CN117093439A - Method, device, electronic equipment and storage medium for capacity data processing - Google Patents
Method, device, electronic equipment and storage medium for capacity data processing Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 41
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- 238000004590 computer program Methods 0.000 claims description 16
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/3024—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a central processing unit [CPU]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3065—Monitoring arrangements determined by the means or processing involved in reporting the monitored data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/30—Arrangements for executing machine instructions, e.g. instruction decode
- G06F9/30003—Arrangements for executing specific machine instructions
- G06F9/30076—Arrangements for executing specific machine instructions to perform miscellaneous control operations, e.g. NOP
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract
The application discloses a method and a device for processing capacity data, electronic equipment and a storage medium, and relates to the technical field of computers. One embodiment of the method comprises the following steps: receiving a processing instruction of system capacity, and acquiring service data corresponding to a system in a preset time period; invoking a preset capacity data processing model, calculating parameter values of preset capacity assessment parameters based on service data, and acquiring historical parameter values of the capacity assessment parameters to generate a transformation trend of the capacity assessment parameters; and responding to the change trend meeting the abnormal condition, acquiring a capacity adjustment strategy associated with the capacity evaluation parameter to generate a system capacity adjustment instruction and sending the system capacity adjustment instruction. The implementation mode can solve the problems that the prior art can not perform reasonable analysis on the system capacity, is easy to cause abnormal operation of a service system, seriously affects service processing of the service system and reduces the system performance.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method and apparatus for processing capacity data, an electronic device, and a storage medium.
Background
With the entering of human society into an informatization age, increasingly vigorous social activities put forward high demands on continuous operation and healthy development of services of each service system, system infrastructure must have extremely high safety and stability, and capacity analysis of the system is important for guaranteeing stable, safe and efficient operation of the system and guaranteeing timely and rapid information processing capability of the information system. In the prior art, the analysis and management modes of the system capacity are various, but the rationalization analysis of the system capacity can not be achieved, so that the operation abnormality of a service system is easy to cause, the service processing of the service system is seriously affected, and the system performance is reduced.
Disclosure of Invention
In view of the above, embodiments of the present application provide a method, an apparatus, an electronic device, and a storage medium for processing capacity data, which can solve the problem that the prior art cannot perform reasonable analysis on system capacity, which easily causes abnormal operation of a service system, seriously affects service processing of the service system, and reduces system performance.
To achieve the above object, according to one aspect of an embodiment of the present application, there is provided a method of capacity data processing.
The method for processing the capacity data comprises the following steps: receiving a processing instruction of system capacity, and acquiring service data corresponding to a system in a preset time period, wherein the service data comprises capability data of system service, response time of service processing and/or concurrence of service data;
invoking a preset capacity data processing model, calculating parameter values of preset capacity assessment parameters based on the service data, and acquiring historical parameter values of the capacity assessment parameters to generate a transformation trend of the capacity assessment parameters;
and responding to the change trend meeting an abnormal condition, acquiring a capacity adjustment strategy associated with the capacity evaluation parameter to generate a system capacity adjustment instruction and sending the system capacity adjustment instruction.
In one embodiment, the capacity assessment parameter includes central processor utilization;
and responding to the change trend meeting an abnormal condition, acquiring a capacity adjustment strategy associated with the capacity evaluation parameter, wherein the capacity adjustment strategy comprises the following steps:
determining a predicted value of the CPU utilization rate based on the change trend;
and responding to the predicted value of the CPU utilization rate meeting a preset abnormal interval, determining that the CPU utilization rate meets an abnormal condition, and acquiring a capacity adjustment strategy associated with the capacity evaluation parameter.
In yet another embodiment, obtaining the capacity adjustment policy associated with the capacity assessment parameter to generate a system capacity adjustment instruction includes:
acquiring a capacity adjustment strategy associated with the capacity evaluation parameter to determine a corresponding system adjustment object identifier;
and acquiring an operation parameter corresponding to the system adjustment object identifier, and generating a system capacity adjustment instruction based on the operation parameter.
In yet another embodiment, obtaining an operation parameter corresponding to the system adjustment object identifier, generating a system capacity adjustment instruction based on the operation parameter, including:
and inquiring the adjustment level associated with the system adjustment object identifiers, and determining the system adjustment object identifiers to be adjusted based on the adjustment level so as to acquire corresponding operation parameters.
In yet another embodiment, generating system capacity adjustment instructions based on the operating parameters includes:
obtaining a standard operation parameter corresponding to the system adjustment object identifier so as to compare the operation parameter with the standard operation parameter;
in response to the operating parameter and the standard operating parameter being different, a system capacity adjustment instruction is generated based on a difference between the operating parameter and the standard operating parameter.
In yet another embodiment, after generating the transformation trend of the capacity estimation parameter, further comprising:
and calling a preset page template to combine the transformation trend, generating a visual page and sending the visual page.
In yet another embodiment, the method further comprises:
and acquiring historical service data of the system to train a preset multiple linear regression analysis model so as to obtain the capacity data processing model.
To achieve the above object, according to another aspect of an embodiment of the present application, there is provided an apparatus for capacity data processing.
The device for processing the capacity data comprises: the system comprises a receiving unit, a processing unit and a processing unit, wherein the receiving unit is used for receiving a processing instruction of system capacity and acquiring service data corresponding to a system in a preset time period, and the service data comprises capability data of system service, response time of service processing and/or concurrency of the service data;
the determining unit is used for calling a preset capacity data processing model, calculating parameter values of preset capacity assessment parameters based on the service data, and obtaining historical parameter values of the capacity assessment parameters so as to generate a transformation trend of the capacity assessment parameters;
and the generation unit is used for responding to the change trend to meet the abnormal condition, acquiring a capacity adjustment strategy associated with the capacity evaluation parameter, generating a system capacity adjustment instruction and sending the system capacity adjustment instruction.
In one embodiment, the capacity assessment parameter includes central processor utilization;
the generating unit is specifically configured to:
determining a predicted value of the CPU utilization rate based on the change trend;
and responding to the predicted value of the CPU utilization rate meeting a preset abnormal interval, determining that the CPU utilization rate meets an abnormal condition, and acquiring a capacity adjustment strategy associated with the capacity evaluation parameter.
In a further embodiment, the generating unit is specifically configured to:
acquiring a capacity adjustment strategy associated with the capacity evaluation parameter to determine a corresponding system adjustment object identifier;
and acquiring an operation parameter corresponding to the system adjustment object identifier, and generating a system capacity adjustment instruction based on the operation parameter.
In a further embodiment, the generating unit is specifically configured to:
and inquiring the adjustment level associated with the system adjustment object identifiers, and determining the system adjustment object identifiers to be adjusted based on the adjustment level so as to acquire corresponding operation parameters.
In a further embodiment, the generating unit is specifically configured to:
obtaining a standard operation parameter corresponding to the system adjustment object identifier so as to compare the operation parameter with the standard operation parameter;
in response to the operating parameter and the standard operating parameter being different, a system capacity adjustment instruction is generated based on a difference between the operating parameter and the standard operating parameter.
In yet another embodiment, the generating unit is further configured to call a preset page template to generate and send a visual page in combination with the transformation trend.
In yet another embodiment, the apparatus further comprises:
and the training unit is used for acquiring historical service data of the system so as to train a preset multiple linear regression analysis model and obtain the capacity data processing model.
To achieve the above object, according to still another aspect of an embodiment of the present application, there is provided an electronic apparatus.
An electronic device according to an embodiment of the present application includes: one or more processors; and the storage device is used for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors are enabled to realize the method for processing the capacity data provided by the embodiment of the application.
To achieve the above object, according to still another aspect of an embodiment of the present application, a computer-readable medium is provided.
A computer readable medium of an embodiment of the present application has stored thereon a computer program which, when executed by a processor, implements a method for capacity data processing provided by the embodiment of the present application.
To achieve the above object, according to still another aspect of an embodiment of the present application, there is provided a computer program product.
A computer program product of an embodiment of the present application includes a computer program that, when executed by a processor, implements a method for capacity data processing provided by the embodiment of the present application.
One embodiment of the above application has the following advantages or benefits: in the embodiment of the application, after receiving the processing instruction of the system capacity, the service data corresponding to the system in the preset time period can be acquired, then the parameter value of the capacity evaluation parameter can be determined through the capacity data processing model, so that the transformation trend of the capacity evaluation parameter can be generated by combining the historical parameter value of the capacity evaluation parameter, and the corresponding system capacity adjustment instruction can be generated after the abnormal condition is determined to be met based on the variation trend, so as to adjust the system capacity. In the embodiment of the application, the capacity evaluation parameters are calculated through the real-time service data, the change trend is analyzed by combining the historical capacity evaluation parameters, so that whether the system capacity is abnormal or not is determined based on the change trend, and a system capacity adjustment instruction associated with the abnormality is generated after the abnormality is determined, thereby realizing the timely adjustment of the system capacity, avoiding the abnormal operation of the system, affecting the service processing and improving the system performance.
Further effects of the above-described non-conventional alternatives are described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the application and are not to be construed as unduly limiting the application. Wherein:
FIG. 1 is a schematic diagram of one main flow of a method of capacity data processing according to an embodiment of the present application;
FIG. 2 is a schematic diagram of yet another main flow of a method of capacity data processing according to an embodiment of the present application;
FIG. 3 is a schematic diagram of yet another main flow of a method of capacity data processing according to an embodiment of the present application;
FIG. 4 is a schematic diagram of the main units of an apparatus for capacity data processing according to an embodiment of the present application;
FIG. 5 is an exemplary system architecture diagram in which embodiments of the present application may be applied;
FIG. 6 is a schematic diagram of a computer system suitable for use in implementing embodiments of the present application.
Detailed Description
Exemplary embodiments of the present application will now be described with reference to the accompanying drawings, in which various details of the embodiments of the present application are included to facilitate understanding, and are to be considered merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
It is noted that embodiments of the application and features of the embodiments may be combined with each other without conflict. The technical scheme of the application obtains, stores, uses, processes and the like the data, which all meet the relevant regulations of national laws and regulations.
The embodiment of the application provides a capacity data processing system which can be used for processing the capacity data of a system, in particular to analyzing the capacity data of the system and timely adjusting the capacity data of the system.
An embodiment of the present application provides a method for capacity data processing, which may be performed by a capacity data processing system, as shown in fig. 1, and includes:
s101: receiving a processing instruction of the system capacity, and acquiring service data corresponding to the system in a preset time period.
Wherein the service data comprises capability data of system service, response time of service processing and/or concurrency of service data. The processing instruction of the system capacity can be sent by external equipment or automatically triggered by the system, for example, the system automatically triggers the processing instruction of the system capacity according to a preset period. In the embodiment of the application, after receiving the processing instruction of the system capacity, the service data corresponding to the system in the preset time period can be acquired, and the preset time period can be set based on requirements, for example, can be one day, one week and the like. The service data may represent data affected by the capacity of the receiving system, for example, may include response time of the service data, concurrency of the service data, capability data of the system service, and the like, and the capability data represents data of the system processing service capability, specifically may be service processing capacity and the like.
S102: and calling a preset capacity data processing model, calculating parameter values of preset capacity assessment parameters based on service data, and acquiring historical parameter values of the capacity assessment parameters to generate a transformation trend of the capacity assessment parameters.
The capacity data processing model may be pre-trained, the input of the capacity data processing model may be service data, the output may be a preset capacity evaluation parameter, and the capacity evaluation parameter may be specifically a Central Processing Unit (CPU) utilization rate. The service data may be input to the capacity data processing model after being acquired in this step to calculate a parameter value corresponding to the capacity estimation parameter.
The parameter values of the capacity estimation parameters can be combined with the historical parameter values of the capacity estimation parameters to compare the two parameters, so as to determine the change trend of the capacity estimation parameters. Since the system capacity generally needs to keep stable or a stable trend to illustrate that the system capacity is kept stable, in the embodiment of the present application, whether the system capacity is stable or not and whether adjustment is needed or not may be determined based on the change trend of the capacity evaluation parameter.
In one implementation of the embodiment of the present application, the capacity data processing model may be implemented using various types of models, for example, a multiple linear regression analysis model. Therefore, in the embodiment of the application, before executing step S102, the historical service data of the system can be obtained to train the preset multiple linear regression analysis model, so as to obtain the capacity data processing model.
The historical service data can comprise service data and parameter values of capacity evaluation parameters in a historical time period so as to train a preset multiple linear regression analysis model, and the training can be used as a capacity data processing model after the training is completed.
S103: and responding to the change trend meeting the abnormal condition, acquiring a capacity adjustment strategy associated with the capacity evaluation parameter to generate a system capacity adjustment instruction and sending the system capacity adjustment instruction.
After the transformation trend of the capacity evaluation parameter is obtained, whether an abnormal condition is satisfied can be judged, and if so, the system capacity needs to be adjusted. In the embodiment of the application, the capacity adjustment strategy associated with the capacity evaluation parameter can be preset, and the system capacity adjustment instruction is generated based on the capacity adjustment strategy, so that the capacity adjustment of the system is conveniently executed through the system capacity adjustment instruction.
In the embodiment of the application, the abnormal condition can be set based on requirements and scenes. For example, a predicted value of the content estimation parameter may be predicted for a period of time based on the variation trend, and then whether the predicted value is within a preset abnormal section of the capacity estimation parameter is determined; if yes, determining that the change trend meets the abnormal condition; if not, it can be determined that the trend of variation does not satisfy the abnormal condition. Specifically, taking the capacity evaluation parameter as an example of the CPU change rate, it may be specifically executed as: determining a predicted value of the CPU utilization rate based on the change trend; and responding to the predicted value of the CPU utilization rate meeting the preset abnormal interval, determining that the CPU utilization rate meets the abnormal condition, and acquiring a capacity adjustment strategy associated with the capacity evaluation parameter. The preset abnormal section may be a section greater than 90%. In order to improve the prediction accuracy, the prediction value in this step may be a prediction value in a short time, such as a prediction value in one day.
It should be noted that, in the embodiment of the present application, the parameter value of the capacity evaluation parameter is obtained in step S102, and whether the parameter value meets the preset abnormal interval may also be directly determined, if yes, the method may be directly performed: and acquiring a capacity adjustment strategy associated with the capacity evaluation parameter to generate a system capacity adjustment instruction and sending the system capacity adjustment instruction. So that the system capacity can be adjusted in time.
In the embodiment of the application, the adjustment of the system capacity can be realized through various adjustment modes, for example, the adjustment of the system capacity can be realized through adjusting hardware management, network equipment management, peripheral equipment management, software management and human resource management. Wherein, the hardware management comprises personal computers, file servers, medium-sized computers, large-sized computers and ultra-large-sized computers; network device management includes one or more of local area networks, wide area networks, bridges, and routers; peripheral management includes storage devices and printers; software management includes operating systems, networks, internally developed software packages, and purchased software packages; human resource management includes the need for sufficient maintenance personnel to prevent delaying end-to-end response times.
The manner in which the adjustment can be used is determined according to the actual structure of the system, and thus the adjustment policy is determined, for example, hardware management in the system includes a personal computer, network device management includes a local area network, and peripheral device management includes a printer, so the adjustment policy may include adjustments to the personal computer, the local area network, and the printer. In order to execute the adjustment policies, in the embodiment of the present application, an association between each adjustment policy and the system adjustment object identifier may be established. For example, the adjustment policy includes an adjustment to a personal computer, and the personal computer included in the system is a system adjustment object, so that an association between a personal computer identifier that can be used for adjustment and this adjustment policy can be established, and this step can be specifically performed as: acquiring a capacity adjustment strategy associated with the capacity evaluation parameter to determine a corresponding system adjustment object identifier; and acquiring an operation parameter corresponding to the system adjustment object identifier, and generating a system capacity adjustment instruction based on the operation parameter. The operating parameters may include a variety of factors, such as whether the system is in an operational state, etc., so that it may be determined how to adjust the system adjustment object in order to generate the system capacity adjustment command.
Specifically, in the embodiment of the present application, a corresponding standard operation parameter may be set for each system adjustment object, that is, an operation parameter value that must be ensured by the system adjustment object under the condition of normal operation of the system, in order to ensure that the system can operate normally, when the system adjustment object is adjusted, the standard operation parameter needs to be used as a reference, so that the system capacity adjustment instruction may be generated in this step: acquiring a standard operation parameter corresponding to the system adjustment object identifier so as to compare the operation parameter with the standard operation parameter; in response to the operating parameter and the standard operating parameter being different, a system capacity adjustment instruction is generated based on a difference between the operating parameter and the standard operating parameter.
The operation parameters are the same as the standard operation parameters, which indicates that the system adjustment object can not be adjusted any more, so that the system adjustment object can not be adjusted at the moment, namely, a system capacity adjustment instruction corresponding to the system adjustment object is not generated; the operation parameters are different from the standard operation parameters, which means that the system adjustment object can be adjusted again, so that the system capacity adjustment instruction is generated based on the difference between the operation parameters and the standard operation parameters.
Taking the system adjustment object as the personal computer as an example, the standard operation parameter can be that the working state is equal to the stop, that is, the personal computer can be turned off, so that when the working state is on in the operation parameter of the personal computer, the system capacity adjustment instruction which can be generated can be an instruction for turning off the personal computer so as to turn off the personal computer.
In the embodiment of the present application, when the capacity adjustment policies associated with the capacity evaluation parameters include a plurality of capacity adjustment policies, an adjustment level may be set for each capacity adjustment policy, and in this step, a system adjustment object identifier to be adjusted for adjustment at this time may be determined based on the adjustment level, so as to execute a step of obtaining a corresponding operation parameter, thereby implementing successive execution of the capacity adjustment policies.
In the embodiment of the application, in order to enable a user to intuitively know the change condition of the system capacity, a page template can be preset to generate a visual page based on the transformation trend and send the visual page to a terminal needing to be displayed.
In the embodiment of the application, the capacity evaluation parameters are calculated through real-time service data, the historical capacity evaluation parameters are integrated to analyze the change trend of the capacity evaluation parameters, so that whether the system capacity is abnormal or not is determined based on the capacity evaluation parameters, a system capacity adjustment instruction associated with the abnormal system capacity is generated after the abnormal system capacity is determined, and the system capacity is adjusted in time by the next person, so that the abnormal system operation is avoided, the influence on service processing is brought, and the system performance is improved.
The method for capacity data processing in the embodiment of the present application is specifically described below with reference to the system architecture shown in fig. 1, and as shown in fig. 2, the method includes:
s201: receiving a processing instruction of the system capacity, and acquiring service data corresponding to the system in a preset time period.
S202: and calling a preset capacity data processing model, and calculating a parameter value of the CPU utilization rate based on the service data.
S203: historical parameter values of the CPU utilization rate are obtained to generate a transformation trend of the CPU utilization rate.
S204: and determining a predicted value of the CPU utilization rate based on the change trend.
S205: and determining that the CPU utilization rate meets an abnormal condition in response to the predicted value of the CPU utilization rate meeting a preset abnormal interval.
S206: and acquiring a capacity adjustment strategy associated with the capacity evaluation parameter to generate a system capacity adjustment instruction.
It should be noted that, in the embodiment of the present application, the data processing principle is the same as the corresponding data processing principle in the real-time exchange rate shown in fig. 1, and will not be described herein.
The method for capacity data processing in the embodiment of the present application is specifically described below with reference to the system architecture shown in fig. 1, and as shown in fig. 2, the method includes:
s301: receiving a processing instruction of the system capacity, and acquiring service data corresponding to the system in a preset time period.
S302: and calling a preset capacity data processing model, and calculating a parameter value of the CPU utilization rate based on the service data.
S303: and determining that the CPU utilization rate meets the abnormal condition in response to the parameter value of the CPU utilization rate meeting the preset abnormal interval.
S304: and acquiring a capacity adjustment strategy associated with the capacity evaluation parameter to generate a system capacity adjustment instruction.
It should be noted that, in the embodiment of the present application, the data processing principle is the same as the corresponding data processing principle in the real-time exchange rate shown in fig. 1, and will not be described herein.
In order to solve the problems existing in the prior art, an embodiment of the present application provides a device 400 for capacity data processing, as shown in fig. 4, the device 400 includes:
a receiving unit 401, configured to receive a processing instruction of a system capacity, and obtain service data corresponding to a system in a preset period of time, where the service data includes capability data of a system service, response time of service processing, and/or concurrency of service data;
a determining unit 402, configured to invoke a preset capacity data processing model, calculate a parameter value of a preset capacity estimation parameter based on the service data, and obtain a historical parameter value of the capacity estimation parameter, so as to generate a transformation trend of the capacity estimation parameter;
and the generating unit 403 is configured to obtain a capacity adjustment policy associated with the capacity evaluation parameter in response to the change trend meeting an abnormal condition, so as to generate and send a system capacity adjustment instruction.
It should be understood that the manner of implementing the embodiment of the present application is the same as that of implementing the embodiment shown in fig. 1, and will not be described herein.
In one embodiment, the capacity assessment parameter includes central processor utilization;
the generating unit 403 is specifically configured to:
determining a predicted value of the CPU utilization rate based on the change trend;
and responding to the predicted value of the CPU utilization rate meeting a preset abnormal interval, determining that the CPU utilization rate meets an abnormal condition, and acquiring a capacity adjustment strategy associated with the capacity evaluation parameter.
In yet another embodiment, the generating unit 403 is specifically configured to:
acquiring a capacity adjustment strategy associated with the capacity evaluation parameter to determine a corresponding system adjustment object identifier;
and acquiring an operation parameter corresponding to the system adjustment object identifier, and generating a system capacity adjustment instruction based on the operation parameter.
In yet another embodiment, the generating unit 403 is specifically configured to:
and inquiring the adjustment level associated with the system adjustment object identifiers, and determining the system adjustment object identifiers to be adjusted based on the adjustment level so as to acquire corresponding operation parameters.
In yet another embodiment, the generating unit 403 is specifically configured to:
obtaining a standard operation parameter corresponding to the system adjustment object identifier so as to compare the operation parameter with the standard operation parameter;
in response to the operating parameter and the standard operating parameter being different, a system capacity adjustment instruction is generated based on a difference between the operating parameter and the standard operating parameter.
In yet another embodiment, the generating unit 403 is further configured to call a preset page template to generate and send a visualized page in combination with the transformation trend.
In yet another embodiment, the apparatus 400 further comprises:
and the training unit is used for acquiring historical service data of the system so as to train a preset multiple linear regression analysis model and obtain the capacity data processing model.
It should be understood that the manner of implementing the embodiments of the present application is the same as that of implementing the embodiments shown in fig. 1, 2 and 3, and will not be described herein.
In the embodiment of the application, the capacity evaluation parameters are calculated through real-time service data, the historical capacity evaluation parameters are integrated to analyze the change trend of the capacity evaluation parameters, so that whether the system capacity is abnormal or not is determined based on the capacity evaluation parameters, a system capacity adjustment instruction associated with the abnormal system capacity is generated after the abnormal system capacity is determined, and the system capacity is adjusted in time by the next person, so that the abnormal system operation is avoided, the influence on service processing is brought, and the system performance is improved.
According to an embodiment of the present application, an electronic device and a readable storage medium are also provided.
The electronic equipment of the embodiment of the application comprises: at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the one processor, and the instructions are executed by the at least one processor, so that the at least one processor performs the method for capacity data processing provided by the embodiment of the present application.
Fig. 5 illustrates an exemplary system architecture 500 of a capacity data processing method or apparatus to which embodiments of the present application may be applied.
As shown in fig. 5, the system architecture 500 may include terminal devices 501, 502, 503, a network 504, and a server 505. The network 504 is used as a medium to provide communication links between the terminal devices 501, 502, 503 and the server 505. The network 504 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
A user may interact with the server 505 via the network 504 using the terminal devices 501, 502, 503 to receive or send messages or the like. Various client applications may be installed on the terminal devices 501, 502, 503.
The terminal devices 501, 502, 503 may be, but are not limited to, smartphones, tablets, laptop and desktop computers, and the like.
The server 505 may be a server providing various services, and may perform processing such as analysis on received data such as a product information query request, and feed back processing results (e.g., product information—merely by way of example) to the terminal device.
It should be noted that, the method for capacity data processing provided by the embodiment of the present application is generally executed by the server 505, and accordingly, the device for capacity data processing is generally disposed in the server 505.
It should be understood that the number of terminal devices, networks and servers in fig. 5 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 6, there is illustrated a schematic diagram of a computer system 600 suitable for use in implementing embodiments of the present application. The computer system shown in fig. 6 is merely an example, and should not be construed as limiting the functionality and scope of use of embodiments of the present application.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU) 601, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the system 600 are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other through a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, mouse, etc.; an output portion 607 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The drive 610 is also connected to the I/O interface 605 as needed. Removable media 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on drive 610 so that a computer program read therefrom is installed as needed into storage section 608.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 609, and/or installed from the removable medium 611. The above-described functions defined in the system of the present application are performed when the computer program is executed by a Central Processing Unit (CPU) 601.
The computer readable medium shown in the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a unit, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present application may be implemented in software or in hardware. The described units may also be provided in a processor, for example, described as: a processor includes a receiving unit, a determining unit, and a generating unit. The names of these units do not constitute a limitation on the unit itself in some cases, and for example, the receiving unit may also be described as a "unit of an instruction receiving function".
As another aspect, the present application also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be present alone without being fitted into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to perform the method of capacity data processing provided by the present application.
As another aspect, the present application also provides a computer program product, including a computer program, where the program when executed by a processor implements a method for capacity data processing provided by an embodiment of the present application.
The above embodiments do not limit the scope of the present application. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives can occur depending upon design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the scope of the present application.
Claims (15)
1. A method of capacity data processing, comprising:
receiving a processing instruction of system capacity, and acquiring service data corresponding to a system in a preset time period, wherein the service data comprises capability data of system service, response time of service processing and/or concurrence of service data;
invoking a preset capacity data processing model, calculating parameter values of preset capacity assessment parameters based on the service data, and acquiring historical parameter values of the capacity assessment parameters to generate a transformation trend of the capacity assessment parameters;
and responding to the change trend meeting an abnormal condition, acquiring a capacity adjustment strategy associated with the capacity evaluation parameter to generate a system capacity adjustment instruction and sending the system capacity adjustment instruction.
2. The method of claim 1, wherein the capacity assessment parameter comprises a central processor utilization;
and responding to the change trend meeting an abnormal condition, acquiring a capacity adjustment strategy associated with the capacity evaluation parameter, wherein the capacity adjustment strategy comprises the following steps:
determining a predicted value of the CPU utilization rate based on the change trend;
and responding to the predicted value of the CPU utilization rate meeting a preset abnormal interval, determining that the CPU utilization rate meets an abnormal condition, and acquiring a capacity adjustment strategy associated with the capacity evaluation parameter.
3. The method of claim 1, wherein obtaining the capacity adjustment policy associated with the capacity assessment parameter to generate a system capacity adjustment instruction comprises:
acquiring a capacity adjustment strategy associated with the capacity evaluation parameter to determine a corresponding system adjustment object identifier;
and acquiring an operation parameter corresponding to the system adjustment object identifier, and generating a system capacity adjustment instruction based on the operation parameter.
4. The method of claim 3, wherein obtaining the operating parameter corresponding to the system adjustment object identifier, generating a system capacity adjustment instruction based on the operating parameter, comprises:
and inquiring the adjustment level associated with the system adjustment object identifiers, and determining the system adjustment object identifiers to be adjusted based on the adjustment level so as to acquire corresponding operation parameters.
5. A method according to claim 3, wherein generating system capacity adjustment instructions based on the operating parameters comprises:
obtaining a standard operation parameter corresponding to the system adjustment object identifier so as to compare the operation parameter with the standard operation parameter;
in response to the operating parameter and the standard operating parameter being different, a system capacity adjustment instruction is generated based on a difference between the operating parameter and the standard operating parameter.
6. The method of claim 1, further comprising, after generating the transform trend of the capacity estimation parameter:
and calling a preset page template to combine the transformation trend, generating a visual page and sending the visual page.
7. The method according to claim 1, wherein the method further comprises:
and acquiring historical service data of the system to train a preset multiple linear regression analysis model so as to obtain the capacity data processing model.
8. An apparatus for capacity data processing, comprising:
the system comprises a receiving unit, a processing unit and a processing unit, wherein the receiving unit is used for receiving a processing instruction of system capacity and acquiring service data corresponding to a system in a preset time period, and the service data comprises capability data of system service, response time of service processing and/or concurrency of the service data;
the determining unit is used for calling a preset capacity data processing model, calculating parameter values of preset capacity assessment parameters based on the service data, and obtaining historical parameter values of the capacity assessment parameters so as to generate a transformation trend of the capacity assessment parameters;
and the generation unit is used for responding to the change trend to meet the abnormal condition, acquiring a capacity adjustment strategy associated with the capacity evaluation parameter, generating a system capacity adjustment instruction and sending the system capacity adjustment instruction.
9. The apparatus of claim 8, wherein the capacity assessment parameter comprises a central processor utilization;
the generating unit is specifically configured to:
determining a predicted value of the CPU utilization rate based on the change trend;
and responding to the predicted value of the CPU utilization rate meeting a preset abnormal interval, determining that the CPU utilization rate meets an abnormal condition, and acquiring a capacity adjustment strategy associated with the capacity evaluation parameter.
10. The apparatus according to claim 8, wherein the generating unit is specifically configured to:
acquiring a capacity adjustment strategy associated with the capacity evaluation parameter to determine a corresponding system adjustment object identifier;
and acquiring an operation parameter corresponding to the system adjustment object identifier, and generating a system capacity adjustment instruction based on the operation parameter.
11. The apparatus according to claim 10, wherein the generating unit is specifically configured to:
and inquiring the adjustment level associated with the system adjustment object identifiers, and determining the system adjustment object identifiers to be adjusted based on the adjustment level so as to acquire corresponding operation parameters.
12. The apparatus according to claim 10, wherein the generating unit is specifically configured to:
obtaining a standard operation parameter corresponding to the system adjustment object identifier so as to compare the operation parameter with the standard operation parameter;
in response to the operating parameter and the standard operating parameter being different, a system capacity adjustment instruction is generated based on a difference between the operating parameter and the standard operating parameter.
13. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs,
when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-7.
14. A computer readable medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any of claims 1-7.
15. A computer program product comprising a computer program, characterized in that the program, when executed by a processor, implements the method according to any of claims 1-7.
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| CN202310705185.5A CN117093439A (en) | 2023-06-14 | 2023-06-14 | Method, device, electronic equipment and storage medium for capacity data processing |
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| CN202310705185.5A CN117093439A (en) | 2023-06-14 | 2023-06-14 | Method, device, electronic equipment and storage medium for capacity data processing |
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