Index data monitoring method, device, computer equipment and storage medium

Abstract

The present application relates to an index data monitoring method, device, computer equipment and storage medium. The method comprises: obtaining index data to be monitored, the index data to be monitored includes a business indicator identifier to be monitored; obtaining historical index data, obtaining historical business data corresponding to the business indicator identifier to be monitored from the historical index data; determining abnormal index data according to the index data to be monitored and the historical business data; and monitoring the abnormal index data according to a target preset monitoring method. The method does not require manual monitoring of index data, thereby improving the monitoring accuracy of index data.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to an index data monitoring method, device, computer equipment and storage medium. Background Art

[0002] At present, with the rapid development of computers, data needs to be monitored. Data monitoring is usually done by manually monitoring the current data to verify whether the current data is abnormal data. However, this manual monitoring method is easily affected by the subjective consciousness and experience of the monitoring personnel, resulting in low data monitoring accuracy. Summary of the invention

[0003] Based on this, it is necessary to provide an index data monitoring method, device, computer equipment and storage medium that does not require manual monitoring of index data and improves the monitoring accuracy of index data in order to address the above technical problems.

[0004] A method for monitoring index data, the method comprising:

[0005] Obtaining the index data to be monitored, where the index data to be monitored includes an identifier of the business indicator to be monitored;

[0006] Obtain historical index data, and obtain historical business data corresponding to the business indicator identifier to be monitored from the historical index data;

[0007] Determine abnormal index data based on the index data to be monitored and historical business data;

[0008] Monitor abnormal index data according to the target preset monitoring method.

[0009] In one of the embodiments, historical index data is obtained, and historical business data corresponding to the business indicator identifier to be monitored is obtained from the historical index data, including: obtaining the historical index data; obtaining a set of candidate business indicator identifiers corresponding to the historical index data, the candidate business indicator identifier set including at least one candidate business indicator identifier, the candidate business indicator identifier including corresponding candidate historical business data; determining a target candidate business indicator identifier corresponding to the business indicator identifier to be monitored from the candidate business indicator identifier set; and determining the candidate historical business data corresponding to the target candidate business indicator identifier as the historical business data corresponding to the business indicator identifier to be monitored.

[0010] In one of the embodiments, determining abnormal index data based on the index data to be monitored and the historical business data includes: comparing whether the index data to be monitored is the same as the historical business data; and determining that the index data to be monitored is abnormal index data when the index data to be monitored is different from the historical business data.

[0011] In one of the embodiments, the index data monitoring method also includes: obtaining a preset abnormal data threshold; when the abnormal index data exceeds the preset abnormal data threshold, entering the step of monitoring the abnormal index data according to a target preset monitoring method; when the abnormal index data does not exceed the preset abnormal data threshold, not monitoring the abnormal index data.

[0012] In one of the embodiments, monitoring the abnormal index data according to a target preset monitoring method includes: obtaining a set of candidate preset monitoring methods; determining a target preset monitoring method from the set of candidate preset monitoring methods; and monitoring the abnormal index data according to the target preset monitoring method.

[0013] In one of the embodiments, the step of constructing the index data to be monitored includes: obtaining preset empty index data; obtaining business data corresponding to the business indicator identifier to be monitored; writing the business data into the preset empty index data to obtain the index data to be monitored.

[0014] An index data monitoring device, the device comprising:

[0015] The module for acquiring index data to be monitored is used to acquire index data to be monitored, where the index data to be monitored includes an identifier of a business indicator to be monitored;

[0016] A historical index data acquisition module is used to acquire historical index data, and to acquire historical business data corresponding to the business indicator identifier to be monitored from the historical index data;

[0017] An abnormal index data determination module is used to determine abnormal index data based on the index data to be monitored and historical business data;

[0018] The abnormal index data monitoring module is used to monitor the abnormal index data according to the target preset monitoring method.

[0019] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following steps are implemented:

[0020] Obtaining the index data to be monitored, where the index data to be monitored includes an identifier of the business indicator to be monitored;

[0021] Obtain historical index data, and obtain historical business data corresponding to the business indicator identifier to be monitored from the historical index data;

[0022] Determine abnormal index data based on the index data to be monitored and historical business data;

[0023] Monitor abnormal index data according to the target preset monitoring method.

[0024] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0025] Obtaining the index data to be monitored, where the index data to be monitored includes an identifier of the business indicator to be monitored;

[0026] Obtain historical index data, and obtain historical business data corresponding to the business indicator identifier to be monitored from the historical index data;

[0027] Determine abnormal index data based on the index data to be monitored and historical business data;

[0028] Monitor abnormal index data according to the target preset monitoring method.

[0029] The above-mentioned index data monitoring method, device, computer equipment and storage medium obtain the index data to be monitored, the index data to be monitored includes the business indicator identifier to be monitored; obtain historical index data, obtain the historical business data corresponding to the business indicator identifier to be monitored from the historical index data; determine the abnormal index data according to the index data to be monitored and the historical business data; monitor the abnormal index data according to the target preset monitoring method. Therefore, by comparing the index data to be monitored with the historical index data, it can be determined whether the index data to be monitored is abnormal data, without the need for manual monitoring, avoiding the subjective consciousness and experience influence brought by manual labor, thereby improving the monitoring accuracy of the index data. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 An application environment diagram of an index data monitoring method in an embodiment;

[0031] Figure 2 A schematic diagram of a flow chart of an index data monitoring method in one embodiment;

[0032] Figure 3 is a structural block diagram of an index data monitoring device in one embodiment;

[0033] Figure 4 is an internal structure diagram of a computer device in one embodiment;

[0034] Figure 5 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0036] The index data monitoring method provided in this application can be applied to Figure 1 In the application environment shown, the terminal 102 communicates with the server 104 through a network. The terminal 102 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices, and the server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0037] Specifically, the terminal 102 sends the index data to be monitored to the server 104, and the index data to be monitored includes the business indicator identifier to be monitored. After receiving the index data to be monitored, the server 104 obtains the historical index data, obtains the historical business data corresponding to the business indicator identifier to be monitored from the historical index data, determines the abnormal index data according to the index data to be monitored and the historical business data, and monitors the abnormal index data according to the target preset monitoring method.

[0038] In another embodiment, the terminal 102 obtains index data to be monitored, the index data to be monitored includes an identifier of a business indicator to be monitored, obtains historical index data, obtains historical business data corresponding to the identifier of the business indicator to be monitored from the historical index data, determines abnormal index data based on the index data to be monitored and the historical business data, and monitors the abnormal index data according to a target preset monitoring method.

[0039] In one embodiment, Figure 2 As shown, a method for monitoring index data is provided, which is applied to Figure 1 The terminal or server in the example is used to illustrate, including the following steps:

[0040] Step 202: Acquire the index data to be monitored, where the index data to be monitored includes an identifier of the business indicator to be monitored.

[0041] The index data to be monitored here refers to the index data currently being monitored. The so-called index data is the index in the full-text search engine Elasticsearch (ES). ES stores data in one or more indexes, and an index is a collection of documents with similar characteristics. Analogously to the traditional relational database field, an index is equivalent to a database in the Structured Query Language (SQL), or a data storage scheme (schema). The index is identified by its name (which must be all lowercase characters), and the document creation, search, update, and deletion operations are completed by referencing this name. Any number of indexes can be created on demand in an ES cluster.

[0042] The index data to be monitored includes the business indicator identifier to be monitored. The business indicator identifier to be monitored is used to identify the business to be monitored this time. Different businesses correspond to different business indicators.

[0043] In one embodiment, the step of constructing the index data to be monitored includes: obtaining preset empty index data, obtaining business data corresponding to the business indicator identifier to be monitored, writing the business data into the preset empty index data, and obtaining the index data to be monitored.

[0044] Among them, the steps for constructing the index data to be monitored can specifically be, obtaining preset empty index data, the preset empty index data can be determined in advance according to business needs, actual application scenarios or product needs to generate an empty index data, and then searching for matching business data according to the business indicator identifier to be monitored. The business data may include pre-sales business data and databases, etc. Finally, the business data is written into the preset empty index data to obtain the index data to be monitored.

[0045] Step 204: Obtain historical index data, and obtain historical business data corresponding to the business indicator identifier to be monitored from the historical index data.

[0046] The historical index data here refers to the index data previously stored by the execution subject. The execution subject may store the corresponding index data in advance, or may determine the monitored index data as the historical index data and store it. Specifically, the historical index data may be obtained according to actual business needs, product needs or actual application scenarios, and then the historical business data corresponding to the business indicator identifier to be monitored may be searched from the historical index data. Specifically, the historical index data may include the corresponding candidate business indicator identifier, and each candidate business indicator identifier has the corresponding candidate business data. The historical business data may be obtained according to the candidate business indicator identifier and the business indicator identifier to be monitored.

[0047] In one embodiment, historical index data is obtained, and historical business data corresponding to the business indicator identifier to be monitored is obtained from the historical index data, including: obtaining the historical index data, obtaining a set of candidate business indicator identifiers corresponding to the historical index data, the candidate business indicator identifier set including at least one candidate business indicator identifier, the candidate business indicator identifier including corresponding candidate historical business data, determining a target candidate business indicator identifier corresponding to the business indicator identifier to be monitored from the candidate business indicator identifier set, and determining the candidate historical business data corresponding to the target candidate business indicator identifier as the historical business data corresponding to the business indicator identifier to be monitored.

[0048] Among them, historical index data is obtained, and historical business data corresponding to the business indicator identifier to be monitored is obtained from the historical index data. Specifically, historical index data can be obtained according to business needs, actual application scenarios or product needs, and then a set of candidate business indicator identifiers corresponding to the historical index data is obtained. The candidate business indicator identifier set includes at least one candidate business indicator identifier, different candidate business indicators correspond to different candidate business indicator identifiers, and each candidate business indicator identifier includes corresponding candidate historical business data. The correspondence between the candidate business indicator identifier and the corresponding candidate historical business data can be determined in advance according to business needs, actual application scenarios or product needs.

[0049] Furthermore, a matching target candidate business indicator identifier can be determined from a set of candidate business indicator identifiers based on the business indicator identifier to be monitored, and then based on the relationship between the candidate business indicator identifier and the candidate business data, the candidate historical business data corresponding to the target candidate business indicator identifier can be used as the historical business data corresponding to the business indicator identifier to be monitored.

[0050] Step 206: determine abnormal index data based on the index data to be monitored and the historical business data.

[0051] Specifically, after obtaining the index data to be monitored and the historical business data, the abnormal index data can be determined according to the index data to be monitored and the historical business data. Specifically, the index data to be monitored and the historical business data are compared to see if they are the same. If they are different, it means that the index data to be monitored and the historical business data do not match, and it can be determined that the index data to be monitored is abnormal index data. If the index data to be monitored is the same as the historical business data, it can be determined that the index data to be monitored is normal index data.

[0052] Among them, to compare whether the index data to be monitored is the same as the historical business data, you can compare whether the field values ​​corresponding to the same fields are the same. If the field values ​​corresponding to the same fields in the index data to be monitored are the same as the field values ​​corresponding to the historical business data, it can be determined that the index data to be monitored is the same as the historical business data, and the index data to be monitored is determined to be normal index data. On the contrary, if the field values ​​corresponding to the same fields in the index to be monitored are different from the field values ​​corresponding to the historical business data, it can be determined that the index data to be monitored is different from the historical business data, and the index data to be monitored is determined to be abnormal index data.

[0053] In one embodiment, determining abnormal index data based on the monitored index data and historical business data includes: comparing whether the monitored index data is the same as the historical business data, and determining that the monitored index data is abnormal index data when the monitored index data is different from the historical business data.

[0054] Among them, the abnormal index data is determined based on the index data to be monitored and the historical business data. Specifically, it can be to compare whether the index data to be monitored is the same as the historical business data, and to compare whether the field values ​​corresponding to the same fields are the same. If the field value corresponding to the index data to be monitored and the field value corresponding to the historical business data are the same, then it can be determined that the index data to be monitored is the same as the historical business data, and the index data to be monitored is determined to be normal index data. On the contrary, if the field value corresponding to the index to be monitored and the field value corresponding to the historical business data are different, then it can be determined that the index data to be monitored is different from the historical business data, and the index data to be monitored can be determined to be abnormal index data.

[0055] Step 208 , obtaining a preset abnormal data threshold, and when the abnormal index data exceeds the preset abnormal data threshold, proceeding to step 212 .

[0056] Step 210: When the abnormal index data does not exceed the preset abnormal data threshold, the abnormal index data is not monitored.

[0057] Among them, before monitoring, the abnormal index data can be judged and detected again to ensure that no misjudgment occurs and to improve the monitoring accuracy of the index data. Specifically, a preset abnormal data threshold is obtained, and the preset abnormal data threshold can be determined in advance according to business needs, product needs or actual application scenarios. Further, compare whether the abnormal index data exceeds the preset abnormal data threshold. If the abnormal index data exceeds the preset abnormal data threshold, it means that the abnormal index data is abnormal, and step 212 can be entered for monitoring. On the contrary, if the abnormal index data does not exceed the abnormal data threshold, it means that the abnormal index data is not abnormal, or the abnormal index data has not yet reached the conditions for monitoring, so there is no need to monitor the abnormal index data.

[0058] Step 212: Monitor the abnormal index data according to the target preset monitoring method.

[0059] Among them, a preset monitoring method set can be determined in advance according to business needs, product needs or actual application scenarios. The preset monitoring method can be but not limited to SMS notification, email notification, etc., and the preset monitoring method set is obtained. The target preset monitoring method is determined from the preset monitoring method set. The method for determining the target preset monitoring method can be customized. Customization can be to arbitrarily determine a candidate preset monitoring method from the preset monitoring method set as the target preset monitoring method, or to determine the target preset monitoring method from the preset monitoring method set according to business needs, actual application scenarios or product needs. Further, the abnormal index data is monitored according to the target preset monitoring method.

[0060] In one embodiment, monitoring the abnormal index data according to a target preset monitoring method includes: obtaining a set of candidate preset monitoring methods, determining a target preset monitoring method from the set of candidate preset monitoring methods, and monitoring the abnormal index data according to the target preset monitoring method.

[0061] Among them, a set of preset monitoring methods can be determined in advance according to business needs, product needs or actual application scenarios. The preset monitoring method can be but not limited to SMS notification, email notification, etc., obtain the set of preset monitoring methods, and determine the target preset monitoring method from the set of preset monitoring methods. The method of determining the target preset monitoring method can be customized. Customization can be to arbitrarily determine a candidate preset monitoring method from the set of preset monitoring methods as the target preset monitoring method, or to determine the target preset monitoring method from the set of preset monitoring methods according to business needs, actual application scenarios or product needs. Among them, the method of determining the target preset monitoring method can also be to obtain the monitoring priority corresponding to each candidate preset monitoring method, determine the candidate preset monitoring method with a high monitoring priority as the target preset monitoring method, and then monitor the abnormal index data through the target preset monitoring method.

[0062] In the above index data monitoring method, the index data to be monitored is obtained, and the index data to be monitored includes the business indicator identifier to be monitored; the historical index data is obtained, and the historical business data corresponding to the business indicator identifier to be monitored is obtained from the historical index data; the abnormal index data is determined according to the index data to be monitored and the historical business data; and the abnormal index data is monitored according to the target preset monitoring method. Therefore, by comparing the index data to be monitored with the historical index data, it can be determined whether the index data to be monitored is abnormal data, without the need for manual monitoring, avoiding the subjective consciousness and experience influence brought by manual labor, thereby improving the monitoring accuracy of the index data.

[0063] In a specific embodiment, a method for monitoring index data is provided, which specifically includes the following steps:

[0064] 1. Obtain the index data to be monitored, which includes the identifier of the business indicator to be monitored.

[0065] 1-1. Get the preset empty index data.

[0066] 1-2. Obtain the business data corresponding to the business indicator identifier to be monitored.

[0067] 1-3. Write the business data into the preset empty index data to obtain the index data to be monitored.

[0068] 2. Obtain historical index data, and obtain historical business data corresponding to the business indicator identifier to be monitored from the historical index data.

[0069] 2-1. Get historical index data.

[0070] 2-2. Obtain a set of candidate business indicator identifiers corresponding to the historical index data, where the set of candidate business indicator identifiers includes at least one candidate business indicator identifier, and the candidate business indicator identifier includes corresponding candidate historical business data.

[0071] 2-3. Determine a target candidate business indicator identifier corresponding to the business indicator identifier to be monitored from the candidate business indicator identifier set.

[0072] 2-4. Determine the candidate historical business data corresponding to the target candidate business indicator identifier as the historical business data corresponding to the business indicator identifier to be monitored.

[0073] 3. Determine abnormal index data based on the index data to be monitored and historical business data.

[0074] 3-1. Compare the index data to be monitored with the historical business data to see if they are the same.

[0075] 3-2. When the index data to be monitored is different from the historical business data, it is determined that the index data to be monitored is abnormal index data.

[0076] 4. Get the preset abnormal data threshold.

[0077] 5. When the abnormal index data exceeds the preset abnormal data threshold, go to step 7.

[0078] 6. When the abnormal index data does not exceed the preset abnormal data threshold, the abnormal index data will not be monitored.

[0079] 7. Monitor abnormal index data according to the target preset monitoring method.

[0080] 7-1. Obtain a set of candidate preset monitoring methods.

[0081] 7-2. Determine a target preset monitoring method from a set of candidate preset monitoring methods.

[0082] 7-3. Monitor the abnormal index data according to the preset monitoring mode of the target. It should be understood that although the various steps in the above flowchart are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless clearly stated in this document, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least part of the steps in the above flowchart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0083] In one embodiment, Figure 3 As shown, an index data monitoring device 300 is provided, comprising: a to-be-monitored index data acquisition module 302, a historical index data acquisition module 304, an abnormal index data determination module 306 and an abnormal index data monitoring module 308, wherein:

[0084] The to-be-monitored index data acquisition module 302 is used to acquire the to-be-monitored index data, where the to-be-monitored index data includes the to-be-monitored business indicator identifier.

[0085] The historical index data acquisition module 304 is used to acquire historical index data, and acquire historical business data corresponding to the business indicator identifier to be monitored from the historical index data.

[0086] The abnormal index data determination module 306 is used to determine the abnormal index data according to the index data to be monitored and the historical business data.

[0087] The abnormal index data monitoring module 308 is used to monitor the abnormal index data according to a target preset monitoring method.

[0088] In one embodiment, the historical index data acquisition module 304 is also used to acquire historical index data, acquire a set of candidate business indicator identifiers corresponding to the historical index data, the candidate business indicator identifier set includes at least one candidate business indicator identifier, the candidate business indicator identifier includes corresponding candidate historical business data, determine the target candidate business indicator identifier corresponding to the business indicator identifier to be monitored from the candidate business indicator identifier set, and determine the candidate historical business data corresponding to the target candidate business indicator identifier as the historical business data corresponding to the business indicator identifier to be monitored.

[0089] In one embodiment, the abnormal index data determination module 306 is further used to compare whether the index data to be monitored is the same as the historical business data, and when the index data to be monitored is different from the historical business data, determine that the index data to be monitored is abnormal index data.

[0090] In one embodiment, the index data monitoring device 300 is also used to obtain a preset abnormal data threshold. When the abnormal index data exceeds the preset abnormal data threshold, it enters the abnormal index data monitoring module 308 to monitor the abnormal index data according to the target preset monitoring method. When the abnormal index data does not exceed the preset abnormal data threshold, the abnormal index data is not monitored.

[0091] In one embodiment, the abnormal index data monitoring module 308 is further used to obtain a set of candidate preset monitoring methods, determine a target preset monitoring method from the set of candidate preset monitoring methods, and monitor the abnormal index data according to the target preset monitoring method.

[0092] In one embodiment, the to-be-monitored index data acquisition module 302 is further used to acquire preset empty index data, acquire business data corresponding to the to-be-monitored business indicator identifier, write the business data into the preset empty index data, and obtain the to-be-monitored index data.

[0093] For the specific definition of the index data monitoring device, please refer to the definition of the index data monitoring method above, which will not be repeated here. Each module in the above-mentioned index data monitoring device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0094] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store abnormal index data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an index data monitoring method is implemented.

[0095] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 5As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an index data monitoring method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0096] Those skilled in the art will understand that Figure 4 or Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0097] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented: obtaining index data to be monitored, the index data to be monitored including an identifier of a business indicator to be monitored, obtaining historical index data, obtaining historical business data corresponding to the identifier of the business indicator to be monitored from the historical index data, determining abnormal index data based on the index data to be monitored and the historical business data, and monitoring the abnormal index data according to a target preset monitoring method.

[0098] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining historical index data; obtaining a set of candidate business indicator identifiers corresponding to the historical index data, the candidate business indicator identifier set including at least one candidate business indicator identifier, the candidate business indicator identifier including corresponding candidate historical business data; determining a target candidate business indicator identifier corresponding to the business indicator identifier to be monitored from the candidate business indicator identifier set; and determining the candidate historical business data corresponding to the target candidate business indicator identifier as the historical business data corresponding to the business indicator identifier to be monitored.

[0099] In one embodiment, when the processor executes the computer program, the following steps are also implemented: comparing whether the index data to be monitored is the same as the historical business data; when the index data to be monitored is different from the historical business data, determining that the index data to be monitored is abnormal index data.

[0100] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining a preset abnormal data threshold; when the abnormal index data exceeds the preset abnormal data threshold, entering the step of monitoring the abnormal index data according to the target preset monitoring method; when the abnormal index data does not exceed the preset abnormal data threshold, not monitoring the abnormal index data.

[0101] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining a set of candidate preset monitoring methods; determining a target preset monitoring method from the set of candidate preset monitoring methods; and monitoring abnormal index data according to the target preset monitoring method.

[0102] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining preset empty index data; obtaining business data corresponding to the business indicator identifier to be monitored; writing the business data into the preset empty index data to obtain the index data to be monitored.

[0103] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: obtaining index data to be monitored, the index data to be monitored includes an identifier of a business indicator to be monitored; obtaining historical index data, obtaining historical business data corresponding to the identifier of the business indicator to be monitored from the historical index data; determining abnormal index data based on the index data to be monitored and the historical business data; and monitoring the abnormal index data according to a target preset monitoring method.

[0104] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining historical index data; obtaining a set of candidate business indicator identifiers corresponding to the historical index data, the candidate business indicator identifier set including at least one candidate business indicator identifier, the candidate business indicator identifier including corresponding candidate historical business data; determining a target candidate business indicator identifier corresponding to the business indicator identifier to be monitored from the candidate business indicator identifier set; and determining the candidate historical business data corresponding to the target candidate business indicator identifier as the historical business data corresponding to the business indicator identifier to be monitored.

[0105] In one embodiment, when the processor executes the computer program, the following steps are also implemented: comparing whether the index data to be monitored is the same as the historical business data; when the index data to be monitored is different from the historical business data, determining that the index data to be monitored is abnormal index data.

[0106] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining a preset abnormal data threshold; when the abnormal index data exceeds the preset abnormal data threshold, entering the step of monitoring the abnormal index data according to the target preset monitoring method; when the abnormal index data does not exceed the preset abnormal data threshold, not monitoring the abnormal index data.

[0107] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining a set of candidate preset monitoring methods; determining a target preset monitoring method from the set of candidate preset monitoring methods; and monitoring abnormal index data according to the target preset monitoring method.

[0108] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining preset empty index data; obtaining business data corresponding to the business indicator identifier to be monitored; writing the business data into the preset empty index data to obtain the index data to be monitored.

[0109] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0110] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0111] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for monitoring index data, characterized in that: The method comprises: Acquire the index data to be monitored, wherein the index data to be monitored includes a business indicator identifier to be monitored; the business indicator identifier to be monitored is used to identify the business to be monitored this time, and the index data to be monitored is obtained by the business data, business requirements or application scenarios or product requirements corresponding to the business indicator identifier to be monitored; Acquire historical index data, and acquire historical business data corresponding to the business indicator identifier to be monitored from the historical index data; Determine abnormal index data according to the index data to be monitored and the historical business data; Monitor the abnormal index data according to the target preset monitoring method; The determining of abnormal index data according to the index data to be monitored and the historical business data includes: Compare whether the field values ​​corresponding to the same fields of the to-be-monitored index data and the historical business data are the same; If the field values ​​corresponding to the same fields of the two are different, it is determined that the index data to be monitored is abnormal index data; The method further comprises: Obtaining a preset abnormal data threshold, where the preset abnormal data threshold is obtained based on business requirements or product requirements or actual application scenarios; When the abnormal index data exceeds the preset abnormal data threshold, entering the step of monitoring the abnormal index data according to a target preset monitoring mode; When the abnormal index data does not exceed the preset abnormal data threshold, the abnormal index data is not monitored; The acquiring of historical index data, acquiring historical business data corresponding to the business indicator identifier to be monitored from the historical index data, includes: Get historical index data; Acquire a set of candidate business indicator identifiers corresponding to the historical index data, wherein the set of candidate business indicator identifiers includes at least one candidate business indicator identifier, each of the candidate business indicator identifiers includes corresponding candidate historical business data, and the relationship between each candidate business indicator identifier and the corresponding candidate historical business data is determined in advance according to business requirements, actual application scenarios, or product requirements; Determine a target candidate business indicator identifier corresponding to the business indicator identifier to be monitored from the candidate business indicator identifier set; Determine the candidate historical business data corresponding to the target candidate business indicator identifier as the historical business data corresponding to the business indicator identifier to be monitored; The monitoring of the abnormal index data according to the target preset monitoring method includes: Obtain a candidate preset monitoring mode set, wherein the preset monitoring mode set includes SMS notification and email notification; Determining a target preset monitoring mode from the set of candidate preset monitoring modes; The abnormal index data is monitored according to the target preset monitoring method.

2. The method according to claim 1, characterized in that The steps of constructing the index data to be monitored include: Get the preset empty index data; Obtaining the business data corresponding to the business indicator identifier to be monitored; The business data is written into the preset empty index data to obtain the index data to be monitored.

3. An index data monitoring device, characterized in that: The device comprises: The module for acquiring index data to be monitored is used to acquire index data to be monitored, wherein the index data to be monitored includes a business indicator identifier to be monitored; the business indicator identifier to be monitored is used to identify the business to be monitored this time, and the index data to be monitored is obtained by the business data, business requirements or application scenarios or product requirements corresponding to the business indicator identifier to be monitored; A historical index data acquisition module, used to acquire historical index data, and to acquire historical business data corresponding to the business indicator identifier to be monitored from the historical index data; An abnormal index data determination module is used to determine abnormal index data according to the index data to be monitored and the historical business data; An abnormal index data monitoring module is used to monitor the abnormal index data according to a target preset monitoring method; The abnormal index data determination module is further used to compare whether the field values ​​corresponding to the same fields of the index data to be monitored and the historical business data are the same; If the field values ​​corresponding to the same fields of the two are different, it is determined that the index data to be monitored is abnormal index data; The historical index data acquisition module is further used to acquire historical index data; acquire a set of candidate business indicator identifiers corresponding to the historical index data, the set of candidate business indicator identifiers includes at least one candidate business indicator identifier, each of the candidate business indicator identifiers includes corresponding candidate historical business data, and the relationship between each candidate business indicator identifier and the corresponding candidate historical business data is determined in advance according to business requirements, actual application scenarios or product requirements; determine a target candidate business indicator identifier corresponding to the business indicator identifier to be monitored from the set of candidate business indicator identifiers; determine the candidate historical business data corresponding to the target candidate business indicator identifier as the historical business data corresponding to the business indicator identifier to be monitored; The abnormal index data monitoring module is also used to obtain a set of candidate preset monitoring methods, which includes SMS notification and email notification; determine a target preset monitoring method from the candidate preset monitoring method set; and monitor the abnormal index data according to the target preset monitoring method.

4. The device according to claim 3, characterized in that The historical index data acquisition module is further used to acquire historical index data, acquire a set of candidate business indicator identifiers corresponding to the historical index data, the set of candidate business indicator identifiers including at least one candidate business indicator identifier, the candidate business indicator identifier including corresponding candidate historical business data, determine a target candidate business indicator identifier corresponding to the business indicator identifier to be monitored from the set of candidate business indicator identifiers, and determine the candidate historical business data corresponding to the target candidate business indicator identifier as the historical business data corresponding to the business indicator identifier to be monitored; The abnormal index data determination module is also used to obtain a preset abnormal data threshold, and the preset abnormal data threshold is obtained by business requirements or product requirements or actual application scenarios; when the abnormal index data exceeds the preset abnormal data threshold, enter the step of monitoring the abnormal index data according to the target preset monitoring method; when the abnormal index data does not exceed the preset abnormal data threshold, the abnormal index data is not monitored.

5. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 2 are implemented.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 2 are implemented.

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