CN112699009A - Data detection method and device, server and storage medium - Google Patents
Data detection method and device, server and storage medium Download PDFInfo
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Abstract
The embodiment of the application provides a data detection method and device, a server and a storage medium, and relates to the technical field of data detection. The data detection method is applied to a server, the server is provided with at least one service to be processed, and the data detection method comprises the following steps: firstly, configuring a corresponding monitoring script according to the type of each service to be processed aiming at each service to be processed; secondly, the correctness of the service to be processed is detected through the monitoring script. By the method, the correctness of different types of business service data can be detected, and the problem of low reliability of data detection caused by the fact that most industrial internet enterprises in the prior art can only monitor the CPU, the memory, the disk and the like of the server and can not detect the correctness of a large amount of business service data is solved.
Description
Technical Field
The present application relates to the field of data detection technologies, and in particular, to a data detection method and apparatus, a server, and a storage medium.
Background
With the rapid development of industrial internet in recent years, each large industrial internet enterprise provides different business services in the form of a public cloud platform to connect thousands of internet-of-things devices, and the pressure of tens of millions of mass internet-of-things device data on a background server is huge. The inventor researches and discovers that in the prior art, most industrial internet enterprises can only monitor the CPU, the memory, the magnetic disk and the like of the server, and can not detect the correctness of a large amount of business service data, so that the problem of low reliability of data detection exists.
Disclosure of Invention
In view of the above, an object of the present application is to provide a data detection method and apparatus, a server, and a storage medium, so as to solve the problems in the prior art.
In order to achieve the above purpose, the embodiment of the present application adopts the following technical solutions:
in a first aspect, the present invention provides a data detection method applied to a server, where the server is provided with at least one to-be-processed service, and the data detection method includes:
configuring a corresponding monitoring script according to the type of each service to be processed aiming at each service to be processed;
and detecting the correctness of the service to be processed through the monitoring script.
In an optional embodiment, the server pre-stores detection frequencies respectively corresponding to various types of to-be-processed service, and the step of performing correctness detection on the to-be-processed service through the monitoring script includes:
searching a detection frequency corresponding to the type of the service to be processed aiming at each service to be processed;
and detecting the service to be processed by the monitoring script at regular time according to the searched detection frequency.
In an optional embodiment, the step of detecting the correctness of the to-be-processed service through the monitoring script includes:
judging whether the service data of the service to be processed is preset data;
if not, alarm information is sent out.
In an optional embodiment, the step of determining whether the service data of the service to be processed is preset data includes:
judging whether the login times of the active user of the to-be-processed business service are greater than a first preset time;
if not, alarm information is sent out.
In an optional implementation manner, the step of determining whether the service data of the service to be processed is preset data includes:
judging whether the login times of the inactive user of the business service to be processed are less than a second preset time;
if not, alarm information is sent out.
In an optional embodiment, the step of determining whether the service data of the service to be processed is preset data includes:
judging whether the type of the service data of the service to be processed is preset type data or not;
if not, alarm information is sent out.
In a second aspect, the present invention provides a data detection apparatus, applied to a server, where the server is provided with at least one to-be-processed service, and the data detection apparatus includes:
the script configuration module is used for configuring a corresponding monitoring script according to the type of each service to be processed aiming at each service to be processed;
and the detection module is used for detecting the correctness of the service to be processed through the monitoring script.
In an optional embodiment, the server pre-stores detection frequencies respectively corresponding to various types of to-be-processed service, and the detection module is specifically configured to:
searching a detection frequency corresponding to the type of the service to be processed aiming at each service to be processed;
and detecting the service to be processed by the monitoring script at regular time according to the searched detection frequency.
In a third aspect, the present invention provides a server, comprising a memory and a processor, wherein the processor is configured to execute an executable computer program stored in the memory to implement the data detection method according to any one of the foregoing embodiments.
In a fourth aspect, the present invention provides a storage medium having stored thereon a computer program which, when executed, implements the steps of the data detection method of any one of the preceding embodiments.
According to the data detection method and device, the server and the storage medium, the corresponding monitoring script is configured according to the type of the business service to be processed, correctness detection is carried out through the monitoring script, correctness detection of different types of business service data is achieved, and the problem that in the prior art, most industrial internet enterprises can only monitor a CPU, a memory, a disk and the like of the server, can not detect correctness of a large amount of business service data, and reliability of data detection is low is solved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a block diagram of a data detection system according to an embodiment of the present disclosure.
Fig. 2 is a schematic flow chart of a data detection method according to an embodiment of the present application.
Fig. 3 is another schematic flow chart of the data detection method according to the embodiment of the present application.
Fig. 4 is another schematic flow chart of the data detection method according to the embodiment of the present application.
Fig. 5 is another schematic flow chart of the data detection method according to the embodiment of the present application.
Fig. 6 is another schematic flow chart of a data detection method according to an embodiment of the present application.
Fig. 7 is another schematic flow chart of a data detection method according to an embodiment of the present application.
Fig. 8 is a block diagram of a data detection apparatus according to an embodiment of the present application.
Icon: 10-a data detection system; 100-a server; 200-industrial equipment; 800-a data detection device; 810-script configuration module; 820-detection module.
Detailed Description
In order to improve at least one of the above technical problems proposed by the present application, embodiments of the present application provide a data detection method and apparatus, a server, and a storage medium, and the following describes technical solutions of the present application through possible implementation manners.
The defects of the above solutions are the results of the inventor after practice and careful study, and therefore, the discovery process of the above problems and the solution proposed by the present application to the above problems should be the contribution of the inventor to the present application in the process of the present application.
For purposes of making the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions of the embodiments of the present application will be described in detail below with reference to the drawings in the embodiments of the present application, and it should be understood that the drawings in the present application are for illustrative and descriptive purposes only and are not used to limit the scope of the present application. Additionally, it should be understood that the schematic drawings are not necessarily drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of the present application. It should be understood that the operations of the flow diagrams may be performed out of order, and steps without logical context may be performed in reverse order or simultaneously. One skilled in the art, under the guidance of this application, may add one or more other operations to, or remove one or more operations from, the flowchart.
In addition, the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
In order to enable a person skilled in the art to make use of the present disclosure, the following embodiments are given. It will be apparent to those skilled in the art that the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the application. Applications of the system or method of the present application may include web pages, plug-ins for browsers, client terminals, customization systems, internal analysis systems, or artificial intelligence robots, among others, or any combination thereof.
It should be noted that in the embodiments of the present application, the term "comprising" is used to indicate the presence of the features stated hereinafter, but does not exclude the addition of further features.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Fig. 1 is a block diagram of a data detection system 10 provided in an embodiment of the present application, which provides a possible implementation manner of the data detection system 10, and referring to fig. 1, the data detection system 10 may include one or more of a server 100 and an industrial device 200, and the server 100 may include a processor for executing instruction operations.
The server 100 can be in communication connection with at least one industrial device 200 to obtain business data uploaded by the industrial device 200, and a business service can be set for each industrial device 200 to process the business data.
For the server 100, it should be noted that, in some embodiments, the server 100 may be a single server device or a server group. The set of servers may be centralized or distributed (e.g., server 100 may be a distributed system). In some embodiments, the server 100 may be local or remote to the industrial device 200. For example, the server 100 can access information and/or data stored in the industrial device 200 via a network. As another example, the server 100 can be directly connected to the industrial device 200 to access stored information and/or data. In some embodiments, the server 100 may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a resilient cloud, a community cloud (community cloud), a distributed cloud, a cross-cloud (inter-cloud), a multi-cloud (multi-cloud), and the like, or any combination thereof. In some embodiments, the server 100 can be implemented on an industrial device 200.
In some embodiments, the server 100 may include a processor. The processor can process information and/or data transmitted by the industrial device 200 to perform one or more of the functions described herein.
The network may be used for the exchange of information and/or data. In some embodiments, one or more components in the data detection system 10 (e.g., the server 100 and the industrial device 200) may send information and/or data to other components. For example, the server 100 can obtain data from the industrial device 200 via a network. In some embodiments, the network may be any type of wired or wireless network, or combination thereof.
In some embodiments, the network may include one or more network access points. For example, the network may include wired or wireless network access points, such as base stations and/or network switching nodes, through which one or more components of the data detection system 10 may connect to the network to exchange data and/or information.
A database may be included in server 100 and may store data and/or instructions. In some embodiments, the database can store data obtained from the industrial device 200. In some embodiments, a database may store data and/or instructions for the exemplary methods described herein. In some embodiments, the database may include mass storage, removable storage, volatile Read-write Memory, or Read-Only Memory (ROM), among others, or any combination thereof.
In some embodiments, the database may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, cross-cloud, multi-cloud, elastic cloud, or the like, or any combination thereof.
In some embodiments, a database may be connected to a network to communicate with one or more components in the data detection system 10 (e.g., the server 100 and the industrial device 200). One or more components in the data detection system 10 may access data or instructions stored in a database via a network. In some embodiments, the database may be directly connected to one or more components in the data detection system 10 (e.g., the server 100 and the industrial device 200). Alternatively, in some embodiments, the database may also be part of the server 100. In some embodiments, one or more components in the data detection system 10 (e.g., the server 100 and the industrial device 200) may have access to a database.
Fig. 2 shows one of flowcharts of a data detection method provided in an embodiment of the present application, where the method is applicable to the server 100 shown in fig. 1 and is executed by the server 100 in fig. 1. It should be understood that, in other embodiments, the order of some steps in the data detection method of this embodiment may be interchanged according to actual needs, or some steps may be omitted or deleted. The flow of the data detection method shown in fig. 2 is described in detail below.
Step S210, configuring a corresponding monitoring script according to the type of each to-be-processed service.
And step S220, carrying out correctness detection on the service to be processed through the monitoring script.
The method configures the corresponding monitoring script according to the type of the service to be processed, and detects the correctness of the monitoring script, thereby realizing the detection of the correctness of different types of service data, and solving the problem that most industrial internet enterprises in the prior art can only monitor the CPU, the memory, the disk and the like of the server 100 and can not detect the correctness of a large amount of service data, which results in low reliability of data detection.
It should be noted that the server 100 may be provided with a service data detection monitoring system built based on Jenkins CICD, and mainly includes four parts, namely, a service, a Jenkins CICD service, a monitoring script execution service, and an alarm service.
The business services refer to all backend services in the industrial internet, and the correctness of the business data of the business services needs to be monitored so as to prevent data errors. The functions of Jenkins CICD service are mainly loading monitoring scripts, alarm configuration information and scheduling frequency setting of business service. The function of executing the monitoring script service is that after the Jenkins CICD service triggers the monitoring of a certain service, the monitoring script is executed according to the configured information to the monitoring script configured for the service. The alarm service function is that when the monitoring script is abnormal, the problem of the service data of the service is shown, and the alarm service is called to inform the user.
For step S210, it should be noted that the specific manner of configuring the monitoring script is not limited, and may be set according to the actual application requirement. For example, in an alternative example, a signal that an operation and maintenance person logs in jenkins service and configures according to the type of the service may be obtained to obtain a monitoring script and alarm information corresponding to the service.
For another example, in another alternative example, the server 100 may pre-store monitoring scripts and alarm information corresponding to various types of to-be-processed service, and for each to-be-processed service, may search for the monitoring script and the alarm information corresponding to the type of the to-be-processed service.
The alarm information may include alarm content, alarm form, alarm content receiver, etc., and may be specifically set according to the type of the service. For example, when the service is a statistical service, the alarm content in the alarm information of the statistical service may be "statistical quantity error", the alarm form may be notified in a manner of short message/mail/mobile phone APP, and the alarm content recipient may be an operation and maintenance person.
For step S220, it should be noted that the specific manner of performing the detection is not limited, and the detection may be set according to the actual application requirement. For example, in an alternative example, the server 100 is pre-stored with detection frequencies respectively corresponding to various types of to-be-processed business services, and the step S220 may include a step of performing detection according to the detection frequencies. Therefore, on the basis of fig. 2, fig. 3 is a schematic flowchart of another data detection method provided in the embodiment of the present application, and referring to fig. 3, step S220 may include:
step S221, for each service to be processed, finding a detection frequency corresponding to the type of the service to be processed.
Step S222, detecting the to-be-processed service through the monitoring script at regular time according to the detected frequency obtained by searching.
In detail, the types of the service to be processed are different, and the detection frequency is also different, for example, when the service is a statistical service, the corresponding detection frequency may be once a day, that is, whether the service data of the statistical service is correct may be detected once a day.
The server 100 may pre-store detection frequencies corresponding to various types of to-be-processed service, and directly search for the corresponding detection frequency according to the type of the to-be-processed service. It should be noted that, in another alternative example, a signal that an operation and maintenance person logs in jenkins service and configures according to the type of the service may be obtained, so as to obtain a detection frequency corresponding to the service.
For another example, in another alternative example, the server 100 stores preset data, and the step S220 may include a step of comparing the service data of the service to be processed with the preset data. Therefore, on the basis of fig. 2, fig. 4 is a schematic flowchart of another data detection method provided in the embodiment of the present application, and referring to fig. 4, step S220 may include:
step S223, determining whether the service data of the service to be processed is preset data.
In the embodiment of the application, when the service data of the service to be processed is preset data, the service data of the service to be processed is judged to be normal; when the service data of the to-be-processed service is not the preset data, it is determined that the service data of the to-be-processed service is abnormal, and step S224 is executed.
Step S224, sending out alarm information.
It should be noted that, the monitoring script is executed to obtain a result returned by the service, and the returned result is processed, and if the monitoring script is successfully executed, no alarm is triggered, and the jenkins cic service is waited for next scheduling execution.
For step S223, it should be noted that the specific manner of determining whether the data is the preset data is not limited, and the data may be set according to the actual application requirement. For example, in an alternative example, the service data includes the login number of the active user, the preset data includes a first preset number, and step S223 may include the step of comparing the login number of the active user with the first preset number. Therefore, on the basis of fig. 4, fig. 5 is a schematic flowchart of another data detection method provided in the embodiment of the present application, and referring to fig. 5, step S223 may include:
step S2231, determining whether the login times of the active user of the pending service is greater than a first preset time.
In the embodiment of the application, when the login times of the active user of the to-be-processed business service are greater than a first preset time, the login times of the active user of the to-be-processed business service are judged to be normal; when the login times of the active user of the pending service is not greater than the first preset time, it is determined that the login times of the active user of the pending service is abnormal, and step S2232 is performed.
Step S2232, an alarm message is issued.
In detail, when the service data includes the login times of the active user, it is required to detect whether the login times are greater than a first preset time, and when the login times are greater than the first preset time, it is proved that the login times of the active user are normal.
Optionally, the specific value of the first preset number is not limited, and may be set according to the actual application requirement. For example, in an alternative example, the first preset number of times may be 10 times.
For another example, in another alternative example, the service data includes the login number of the inactive user, the preset data includes a second preset number, and step S223 may include the step of comparing the login number of the inactive user with the second preset number. Therefore, on the basis of fig. 4, fig. 6 is a schematic flowchart of another data detection method provided in the embodiment of the present application, and referring to fig. 6, step S223 may include:
step S2233, determining whether the login times of the inactive user of the to-be-processed service is less than a second preset time;
in the embodiment of the application, when the login times of the inactive user of the to-be-processed service are less than a second preset time, it is determined that the login times of the inactive user of the to-be-processed service are normal; when the login number of the inactive user of the to-be-processed service is not less than the second preset number, it is determined that the login number of the inactive user of the to-be-processed service is abnormal, and step S2234 is performed.
Step S2234, an alarm message is sent.
In detail, when the service data includes the login times of the inactive user, it is required to detect whether the login times is less than a second preset time, and when the login times is less than the second preset time, it is proved that the login times of the inactive user is normal.
Optionally, the specific value of the second preset number is not limited, and may be set according to the actual application requirement. For example, in an alternative example, the second preset number may be 3.
For another example, in another alternative example, the service data includes a type of the service data, the preset data includes preset type data, and step S223 may include a step of comparing the type of the service data with the preset type data. Therefore, on the basis of fig. 4, fig. 7 is a schematic flowchart of another data detection method provided in the embodiment of the present application, and referring to fig. 7, step S223 may include:
step S2235, determining whether the type of the to-be-processed service data is preset type data.
In the embodiment of the application, when the type of the service data of the service to be processed is the preset type data, judging that the type of the service data of the service to be processed is normal; when the type of the to-be-processed service data is not the preset type data, it is determined that the type of the to-be-processed service data is abnormal, and step S2236 is performed.
Step S2236, an alarm message is issued.
In detail, when the service data includes the type of the service data, it is required to detect whether the type of the service data is the preset type data, and when the type of the service data is the preset type data, it is proved that the type of the service data of the service to be processed is normal.
Optionally, the specific type of the preset type data is not limited, and may be set according to the actual application requirement. For example, in an alternative example, the preset type data may be statistical data, that is, it needs to detect whether the type of the service traffic data of the service to be processed is statistical data.
For step S224, it should be noted that when the return result is abnormal, the alarm service is called to perform an alarm, and then the jenkins cic service is waited to perform next scheduling execution.
By the method, the business data detection monitoring system built based on Jenkins CICD can accurately detect the correctness of the business data of a plurality of back-end business services in real time and give abnormal alarm notification, saves more resources for enterprises in a software design mode, is convenient to adapt to the business scene of tens of millions of equipment, and ensures the correctness of the equipment data.
With reference to fig. 8, an embodiment of the present application further provides a data detection apparatus 800, where functions implemented by the data detection apparatus 800 correspond to steps executed by the foregoing method. The data detection device 800 may be understood as a processor of the server 100, or may be understood as a component that is independent of the server 100 or the processor and that implements the functions of the present application under the control of the server 100. Data detection apparatus 800 may include script configuration module 810 and detection module 820, among other things.
The script configuration module 810 is configured to configure, for each to-be-processed service, a corresponding monitoring script according to the type of the to-be-processed service. In the embodiment of the present application, the script configuration module 810 may be configured to perform step S210 shown in fig. 2, and reference may be made to the foregoing description of step S210 regarding relevant contents of the script configuration module 810.
And the detecting module 820 is configured to perform correctness detection on the to-be-processed service through the monitoring script. In the embodiment of the present application, the detection module 820 may be configured to perform step S220 shown in fig. 2, and reference may be made to the foregoing description of step S220 for relevant contents of the detection module 820.
In addition, an embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program performs the steps of the data detection method.
The computer program product of the data detection method provided in the embodiment of the present application includes a computer-readable storage medium storing a program code, where instructions included in the program code may be used to execute steps of the data detection method in the above method embodiment, which may be referred to specifically in the above method embodiment, and details are not described here again.
To sum up, the data detection method and apparatus, the server and the storage medium provided in the embodiments of the present application configure the corresponding monitoring script according to the type of the service to be processed, and perform correctness detection through the monitoring script, thereby achieving correctness detection of different types of service data, and solving the problem in the prior art that most industrial internet enterprises can only monitor CPUs, memories, disks, and the like of the servers, cannot detect correctness of a large amount of service data, and thus reliability of data detection is low.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server 100, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A data detection method is applied to a server, wherein the server is provided with at least one service to be processed, and the data detection method comprises the following steps:
configuring a corresponding monitoring script according to the type of each service to be processed aiming at each service to be processed;
and detecting the correctness of the service to be processed through the monitoring script.
2. The data detection method according to claim 1, wherein the server pre-stores detection frequencies respectively corresponding to various types of to-be-processed service, and the step of performing correctness detection on the to-be-processed service through the monitoring script comprises:
searching a detection frequency corresponding to the type of the service to be processed aiming at each service to be processed;
and detecting the service to be processed by the monitoring script at regular time according to the searched detection frequency.
3. The data detection method of claim 1, wherein the step of performing correctness detection on the to-be-processed service through the monitoring script comprises:
judging whether the service data of the service to be processed is preset data;
if not, alarm information is sent out.
4. The data detection method according to claim 3, wherein the service data includes login times of active users, the preset data includes a first preset number of times, and the step of determining whether the service data of the service to be processed is preset data includes:
judging whether the login times of the active user of the to-be-processed business service are greater than a first preset time;
if not, alarm information is sent out.
5. The data detection method of claim 3, wherein the service data includes login times of an inactive user, the preset data includes a second preset number of times, and the step of determining whether the service data of the service to be processed is the preset data includes:
judging whether the login times of the inactive user of the business service to be processed are less than a second preset time;
if not, alarm information is sent out.
6. The data detection method according to claim 3, wherein the service data includes a type of service data, the preset data includes preset type data, and the step of determining whether the service data of the service to be processed is the preset data includes:
judging whether the type of the service data of the service to be processed is preset type data or not;
if not, alarm information is sent out.
7. A data detection device is applied to a server, wherein the server is provided with at least one service to be processed, and the data detection device comprises:
the script configuration module is used for configuring a corresponding monitoring script according to the type of each service to be processed aiming at each service to be processed;
and the detection module is used for detecting the correctness of the service to be processed through the monitoring script.
8. The data detection apparatus according to claim 7, wherein the server pre-stores detection frequencies respectively corresponding to various types of to-be-processed service services, and the detection module is specifically configured to:
searching a detection frequency corresponding to the type of the service to be processed aiming at each service to be processed;
and detecting the service to be processed by the monitoring script at regular time according to the searched detection frequency.
9. A server, comprising a memory and a processor, the processor being configured to execute an executable computer program stored in the memory to implement the data detection method of any one of claims 1 to 6.
10. A storage medium having stored thereon a computer program which, when executed, carries out the steps of the data detection method of any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110036647.XA CN112699009A (en) | 2021-01-12 | 2021-01-12 | Data detection method and device, server and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202110036647.XA CN112699009A (en) | 2021-01-12 | 2021-01-12 | Data detection method and device, server and storage medium |
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