CN113515426A - System performance data processing method and device - Google Patents

System performance data processing method and device Download PDF

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Publication number
CN113515426A
CN113515426A CN202110546493.9A CN202110546493A CN113515426A CN 113515426 A CN113515426 A CN 113515426A CN 202110546493 A CN202110546493 A CN 202110546493A CN 113515426 A CN113515426 A CN 113515426A
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data
system performance
performance data
change rate
time period
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刘春雨
胡平
朱正浩
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Industrial and Commercial Bank of China Ltd ICBC
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Industrial and Commercial Bank of China Ltd ICBC
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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
    • G06F11/3072—Monitoring arrangements determined by the means or processing involved in reporting the monitored data where the reporting involves data filtering, e.g. pattern matching, time or event triggered, adaptive or policy-based reporting
    • G06F11/3079—Monitoring arrangements determined by the means or processing involved in reporting the monitored data where the reporting involves data filtering, e.g. pattern matching, time or event triggered, adaptive or policy-based reporting the data filtering being achieved by reporting only the changes of the monitored data
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2201/00—Indexing scheme relating to error detection, to error correction, and to monitoring
    • G06F2201/80—Database-specific techniques

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Abstract

The embodiment of the application provides a system performance data processing method and a device, which can also be used in the financial field, and the method comprises the following steps: determining a corresponding average data change rate according to a plurality of system performance data acquired within a set time period; storing the system performance data into a database of corresponding index types according to the average data change rate and a preset data uploading rule; according to the method and the device, the frequency of data uploading is reduced and the processing efficiency of the system performance data is improved on the premise that the system performance data shows the change characteristics.

Description

System performance data processing method and device
Technical Field
The application relates to the field of data processing, can also be used in the field of finance, and particularly relates to a system performance data processing method and device.
Background
When a transaction of a business system is abnormal, whether a performance bottleneck occurs needs to be judged by analyzing performance data indexes such as the utilization rate of a CPU (central processing unit), a memory, a database connection pool and the like of the system. Since problem analysis has hysteresis, business systems may have recovered to normal when a professional begins analyzing the problem. Therefore, historical performance data needs to be stored for later problem analysis.
In the prior art, there are two storage modes for system performance data: the system local storage and the data centralized storage specifically comprise:
(1) the system stores the metadata locally, most often using the nmon tool, in a file locally. When the index graphs need to be checked, the index graphs are analyzed through an analysis tool. The inventor finds that the mode has the following defects: 1. the acquisition tool defines all indexes, and the indexes are difficult to expand; 2. the process of taking and analyzing the file is needed for the display of the index chart, and the process is complicated.
(2) In order to overcome the defect of local data storage, a common mode in the industry is to deploy an agent through a server to acquire performance data, upload the performance data to a server for centralized storage, and provide a foreground for data query. The inventor finds that, in this way, as the collected indexes are more and the number of servers is more and more, the Server has a performance bottleneck, which may cause the loss of performance data. Meanwhile, the data in the DB is more and more, and the foreground queries the DB slowly.
Disclosure of Invention
Aiming at the problems in the prior art, the application provides a system performance data processing method and device, which can reduce the data uploading frequency and improve the processing efficiency of the system performance data on the premise of ensuring that the system performance data embody the change characteristics.
In order to solve at least one of the above problems, the present application provides the following technical solutions:
in a first aspect, the present application provides a system performance data processing method, including:
determining a corresponding average data change rate according to a plurality of system performance data acquired within a set time period;
and storing the system performance data into a database of a corresponding index category according to the average data change rate and a preset data uploading rule.
Further, the determining a corresponding average data change rate according to a plurality of system performance data collected within a set time period includes:
determining a corresponding local data change rate according to a data difference value of adjacent system performance data acquired within a set time period;
and determining the corresponding average data change rate according to each local data change rate in the set time period.
Further, the storing the system performance data into a database of a corresponding index category according to the average data change rate and a preset data uploading rule includes:
judging whether at least one local data change rate larger than the average data change rate exists in the set time period, if so, judging that the system performance data accords with a preset data uploading rule;
and storing the system performance data into a corresponding database according to the instruction type of the system performance data.
Further, after the determining that the system performance data meets the preset data uploading rule, before the storing the system performance data into the corresponding database according to the instruction type of the system performance data, the method further includes:
caching system performance data which accords with a preset data uploading rule into a message queue, and sequentially acquiring the system performance data from the message queue according to a set frequency.
In a second aspect, the present application provides a system performance data processing apparatus, comprising:
the change rate determining module is used for determining the corresponding average data change rate according to a plurality of system performance data acquired within a set time period;
and the data falling module is used for storing the system performance data into a database of a corresponding index type according to the average data change rate and a preset data uploading rule.
Further, the rate of change determination module includes:
the local data change rate determining unit is used for determining the corresponding local data change rate according to the data difference value of the performance data of the adjacent system acquired in the set time period;
and the average data change rate determining unit is used for determining the corresponding average data change rate according to each local data change rate in the set time period.
Further, the database falling module comprises:
the data fluctuation judging unit is used for judging whether at least one local data change rate larger than the average data change rate exists in the set time period or not, and if so, judging that the system performance data accord with a preset data uploading rule;
and the classification storage unit is used for storing the system performance data into a corresponding database according to the instruction type of the system performance data.
Further, the database module further comprises:
and the queue caching unit is used for caching the system performance data which accords with the preset data uploading rule into a message queue and sequentially acquiring the system performance data from the message queue according to a set frequency.
In a third aspect, the present application provides an electronic device, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the system performance data processing method.
In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the system performance data processing method.
According to the technical scheme, the change fluctuation of the system performance data collected in the set time period is analyzed, the database dropping operation is executed on the system performance data when the preset data uploading rule is met, and the classification database dropping rule is followed when the database dropping operation is carried out, so that the uploading data frequency is reduced and the processing efficiency of the system performance data is improved on the premise that the system performance data embody the change characteristics.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flow chart of a system performance data processing method according to an embodiment of the present application;
FIG. 2 is a second flowchart of a system performance data processing method according to an embodiment of the present application;
FIG. 3 is a third flowchart illustrating a system performance data processing method according to an embodiment of the present application;
FIG. 4 is a block diagram of one embodiment of a system performance data processing apparatus;
FIG. 5 is a second block diagram of a system performance data processing apparatus according to an embodiment of the present application;
FIG. 6 is a third block diagram of a system performance data processing apparatus according to an embodiment of the present application;
FIG. 7 is a fourth block diagram of a system performance data processing apparatus according to an embodiment of the present application;
FIG. 8 is a general diagram illustrating a system performance data processing method according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In consideration of the problems that in the prior art, the process is complicated when system performance data are collected and stored, and the system operation efficiency is affected by frequent interaction, the application provides a method and a device for processing the system performance data.
In order to reduce the frequency of data uploading and improve the processing efficiency of system performance data on the premise of ensuring that the system performance data represents the change characteristics, the present application provides an embodiment of a system performance data processing method, which specifically includes the following contents, with reference to fig. 1:
step S101: and determining the corresponding average data change rate according to a plurality of system performance data acquired within a set time period.
Optionally, the system performance data can be acquired at regular time by setting a plurality of Agent (Agent) servers, but after acquisition, the data uploading time is determined according to the average data change rate of the system performance data in a set time period.
It can be understood that, in general, an Agent will adopt a fixed frequency to collect data, and when the index value changes less, the fixed frequency collection will cause some meaningless data to be uploaded, increasing the data storage amount at the Server end. For example, 5 data of 0, 0 are sent in 5 minutes, and only 0, 0 is needed to react to the trend.
Optionally, the present application may adopt a data uploading method with an unfixed frequency. Specifically, the method comprises the following steps:
an is used to denote the nth data acquired at a fixed frequency.
Defining local change rate, representing the data change condition:
local rate of change is an-An-1；
Defining an average change rate, representing the average condition of data change:
Figure BDA0003073707790000051
step S102: and storing the system performance data into a database of a corresponding index category according to the average data change rate and a preset data uploading rule.
Optionally, the present application may further determine whether the average data change rate meets a preset data uploading rule, for example, a data uploading rule, according to the average data change rate:
defining fixed uploading frequency m, and uploading data when n/m is 0. When n/m! And when the change rate is 0, if the change rate is larger than the average change rate, uploading the data, otherwise, not uploading the data.
Therefore, by uploading data at an unfixed frequency, the amount of data uploading is reduced, and the change of the data is kept.
As can be seen from the above description, the method for processing system performance data provided in the embodiment of the present application can analyze the variation fluctuation of the system performance data collected within a set time period, perform a database dropping operation on the system performance data when a preset data uploading rule is satisfied, and follow a classification database dropping rule when the database dropping operation is performed, so that on the premise that the system performance data shows variation characteristics, the frequency of uploading data is reduced, and the processing efficiency of the system performance data is improved.
In order to accurately analyze the change of the system performance data collected within the set time period, in an embodiment of the system performance data processing method of the present application, referring to fig. 2, the step S101 may further include the following steps:
step S201: and determining the corresponding local data change rate according to the data difference value of the performance data of the adjacent systems acquired in the set time period.
Step S202: and determining the corresponding average data change rate according to each local data change rate in the set time period.
Optionally, the present application may adopt a data uploading method with an unfixed frequency. Specifically, the method comprises the following steps:
an is used to denote the nth data acquired at a fixed frequency.
Defining local change rate, representing the data change condition:
local rate of change is an-An-1；
Defining an average change rate, representing the average condition of data change:
Figure BDA0003073707790000061
in order to determine the data uploading timing accurately according to the change of the system performance data, in an embodiment of the system performance data processing method of the present application, referring to fig. 3, the step S102 may further include the following steps:
step S301: and judging whether at least one local data change rate larger than the average data change rate exists in the set time period, if so, judging that the system performance data accords with a preset data uploading rule.
Step S302: and storing the system performance data into a corresponding database according to the instruction type of the system performance data.
Optionally, the present application may further determine whether the average data change rate meets a preset data uploading rule, for example, a data uploading rule, according to the average data change rate:
defining fixed uploading frequency m, and uploading data when n/m is 0. When n/m! And when the change rate is 0, if the change rate is larger than the average change rate, uploading the data, otherwise, not uploading the data.
Therefore, by uploading data at an unfixed frequency, the amount of data uploading is reduced, and the change of the data is kept.
Meanwhile, the method and the device can also define database dropping rules, and different index data are stored in different databases. When a new index is added, the database is transversely expanded, so that the new index falls into the new database, and the data magnitude of the database where the stock index is located is ensured to be unchanged.
In order to ensure high availability of the system, in an embodiment of the system performance data processing method of the present application, the following may be specifically included between the step S301 and the step S302:
caching system performance data which accords with a preset data uploading rule into a message queue, and sequentially acquiring the system performance data from the message queue according to a set frequency.
It can be understood that the data uploading has a characteristic that the Server side can have high concurrency at the moment of the Agent data uploading. Otherwise, the Server end has no pressure. Thus, data may be buffered through a message queue in the present application.
Optionally, the method and the device can directly store the received data into the message queue, so that the high performance of the node is ensured. And meanwhile, the data is taken from the message queue according to a fixed frequency for processing, and the data is only required to be ensured to be free of extrusion. When the data of the message queue is backlogged, the processing capacity can be ensured by transversely expanding the data processing nodes.
In order to reduce the frequency of data uploading and improve the processing efficiency of system performance data on the premise of ensuring that the system performance data represents a change characteristic, the present application provides an embodiment of a system performance data processing apparatus for implementing all or part of the content of the system performance data processing method, and referring to fig. 4, the system performance data processing apparatus specifically includes the following content:
the change rate determining module 10 is configured to determine a corresponding average data change rate according to a plurality of system performance data acquired within a set time period.
And the database falling module 20 is used for storing the system performance data into a database of a corresponding index type according to the average data change rate and a preset data uploading rule.
As can be seen from the above description, the system performance data processing apparatus provided in the embodiment of the present application can perform a library dropping operation on the system performance data only when a preset data uploading rule is satisfied by analyzing the variation fluctuation of the system performance data collected within a set time period, and follow a classification library entering rule when the library dropping operation is performed, so that on the premise that the system performance data shows variation characteristics, the frequency of uploading data is reduced, and the processing efficiency of the system performance data is improved.
In order to accurately analyze the change of the system performance data collected within the set time period, in an embodiment of the system performance data processing apparatus of the present application, referring to fig. 5, the change rate determining module 10 includes:
and the local data change rate determining unit 11 is configured to determine a corresponding local data change rate according to a data difference of the adjacent system performance data acquired within a set time period.
An average data change rate determining unit 12, configured to determine a corresponding average data change rate according to each local data change rate in the set time period.
In order to accurately determine the data uploading time according to the change of the system performance data, in an embodiment of the system performance data processing apparatus of the present application, referring to fig. 6, the data library module 20 includes:
and the data fluctuation judging unit 21 is configured to judge whether at least one local data change rate greater than the average data change rate exists in the set time period, and if so, judge that the system performance data meets a preset data uploading rule.
And the classification storage unit 22 is used for storing the system performance data into a corresponding database according to the instruction type of the system performance data.
In order to ensure high availability of the system, in an embodiment of the system performance data processing apparatus of the present application, referring to fig. 7, the database module 20 further includes:
the queue buffer unit 23 is configured to buffer system performance data that meets a preset data uploading rule into a message queue, and sequentially obtain the system performance data from the message queue according to a set frequency.
To further explain the present solution, the present application further provides a specific application example of implementing the method for processing system performance data by using the above-mentioned system performance data processing apparatus, and with reference to fig. 8, the following contents are specifically included:
the system comprises a data acquisition Agent, a data acquisition node, a message queue, a data processing node, a DB and a data query node. Specifically, the method comprises the following steps:
(1) the data acquisition Agent: and the data acquisition system is responsible for acquiring the data of each performance index and uploading the acquired data to the data acquisition node.
(2) A data acquisition node: the data is sent directly to the message queue without logical processing.
(3) Message queue: and the data buffer area is used for caching the data sent by the data acquisition node.
(4) The data processing node: and acquiring data from the message queue, analyzing and storing the data into the DB.
(5) DB: and storing the performance data.
(6) And (3) data query node: and displaying the performance chart in the foreground.
Meanwhile, in the embodiment, data uploading with unfixed frequency is adopted, the Agent usually adopts fixed frequency to collect data, and when the index value changes less, the fixed frequency collection can cause uploading of some meaningless data, so that the data storage amount of the Server side is increased. For example, 5 data of 0, 0 are sent in 5 minutes, and only 0, 0 is needed to react to the trend. Therefore, the present embodiment adopts a data uploading method with an unfixed frequency. Specifically, the method comprises the following steps:
an is used to denote the nth data acquired at a fixed frequency.
Defining a change rate, representing the situation of data change:
rate of change is An-An-1；
Defining an average change rate, representing the average condition of data change:
Figure BDA0003073707790000081
defining fixed uploading frequency m, and uploading data when n/m is 0. When n/m! And when the change rate is 0, if the change rate is larger than the average change rate, uploading the data, otherwise, not uploading the data.
By uploading data at an unfixed frequency, the amount of data uploading is reduced while preserving the variation of the data.
In addition, the data transmission has a characteristic that the Server end can have high concurrency at the moment of the Agent data transmission. Otherwise, the Server end has no pressure. Thus, in this embodiment data is buffered by the message queue.
Specifically, the data acquisition node has no data processing logic, and directly stores the received data into the message queue, so that the high performance of the node is ensured. The data processing node receives the data from the message queue according to the fixed frequency and processes the data as long as no extrusion of the data is ensured. When the data of the message queue is backlogged, the processing capacity can be ensured by transversely expanding the data processing nodes.
In addition, the embodiment may further define a database dropping rule, and store different index data into different databases. When a new index is added, the database is transversely expanded, so that the new index falls into the new database, and the data magnitude of the database where the stock index is located is ensured to be unchanged.
As can be seen from the above, the present application can achieve at least the following technical effects:
1. and the Agent intelligently analyzes, reduces the uploading amount of performance data and reduces the pressure of the Server end.
2. And buffering the message queue to ensure no loss.
3. The database is divided according to the performance index, the data volume of a single database is relatively fixed, and the foreground query performance is good.
In terms of hardware, in order to reduce the frequency of uploading data and improve the processing efficiency of system performance data on the premise of ensuring that the system performance data embodies the changing characteristics, the present application provides an embodiment of an electronic device for implementing all or part of the contents in the system performance data processing method, where the electronic device specifically includes the following contents:
a processor (processor), a memory (memory), a communication Interface (Communications Interface), and a bus; the processor, the memory and the communication interface complete mutual communication through the bus; the communication interface is used for realizing information transmission between the system performance data processing device and relevant equipment such as a core service system, a user terminal, a relevant database and the like; the logic controller may be a desktop computer, a tablet computer, a mobile terminal, and the like, but the embodiment is not limited thereto. In this embodiment, the logic controller may be implemented with reference to the embodiment of the system performance data processing method and the embodiment of the system performance data processing apparatus in the embodiment, and the contents thereof are incorporated herein, and repeated descriptions are omitted.
It is understood that the user terminal may include a smart phone, a tablet electronic device, a network set-top box, a portable computer, a desktop computer, a Personal Digital Assistant (PDA), an in-vehicle device, a smart wearable device, and the like. Wherein, intelligence wearing equipment can include intelligent glasses, intelligent wrist-watch, intelligent bracelet etc..
In practical applications, part of the system performance data processing method may be executed on the electronic device side as described above, or all operations may be completed in the client device. The selection may be specifically performed according to the processing capability of the client device, the limitation of the user usage scenario, and the like. This is not a limitation of the present application. The client device may further include a processor if all operations are performed in the client device.
The client device may have a communication module (i.e., a communication unit), and may be communicatively connected to a remote server to implement data transmission with the server. The server may include a server on the task scheduling center side, and in other implementation scenarios, the server may also include a server on an intermediate platform, for example, a server on a third-party server platform that is communicatively linked to the task scheduling center server. The server may include a single computer device, or may include a server cluster formed by a plurality of servers, or a server structure of a distributed apparatus.
Fig. 9 is a schematic block diagram of a system configuration of an electronic device 9600 according to an embodiment of the present application. As shown in fig. 9, the electronic device 9600 can include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. Notably, this fig. 9 is exemplary; other types of structures may also be used in addition to or in place of the structure to implement telecommunications or other functions.
In one embodiment, the system performance data processing method functions may be integrated into the central processor 9100.
The central processor 9100 may be configured to control as follows:
step S101: and determining the corresponding average data change rate according to a plurality of system performance data acquired within a set time period.
Step S102: and storing the system performance data into a database of a corresponding index category according to the average data change rate and a preset data uploading rule.
As can be seen from the above description, according to the electronic device provided in the embodiment of the present application, by analyzing the variation fluctuation of the system performance data collected within a set time period, the library dropping operation is performed on the system performance data only when the preset data uploading rule is satisfied, and the classification library entering rule is followed when the library dropping operation is performed, so that on the premise that the system performance data shows the variation characteristic, the frequency of uploading data is reduced, and the processing efficiency of the system performance data is improved.
In another embodiment, the system performance data processing apparatus may be configured separately from the central processing unit 9100, for example, the system performance data processing apparatus may be configured as a chip connected to the central processing unit 9100, and the system performance data processing method function is realized by the control of the central processing unit.
As shown in fig. 9, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is noted that the electronic device 9600 also does not necessarily include all of the components shown in fig. 9; in addition, the electronic device 9600 may further include components not shown in fig. 9, which may be referred to in the prior art.
As shown in fig. 9, a central processor 9100, sometimes referred to as a controller or operational control, can include a microprocessor or other processor device and/or logic device, which central processor 9100 receives input and controls the operation of the various components of the electronic device 9600.
The memory 9140 can be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information relating to the failure may be stored, and a program for executing the information may be stored. And the central processing unit 9100 can execute the program stored in the memory 9140 to realize information storage or processing, or the like.
The input unit 9120 provides input to the central processor 9100. The input unit 9120 is, for example, a key or a touch input device. Power supply 9170 is used to provide power to electronic device 9600. The display 9160 is used for displaying display objects such as images and characters. The display may be, for example, an LCD display, but is not limited thereto.
The memory 9140 can be a solid state memory, e.g., Read Only Memory (ROM), Random Access Memory (RAM), a SIM card, or the like. There may also be a memory that holds information even when power is off, can be selectively erased, and is provided with more data, an example of which is sometimes called an EPROM or the like. The memory 9140 could also be some other type of device. Memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application/function storage portion 9142, the application/function storage portion 9142 being used for storing application programs and function programs or for executing a flow of operations of the electronic device 9600 by the central processor 9100.
The memory 9140 can also include a data store 9143, the data store 9143 being used to store data, such as contacts, digital data, pictures, sounds, and/or any other data used by an electronic device. The driver storage portion 9144 of the memory 9140 may include various drivers for the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging applications, contact book applications, etc.).
The communication module 9110 is a transmitter/receiver 9110 that transmits and receives signals via an antenna 9111. The communication module (transmitter/receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, which may be the same as in the case of a conventional mobile communication terminal.
Based on different communication technologies, a plurality of communication modules 9110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, may be provided in the same electronic device. The communication module (transmitter/receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and receive audio input from the microphone 9132, thereby implementing ordinary telecommunications functions. The audio processor 9130 may include any suitable buffers, decoders, amplifiers and so forth. In addition, the audio processor 9130 is also coupled to the central processor 9100, thereby enabling recording locally through the microphone 9132 and enabling locally stored sounds to be played through the speaker 9131.
An embodiment of the present application further provides a computer-readable storage medium capable of implementing all the steps in the system performance data processing method in which the execution subject is the server or the client in the foregoing embodiments, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements all the steps in the system performance data processing method in which the execution subject is the server or the client in the foregoing embodiments, for example, when the processor executes the computer program, the processor implements the following steps:
step S101: and determining the corresponding average data change rate according to a plurality of system performance data acquired within a set time period.
Step S102: and storing the system performance data into a database of a corresponding index category according to the average data change rate and a preset data uploading rule.
As can be seen from the above description, the computer-readable storage medium provided in the embodiment of the present application analyzes the variation fluctuation of the system performance data collected within a set time period, performs a library dropping operation on the system performance data when a preset data uploading rule is satisfied, and follows a classification library entering rule when the library dropping operation is performed, so that the frequency of uploading data can be reduced and the processing efficiency of the system performance data can be improved on the premise of ensuring that the system performance data embodies the variation characteristics.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principle and the implementation mode of the invention are explained by applying specific embodiments in the invention, and the description of the embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims (10)

1. A method for processing system performance data, the method comprising:
determining a corresponding average data change rate according to a plurality of system performance data acquired within a set time period;
and storing the system performance data into a database of a corresponding index category according to the average data change rate and a preset data uploading rule.
2. The method according to claim 1, wherein the determining a corresponding average data change rate according to the plurality of system performance data collected within the set time period comprises:
determining a corresponding local data change rate according to a data difference value of adjacent system performance data acquired within a set time period;
and determining the corresponding average data change rate according to each local data change rate in the set time period.
3. The method according to claim 2, wherein the storing the system performance data into a database of a corresponding index category according to the average data change rate and a preset data uploading rule comprises:
judging whether at least one local data change rate larger than the average data change rate exists in the set time period, if so, judging that the system performance data accords with a preset data uploading rule;
and storing the system performance data into a corresponding database according to the instruction type of the system performance data.
4. The method according to claim 3, wherein after the determining that the system performance data meets the predetermined data uploading rule, before the storing the system performance data into the corresponding database according to the instruction type of the system performance data, the method further comprises:
caching system performance data which accords with a preset data uploading rule into a message queue, and sequentially acquiring the system performance data from the message queue according to a set frequency.
5. A system performance data processing apparatus, comprising:
the change rate determining module is used for determining the corresponding average data change rate according to a plurality of system performance data acquired within a set time period;
and the data falling module is used for storing the system performance data into a database of a corresponding index type according to the average data change rate and a preset data uploading rule.
6. The system performance data processing apparatus of claim 5, wherein the rate of change determination module comprises:
the local data change rate determining unit is used for determining the corresponding local data change rate according to the data difference value of the performance data of the adjacent system acquired in the set time period;
and the average data change rate determining unit is used for determining the corresponding average data change rate according to each local data change rate in the set time period.
7. The system performance data processing apparatus of claim 6, wherein the database library module comprises:
the data fluctuation judging unit is used for judging whether at least one local data change rate larger than the average data change rate exists in the set time period or not, and if so, judging that the system performance data accord with a preset data uploading rule;
and the classification storage unit is used for storing the system performance data into a corresponding database according to the instruction type of the system performance data.
8. The system performance data processing apparatus of claim 7, wherein the database library module further comprises:
and the queue caching unit is used for caching the system performance data which accords with the preset data uploading rule into a message queue and sequentially acquiring the system performance data from the message queue according to a set frequency.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the system performance data processing method according to any of claims 1 to 4 are implemented when the processor executes the program.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the system performance data processing method of any one of claims 1 to 4.
CN202110546493.9A 2021-05-19 2021-05-19 System performance data processing method and device Pending CN113515426A (en)

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Application Number Priority Date Filing Date Title
CN202110546493.9A CN113515426A (en) 2021-05-19 2021-05-19 System performance data processing method and device

Publications (1)

Publication Number Publication Date
CN113515426A true CN113515426A (en) 2021-10-19

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