CN115016972A - Method, device, equipment and medium for diagnosing diagnosis duration of server test item - Google Patents
Method, device, equipment and medium for diagnosing diagnosis duration of server test item Download PDFInfo
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Abstract
The invention belongs to the technical field of server testing, and particularly provides a method, a device, equipment and a medium for diagnosing the diagnosis duration of a server test item, wherein the method comprises the following steps: configuring data which needs to be customized and comprises dimension codes and names, index codes and names, codes and names of early warning threshold values, early warning values and combination relations of dimension indexes on a page; acquiring dimension and index data, and processing the dimension and the index data to generate standard diagnosis duration; periodically polling a database according to the dimension and the index, and counting the diagnosis duration of the current dimension index of the machine under diagnosis from the database as the current diagnosis duration; and under the same dimensionality, comparing the current diagnosis time length of each machine with the standard diagnosis time length, and generating early warning data when the current diagnosis time length exceeds a set early warning threshold value. The hidden trouble of the machine is eliminated, thereby improving the diagnosis quality. After the diagnostic program is optimized, the diagnostic time is saved, and certain production cost can be reduced.
Description
Technical Field
The invention relates to the technical field of server testing, in particular to a method, a device, equipment and a medium for diagnosing the diagnosis duration of a server test item.
Background
Before leaving the factory, the server performs a series of complete machine diagnosis and detection, including refreshing of BMC and BIOS, and pressure testing of CPU, memory and hard disk. The machine customized for the large customer can even increase the diagnostic detection program of the customer according to the customer requirement. The diagnosis methods effectively ensure the quality of the factory machine.
The traditional diagnosis mode focuses more on the detection whether the whole machine passes through the diagnosis program. However, in the current intelligent manufacturing era, higher requirements are put forward in the manufacturing field, and the diagnosis quality needs to be further improved. Although the individual machines pass the detection of the diagnostic program, if the diagnostic time of a certain test item or the overall diagnostic time is too long, whether the undetected hidden trouble exists or not is also a problem that the analysis needs to be concerned.
Disclosure of Invention
The traditional diagnosis mode focuses more on the detection whether the whole machine passes through the diagnosis program. However, in the current intelligent manufacturing era, higher requirements are put forward in the manufacturing field, and the diagnosis quality needs to be further improved. Although the individual machines pass the detection of the diagnostic program, if the diagnostic time of a certain test item or the overall diagnostic time is too long, whether the undetected hidden trouble exists or not is also a problem that the analysis needs to be concerned. The invention provides a method, a device, equipment and a medium for diagnosing the diagnosis duration of a server test item.
In a first aspect, a technical solution of the present invention provides a method for diagnosing a diagnosis duration of a server test item, including the steps of:
configuring data which needs to be customized and comprises dimension codes and names, index codes and names, codes and names of early warning threshold values, early warning values and combination relations of dimension indexes on a page;
acquiring dimension and index data, and processing the dimension and the index data to generate standard diagnosis duration;
periodically polling a database according to the dimension and the index, and counting the diagnosis duration of the current dimension index of the machine under diagnosis from the database as the current diagnosis duration;
and under the same dimensionality, comparing the current diagnosis time length of each machine with the standard diagnosis time length, and generating early warning data when the current diagnosis time length exceeds a set early warning threshold value.
Further, the step of obtaining dimension and index data for processing to generate standard diagnosis duration comprises:
dimension and index data are obtained;
filtering the garbage data according to the statistical dimension and the index;
and periodically counting the average value of the diagnosis time length in the set time range from the database as the standard diagnosis time length.
Furthermore, in the step of filtering the junk data according to the statistical dimension and the index, the junk data refers to data which does not meet the statistical requirement, and includes data which has an error report of the test item to be counted and data which has not been diagnosed yet for the test item.
Further, the method further comprises:
displaying machine data with the diagnosis duration exceeding a preset duration on a web page; or,
and displaying the generated early warning data in a report form.
In a second aspect, the technical solution of the present invention further provides a diagnostic apparatus for diagnosing the time length of a server test item, which includes a customization module, a standard diagnostic time length module, a current diagnostic time length module, and an early warning module;
the customization module is used for configuring data which is required to be customized and comprises dimension codes and names, index codes and names, codes of early warning threshold values and the combination relation of the names, the early warning values and the dimension indexes on a page;
the standard diagnosis duration module is used for acquiring dimension and index data and processing the dimension and the index data to generate standard diagnosis duration;
the current diagnosis duration module is used for periodically polling the database according to the dimension and the index, and counting the diagnosis duration of the current dimension index of the machine under diagnosis from the database as the current diagnosis duration;
and the early warning module is used for comparing the current diagnosis time length of each machine with the standard diagnosis time length under the same dimensionality, and generating early warning data when the current diagnosis time length exceeds a set early warning threshold value.
Further, the standard diagnosis duration module comprises an acquisition unit, a processing unit and a calculation unit;
an acquisition unit configured to acquire dimension and index data;
the processing unit is used for filtering the garbage data according to the statistical dimension and the index;
and the calculating unit is used for regularly counting the average value of the diagnosis time length in the set time range from the database as the standard diagnosis time length.
Further, the junk data refers to data that does not meet the statistical requirements, and includes data that the test item to be counted has an error and data that the test item has not completed diagnosis.
Further, the device also comprises a display module, a judging module and a display module, wherein the display module is used for displaying the machine data with the diagnosis time length exceeding the preset time length on the web page; or the generated early warning data is displayed in a report form.
In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores computer program instructions executable by the at least one processor to enable the at least one processor to perform the method of diagnosing for server test item diagnostic durations as described in the first aspect.
In a fourth aspect, the present invention also provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the method for diagnosing the diagnosis duration of the server test item according to the first aspect.
According to the technical scheme, the invention has the following advantages: in the whole machine diagnosis process, the invention can carry out early warning on the machine with the test item diagnosis duration exceeding the early warning threshold. Technicians can check the alarm machine and search the reason for the overlong diagnosis time of the test item, so that the diagnosis program can be optimized in a targeted manner, the hidden danger of the machine is eliminated, and the diagnosis quality is improved. After the diagnostic program is optimized, the diagnostic time is saved, and certain production cost can be reduced.
In addition, the invention has reliable design principle, simple structure and very wide application prospect.
Therefore, compared with the prior art, the invention has prominent substantive features and remarkable progress, and the beneficial effects of the implementation are also obvious.
Drawings
In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present invention, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a schematic flow diagram of a method of one embodiment of the invention.
Fig. 2 is a schematic block diagram of an apparatus of one embodiment of the present invention.
Detailed Description
In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is obvious that the described embodiment is only a part of the embodiment of the present invention, and not all 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. The current complete machine diagnostic program stores order data, material data, diagnostic log data and the like in a database, wherein the order data, the material data, the diagnostic log data and the like comprise sn (serial number of a machine), an order number, a machine type, a package name, an instruction name, the number of machines of an order, a current diagnostic test item, a current diagnostic state, diagnostic starting time and diagnostic ending time of each test item and the like. The invention processes and processes the data and provides a test item diagnosis duration early warning method.
As shown in fig. 1, embodiment 1 of the present invention provides a method for diagnosing a diagnosis duration of a server test item, including the following steps:
step 1: configuring data which needs to be customized and comprises dimension codes and names, index codes and names, codes and names of early warning threshold values, early warning values and combination relations of dimension indexes on a page;
step 2: acquiring dimension and index data, and processing the dimension and the index data to generate standard diagnosis duration;
and 3, step 3: periodically polling a database according to the dimension and the index, and counting the diagnosis duration of the current dimension index of the machine under diagnosis from the database as the current diagnosis duration;
and 4, step 4: and under the same dimensionality, comparing the current diagnosis time length of each machine with the standard diagnosis time length, and generating early warning data when the current diagnosis time length exceeds a set early warning threshold value.
The embodiment 2 of the invention provides a method for diagnosing the diagnosis duration of a server test item, which comprises the following steps:
step 1: configuring data which needs to be customized and comprises dimension codes and names, index codes and names, codes and names of early warning threshold values, early warning values and combination relations of dimension indexes on a page;
it should be noted that the dimension, i.e., the dimension that needs to be counted, may be configured as a model, a package, an instruction, and the like. The index is an index which needs to be compared with the diagnosis time, and can be configured to be the diagnosis time of the client program, the total time of the previous measurement, the total time of the aging and the like. The model and the total duration of the previous measurement, the total aging duration and the like can be combined to count the duration data of the model. For example, dimension is package, index is client program diagnosis duration, and early warning threshold is as follows: 10 percent. Namely, the client program diagnosis time of each set of meal is 10% longer than the standard diagnosis time, and then early warning is carried out.
Step 2: acquiring dimension and index data, and processing the dimension and the index data to generate standard diagnosis duration;
the method specifically comprises the following steps: step 21: dimension and index data are obtained;
step 22: filtering the garbage data according to the statistical dimension and the index;
step 23: and periodically counting the average value of the diagnosis time length in the set time range from the database as the standard diagnosis time length.
It should be noted that the garbage data refers to data that does not meet statistical requirements, and includes data that has an error in a test item to be counted and data that has not been diagnosed yet for the test item. For example, 1 point every morning, according to the dimension of each package, the average value of the client program diagnosis duration in 365 days before each package is counted as the standard diagnosis duration of the client program diagnosis duration of the package.
And step 3: periodically polling a database according to the dimension and the index, and counting the diagnosis duration of the current dimension index of the machine under diagnosis from the database as the current diagnosis duration;
to meet the timeliness of the data, the polling database interval is set to be relatively small, such as 10 minutes. For example, every 10 minutes, counting the diagnosis duration of the client program of each machine for the machine currently being diagnosed, and if the client program test item is diagnosed, taking the interval between the diagnosis start time and the diagnosis end time of the client program as the current diagnosis duration; if the client test item has already started diagnosis but has not ended, the interval between the client diagnosis start time and the current time is taken as the current diagnosis duration.
And 4, step 4: and under the same dimensionality, comparing the current diagnosis time length of each machine with the standard diagnosis time length, and generating early warning data when the current diagnosis time length exceeds a set early warning threshold value.
And 5: displaying machine data with the diagnosis duration exceeding a preset duration on a web page; or the generated early warning data is displayed in a report form. For example, after the current diagnosis time length is obtained, the current diagnosis time length is compared with the obtained standard diagnosis time length of the package, 10% more diagnosis time length is obtained, and early warning data is generated and displayed on a web page.
In the whole machine diagnosis process, the invention can carry out early warning on the machine with the test item diagnosis duration exceeding the early warning threshold. Technicians can check the alarm machine and search the reason for the overlong diagnosis time of the test item, so that the diagnosis program can be optimized in a targeted manner, the hidden danger of the machine is eliminated, and the diagnosis quality is improved. After the diagnostic program is optimized, the diagnostic time is saved, and certain production cost can be reduced.
As shown in fig. 2, embodiment 3 of the present invention further provides a diagnostic apparatus for server test item diagnosis duration, including a customization module, a standard diagnosis duration module, a current diagnosis duration module, and an early warning module;
the customization module is used for configuring data which is required to be customized and comprises dimension codes and names, index codes and names, codes of early warning threshold values and the combination relation of the names, the early warning values and the dimension indexes on a page;
the standard diagnosis duration module is used for acquiring dimension and index data and processing the dimension and the index data to generate standard diagnosis duration;
the current diagnosis duration module is used for periodically polling the database according to the dimension and the index, and counting the diagnosis duration of the current dimension index of the machine under diagnosis from the database as the current diagnosis duration;
and the early warning module is used for comparing the current diagnosis time length of each machine with the standard diagnosis time length under the same dimensionality, and generating early warning data when the current diagnosis time length exceeds a set early warning threshold value.
The embodiment 4 of the invention also provides a diagnostic device for the diagnosis time of the server test item, which comprises a customization module, a standard diagnosis time module, a current diagnosis time module, an early warning module and a display module;
the customization module is used for configuring data which is required to be customized and comprises dimension codes and names, index codes and names, codes of early warning threshold values and the combination relation of the names, the early warning values and the dimension indexes on a page; and a customization module, namely configuring data needing customization on the page. The method comprises dimension codes and names, index codes and names, codes and names of early warning threshold values, early warning values, combination relations of dimension indexes and the like. The dimension is the dimension which needs statistics, and can be configured into a model, a package, an instruction and the like. The index is an index which needs to be compared with the diagnosis time, and can be configured to be the diagnosis time of the client program, the total time of the previous measurement, the total time of the aging and the like. The model and the total duration of the previous measurement, the total aging duration and the like can be combined to count the duration data of the model.
Examples are: dimension, package, index, client program diagnosis duration, early warning threshold: 10 percent. Namely, the client program diagnosis time of each set of meal is 10% longer than the standard diagnosis time, and then early warning is carried out.
The standard diagnosis duration module is used for acquiring dimension and index data and processing the dimension and the index data to generate standard diagnosis duration; the standard diagnosis duration module comprises an acquisition unit, a processing unit and a calculation unit; an acquisition unit configured to acquire dimension and index data; the processing unit is used for filtering the garbage data according to the statistical dimension and the index; and the calculating unit is used for regularly counting the average value of the diagnosis duration in the set time range from the database as the standard diagnosis duration.
From the customization module, data such as dimensions and indexes can be acquired. And the standard diagnosis duration module filters the junk data according to the statistical dimensionality and the indexes, and periodically counts the average value of the diagnosis durations within a certain time range from the database to serve as the standard diagnosis duration. The term "garbage data" as used herein refers to data that does not satisfy the statistical requirements, including data that has errors in the test items to be counted, and data that has not been diagnosed yet.
Examples are: and counting the average value of the client program diagnosis duration of each package at 365 days before each package at 1 point every morning according to the package dimension, wherein the average value is used as the standard diagnosis duration of the client program diagnosis duration of the package.
The current diagnosis duration module is used for periodically polling the database according to the dimension and the index, and counting the diagnosis duration of the current dimension index of the machine under diagnosis from the database as the current diagnosis duration;
and the current diagnosis duration module is used for periodically polling the database according to the dimension and the index, and counting the diagnosis duration of the current dimension index of the machine under diagnosis from the database as the current diagnosis duration. To meet the timeliness of the data, the polling database interval is set to be relatively small, such as 10 minutes.
Examples are: counting the diagnosis duration of a client program of each machine for the machine currently under diagnosis every 10 minutes, and taking the interval between the diagnosis start time and the diagnosis end time of the client program as the current diagnosis duration if the client program test item is diagnosed; if the client test item has already started diagnosis but has not ended, the interval between the client diagnosis start time and the current time is taken as the current diagnosis duration.
And the early warning module is used for comparing the current diagnosis time length of each machine with the standard diagnosis time length under the same dimensionality, and generating early warning data when the current diagnosis time length exceeds a set early warning threshold value.
The display module is used for displaying the machine data with the diagnosis time length exceeding the preset time length on the web page; or the generated early warning data is displayed in a report form.
And under the same dimensionality, the current diagnosis time length of each machine generated by the current diagnosis time length module is compared with the standard diagnosis time length in the standard diagnosis time length module, and early warning data is generated when the current diagnosis time length exceeds an early warning threshold value set in the customization module. Machine data with the diagnosis time length exceeding the preset time length are displayed on the web page, and if the early warning is already checked, the machine data can be clicked to be cancelled. The generated data can also be displayed in a report form.
Examples are: and after the current diagnosis time length is obtained, comparing the current diagnosis time length with the obtained standard diagnosis time length of the package, and if the diagnosis time length is 10% more, generating early warning data and displaying the early warning data on a web page.
Embodiment 5 of the present invention further provides an electronic device, where the electronic device includes: the system comprises a processor, a communication interface, a memory and a bus, wherein the processor, the communication interface and the memory are communicated with each other through the bus. The bus may be used for information transfer between the electronic device and the sensor. The processor may call logic instructions in memory to perform the following method: step 1: configuring data which needs to be customized and comprises dimension codes and names, index codes and names, codes and names of early warning threshold values, early warning values and combination relations of dimension indexes on a page; and 2, step: acquiring dimension and index data, and processing the dimension and the index data to generate standard diagnosis duration; and step 3: periodically polling a database according to the dimension and the index, and counting the diagnosis duration of the current dimension index of the machine under diagnosis from the database as the current diagnosis duration; and 4, step 4: and under the same dimensionality, comparing the current diagnosis time length of each machine with the standard diagnosis time length, and generating early warning data when the current diagnosis time length exceeds a set early warning threshold value.
In some specific embodiments, the processor may call logic instructions in the memory to perform the following method: step 21: obtaining dimension and index data; step 22: filtering the garbage data according to the statistical dimension and the index; step 23: and periodically counting the average value of the diagnosis time length in the set time range from the database as the standard diagnosis time length.
In addition, the logic instructions in the memory may be implemented in the form of software functional units and may be stored in a computer readable storage medium when sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. 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.
Embodiment 6 of the present invention provides a non-transitory computer-readable storage medium storing computer instructions, which cause a computer to execute the method provided by the above method embodiment, for example, including: step 1: configuring data which needs to be customized and comprises dimension codes and names, index codes and names, codes and names of early warning threshold values, early warning values and combination relations of dimension indexes on a page; step 2: acquiring dimension and index data, and processing the dimension and the index data to generate standard diagnosis duration; and step 3: periodically polling a database according to the dimension and the index, and counting the diagnosis duration of the current dimension index of the machine under diagnosis from the database as the current diagnosis duration; and 4, step 4: and under the same dimensionality, comparing the current diagnosis time length of each machine with the standard diagnosis time length, and generating early warning data when the current diagnosis time length exceeds a set early warning threshold value.
In some specific embodiments, the program instructions executed by the processor in the readable storage medium may specifically implement the following steps: step 21: dimension and index data are obtained; step 22: filtering the garbage data according to the statistical dimension and the index; step 23: and periodically counting the average value of the diagnosis time length in the set time range from the database as the standard diagnosis time length.
Although the present invention has been described in detail by referring to the drawings in connection with the preferred embodiments, the present invention is not limited thereto. Various equivalent modifications or substitutions can be made on the embodiments of the present invention by those skilled in the art without departing from the spirit and scope of the present invention, and these modifications or substitutions are within the scope of the present invention/any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A diagnostic method for server test item diagnostic duration is characterized by comprising the following steps:
configuring data which needs to be customized and comprises dimension codes and names, index codes and names, codes and names of early warning threshold values, early warning values and combination relations of dimension indexes on a page;
acquiring dimension and index data, and processing the dimension and the index data to generate standard diagnosis duration;
periodically polling a database according to the dimension and the index, and counting the diagnosis duration of the current dimension index of the machine under diagnosis from the database as the current diagnosis duration;
and under the same dimensionality, comparing the current diagnosis time length of each machine with the standard diagnosis time length, and generating early warning data when the current diagnosis time length exceeds a set early warning threshold value.
2. The method for diagnosing the diagnosis duration of the server test item according to claim 1, wherein the step of obtaining dimension and index data for processing to generate the standard diagnosis duration includes:
dimension and index data are obtained;
filtering the garbage data according to the statistical dimension and the index;
and periodically counting the average value of the diagnosis time length in the set time range from the database as the standard diagnosis time length.
3. The method for diagnosing the diagnosis duration of the server test item according to claim 2, wherein in the step of filtering out the junk data according to the statistical dimension and the index, the junk data refers to data which do not meet the statistical requirement, and includes data which have errors reported by the test item to be counted and data which have not been diagnosed by the test item.
4. The method for diagnosing duration of server test item diagnosis according to claim 3, further comprising:
displaying machine data with the diagnosis duration exceeding a preset duration on a web page; or,
and displaying the generated early warning data in a report form.
5. A diagnostic device for diagnosing the time length of a server test item is characterized by comprising a customization module, a standard diagnostic time length module, a current diagnostic time length module and an early warning module;
the customization module is used for configuring data which is required to be customized and comprises dimension codes and names, index codes and names, codes of early warning threshold values and the combination relation of the names, the early warning values and the dimension indexes on a page;
the standard diagnosis duration module is used for acquiring dimension and index data and processing the dimension and the index data to generate standard diagnosis duration;
the current diagnosis duration module is used for periodically polling the database according to the dimension and the index, and counting the diagnosis duration of the current dimension index of the machine under diagnosis from the database as the current diagnosis duration;
and the early warning module is used for comparing the current diagnosis time length of each machine with the standard diagnosis time length under the same dimensionality, and generating early warning data when the current diagnosis time length exceeds a set early warning threshold value.
6. The diagnostic apparatus for server test item diagnostic duration according to claim 5, wherein the standard diagnostic duration module includes an obtaining unit, a processing unit, a calculating unit;
an acquisition unit configured to acquire dimension and index data;
the processing unit is used for filtering the garbage data according to the statistical dimension and the index;
and the calculating unit is used for regularly counting the average value of the diagnosis duration in the set time range from the database as the standard diagnosis duration.
7. The apparatus for diagnosing duration of server test item diagnosis of claim 6, wherein the garbage data is data that does not satisfy the statistical requirements, and includes data that the test item to be counted has an error and data that the test item has not completed diagnosis.
8. The apparatus for diagnosing the diagnosis duration of the server test item according to claim 7, further comprising a display module for presenting the machine data of which the diagnosis duration exceeds a predetermined duration on a web page; or displaying the generated early warning data in a report form.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores computer program instructions executable by at least one processor to enable the at least one processor to perform the method of diagnosing durations of server test items as claimed in any one of claims 1 to 5.
10. A non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the method for diagnosing the diagnosis duration of the server test item according to any one of claims 1 to 5.
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| CN113377637A (en) * | 2021-06-11 | 2021-09-10 | 中国工商银行股份有限公司 | Performance capacity diagnostic method and device |
| CN114490238A (en) * | 2021-12-23 | 2022-05-13 | 苏州浪潮智能科技有限公司 | Method, system, terminal and storage medium for monitoring whole server diagnosis process |
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| CN113377637A (en) * | 2021-06-11 | 2021-09-10 | 中国工商银行股份有限公司 | Performance capacity diagnostic method and device |
| CN114490238A (en) * | 2021-12-23 | 2022-05-13 | 苏州浪潮智能科技有限公司 | Method, system, terminal and storage medium for monitoring whole server diagnosis process |
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