Business system flow counting and control method and device based on multi-dimensional rule

Abstract

The embodiment of the invention discloses a business system flow counting and control method and device based on a multi-dimensional rule, and relates to the technical field of data processing. The method comprises the following steps: firstly, based on a data reporting mechanism of a service system, creating a counting control rule of the service system, and generating a rule dimension; then collecting the service information, generating service parameters, and analyzing the service parameters by querying rule dimensions to generate analysis data; then, based on the rule dimension, accumulated counting is carried out on the analysis data, and counting data is generated; and finally, on the basis of a real-time monitoring early warning rule, counting data is compared with rule dimensions, counting issuing information is generated and sent to a service system, and counting and management and control of the traffic of the service system are completed. According to the embodiment of the invention, unified data reporting, flexible rule setting, real-time monitoring and early warning and accurate management and control are realized, so that the data processing efficiency and accuracy are ensured, and the system stability and adaptability are improved.

Description

Technical Field

[0001] The present disclosure relates to data processing technology, and in particular to a method and device for counting and controlling business system traffic based on multi-dimensional rules. Background Art

[0002] In today's digital age, enterprises are facing a rapidly changing market environment, with various business systems emerging and increasing complexity and diversity in operations. With the popularization of technologies such as big data, cloud computing and artificial intelligence, data storage, analysis and application have become more efficient. The combination of these technologies enables enterprises to gain real-time insights in complex environments, thereby optimizing operations and improving customer experience.

[0003] However, the existing business systems have many deficiencies in terms of counting and control. On the one hand, different business systems have different ways of reporting data and lack unified standards and mechanisms, which makes data integration and analysis difficult; on the other hand, the counting and control of business operations are not accurate enough to meet the needs of different scenarios. For example, in terms of limiting the number of user visits and controlling transaction frequency, existing methods often cannot achieve real-time, dynamic adjustments and early warnings. These problems not only affect the effective operation of the business, but also restrict the further development of enterprises in the process of digital transformation.

[0004] Therefore, one or more methods are needed to solve the above problems.

[0005] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0006] The purpose of the present disclosure is to provide a method and device for counting and controlling business system traffic based on multi-dimensional rules, thereby overcoming one or more problems caused by limitations and defects of related technologies at least to a certain extent.

[0007] According to one aspect of the present disclosure, a method for counting and controlling traffic of a business system based on multi-dimensional rules is provided, comprising: Based on the data reporting mechanism of the business system, the counting control rules of the business system are created to generate rule dimensions; Based on the business system management and control requirements, business parameters are generated by collecting business information, and the business parameters are parsed by querying the rule dimensions to generate parsed data; Based on the rule dimension, generating counting data by accumulating and counting the parsed data; Based on the real-time monitoring and early warning rules, the counting data is compared with the rule dimensions to generate counting information, and the counting information is sent to the business system to complete the counting and control of the business system traffic.

[0008] In an exemplary embodiment of the present disclosure, the rule dimensions include rule unique value, parsing rule type, rule control parameters, unit time, whitelist value, warning issuance value, unit time maximum value, effective buffer value, and effective cache period.

[0009] In an exemplary embodiment of the present disclosure, business parameters are generated by collecting business information, and the business parameters are parsed by querying the rule dimension, including: Based on the business system management and control requirements, the unique value of the business rule is generated by issuing the unique value of the business system rule; Based on the data communication mechanism, the service parameters are generated by collecting the reported information and reported parameters; Based on the unique value of the business rule, a rule ID is generated by parsing the reported information; Based on the rule ID, a parsing type is generated by determining a parsing rule type of the business system; Based on the rule ID, generating parsing parameters by determining rule control parameters of the business system; Based on the analysis type, the reporting parameter is analyzed by the analysis parameter to generate a counting dimension; The analysis data is generated by integrating the rule ID and the counting dimension.

[0010] In an exemplary embodiment of the present disclosure, accumulating and counting the parsed data includes: Based on the analysis data, generating a counting task judgment result by judging the existence of the original counting task within the unit time of the counting unit; When the counting task judgment result is positive, the counting task creation time is generated by querying the counting task creation time; When the counting task judgment result is negative, the counting task is created by querying the preset counting rule to generate a rule counting task; Based on the rule counting task, the parsed data is cumulatively counted through the stream computing engine to generate counting data.

[0011] In an exemplary embodiment of the present disclosure, accumulating and counting the parsed data includes: When the creation time of the counting task is not greater than the preset counting period, the parsed data is accumulated and counted by the original counting task to generate counting data; When the counting task creation time is greater than the preset counting cycle, the original counting task is deleted and the preset counting rule is queried to create the task, thereby generating a rule counting task.

[0012] In an exemplary embodiment of the present disclosure, by comparing the count data with the rule dimension, including: Based on the real-time monitoring warning rule, when the range of the count data is within the whitelist value, statistical information is generated by monitoring the count data; Based on the real-time monitoring warning rules, when the range of the counting data is not within the whitelist value, the counting data is controlled by rules to generate whitelist alarm information; Based on the whitelist alarm information, when the count data is not greater than the warning value, statistical information is generated by monitoring the count data; Based on the whitelist alarm information, when the count data is greater than the warning value, generate warning information by performing rule control on the count data; Based on the warning information, when the count data is not greater than the maximum value of the unit time, generating statistical information by performing data monitoring on the count data; Based on the early warning information, when the counting data is greater than a unit time maximum value, unit time alarm information is generated by performing rule control on the counting data.

[0013] In an exemplary embodiment of the present disclosure, by comparing the count data with the rule dimension, it also includes: Based on the unit time alarm information, buffer data is generated by performing buffer time management and control on the counting data; Based on the buffer control rule, when the buffer data is greater than the sum of the unit time maximum value and the effective buffer value, interception information is generated by monitoring the buffer data; Based on the buffer control rule, when the buffer data is not greater than the sum of the unit time maximum value and the effective buffer value, the buffer countdown is generated by controlling the buffer timeliness of the buffer data according to the rule; Based on the buffer control rule, when the buffer countdown is greater than the effective buffer period, interception information is generated by monitoring the buffer data; Based on the buffer control rule, when the buffer countdown is not greater than the effective buffer period, statistical information is generated by monitoring the buffer data; By integrating the statistical information, early warning information, and interception information, counting and sending information is generated, and by sending the counting and sending information to the business system, the counting and control of the business system traffic is completed.

[0014] In another aspect of the present disclosure, a traffic counting and control device for a business system based on multi-dimensional rules is provided, comprising: The rule setting module is used to create counting control rules for the business system; A collection and analysis module, used to collect business information, generate business parameters, and analyze the business parameters by querying the rule dimension; A counting module, used for accumulating and counting the parsed data; The rule comparison module is used to compare the counting data with the rule dimension, generate counting information, and complete the counting and control of the business system traffic by sending the counting information to the business system.

[0015] In one aspect of the present disclosure, there is also provided an electronic device, comprising: A processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the method according to any one of the above items is implemented.

[0016] In one aspect of the present disclosure, a computer-readable storage medium is further provided, on which a computer program is stored. When the computer program is executed by a processor, the method according to any one of the above items is implemented.

[0017] Based on the embodiment of the present disclosure, first, based on the data reporting mechanism of the business system, the counting control rules of the business system are created to generate rule dimensions. After that, the business information is collected to generate business parameters, and the business parameters are parsed by querying the rule dimensions to generate parsed data. Then, based on the rule dimensions, the parsed data is cumulatively counted to generate counting data. Finally, based on the real-time monitoring and early warning rules, the counting data is compared with the rule dimensions to generate counting information, and sent to the business system to complete the counting and control of the business system traffic. Therefore, the embodiment of the present disclosure provides a unified data collection and rule control solution, which can flexibly adapt to multiple business scenarios, realize unified data reporting, flexible rule setting, real-time monitoring and early warning, and precise control, so as to ensure data processing efficiency and accuracy, and improve system stability and adaptability. It should be understood that the above general description and the detailed description below are only exemplary and explanatory, and cannot limit the present disclosure.

[0018] The technical solution of the present disclosure is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings, which constitute a part of the specification, illustrate embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0020] The present disclosure may be more clearly understood from the following detailed description with reference to the accompanying drawings, in which: Figure 1 This is a flow chart of a method for counting and controlling business system traffic based on multi-dimensional rules in one embodiment of the disclosed method; Figure 2 A decision logic flow chart of a method for counting and controlling business system traffic based on multi-dimensional rules in one embodiment of the disclosed method; Figure 3 This is a structural block diagram of a business system traffic counting and control device based on multi-dimensional rules in one embodiment of the disclosed method; Figure 4 A block diagram of an electronic device according to an embodiment of the method disclosed herein. DETAILED DESCRIPTION

[0021] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be comprehensive and complete and will fully convey the concepts of the example embodiments to those skilled in the art. The same reference numerals in the figures represent the same or similar parts, and thus their repeated description will be omitted.

[0022] In addition, the described features, structures or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of the specific details, or other methods, components, materials, devices, steps, etc. may be adopted. In other cases, known structures, methods, devices, implementations, materials or operations are not shown or described in detail to avoid blurring the various aspects of the present disclosure.

[0023] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or these functional entities or parts of functional entities may be implemented in one or more software hardened modules, or these functional entities may be implemented in different networks and / or processor devices and / or microcontroller devices.

[0024] In the embodiment of the present disclosure, a method for counting and controlling business system traffic based on multi-dimensional rules is first provided; Figure 1As shown in , the method may include the following steps: Step S110, based on the data reporting mechanism of the business system, a count control rule of the business system is created to generate a rule dimension; Step S120, based on the business system management and control requirements, business parameters are generated by collecting business information, and the business parameters are parsed by querying the rule dimensions to generate parsed data; Step S130, generating counting data by accumulating and counting the parsed data based on the rule dimension; Step S140, based on the real-time monitoring warning rules, generates counting information by comparing the counting data with the rule dimensions, and sends the counting information to the business system to complete the counting and control of the business system traffic.

[0025] Below, as Figure 2 As shown, a business system traffic counting and control method based on multi-dimensional rules in an embodiment of the present disclosure will be further explained.

[0026] In step S110, based on the data reporting mechanism of the business system, a count control rule of the business system may be created to generate a rule dimension.

[0027] In some optional embodiments of this example, the outside world may be allowed to set various rules for the system, including supporting the setting of basic rule dimensions.

[0028] Among them, first, a white list value can be set, and the items in the list will not be blocked or warned.

[0029] After that, the unique value of the rule used to identify each rule is set. The unit time of the counting time range, and the maximum value of the unit time is the maximum number of counts within the unit time range.

[0030] On this basis, the parsing rule types are set, such as jwt parsing and json parameter parsing. Then the rule control parameters are set according to different parsing types. For example, [orgId, userId] needs to be set for jwt parsing, and [$.name, $.userId] needs to be set for jsonPath parsing.

[0031] Then, the warning issuance value is set according to the percentage of the maximum value of the unit time. For example, a warning is issued when 90% of the maximum value of the unit time is reached.

[0032] Finally, when the maximum value of the unit time is exceeded, the effective buffer value is set to allow a certain range of exceeding the limit, and when the maximum value of the unit time is exceeded but not exceeding the sum of the maximum value of the unit time and the effective buffer value, the effective buffer period allowed for the excess time is set.

[0033] In a specific example, system A can set the unit time to 5 days, and for the combined dimension of parameter B and parameter C, the maximum value of the unit time allowed is 500 accesses, the effective buffer period is 3 hours, the effective cache value is 50 times, the parsing rule type is json parsing, and the rule control parameters are [$.paramB, $.paramB]. Then, after the system reports, the corresponding parameters B and C parsed from the reported json will be counted and controlled.

[0034] Preferably, it is also possible to support separate settings for multiple tenants for a single rule. Specifically, in addition to the public settings, certain parameters can be individually controlled. This setting of separate control rules is effective when different customers are billed according to different quantities. For example, after user A places an order to purchase a system access certificate for 5,000 times per month, a configuration with a unit time of one month and a maximum unit time of 5,000 times can be automatically added to user A.

[0035] In this way, through the rich rule setting dimensions, it can meet the needs of different business scenarios, adapt to various complex business environments, and reduce development costs and maintenance difficulties. The separate settings of multiple tenants can meet the personalized counting and management services of different customers, improving the adaptability and flexibility of the system.

[0036] In step S120, based on the business system management and control requirements, business parameters can be generated by collecting business information, and the business parameters can be parsed by querying the rule dimensions to generate parsed data.

[0037] In some optional embodiments of this example, first, based on the business system management and control requirements, each business system that needs to be counted and controlled generates a unique value of the business rule of the business system by issuing the uniqueness of the rules of the business system when it needs to report information. Specifically, before reporting, business system A needs to go to the rule control unit to apply for the unique value of business rule A belonging to business system A (a system, an interface within a system, even a method, or a piece of code can apply for a rule).

[0038] Afterwards, the unique value of the business rules matched by each business system, as well as the reporting parameters and reporting information, are reported to the data collection unit through various data communication mechanisms (such as HTTP requests, message queues, log writing, etc.) to generate business information.

[0039] After receiving the business information of each business system through the above-mentioned multiple data communication mechanisms, the receiving unit in the data collection unit will transfer the business information to the parsing unit in the data collection unit.

[0040] The parsing unit parses the reported information based on the unique value of the business rule, generates a rule ID, and then determines the parsing rule type based on the rule ID, generates a parsing type, and determines the rule control parameters, and generates parsing parameters.

[0041] Finally, the reported parameters are parsed by determining the parsing type and parsing parameters to generate the counting dimension, and then the rule ID is integrated with the parsed counting dimension to generate the parsing data of each business system and send it to the counting unit.

[0042] In step S130, counting data may be generated by cumulatively counting the parsed data based on the rule dimension.

[0043] In some optional embodiments of this example, after the counting unit receives the parsed data of each business system, it first needs to determine whether there is an original counting task of the business system within the unit time, and generate a counting task determination result.

[0044] If the counting task judgment result is positive according to the rule ID in the parsed data (that is, the original counting task of the business system exists in the counting unit), the creation time of the existing counting task is queried.

[0045] If the result of the counting task is negative (i.e., the original counting task of the business system does not exist in the counting unit), the preset counting rule is obtained by querying the rule control unit, and the rule counting task of the business system is created according to the preset counting rule of each business system. Then, the streaming computing engine is used to accumulate and count the parsed data delivered by the data collection unit to generate the counting data of each business system.

[0046] In some optional embodiments of this example, the queried counting task creation time is compared with a preset counting period.

[0047] When the creation time of the counting task is not greater than the preset counting cycle, the original counting task already in the counting unit is used to accumulate and count the parsed data delivered by the data collection unit to generate the counting data of each business system.

[0048] When the creation time of the counting task is greater than the preset counting cycle, the original counting task is deleted and then the rule counting tasks of each business system are created by querying the rule control unit.

[0049] In this way, the bandwidth occupied by directly creating new rule counting tasks is greatly avoided, while ensuring the accuracy and real-time performance of the data in the counting tasks.

[0050] In step S140, based on the real-time monitoring warning rules, the counting data can be compared with the rule dimensions to generate counting information, and the counting information can be sent to the business system to complete the counting and control of the business system traffic.

[0051] In some optional embodiments of this example, after the counting unit obtains the counting data of each business system through counting, the rule comparison unit can work together to monitor the number of calls and accesses of each business system in real time, so as to send statistical information, warning information, and interception information to the business system in a timely manner, effectively prevent abnormal situations from occurring in the business system, and improve the stability and security of the business system.

[0052] Specifically, in the first step, the whitelist value is queried according to the unique value and count dimension of the business rule. If the count data of the business system is within the range of the whitelist value, there is no need to execute subsequent rule control. The count data is directly monitored to generate statistical information.

[0053] If the count data of the business system is not within the range of the whitelist value, the count data is subject to rule control, and whitelist alarm information is generated for the next step of rule judgment.

[0054] The second step is to determine the warning value for the counting data that is not in the whitelist value. If the counting data is not greater than the warning value, there is no need to execute subsequent rule control. The counting data is directly monitored to generate statistical information.

[0055] If the count data is greater than the warning value, the next step of rule control is performed on the whitelist alarm information to generate a warning message.

[0056] Preferably, before this step, a separate setting of a single rule of the current business system can also be judged. If the business system has a separate setting of a single rule, the counting data is judged using the rule range of the separate setting. If the business system does not have a separate setting of a single rule, the counting data is judged using the rule range of the basic setting.

[0057] The third step is to determine the maximum value of the unit time for the counting data that is greater than the warning value. If the counting data is not greater than the maximum value of the unit time, there is no need to execute subsequent rule control. The counting data is directly monitored to generate statistical information.

[0058] If the count data is greater than the maximum value of the unit time, the warning information is subjected to the next rule control to generate the unit time alarm information.

[0059] In some optional embodiments of this example, in the fourth step, if a business system in the above embodiment generates a unit time alarm information, a buffer time control of the business system counting data is established, buffer data is generated, and the effective buffer value and effective buffer period belonging to the business system are found from the rule control unit. The control of the buffer time can give the business system a certain buffer time, which not only ensures the stability of the system, but also does not restrict business operations too strictly, achieving a balance between accurate counting and reasonable control.

[0060] Step 5: If the buffer data of the business system is greater than the sum of the maximum value of the unit time and the effective buffer value, the interception information is directly sent to the current business system.

[0061] If the buffer data of the business system is not greater than the sum of the unit time maximum value and the effective buffer value, a buffer countdown for the business system is established, and the buffer countdown is compared with the effective buffer period for rule control.

[0062] Step 6: If the buffer countdown of the business system is greater than the effective buffer period (ie, the countdown period allowed for buffering by the business system expires), an interception message is directly sent to the current business system.

[0063] If the buffer countdown of the business system is not greater than the effective buffer period (that is, the countdown allowed for buffering by the business system has not expired), the statistical information is directly sent to the current business system.

[0064] In this way, according to the above six steps, by sending the generated statistical information, warning information, and interception information to the business system, the business counting requirements in different scenarios can be met.

[0065] By sending out counting information composed of statistical information, early warning information, interception information, etc., the system can realize real-time monitoring, early warning and precise control, ensure the efficiency and accuracy of data processing, and improve the stability and adaptability of the system.

[0066] In a specific example, assume that user A with isvId=1 can make a maximum of 10 calls within a day, the warning issuance value is 80%, the effective buffer value is 2 times, and the effective buffer period is 1 hour.

[0067] Then, if the number of times the user calls the interface exceeds 8 times within the unit time, an early warning message will be sent to the business system that initiated the call; if it exceeds 10 times, but does not exceed the maximum allowed value plus the effective buffer value, that is, 12 times, the current reported data will be placed in the buffer countdown queue for buffer countdown. When entering the buffer countdown queue, it will simultaneously determine whether the cumulative number exceeds 12 times and whether the countdown of 1 hour has ended. As long as one of the two is met, an interception message will be immediately sent to the open platform business system to prevent the user from continuing to call the interface. If none of the above occurs, only statistical information of the statistical count will be sent.

[0068] It should be noted that, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0069] In addition, in this exemplary embodiment, a business system traffic counting and control device based on multi-dimensional rules is also provided. Figure 3 As shown, the device 300 may include: a rule setting module 310, a collection and analysis module 320, a counting module 330 and a rule comparison module 340. Among them: A rule setting module 310 is used to create a counting control rule for a business system; The collection and analysis module 320 is used to collect business information, generate business parameters, and analyze the business parameters by querying the rule dimension; A counting module 330, configured to accumulate and count the parsed data; The rule comparison module 340 is used to compare the counting data with the rule dimension, generate counting information, and complete the counting and control of the business system traffic by sending the counting information to the business system.

[0070] The business system traffic counting and control device based on multidimensional rules of the embodiment of the present disclosure corresponds to the embodiment of the business system traffic counting and control method based on multidimensional rules of the present disclosure, and the relevant contents can be referenced to each other, which will not be repeated here. The beneficial technical effects corresponding to the business system traffic counting and control device based on multidimensional rules of the embodiment of the present disclosure can be referred to the corresponding beneficial technical effects of the corresponding exemplary method part above, which will not be repeated here.

[0071] It should be noted that although several modules or units of the multi-dimensional rule-based business system traffic counting and control device 300 are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiment of the present disclosure, the features and functions of two or more modules or units described above can be concretized in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be concretized.

[0072] Below, reference Figure 4 The electronic device according to the embodiment of the present disclosure is described. The electronic device may be any one or both of the first device and the second device, or a stand-alone device independent of them, and the stand-alone device may communicate with the first device and the second device to receive the collected input signals from them.

[0073] Figure 4 A block diagram of an electronic device according to an embodiment of the present disclosure is illustrated.

[0074] like Figure 4 As shown, the electronic device includes one or more processors and memory.

[0075] The processor may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0076] The memory may store one or more computer program products, and the memory may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory (cache), etc. The non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc. One or more computer program products may be stored on the computer-readable storage medium, and the processor may run the computer program product to implement the various embodiments of the present disclosure described above and / or other desired functions.

[0077] In one example, the electronic device may further include: an input device and an output device, and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0078] In addition, the input device may also include, for example, a keyboard, a mouse, and the like.

[0079] The output device can output various information to the outside, including determined distance information, direction information, etc. The output device can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, and the like.

[0080] Of course, to simplify, Figure 4 Only some of the components related to the present disclosure in the electronic device are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, according to specific application situations, the electronic device may further include any other appropriate components.

[0081] In addition to the above methods and devices, an embodiment of the present disclosure may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present disclosure described in the above part of this specification.

[0082] The computer program product may be written in any combination of one or more programming languages ​​to write program code for performing the operations of the disclosed embodiments, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0083] In addition, an embodiment of the present disclosure may also be a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, enables the processor to execute the steps of the method according to various embodiments of the present disclosure described in the above part of this specification.

[0084] The computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0085] The basic principles of the present disclosure are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present disclosure are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present disclosure. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, and are not limitations. The above details do not limit the present disclosure to the necessity of adopting the above specific details to be implemented.

[0086] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0087] The block diagrams of the devices, apparatuses, equipment, and systems involved in this disclosure are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including," "comprising," "having," and the like are open words, referring to "including but not limited to," and can be used interchangeably therewith. The words "or" and "and" used herein refer to the words "and / or," and can be used interchangeably therewith, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to," and can be used interchangeably therewith.

[0088] The method and apparatus of the present disclosure may be implemented in many ways. For example, the method and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above order of steps for the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above, unless otherwise specifically stated. In addition, in some embodiments, the present disclosure may also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present disclosure. Therefore, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.

[0089] It should also be noted that in the apparatus, device and method of the present disclosure, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present disclosure.

[0090] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

[0091] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A method for counting and controlling business system traffic based on multi-dimensional rules, characterized in that: include: Based on the data reporting mechanism of the business system, the counting control rules of the business system are created to generate rule dimensions; Based on the business system management and control requirements, business parameters are generated by collecting business information, and the business parameters are parsed by querying the rule dimensions to generate parsed data; Based on the rule dimension, generating counting data by accumulating and counting the parsed data; Based on the real-time monitoring and early warning rules, the counting data is compared with the rule dimensions to generate counting information, and the counting data information is sent to the business system to complete the counting and control of the business system traffic.

2. The method according to claim 1, characterized in that: The rule dimensions include rule unique value, parsing rule type, rule control parameter, unit time, whitelist value, warning issuance value, unit time maximum value, effective buffer value, and effective cache period.

3. The method according to claim 2, characterized in that The business parameters are generated by collecting the business information, and the business parameters are parsed by querying the rule dimension, including: Based on the business system management and control requirements, the unique value of the business rule is generated by issuing the unique value of the business system rule; Based on the data communication mechanism, the service parameters are generated by collecting the reported information and reported parameters; Based on the unique value of the business rule, a rule ID is generated by parsing the reported information; Based on the rule ID, a parsing type is generated by determining a parsing rule type of the business system; Based on the rule ID, generating parsing parameters by determining rule control parameters of the business system; Based on the analysis type, the reporting parameter is analyzed by the analysis parameter to generate a counting dimension; The analysis data is generated by integrating the rule ID and the counting dimension.

4. The method according to claim 2, characterized in that: By accumulating and counting the parsed data, including: Based on the analysis data, generating a counting task judgment result by judging the existence of the original counting task within the unit time of the counting unit; When the counting task judgment result is positive, the counting task creation time is generated by querying the counting task creation time; When the counting task judgment result is negative, the counting task is created by querying the preset counting rule to generate a rule counting task; Based on the rule counting task, the parsed data is cumulatively counted through the stream computing engine to generate counting data.

5. The method according to claim 4, characterized in that By accumulating and counting the parsed data, the method further comprises: When the creation time of the counting task is not greater than the preset counting period, the parsed data is accumulated and counted by the original counting task to generate counting data; When the counting task creation time is greater than the preset counting cycle, the original counting task is deleted and the preset counting rule is queried to create the task, thereby generating a rule counting task.

6. The method according to claim 2, characterized in that By comparing the count data with the rule dimension, including: Based on the real-time monitoring warning rule, when the range of the count data is within the whitelist value, statistical information is generated by monitoring the count data; Based on the real-time monitoring warning rules, when the range of the counting data is not within the whitelist value, the counting data is controlled by rules to generate whitelist alarm information; Based on the whitelist alarm information, when the count data is not greater than the warning value, statistical information is generated by monitoring the count data; Based on the whitelist alarm information, when the count data is greater than the warning value, generate warning information by performing rule control on the count data; Based on the warning information, when the count data is not greater than the maximum value of the unit time, generating statistical information by performing data monitoring on the count data; Based on the early warning information, when the counting data is greater than a unit time maximum value, unit time alarm information is generated by performing rule control on the counting data.

7. The method according to claim 6, characterized in that By comparing the count data with the rule dimension, it also includes: Based on the unit time alarm information, buffer data is generated by performing buffer time management and control on the counting data; Based on the buffer control rule, when the buffer data is greater than the sum of the unit time maximum value and the effective buffer value, interception information is generated by monitoring the buffer data; Based on the buffer control rule, when the buffer data is not greater than the sum of the unit time maximum value and the effective buffer value, the buffer countdown is generated by controlling the buffer timeliness of the buffer data according to the rule; Based on the buffer control rule, when the buffer countdown is greater than the effective buffer period, interception information is generated by monitoring the buffer data; Based on the buffer control rule, when the buffer countdown is not greater than the effective buffer period, statistical information is generated by monitoring the buffer data; The counting and control of the traffic of the business system is completed by integrating the statistical information, the warning information and the interception information to generate counting and sending information, and sending the counting and sending information to the business system.

8. A business system traffic counting and control device based on multi-dimensional rules, characterized in that: include: The rule setting module is used to create counting control rules for the business system and generate rule dimensions; A collection and analysis module, used to collect business information, generate business parameters, and analyze the business parameters by querying the rule dimensions to generate analysis data; A counting module, used for accumulating and counting the parsed data to generate counting data; The rule comparison module is used to compare the counting data with the rule dimension, generate counting information, and complete the counting and control of the business system traffic by sending the counting information to the business system.

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