when processing read-write operations, but is also more susceptible to frequent read-write requests. Through this differentiated setting of characteristic value (parameter) weights, the corresponding parameter adjustment of the data model is performed according to the weight adjustment coefficient of each parameter, so that the optimized data model can not only reflect the actual application scenario of the server, but also adapt to the back-end disk array storage medium of the data storage system, further improving the reliability of the target data storage strategy determination result, and further improving the performance of the data storage system.

[0119] Based on the above embodiment, as an implementable manner, in one embodiment, based on the target data storage policy, storage resources are allocated to the business request to store the data to be stored in the business request in the data storage system, including:

[0120] Step 2041, binding a processor core for the service request in the data storage system according to the target data storage policy;

[0121] Step 2042: Based on the processor core responding to the service request, the to-be-stored data of the service request is stored in the data storage system.

[0122] Storage resources include processor cores. Different data models of business requests have different resource requirements for the data storage system, so different processor core binding strategies need to be adopted. For high-frequency random business requests, a multi-core binding strategy can be adopted to allocate more computing resources to the cores that process these requests to improve processing efficiency. For sequential business requests, a single-core binding strategy can be adopted to concentrate resources to process continuous read and write operations to improve the performance of sequential processing, thereby maximizing system performance.

[0123] Specifically, the processor core to be bound to the current service request may be determined according to the target data storage policy, and then the processor core to be bound may be bound to the current service request.

[0124] Based on the above embodiment, as an implementable manner, in one embodiment, the method further includes:

[0125] Step 301, determining changes in the service request of the server according to the data model of the service request;

[0126] Step 302: adjusting the sampling rate of the service requests from the server according to the changes in the service requests from the server.

[0127] It should be noted that the method provided in the embodiment of the present application actually collects the business requests sent by the server according to a certain sampling rate, and determines the corresponding target data storage strategy. Before collecting the business requests of the next cycle, the business requests initiated by the server are processed according to the target data storage strategy.

[0128] Specifically, after completing the construction of a data model, the data model is compared with the previously constructed data model to determine the extent of change in the data model. According to the changes in business requests represented by the extent of change in the data model, the sampling rate of business requests to the server is increased or decreased.

[0129] There are different sampling rate change ranges for the normal mode and the high availability mode, and the sampling rate adjustment granularity in the high availability mode is smaller than that in the normal mode.

[0130] Specifically, when the data model changes dramatically, for example, a random business request suddenly becomes a sequential business request, the sampling rate will be rapidly increased to capture new data model features more quickly, thereby adjusting the target data storage strategy in a timely manner. When the data model changes only slightly, the sampling rate will be reduced to reduce the impact of the sampling process on system performance. Among them, increasing the sampling rate means shortening the time interval for collecting business requests, such as increasing the collection of business requests from once every 5 minutes to once every 3 minutes. Reducing the sampling rate means increasing the time interval for collecting business requests, such as reducing the collection of business requests from once every 5 minutes to once every 8 minutes.

[0131] The data storage resource processing method provided in the embodiment of the present application obtains the characteristic information of the business request sent by the server to the data storage system and the current business mode of the server; constructs the data model of the business request according to the characteristic information; determines the target data storage strategy corresponding to the business request according to the data model and the current business mode of the server; and allocates storage resources to the business request based on the target data storage strategy to store the data to be stored in the business request to the data storage system. The method provided by the above scheme improves the performance of the data storage system by allocating storage resources according to the business request characteristics and the current business mode of the server, ensuring that the storage resource allocation result matches the actual application scenario of the server, thereby laying a foundation for improving the front-end business response rate of the server. In addition, by adjusting the sampling rate of the business request according to the changes in the data model, the utilization rate of system resources is improved, and the performance of the data storage system is further guaranteed. In addition, by adjusting the differentiated strategy adjustments in two different storage modes, the normal mode and the high availability mode, the abnormal problems such as the inability of the cluster to respond to the front-end business in a timely manner in extreme scenarios are avoided, thereby improving the availability of the whole system.

[0132] An embodiment of the present application provides a data storage resource processing device for executing the data storage resource processing method provided in the above embodiment.

[0133] like Figure 3 , which is a schematic diagram of a data storage resource processing device provided in an embodiment of the present application. The data storage resource processing device 30 comprises: an acquisition module 301 , a construction module 302 , a determination module 303 and a processing module 304 .

[0134] Among them, the acquisition module is used to obtain the characteristic information of the business request sent by the server to the data storage system and the current business mode of the server; the construction module is used to construct the data model of the business request according to the characteristic information; the determination module is used to determine the target data storage strategy corresponding to the business request according to the data model and the current business mode of the server; the processing module is used to allocate storage resources to the business request based on the target data storage strategy, so as to store the data to be stored in the business request to the data storage system.

[0135] Specifically, in one embodiment, the construction module is specifically used to:

[0136] According to the characteristic information, several characteristic indicators of the business request are determined;

[0137] Construct a data model for business requests based on the preset data structure and several characteristic indicators of the data model.

[0138] Specifically, in one embodiment, the determination module is specifically used to:

[0139] Determine whether the data model needs parameter adjustment based on the current business model of the server;

[0140] When it is determined that the data model needs to be adjusted, the performance of the data storage system for different types of business requests is determined based on the backend disk array storage medium of the data storage system;

[0141] Determine the parameter adjustment strategy of the data model based on the performance of the data storage system for different types of business requests;

[0142] According to the parameter adjustment strategy of the data model, the parameters of the data model are adjusted to obtain an optimized data model;

[0143] Matching the optimized data model with the standard data model in the preset database to obtain a data model matching result;

[0144] Determine the target data storage strategy corresponding to the business request based on the data model matching result;

[0145] The service mode of the server is divided into at least two types: a normal mode and a high availability mode. When the current service mode of the server is a high availability mode, it is determined that the data model needs to be adjusted in parameters.

[0146] Specifically, in one embodiment, the determination module is further used to:

[0147] When the current business mode of the server is the normal mode, it is determined that the data model does not need parameter adjustment;

[0148] Directly match the data model with the standard data model in the preset database to obtain the data model matching result;

[0149] According to the data model matching results, determine the target data storage strategy corresponding to the business request.

[0150] Specifically, in one embodiment, the determination module is specifically used to:

[0151] According to the parameter adjustment strategy of the data model, determine the weight adjustment coefficient of each parameter in the data model;

[0152] According to the weight adjustment coefficient of each parameter in the data model, the parameters of the data model are adjusted to obtain an optimized data model;

[0153] The parameters in the data model include characteristic indicators of the business request.

[0154] Specifically, in one embodiment, the processing module is specifically used to:

[0155] Binding processor cores for business requests in a data storage system according to a target data storage policy;

[0156] Responding to the service request based on the processor core to store the data to be stored in the service request to the data storage system;

[0157] Among them, the storage resources include processor cores.

[0158] Specifically, in one embodiment, the device further includes:

[0159] The sampling rate adjustment module is used to determine the change of the service request of the server according to the data model of the service request; and adjust the sampling rate of the service request of the server according to the change of the service request of the server.

[0160] For example, as another division of logical functions, Figure 4As shown, it is a structural schematic diagram of another data storage resource processing device provided by an embodiment of the present application, the device includes a data model prediction management module, a business module, a data model analysis module, a sampling rate adjustment module, a characteristic value database module, a parameter module and a storage policy adjustment module. The data model prediction management module (DMP management module) is located on the board of the server, and is mainly implemented by programmable logic devices such as ARM. The DMP management module can dynamically manage the data model analysis module, the sampling rate adjustment module, the characteristic value database module and the storage policy adjustment module in normal mode and high availability mode respectively based on the method provided in the above embodiment. The data model analysis module is responsible for receiving I / O business requests from business modules such as servers, and extracting the characteristic values ​​of the requests to the DMP management module. The parameter module can perform information exchange between the outside world and the DMP management module, parameter preset and activation of related functions, etc. The data storage resource processing device provided by the embodiment of the present application has strong practical value and broad application prospects, and is suitable for performance optimization of various centralized storage systems.

[0161] Regarding the data storage resource processing device in this embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0162] The data storage resource processing device provided in the embodiment of the present application is used to execute the data storage resource processing method provided in the above embodiment. Its implementation method and principle are the same and will not be repeated here.

[0163] An embodiment of the present application provides an electronic device for executing the data storage resource processing method provided in the above embodiment.

[0164] like Figure 5 FIG. 5 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device 50 includes: at least one processor 51 and a memory 52.

[0165] The memory stores computer-executable instructions; at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the data storage resource processing method provided in the above embodiment.

[0166] The electronic device provided in the embodiment of the present application is used to execute the data storage resource processing method provided in the above embodiment. Its implementation method and principle are the same and will not be repeated here.

[0167] An embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the data storage resource processing method provided in any of the above embodiments is implemented.

[0168] The storage medium containing computer executable instructions provided in the embodiments of the present application can be used to store computer executable instructions of the data storage resource processing method provided in the aforementioned embodiments. The implementation method and principle are the same and will not be repeated here.

[0169] An embodiment of the present application provides a computer program product, including computer instructions, which are used to enable a computer to execute the data storage resource processing method provided in the above-mentioned embodiment.

[0170] The embodiments of the present application provide a computer program product that can be used to execute computer instructions of the data storage resource processing method provided in the aforementioned embodiments. The implementation method and principle are the same and will not be repeated here.

[0171] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0172] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0173] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0174] The above-mentioned integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform some steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0175] A part of the present application may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of computer program instructions in computer-readable media includes, but is not limited to, source files, executable files, installation package files, etc., and accordingly, the way in which computer program instructions are executed by a computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to the computer.

[0176] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0177] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A data storage resource processing method, characterized in that: include: Acquire characteristic information of a service request sent by a server to a data storage system and a current service mode of the server; Constructing a data model of the business request according to the characteristic information; Determine a target data storage strategy corresponding to the business request according to the data model and the current business mode of the server; Based on the target data storage policy, storage resources are allocated to the business request to store the data to be stored in the business request in the data storage system.

2. The method according to claim 1, characterized in that The step of constructing a data model of the service request according to the characteristic information includes: Determining several characteristic indicators of the service request according to the characteristic information; A data model of the business request is constructed according to a preset data structure of the data model and the plurality of characteristic indicators.

3. The method according to claim 1, characterized in that: Determining the target data storage strategy corresponding to the business request according to the data model and the current business mode of the server includes: According to the current business mode of the server, determining whether the data model needs to be adjusted in parameters; In the case where it is determined that the data model needs to be adjusted in parameters, determining the performance of the data storage system for different types of business requests according to the backend disk array storage medium of the data storage system; Determining a parameter adjustment strategy for the data model according to the performance of the data storage system for different types of business requests; According to the parameter adjustment strategy of the data model, the parameters of the data model are adjusted to obtain an optimized data model; Matching the optimized data model with a standard data model in a preset database to obtain a data model matching result; Determining a target data storage strategy corresponding to the business request according to the data model matching result; The service mode of the server is divided into at least two types: a normal mode and a high availability mode. When the current service mode of the server is the high availability mode, it is determined that the data model needs to be adjusted in parameters.

4. The method according to claim 3, characterized in that: The method further comprises: When the current service mode of the server is a normal mode, determining that the data model does not need parameter adjustment; Directly matching the data model with a standard data model in a preset database to obtain a data model matching result; A target data storage strategy corresponding to the business request is determined according to the data model matching result.

5. The method according to claim 3, characterized in that: The step of adjusting the parameters of the data model according to the parameter adjustment strategy of the data model to obtain an optimized data model includes: Determining a weight adjustment coefficient of each parameter in the data model according to a parameter adjustment strategy of the data model; According to the weight adjustment coefficient of each parameter in the data model, the parameters of the data model are adjusted to obtain an optimized data model; The parameters in the data model include characteristic indicators of the business request.

6. The method according to claim 1, characterized in that The allocating storage resources to the business request based on the target data storage policy to store the data to be stored of the business request in the data storage system includes: Binding a processor core for the service request in the data storage system according to the target data storage policy; Responding to the service request based on the processor core to store the to-be-stored data of the service request in the data storage system; Wherein, the storage resource includes a processor core.

7. The method according to claim 1, characterized in that The method further comprises: Determining changes in the service request of the server according to the data model of the service request; According to changes in the service requests of the server, the sampling rate of the service requests of the server is adjusted.

8. A data storage resource processing device, characterized in that: include: An acquisition module, used to acquire characteristic information of a service request sent by a server to a data storage system and a current service mode of the server; A construction module, used to construct a data model of the business request according to the characteristic information; A determination module, used to determine a target data storage strategy corresponding to the business request according to the data model and the current business mode of the server; A processing module is used to allocate storage resources to the business request based on the target data storage policy, so as to store the data to be stored of the business request in the data storage system.

9. An electronic device, characterized in that: include: at least one processor and memory; The memory stores computer-executable instructions; The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor performs the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when a processor executes the computer-executable instructions, the method according to any one of claims 1 to 7 is implemented.

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