Data processing method and device, equipment, medium and program product

Abstract

The embodiment of the invention provides a data processing method, device and equipment, a medium and a program product, which are applied to a data monitoring system, and the method comprises the following steps: collecting operation state data of a data exchange node of a data exchange system based on an initial heartbeat frequency, inputting the operation state data into a state scoring algorithm for state scoring calculation, the method comprises the following steps: acquiring a node state score, comparing the node state score with a score threshold, calculating a target heartbeat frequency according to a comparison result and an initial heartbeat frequency, and performing state data acquisition of a data exchange node according to the target heartbeat frequency, thereby realizing automatic adjustment of a monitoring frequency according to system changes. And the monitoring of the system is more efficient and accurate.

Description

TECHNICAL FIELD

[0001] The present document relates to the technical field of data processing, and in particular to a data processing method and device, equipment, medium and program product. BACKGROUND

[0002] With the in-depth development of informatization construction, data sharing services and data exchange services play an increasingly important role in information exchange. In order to ensure the efficiency and security of data exchange, real-time monitoring of the state of services becomes particularly important. The traditional exchange node heartbeat detection mechanism performs health monitoring by using HTTP request. This heartbeat monitoring method mainly sends an HTTP request to the monitored node, and then judges whether the service node is normally running according to whether a normal status code can be returned. Although the existing method can realize simple service state monitoring, its efficiency and accuracy cannot meet the needs when facing large-scale and high-concurrency data sharing scenarios. Therefore, it is particularly necessary to develop a more efficient and accurate heartbeat monitoring method for data exchange services. SUMMARY

[0003] An embodiment of the present specification aims to provide a data processing method, device, equipment, medium and program product to solve the problem that monitoring of a data exchange system is not efficient and accurate enough.

[0004] To solve the above technical problems, an embodiment of the present specification is implemented as follows: In a first aspect, an embodiment of the present specification provides a data processing method applied to a data monitoring system, and the method comprises: collecting running state data of a data exchange node of a data exchange system based on an initial heartbeat frequency; inputting the running state data into a state scoring algorithm to perform state scoring calculation and obtain a node state score; comparing the node state score with a score threshold value, and calculating a target heartbeat frequency according to the comparison result and the initial heartbeat frequency, so as to collect the state data of the data exchange node according to the target heartbeat frequency.

[0005] In a second aspect, another embodiment of the present specification provides a data processing device running in a data monitoring system, and the device comprises: a state data collection module configured to collect running state data of a data exchange node of a data exchange system based on an initial heartbeat frequency; a score calculation module configured to input the running state data into a state scoring algorithm to perform state scoring calculation and obtain a node state score; The comparison module is configured to compare the node state score with a score threshold, and calculate a target heartbeat frequency according to the comparison result and the initial heartbeat frequency, so as to collect state data of the data exchange node according to the target heartbeat frequency.

[0006] In a third aspect, a further example of the present specification provides a data processing device, comprising a memory, a processor, and computer executable instructions stored on the memory and executable on the processor, wherein the computer executable instructions, when executed by the processor, implement the steps of the data processing method according to the first aspect.

[0007] In a fourth aspect, a further example of the present specification provides a computer readable storage medium for storing computer executable instructions, wherein the computer executable instructions, when executed by a processor, implement the steps of the data processing method according to the first aspect.

[0008] In a fifth aspect, a further example of the present specification provides a computer program product comprising a data processing program, wherein the data processing program, when executed by a processor, implements the steps of the data processing method according to the first aspect.

[0009] The data processing method provided by the present example, in the process of data processing, first collects the running state data of the data exchange node of the data exchange system based on the initial heartbeat frequency, then inputs the running state data into a state scoring algorithm for state scoring calculation to obtain a node state score, so as to evaluate whether the data transmission of the data exchange node is normal, and finally compares the node state score with a score threshold, and calculates a target heartbeat frequency according to the comparison result and the initial heartbeat frequency, so as to collect the state data of the data exchange node according to the target heartbeat frequency, which realizes automatic adjustment of the monitoring frequency according to the changes of the data exchange system, and makes the monitoring of the data exchange system more efficient and accurate. BRIEF DESCRIPTION OF DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the one or more embodiments of the present specification or the prior art, the drawings needed in the embodiment or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments described in the present specification, and those skilled in the art can also obtain other drawings according to these drawings without any creative effort; Figure 1 A data processing method processing flowchart provided by one or more embodiments of the present specification; Figure 2 An architecture diagram of a data monitoring system provided by one or more embodiments of the present specification; Figure 3 A data processing method processing flowchart applied to a government data processing scene is provided for one or more embodiments of the present specification. Figure 4 A data processing device schematic diagram is provided for one or more embodiments of the present specification. Figure 5 A structural schematic diagram of a data processing device is provided for one or more embodiments of the present specification. DETAILED DESCRIPTION

[0011] In order to enable personnel in the technical field to better understand the technical solutions in one or more embodiments of the present specification, the technical solutions in one or more embodiments of the present specification will be described clearly and completely below in conjunction with the drawings in one or more embodiments of the present specification. Obviously, the described embodiments are only a part of the embodiments of the present specification, rather than all the embodiments. Based on one or more embodiments of the present specification, all other embodiments obtained by those skilled in the art without creative labor should belong to the protection scope of the present document.

[0012] An embodiment of the data processing method provided in the present specification is as follows: Referring to Figure 1 , a data processing method processing flowchart provided in the present embodiment is shown, referring to Figure 3 , a data processing method processing flowchart applied to a government data processing scene provided in the present embodiment is shown.

[0013] Referring to Figure 1 , the data processing method provided in the present embodiment is applied to a data monitoring system, and specifically includes the following steps S102 to S106.

[0014] Step S102, collecting running state data of a data exchange node of a data exchange system based on an initial heartbeat frequency.

[0015] The initial heartbeat frequency described in the present embodiment refers to the frequency of heartbeat signal transmission used to check whether a target (such as a server, an application or a service) is in an active state. The heartbeat detection frequency determines the time interval of mutual heartbeat signal transmission between systems to ensure that the connection between components is active. Here, the initial heartbeat frequency can be an initial heartbeat detection frequency .

[0016] The data exchange system can be a system responsible for government data exchange and sharing, and a plurality of data exchange nodes are configured in the data exchange system and can be used for data exchange. The number of data exchange nodes can be one or more, data exchange can be performed between each data exchange node, and data exchange can also be performed between the data exchange node and other systems or other system nodes outside.

[0017] The running state data refers to data representing the node running state of the data exchange node. Here, the running state data can also be heartbeat data or a heartbeat data packet. Optionally, the running state data includes at least one of the following: node IP, port, node name, CPU usage, memory usage, network delay rate, error rate, and timestamp.

[0018] The data monitoring system in this embodiment can include a data acquisition module, a score calculation module, an evaluation module, a warning module, a storage module, and / or a display module. For example Figure 2 The architecture diagram of the data monitoring system is shown in the figure. The data acquisition module acquires the running state data of the data exchange node of the data exchange system based on the initial heartbeat frequency, and sends the running state data to the score calculation module. The score calculation module inputs the running state data into a state score algorithm to calculate the node state score. After receiving the node state score sent by the score calculation module, the evaluation module compares the node state score with the score threshold, and calculates the target heartbeat frequency according to the comparison result and the initial heartbeat frequency. The target heartbeat frequency is returned to the data acquisition module through the score calculation module. The evaluation module is also responsible for determining whether the node state of the data exchange node is abnormal. If it is abnormal, the warning module is used for warning. In addition, the evaluation module can also store the node state score and the running state data in the storage module.

[0019] In the specific execution process, the data acquisition module can acquire the running state data of each data exchange node of the data exchange system at the initial heartbeat frequency. After that, the data acquisition module sends the acquired running state data to the score calculation module for state score calculation.

[0020] Specifically, the data acquisition module can configure a communication protocol with the score calculation module and start a communication thread with the score calculation module to realize data communication. The acquired running state data is sent to the score calculation module according to the initial heartbeat frequency.

[0021] In addition, if the receiving success response returned by the score calculation module is accepted, the initial heartbeat frequency is continued to be used for data collection and transmission, and if the receiving success response returned by the score calculation module is not accepted, the initial heartbeat frequency is modified, and data collection and transmission are performed according to the obtained modified frequency, for example, the initial heartbeat frequency is increased in the modification process, and data collection and transmission are performed according to 1 / 4 of the initial heartbeat frequency.

[0022] In step S104, the running state data is input into a state score algorithm to perform state score calculation, and a node state score is obtained.

[0023] After the running state data of the data exchange node of the data exchange system based on the initial heartbeat frequency is collected, in this step, the running state data is input into a state score algorithm to perform state score calculation, and a node state score is obtained. The node state score refers to the evaluation of the health state of the data exchange node to form a standard quantifiable node health score.

[0024] In the specific execution process, step S104 can be executed by a score calculation module, that is, the running state data sent by the data collection module is received by the score calculation module, the running state data is input into a state score algorithm to perform state score calculation, and a node state score is obtained. Thereafter, the node state score is sent to the evaluation module for comparison processing, or the running state data can also be sent to the evaluation module for subsequent processing, or the node state score and the running state data can also be sent to the evaluation module for subsequent processing.

[0025] In an optional implementation of the embodiment, the state score calculation includes: determining historical state scores corresponding to each state influence factor in the running state data, calculating weights of the state influence factors based on the historical state scores; performing state score calculation according to the weights and the running state data to obtain the node state score.

[0026] The state influence factor can be a parameter that has an influence on the node state, for example, CPU usage rate C, memory usage rate M, network delay rate L, and error rate E.

[0027] Specifically, the historical state scores corresponding to each state influence factor in the running state data can be determined, the weights of the state influence factors can be calculated based on the historical state scores, and the node state score can be obtained by performing state score calculation according to the weights and the running state data.

[0028] For example, the state score algorithm is as follows:

[0029] Wherein, ω1, ω2, ω3, ω4 are weights, which can correspond to the importance of CPU usage, memory usage, network delay rate and error rate respectively; It should be noted that the weight ωi can be adjusted according to actual needs, or the weight ωi can also be determined according to historical data of the influence of the state influence factor on the node. Specifically, a data score matrix S is configured, wherein Sij represents the score of the i-th state influence factor in the j-th evaluation, and the weight coefficient can be calculated using the following formula:

[0030] Wherein, n is the number of evaluations.

[0031] Further, in order to make the weight more flexible, the weight can be dynamically adjusted according to the current state. In an optional embodiment provided by the present embodiment, the weight is updated as follows: Statistically, the number of abnormalities of each state influence factor within a preset time period is counted. The weight is updated according to the adjustment factor and the number of abnormalities to obtain an updated weight. Correspondingly, the state score calculation according to the weight and the running state data to obtain the node state score includes: The state score calculation according to the updated weight and the running state data to obtain the node state score.

[0032] Wherein, the state influence factor has a normal value range, and if the value of the state influence factor exceeds the normal value range, it means that the state influence factor is abnormal.

[0033] For example, if a certain state influence factor frequently appears problems within a preset time, its weight can be increased, and the formula for dynamic adjustment is as follows:

[0034] Wherein, α is an adjustment factor (usually taking a value between 0 and 1), i is the number of abnormalities of the i-th index within a preset time.

[0035] Step S106, compare the node state score with the score threshold, and calculate the target heartbeat frequency according to the comparison result and the initial heartbeat frequency, so as to collect the state data of the data exchange node according to the target heartbeat frequency.

[0036] After the above-mentioned running state data is input into the state scoring algorithm to calculate the node state score, in this step, the node state score is compared with the score threshold, and the target heartbeat frequency is calculated according to the comparison result and the initial heartbeat frequency, so as to collect the state data of the data exchange node according to the target heartbeat frequency.

[0037] In specific implementation, the above-mentioned step S106 can be performed by the evaluation module, that is, the evaluation module receives the node state score sent by the score calculation module, compares the node state score with the score threshold, and calculates the target heartbeat frequency according to the comparison result and the initial heartbeat frequency, so as to collect the state data of the data exchange node according to the target heartbeat frequency; in addition, the evaluation module can also receive the running state data sent by the score calculation module and send the running state data to the storage module for data storage, or the evaluation module can also send the node state score to the storage module for data storage.

[0038] Specifically, the comparison result obtained by comparing the node state score with the score threshold can be a first comparison result or a second comparison result, wherein the first comparison result can be that the node state score is lower than the score threshold, and the second comparison result can be that the node state score is higher than the score threshold. Here, if the first comparison result is obtained, the node monitoring frequency can be increased, so that the abnormality can be found and warned in time; if the second comparison result is obtained, the node monitoring frequency can be appropriately reduced, so as to save network and node resources.

[0039] In specific execution process, after the comparison result is obtained, the adjustment factor can be determined according to the comparison result, and the product of the adjustment factor and the initial heartbeat frequency is taken as the target heartbeat frequency.

[0040] For example, the specific generation method of the target heartbeat frequency is as follows:

[0041] Wherein, f is the target heartbeat frequency, is the initial heartbeat frequency, k is the adjustment coefficient, H is the node state score, and T is the score threshold; The target heartbeat frequency f is calculated by multiplying the initial heartbeat frequency f by an adjustment factor. The adjustment factor 1+k×(H-T) is determined according to the difference between the node state score H and the score threshold T. If the node state score H is higher than the score threshold T, the adjustment factor is greater than 1, and the initial heartbeat frequency is reduced; if the node state score H is lower than the score threshold T, the adjustment factor is less than 1, and the initial heartbeat frequency is increased.

[0042] After that, the target heartbeat frequency is sent to the data collection module by the evaluation module through the score calculation module, so that the data collection module collects the state data of the data exchange node according to the target heartbeat frequency, and in addition, the data collection module sends the newly collected running state data to the score calculation module according to the target heartbeat frequency.

[0043] The embodiment provides a data processing method of the point, and is further provided with a warning module. Specifically, in a case where the evaluation module detects that the node state scores of a plurality of nodes in a preset time period are all lower than the score threshold, or in a case where the evaluation module detects that the collection times of the running state data in a preset time period are less than the preset collection times, a warning command is sent to the warning module to perform warning. In an optional implementation of the embodiment, the warning is performed in the following manner: if it is detected that the node state scores of a plurality of nodes in a preset time period are all lower than the score threshold, it is determined that the node state of the data exchange node is an abnormal state; a state reminder for the abnormal state is generated and sent to an auditing personnel for auditing.

[0044] In another optional implementation of the embodiment, the warning is performed in the following manner: if it is detected that the collection times of the running state data in a preset time period are less than the preset collection times, it is determined that the node state of the data exchange node is an abnormal state; a state reminder for the abnormal state is generated and sent to an auditing personnel for auditing.

[0045] Specifically, in a case where the evaluation module detects that the node state scores of a plurality of nodes in a preset time period are all lower than the score threshold, or in a case where the evaluation module detects that the collection times of the running state data in a preset time period are less than the preset collection times, it is determined that the node state of the data exchange node is an abnormal state, and a warning command is sent to the warning module. After receiving the warning command sent by the evaluation module, the warning module generates warning information and sends the warning information to the operation and maintenance personnel corresponding to the node for manual intervention. The warning forms include but are not limited to short message, email, third-party platform and the like. In addition, the generated warning information is sent to the data record module for storage and subsequent query and display.

[0046] In an optional implementation of the embodiment, the storage is performed in the following manner: the heartbeat data and the node state score are stored. Specifically, the running state data and the node state score sent by the evaluation module can also be accepted by the storage module included in the data monitoring system, and after analysis, the data is stored in a database. The stored data includes but is not limited to node IP, port, node name, CPU usage, memory usage, network delay, error rate, timestamp, health score and the like. If the data exchange node is abnormal, the warning information received from the warning module is also stored.

[0047] In an optional implementation of the embodiment, the display is performed in the following manner: a display image of the node state score is generated, and the display image is displayed through a visual interface of a display terminal. Specifically, the data display can be performed by the display module through websocket technology. Specifically, the real-time node state score and early warning information of each data exchange node are obtained, and the health status and abnormal conditions of each data exchange node are displayed intuitively in a graphical manner.

[0048] To sum up, the one or more data processing methods provided in the embodiment first acquire the running state data of the data exchange nodes of the data exchange system based on the initial heartbeat frequency, then input the running state data into a state scoring algorithm for state scoring calculation to obtain the node state score, so as to evaluate whether the data transmission of the data exchange nodes is normal, and finally compare the node state score with the score threshold, and calculate the target heartbeat frequency according to the comparison result and the initial heartbeat frequency, so as to collect the state data of the data exchange nodes according to the target heartbeat frequency, which realizes automatic adjustment of the monitoring frequency according to the change of the data exchange system, and makes the monitoring of the data exchange system more efficient and accurate.

[0049] The following is combined Figure 3 The data processing method provided in the embodiment is further described by taking the application of the data processing method provided in the embodiment in a government affair data processing scenario as an example. Referring to Figure 3 , the data processing method applied in the government affair data processing scenario specifically includes steps S302 to S320.

[0050] Step S302, the running state data of the data exchange nodes of the data exchange system is collected based on the initial heartbeat frequency.

[0051] Step S304, the historical state scores corresponding to each state influence factor in the running state data are determined, and the weights of each state influence factor are calculated based on the historical state scores.

[0052] Step S306, the number of abnormalities of each state influence factor in a preset time period is counted.

[0053] Step S308, the weight is updated according to the adjustment factor and the number of abnormalities to obtain an updated weight.

[0054] Step S310, the state scoring calculation is performed according to the updated weight and the running state data to obtain the node state score.

[0055] Step S312, the node state score is compared with the score threshold, and the target heartbeat frequency is calculated according to the comparison result and the initial heartbeat frequency.

[0056] Step S314, if it is detected that the node state scores of multiple nodes within a preset time period are all lower than the score threshold, it is determined that the node state of the data exchange node is an abnormal state.

[0057] Step S316, a state reminder for the abnormal state is generated and sent to an auditor for auditing.

[0058] Step S318, the heartbeat data and the node state score are stored.

[0059] Step S320, a display image for the node state score is generated, and the display image is displayed through a visual interface of a display terminal.

[0060] It should be noted that any one step or combination of any multiple steps of steps S302 to S320 can be selected as any one step or combination of any multiple steps of steps S102 to S106 to form a new implementation mode according to the needs of implementation and deployment; and any one or any multiple technical features in the technical solution composed of steps S302 to S320 can also be selected to form a new implementation mode in combination with any one or multiple technical features in the technical solution composed of steps S102 to S106 according to the actual needs of deployment, or the technical features in one or more optional implementation modes provided by steps S102 to S106 are selected to form a new implementation mode, which will not be described here.

[0061] Figure 4 A schematic diagram of a data processing device provided by an embodiment of the present application is shown in FIG. 4, which includes: Figure 4 A state data acquisition module 402 is configured to acquire running state data of a data exchange node of a data exchange system based on an initial heartbeat frequency. A score calculation module 404 is configured to input the running state data into a state score algorithm to calculate a node state score. A comparison module 406 is configured to compare the node state score with a score threshold, and calculate a target heartbeat frequency according to a comparison result and the initial heartbeat frequency, so as to acquire state data of the data exchange node according to the target heartbeat frequency.

[0062] ​The data processing apparatus provided by the embodiment first collects running state data of a data exchange node of a data exchange system based on an initial heartbeat frequency by the running state data collection module 402 during data processing, then inputs the running state data into a state score algorithm for state score calculation by the score calculation module 404 to obtain a node state score, and finally compares the node state score with a score threshold by the comparison module 406, and calculates a target heartbeat frequency according to the comparison result and the initial heartbeat frequency, so that the state data collection of the data exchange node is performed according to the target heartbeat frequency, and the monitoring frequency is automatically adjusted according to the change of the data exchange system, and the monitoring of the data exchange system is more efficient and accurate.

[0063] The data processing apparatus provided by the embodiment of the present specification can implement each process in the foregoing method embodiment and achieve the same functions and effects, which are not repeated here.

[0064] Further, one embodiment of the present specification also provides a data processing device, Figure 5 The structural schematic diagram of the data processing device provided by one embodiment of the present specification is shown in the figure, which includes a memory 501, a processor 502, a bus 503 and a communication interface 504. The memory 501, the processor 502 and the communication interface 504 communicate through the bus 503, and the communication interface 504 can include an input and output interface, which includes but is not limited to a keyboard, a mouse, a display, a microphone, a loudspeaker and the like. Figure 5

[0065] Figure 5 In the embodiment, the memory 501 stores computer executable instructions that can run on the processor 502, and the computer executable instructions are executed by the processor 502 to implement the following processes: Collect running state data of a data exchange node of a data exchange system based on an initial heartbeat frequency; Input the running state data into a state score algorithm for state score calculation to obtain a node state score; Compare the node state score with a score threshold, and calculate a target heartbeat frequency according to the comparison result and the initial heartbeat frequency, so that the state data collection of the data exchange node is performed according to the target heartbeat frequency.

[0066] ​The data processing device provided in the embodiment can realize the processes in the method embodiments and achieve the same functions and effects, which are not repeated here.

[0067] The data processing device provided in the embodiment can realize the processes in the method embodiments and achieve the same functions and effects, which are not repeated here.

[0068] Further, another embodiment of the present specification also provides a computer readable storage medium, the computer readable storage medium is used to store computer executable instructions, the computer executable instructions are executed by the processor to realize the following flow: acquire running state data of a data exchange node of a data exchange system based on an initial heartbeat frequency; input the running state data into a state scoring algorithm to perform state scoring calculation and obtain a node state score; compare the node state score with a score threshold value, and calculate a target heartbeat frequency according to a comparison result and the initial heartbeat frequency, so as to perform state data collection of the data exchange node according to the target heartbeat frequency.

[0069] The computer readable storage medium provided in the embodiment can realize the processes in the method embodiments and achieve the same functions and effects, which are not repeated here.

[0070] The computer readable storage medium includes a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0071] The computer readable storage medium provided by the embodiment of the present specification can realize the processes in the foregoing method embodiments and achieve the same functions and effects, which are not repeated here.

[0072] Further, another embodiment of the present specification also provides a computer program product, which realizes the following processes when executed by a processor: Based on the initial heartbeat frequency, the running state data of the data exchange node of the data exchange system is collected. The running state data is input into a state scoring algorithm for state scoring calculation to obtain a node state score. The node state score is compared with a scoring threshold, and a target heartbeat frequency is calculated according to the comparison result and the initial heartbeat frequency, so that the state data collection of the data exchange node is performed according to the target heartbeat frequency.

[0073] The computer program product provided by the embodiment collects the running state data of the data exchange node of the data exchange system based on the initial heartbeat frequency, inputs the running state data into a state scoring algorithm for state scoring calculation to obtain a node state score, so as to evaluate whether the data transmission of the data exchange node is normal, and finally compares the node state score with a scoring threshold, and calculates a target heartbeat frequency according to the comparison result and the initial heartbeat frequency, so that the state data collection of the data exchange node is performed according to the target heartbeat frequency, which realizes automatic adjustment of the monitoring frequency according to the change of the data exchange system, and makes the monitoring of the data exchange system more efficient and accurate.

[0074] The computer program product provided by the embodiment of the present specification can realize the processes in the foregoing method embodiments and achieve the same functions and effects, which are not repeated here.

[0075] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.

[0076] The computer program instructions can 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 block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or blocks can be implemented by computer program instructions. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or blocks can be implemented by computer program instructions.

[0077] These computer program instructions can 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 instructions which implement the function specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or blocks can be implemented by computer program instructions. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or blocks can be implemented by computer program instructions.

[0078] These computer program instructions can 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 block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or blocks can be implemented by computer program instructions. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or blocks can be implemented by computer program instructions.

[0079] In one typical configuration, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0080] The memory can include non-persistent memory and / or volatile memory, such as a random access memory (RAM) including a cache area for the temporary storage of data. A

[0081] Computer-readable storage media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer-readable storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile discs (DVDs) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer-readable storage media does not include transitory media, such as modulated data signals and carrier waves.

[0082] It should also be noted that the terms "comprising", "containing", or any other similar term are intended to encompass non-exclusive inclusions such that a process, method, article, or apparatus that comprises a list of elements does not include those elements solely, but can also include other elements not expressly listed, or also include inherent elements of such process, method, article, or apparatus. Without more limitations, an element defined by the phrase "comprising a" does not exclude the existence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0083] Those skilled in the art will understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk memory, CD-ROM, optical memory, etc.) containing computer-usable program code.

[0084] The above only describes the embodiments of the present application and is not intended to limit the present application. Those skilled in the art can make various modifications and changes to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the scope of the claims of the present application.

Claims

1. A data processing method, characterized by, The method is applied to a data monitoring system, and comprises: collecting running state data of a data exchange node of a data exchange system based on an initial heartbeat frequency; inputting the running state data into a state scoring algorithm to perform state scoring calculation, and obtaining a node state score; comparing the node state score with a score threshold, and calculating a target heartbeat frequency according to a comparison result and the initial heartbeat frequency, so as to collect state data of the data exchange node according to the target heartbeat frequency.

2. The data processing method according to claim 1, characterized in that, The step of inputting the running state data into the state scoring algorithm to perform state scoring calculation and obtaining the node state score comprises: determining historical state scores corresponding to each state influence factor in the running state data, calculating weights of the state influence factors based on the historical state scores; performing state scoring calculation according to the weights and the running state data, and obtaining the node state score.

3. The data processing method according to claim 2, characterized in that, After the step of determining the historical state scores corresponding to each state influence factor in the running state data and calculating the weights of the state influence factors is performed, and before the step of performing state scoring calculation according to the weights and the running state data and obtaining the node state score is performed, the method further comprises: counting abnormal times of the state influence factors within a preset time period; updating the weights according to an adjustment factor and the abnormal times, and obtaining updated weights; Correspondingly, the step of performing state scoring calculation according to the weights and the running state data and obtaining the node state score comprises: performing state scoring calculation according to the updated weights and the running state data, and obtaining the node state score.

4. The data processing method of claim 1, wherein, The method further comprises: if it is detected that node state scores of multiple nodes within a preset time period are all lower than the score threshold, determining that a node state of the data exchange node is an abnormal state; generating a state reminder for the abnormal state, and sending the state reminder to an auditor for auditing.

5. The data processing method of claim 1, wherein, The method further comprises: if it is detected that a collection number of the running state data within a preset time period is less than a preset collection number, determining that the node state of the data exchange node is an abnormal state; generating a state reminder for the abnormal state, and sending the state reminder to an auditor for auditing.

6. The data processing method of claim 1, wherein, The method further comprises: storing the heartbeat data and the node state score; generating a display image for the node state score, and displaying the display image through a visual interface of a display terminal.

7. A data processing apparatus, characterized by, The device runs in a data monitoring system, and comprises: a state data collection module configured to collect running state data of a data exchange node of a data exchange system based on an initial heartbeat frequency; a scoring calculation module configured to input the running state data into a state scoring algorithm to perform state scoring calculation, and obtain a node state score; a comparison module configured to compare the node state score with a score threshold, and calculate a target heartbeat frequency according to a comparison result and the initial heartbeat frequency, so as to collect state data of the data exchange node according to the target heartbeat frequency.

8. A data processing device, characterized by The device comprises a memory and a processor, the memory has computer executable instructions stored thereon, and the computer executable instructions can implement the steps of the data processing method in any one of claims 1-6 when executed on the processor.

9. A computer-readable storage medium having stored computer-executable instructions, the computer-executable instructions comprising, The computer executable instructions can implement the steps of the data processing method in any one of claims 1-6 when executed on the processor.

10. A computer program product, characterised in that, The computer program product comprises a data processing program, and the data processing program can implement the steps of the data processing method in any one of claims 1-6 when executed on the processor.

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