CN113157528A - Operation change monitoring method and device based on big data service cloud - Google Patents
Operation change monitoring method and device based on big data service cloud Download PDFInfo
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- CN113157528A CN113157528A CN202110458550.8A CN202110458550A CN113157528A CN 113157528 A CN113157528 A CN 113157528A CN 202110458550 A CN202110458550 A CN 202110458550A CN 113157528 A CN113157528 A CN 113157528A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/302—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a software system
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
- G06F11/14—Error detection or correction of the data by redundancy in operation
- G06F11/1402—Saving, restoring, recovering or retrying
- G06F11/1446—Point-in-time backing up or restoration of persistent data
- G06F11/1448—Management of the data involved in backup or backup restore
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3051—Monitoring arrangements for monitoring the configuration of the computing system or of the computing system component, e.g. monitoring the presence of processing resources, peripherals, I/O links, software programs
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/60—Software deployment
- G06F8/65—Updates
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/445—Program loading or initiating
- G06F9/44505—Configuring for program initiating, e.g. using registry, configuration files
Abstract
The invention provides a big data service cloud-based operation change monitoring method and device, which can be applied to the technical field of big data, and the method comprises the following steps: acquiring a job file of an application program in real time; comparing the operation file with a pre-stored operation backup file to obtain an operation state mark; and acquiring the execution completion time of the job, and determining whether the updating of the job is successful according to the sequence of the execution completion time and the completion time of the job state mark. The application overcomes the defect that a big data service cloud program change monitoring device is lacked in the prior art, the technical barrier that a big data service cloud access application lacks a unified monitoring management function is broken through, the fact that big data service cloud application testers can flexibly and easily learn respective application program change conditions and actual coverage verification conditions through a certain graphical interface is achieved, and a barrier protection which is unified to close is opened up for acceptance testing of the cloud access application.
Description
Technical Field
The application belongs to the technical field of big data processing, and particularly relates to a program change monitoring method and device based on a big data service cloud.
Background
The big data service cloud provides basic services such as data access, storage, calculation, safety management, resource management and the like, so that each access application can complete rapid development and operation of business functions. Along with the continuous improvement of the construction of the enterprise big data service cloud system, the technical system is increasingly huge, the carried service functions are increasingly rich, and the magnitude of the operation program based on the big data service cloud is increasingly expanded.
In acceptance testing work of related big data service cloud access applications, how to accurately judge the modification content of an application program from the perspective of actual change of the application program gradually becomes one of the focuses of big data service cloud testers. How to perform program change reminding, program coverage verification notification and the like in a big data platform for the application program change situation on the cloud is not a feasible method in the industry at present.
Disclosure of Invention
The application provides a program change monitoring method and device based on a big data service cloud, and aims to at least solve the problems that program change reminding and program coverage verification notification cannot be timely performed when an application program on the big data service cloud changes.
According to one aspect of the application, a job change monitoring method based on a big data service cloud is provided, and comprises the following steps:
acquiring a job file of an application program in real time;
comparing the operation file with a pre-stored operation backup file to obtain an operation state mark; the job backup file includes: job configuration backup files and script backup files;
and acquiring the execution completion time of the job, and determining whether the updating of the job is successful according to the sequence of the execution completion time and the completion time of the job state mark.
In an embodiment, the big data service cloud-based job change monitoring method further includes:
and regularly backing up the job script file and the job configuration file of the application program in the big data service cloud client server to generate a job backup file.
In an embodiment, when the job file is a script file, comparing the job file with a pre-stored job backup file to obtain a job status flag includes:
comparing the script file with the script backup file;
marking the operation states with inconsistent comparison results; and marking the operation state as modified, added or deleted according to the comparison result.
In an embodiment, when the job file is the job configuration file, comparing the job file with a pre-stored job backup file to obtain a job status flag includes:
comparing the job configuration file with the job configuration backup file in a table comparison mode;
and analyzing the state mark of the operation according to the application name, the operation group name and the operation dimension according to the comparison result.
In an embodiment, determining whether the update of the job is successful according to the sequence of the execution completion time and the completion time of the job status flag includes:
if the execution completion time is later than the completion time of the job status flag, the job update override is successful;
if the execution completion time is earlier than the completion time of the job status flag, the job update is not covered.
According to another aspect of the present application, there is also provided a job change monitoring apparatus based on a big data service cloud, including:
a job file acquisition unit for acquiring a job file of an application program in real time;
the comparison unit is used for comparing the operation file with a pre-stored operation backup file to obtain an operation state mark; the job backup file includes: job configuration backup files and script backup files;
and the time judging unit is used for acquiring the execution completion time of the job and determining whether the updating of the job is successful according to the sequence of the execution completion time and the completion time of the job state mark.
In one embodiment, the big data service cloud-based job change monitoring apparatus further includes:
and the backup file generation unit is used for regularly backing up the job script file and the job configuration file of the application program in the big data service cloud client server to generate a job backup file.
In one embodiment, when the job file is a script file, the comparing unit includes:
the script comparison module is used for comparing the script file with the script backup file;
the state marking module is used for marking the operation states with inconsistent comparison results; and marking the operation state as modified, added or deleted according to the comparison result.
In one embodiment, when the job file is a job configuration file, the comparing unit includes:
the configuration comparison module is used for comparing the job configuration file with the job configuration backup file in a table comparison mode;
and the state updating module is used for analyzing the state mark of the operation according to the application name, the operation group name and the operation dimension according to the comparison result.
In one embodiment, the time determination unit includes:
the coverage success judging module is used for successfully updating the coverage of the operation if the execution completion time is later than the completion time of the operation state mark;
and the coverage failure judging module is used for updating the job without coverage if the execution completion time is earlier than the completion time of the job status mark.
The application overcomes the defect that a big data service cloud program change monitoring device is lacked in the prior art, and through providing the device with automatic monitoring and visual display, the technical barrier that a big data service cloud access application lacks a unified monitoring management function is broken through, the situation that a big data service cloud application tester can directly and flexibly learn the change situation of each application program through a certain graphical interface, the transformation point and the actual coverage verification situation are conveniently and easily obtained, and barrier protection of unified closing points is opened up for acceptance test of the access application on the cloud.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of an operation change monitoring method based on a big data service cloud according to the present application.
FIG. 2 is a flowchart illustrating the process of marking job status when the job file is a job script file according to an embodiment of the present application.
Fig. 3 is a flowchart illustrating the operation status flag when the job file is the job configuration file according to the embodiment of the present application.
Fig. 4 is a flowchart of coverage determination in the embodiment of the present application.
FIG. 5 is an embodiment of the present application.
Fig. 6 is a block diagram of a job change monitoring apparatus based on a big data service cloud according to the present application.
Fig. 7 is a block diagram of a comparison unit in the embodiment of the present application.
Fig. 8 is a block diagram of another comparing unit in the embodiment of the present application.
Fig. 9 is a block diagram of a time determination unit in the embodiment of the present application.
Fig. 10 is a specific implementation of an electronic device in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the operation change monitoring method and apparatus based on the big data service cloud disclosed in the present application may be applied to the big data technology field, and may also be applied to other fields except the big data technology field.
Along with the continuous perfection of the construction of the enterprise big data service cloud system, the technical system is increasingly huge, the carried service functions are increasingly rich, and the magnitude of the operation program based on the big data service cloud is increasingly expanded. Based on the problem that operation and maintenance personnel cannot timely know a program change notification and a program coverage verification notification when a job operation program in a big data service cloud is modified, the application provides a job change monitoring method based on the big data service cloud, as shown in fig. 1, and the method comprises the following steps:
s101: and acquiring the job file of the application program in real time.
S102: and comparing the operation file with a pre-stored operation backup file to obtain an operation state mark. The job backup file includes: job configuration backup files and script backup files;
s103: and acquiring the execution completion time of the job, and determining whether the updating of the job is successful according to the sequence of the execution completion time and the completion time of the job state mark.
The method comprises the steps of backing up configuration files and operation scripts corresponding to application programs on a big data service cloud regularly, setting a monitoring program on a node of a big data service cloud client, when a program updating process is detected, scanning all application configurations and scripts, comparing the application configurations and the scripts with the backup files, combing and summarizing generated change information, and then butting the information to a foreground page for visual display. And finally, detecting the operation execution history information recorded in the big data service cloud oracle database, analyzing the application program, and then obtaining the operation coverage condition and the operation passing condition.
In an embodiment, the big data service cloud-based job change monitoring method further includes:
and regularly backing up the job script file and the job configuration file of the application program in the big data service cloud client server to generate a job backup file.
In a specific embodiment, a backup program is developed, files for storing job scripts and application configuration files in pgm paths of all the platform applications on the big data service cloud client server are backed up at regular time per hour, and the latest backup file is used as a change comparison basic version. The backup of the script file of the job is used for detecting whether the script is modified, the configuration file is the configuration information of all jobs, wherein the configuration information comprises the frequency and the dependency relationship of the job and is used for detecting the configuration of the job) whether the script is modified, and the operation group and the operation are used as dimensions to detect whether the operation is newly added or deleted. And taking the program before each application transformation as a comparison basis, and carrying out detection comparison at regular time. The operation script is classified and backed up according to three dimensions of application name, program type and operation group.
In an embodiment, when the job file is a script file, the comparing the job file with a pre-stored job backup file to obtain a job status flag, as shown in fig. 2, includes:
s201: and comparing the script file with the script backup file.
S202: marking the operation states with inconsistent comparison results; and marking the operation state as modified, added or deleted according to the comparison result.
In a specific embodiment, a detection program is arranged on a big data service cloud client server and used for detecting an application program and a configuration file updating process in real time. When the script updating process is detected, the synchronous operation of the script file is performed, and at the moment, a detection comparison program is executed, the job script information of all the applications is detected, and the comparison analysis is performed with the previous backup file. Each homonym hql file is text-compared by application, job group, job dimension. If the same-name files have difference in comparison, outputting the text content with specific difference, and marking the operation state as modified; if the job file name only exists in the existing application directory but not in the backup directory, marking the job state as a newly added job; if the job filename exists only under the backup directory and not under the existing application directory, the job status is marked as a delete job. The adding and deleting modification conditions of all the operations are counted to obtain a specific result through the three detection methods.
In an embodiment, when the job file is the job configuration file, the comparing the job file with the pre-stored job backup file to obtain the job status flag, as shown in fig. 3, includes:
s301: and comparing the job configuration file with the job configuration backup file in a table comparison mode.
S302: and analyzing the state mark of the operation according to the application name, the operation group name and the operation dimension according to the comparison result.
In a specific embodiment, when a configuration updating process is detected, it is indicated that an application uploads a latest configuration file, at this time, a configuration comparison detection program is executed, job configuration information files of all applications are detected in a table comparison mode, comparison analysis is performed on the job configuration information files and previous backup files, configuration modification of the job is analyzed according to the application, job group and job dimension, and the situations of addition and deletion are newly increased; and summarizing and counting the two detection results and writing the two detection results into a table file through a written Python program, namely summarizing the total detection results.
In an embodiment, determining whether the update of the job is successful according to the sequence of the execution completion time and the completion time of the job status flag, as shown in fig. 4, includes:
s401: if the execution completion time is later than the completion time of the job status flag, the job update override is successful.
S402: if the execution completion time is earlier than the completion time of the job status flag, the job update is not covered.
The oracle knowledge base of the big data service cloud records the job execution conditions of all applications accessed into the big data service cloud, so that all the detected changed job states are set as the initialization states, and the history execution information corresponding to the jobs in the job execution history table can be inquired by connecting the oracle knowledge base of the big data service cloud at regular time. And after each detection task is successfully executed, the summarized table file is updated, and at the moment, according to the application name, the job group name and the job name in the table as query conditions, the big data service cloud oracle knowledge base is logged in for sql query, and the execution records of the job modified by the job program and the job configuration information are queried. If the execution completion time of the job is later than the detection time stamp in the query result, the job is executed successfully after being modified, namely the coverage is successful. Setting the operation covering condition as covered; if the execution completion time of the job is earlier than the detection timestamp in the query result, it indicates that the job has not been executed after modification, i.e. the test is not covered to the job, and at this time, the job coverage condition is updated to be uncovered. In this way, the coverage condition of each newly added and modified program of each application accessing the big data service cloud is counted.
In one embodiment, as shown in FIG. 5, the configuration-modified job information is detected by the detection program when it is detected that configuration modification occurs at 1:13, 6/15/2020. Wherein the application name is F-CBMS, and the operation group name is: F-CBMS _000012, job name: CBMS _ CW _ TRC _ STATIC _ INF _ 030. When a configuration modification is detected for a job, the time is updated in the timestamp field to the detection time. After detection is finished, querying the historical execution condition of the corresponding operation by connecting a big data service cloud oracle knowledge base, if the latest execution time in the historical record is earlier than 6/15/6/2020, indicating that the current operation does not finish the coverage test, marking the coverage rate as uncovered; if the latest execution time in the history record is 1:13 later than 6/15/2020, indicating that the current job has completed the coverage test, the coverage rate is updated to covered. In addition, visual display is carried out on the foreground of the device, the table files of all the counted information are loaded into an oracle database by using an sqlloader, and the information in the database is read in real time by developing a foreground page. And meanwhile, a packaged automatic mail sending device is deployed, and when newly added operation change is detected, the modification information is automatically sent to an application responsible person corresponding to the operation through a mail, so that the purpose of timely notification is achieved.
Based on the same inventive concept, the embodiment of the present application further provides a job change monitoring apparatus based on a big data service cloud, which can be used to implement the method described in the above embodiments, as described in the following embodiments. Because the principle of solving the problems of the operation change monitoring device based on the big data service cloud is similar to the operation change monitoring method based on the big data service cloud, the implementation of the operation change monitoring device based on the big data service cloud can refer to the implementation of the operation change monitoring method based on the big data service cloud, and repeated parts are not repeated. As used hereinafter, the term "unit" or "module" may be a combination of software and/or hardware that implements a predetermined function. While the system described in the embodiments below is preferably implemented in software, implementations in hardware, or a combination of software and hardware are also possible and contemplated.
According to another aspect of the present application, there is also provided a big data service cloud-based job change monitoring apparatus, as shown in fig. 6, including:
a job file acquisition unit 601 configured to acquire a job file of an application in real time;
a comparing unit 602, configured to compare the job file with a pre-stored job backup file to obtain a job status flag; the job backup file includes: job configuration backup files and script backup files;
the time determining unit 603 is configured to obtain the execution completion time of the job, and determine whether the update of the job is successful according to the sequence of the execution completion time and the completion time of the job status flag.
In one embodiment, the big data service cloud-based job change monitoring apparatus further includes:
and the backup file generation unit is used for regularly backing up the job script file and the job configuration file of the application program in the big data service cloud client server to generate a job backup file.
In an embodiment, when the job file is a script file, as shown in fig. 7, the comparing unit 602 includes:
a script comparison module 701, configured to compare the script file with the script backup file;
a status marking module 702, configured to mark the job status with inconsistent comparison result; and marking the operation state as modified, added or deleted according to the comparison result.
In one embodiment, when the job file is a job configuration file, as shown in fig. 8, the comparing unit 602 includes:
a configuration comparison module 801, configured to compare the job configuration file with the job configuration backup file in a table comparison manner;
and a state updating module 802, configured to parse the state flag of the job according to the application name, the job group name, and the job dimension according to the comparison result.
In one embodiment, as shown in fig. 9, the time determination unit 603 includes:
a coverage success judging module 901, configured to, if the execution completion time is later than the completion time of the job status flag, successfully update the coverage of the job;
an override failure determination module 902 is configured to, if the execution completion time is earlier than the completion time of the job status flag, then the job update is not overridden.
An embodiment of the present application further provides a specific implementation manner of an electronic device capable of implementing all steps in the method in the foregoing embodiment, and referring to fig. 10, the electronic device specifically includes the following contents:
a processor (processor)1001, a memory 1002, a communication Interface (Communications Interface)1003, a bus 1004, and a nonvolatile memory 1005;
the processor 1001, the memory 1002, and the communication interface 1003 complete mutual communication through the bus 1004;
the processor 1001 is configured to call the computer programs in the memory 1002 and the nonvolatile memory 1005, and when the processor executes the computer programs, the processor implements all the steps in the method in the foregoing embodiments, for example, when the processor executes the computer programs, the processor implements the following steps:
s101: and acquiring the job file of the application program in real time.
S102: and comparing the operation file with a pre-stored operation backup file to obtain an operation state mark.
S103: and acquiring the execution completion time of the job, and determining whether the updating of the job is successful according to the sequence of the execution completion time and the completion time of the job state mark.
Embodiments of the present application also provide a computer-readable storage medium capable of implementing all the steps of the method in the above embodiments, where the computer-readable storage medium stores thereon a computer program, and the computer program when executed by a processor implements all the steps of the method in the above embodiments, for example, the processor implements the following steps when executing the computer program:
s101: and acquiring the job file of the application program in real time.
S102: and comparing the operation file with a pre-stored operation backup file to obtain an operation state mark.
S103: and acquiring the execution completion time of the job, and determining whether the updating of the job is successful according to the sequence of the execution completion time and the completion time of the job state mark.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the hardware + program class embodiment, since it is substantially similar to the method embodiment, the description is simple, and the relevant points can be referred to the partial description of the method embodiment. Although embodiments of the present description provide method steps as described in embodiments or flowcharts, more or fewer steps may be included based on conventional or non-inventive means. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an actual apparatus or end product executes, it may execute sequentially or in parallel (e.g., parallel processors or multi-threaded environments, or even distributed data processing environments) according to the method shown in the embodiment or the figures. 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, the presence of additional identical or equivalent elements in a process, method, article, or apparatus that comprises the recited elements is not excluded. For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, in implementing the embodiments of the present description, the functions of each module may be implemented in one or more software and/or hardware, or a module implementing the same function may be implemented by a combination of multiple sub-modules or sub-units, and the like. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form. The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein. The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment. In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of an embodiment of the specification. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction. The above description is only an example of the embodiments of the present disclosure, and is not intended to limit the embodiments of the present disclosure. Various modifications and variations to the embodiments described herein will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present specification should be included in the scope of the claims of the embodiments of the present specification.
Claims (13)
1. A job change monitoring method based on big data service cloud is characterized by comprising the following steps:
acquiring a job file of an application program in real time;
comparing the operation file with a pre-stored operation backup file to obtain an operation state mark; the job backup file includes: job configuration backup files and script backup files;
and acquiring the execution completion time of the operation, and determining whether the updating of the operation is successful according to the sequence of the execution completion time and the completion time of the operation state mark.
2. The big data service cloud-based job change monitoring method according to claim 1, further comprising:
and backing up the job script file and the job configuration file of the application program in the big data service cloud client server at regular time to generate the job backup file.
3. The big data service cloud-based job change monitoring method according to claim 2, wherein when the job file is a script file, the comparing the job file with a pre-stored job backup file to obtain a job status flag comprises:
comparing the script file with the script backup file;
marking the operation states with inconsistent comparison results; and marking the operation state as modified, added or deleted according to the comparison result.
4. The big data service cloud-based job change monitoring method according to claim 2, wherein when the job file is a job configuration file, the comparing the job file with a pre-stored job backup file to obtain a job status flag comprises:
comparing the job configuration file with the job configuration backup file in a table comparison mode;
and analyzing the state mark of the operation according to the application name, the operation group name and the operation dimension according to the comparison result.
5. The big data service cloud-based job change monitoring method according to claim 3 or 4, wherein the determining whether the update of the job is successful according to the sequence of the execution completion time and the completion time of the job status flag includes:
if the execution completion time is later than the completion time of the job status flag, the job update override is successful;
if the execution completion time is earlier than the completion time of the job status flag, the job update is not covered.
6. The big data service cloud-based job change monitoring method according to claim 1, wherein the comparing the job file with a pre-stored job backup file to obtain a job status flag comprises:
comparing the operation file with the operation backup file to obtain a comparison result;
and screening the job files with inconsistent comparison results from the comparison results, and marking to obtain job state marks.
7. The big data service cloud-based job change monitoring method according to claim 6, wherein the step of screening the job files with inconsistent comparison results from the comparison results and marking the job files to obtain job status marks comprises:
if the content is newly added, the operation state is marked as new addition;
if the comparison result shows that the content is missing, the operation state is marked as deleted;
and if the comparison result is that the content has the replacement, marking the job status as modified.
8. A job change monitoring device based on big data service cloud, comprising:
a job file acquisition unit for acquiring a job file of an application program in real time;
the comparison unit is used for comparing the operation file with a pre-stored operation backup file to obtain an operation state mark; the job backup file includes: job configuration backup files and script backup files;
and the time judging unit is used for acquiring the execution completion time of the job and determining whether the updating of the job is successful according to the sequence of the execution completion time and the completion time of the job state mark.
9. The big data service cloud based job change monitoring device according to claim 8, further comprising:
and the backup file generation unit is used for regularly backing up the job script file and the job configuration file of the application program in the big data service cloud client server to generate the job backup file.
10. The big data service cloud-based job change monitoring device according to claim 9, wherein when the job file is a script file, the comparing unit includes:
the script comparison module is used for comparing the script file with the script backup file;
the state marking module is used for marking the operation states with inconsistent comparison results; and marking the operation state as modified, added or deleted according to the comparison result.
11. The big data service cloud-based job change monitoring device according to claim 10, wherein the time determination unit includes:
the coverage success judging module is used for successfully updating the coverage of the operation if the execution completion time is later than the completion time of the operation state mark;
and the coverage failure judging module is used for updating the operation without coverage if the execution completion time is earlier than the completion time of the operation state mark.
12. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the big data service cloud based job change monitoring method according to any one of claims 1 to 7 when executing the program.
13. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the big data service cloud based job change monitoring method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110458550.8A CN113157528A (en) | 2021-04-27 | 2021-04-27 | Operation change monitoring method and device based on big data service cloud |
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| CN114328134B (en) * | 2022-03-16 | 2022-05-31 | 深圳超盈智能科技有限公司 | Dynamic testing system for computer memory |
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