CN114358487A - Performance assessment method and device and computer readable storage medium - Google Patents
Performance assessment method and device and computer readable storage medium Download PDFInfo
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- CN114358487A CN114358487A CN202111448323.3A CN202111448323A CN114358487A CN 114358487 A CN114358487 A CN 114358487A CN 202111448323 A CN202111448323 A CN 202111448323A CN 114358487 A CN114358487 A CN 114358487A
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Abstract
The application provides a performance assessment method, a device and a computer readable storage medium, wherein the method comprises the following steps: each subtask processing node of the distributed task system extracts service data with corresponding identification fields from an original database according to the node identification of the subtask processing node; normalizing all the extracted service data according to the preset key type field to generate a normalized data table; selecting corresponding service data from the normalized data table according to the index item to be calculated to perform combined operation to obtain an index calculation value; and calculating a performance assessment result by combining all index calculation values to be calculated of the object to be assessed. Through the implementation of the scheme, each task node calls corresponding business data according to the assessment requirements, then index values corresponding to the subdivided index items are calculated, and the assessment results are calculated by combining the index values, so that the data source is clear and stable, the calculation model hierarchy is complete, the diversity of performance assessment projects is expanded, and the effectiveness of the performance assessment results is improved.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a performance assessment method, apparatus, and computer-readable storage medium.
Background
In order to continuously improve the management level from the inside and reduce the operation cost of an enterprise, performance assessment is an important link in the operation process of the enterprise, a scientific assessment mode is adopted to assess the work task completion condition, the work responsibility fulfillment degree and the development condition of employees, and effective guidance can be provided for the subsequent operation management of the enterprise.
However, the assessment rules of the current performance assessment mode are limited, the number of the supported assessment items is small, and the objectivity of the assessment results cannot be guaranteed in a scene with complex business data.
Disclosure of Invention
The embodiment of the application provides a performance assessment method, a performance assessment device and a computer readable storage medium, which can at least solve the problems that assessment rules of a performance assessment mode provided in the related technology are limited, the number of assessment items supported is small, and the objectivity of an assessment result cannot be guaranteed in a scene with complex business data.
A first aspect of an embodiment of the present application provides a performance assessment method, which is applied to a subtask processing node of a distributed task system, and includes:
extracting service data with corresponding identification fields from an original database according to the node identification of the service data;
normalizing all the extracted service data according to a preset key type field to generate a normalized data table; wherein the key type field comprises at least one of: data statistics period, data type and data statistics dimension;
selecting corresponding service data from the normalized data table according to the index item to be calculated to perform combined operation to obtain an index calculation value;
and calculating a performance assessment result by combining the index calculation values corresponding to all the index items to be calculated of the object to be assessed.
A second aspect of the embodiments of the present application provides a performance assessment apparatus, which is applied to a subtask processing node of a distributed task system, and includes:
the extraction module is used for extracting the service data with the corresponding identification fields from the original database according to the node identification of the extraction module;
the processing module is used for carrying out normalization processing on all the extracted service data according to a preset key type field to generate a normalized data table; wherein the key type field comprises at least one of: data statistics period, data type and data statistics dimension;
the first calculation module is used for selecting corresponding service data from the normalized data table according to the index item to be calculated to perform combined operation to obtain an index calculation value;
and the second calculation module is used for calculating a performance assessment result by combining all the index calculation values corresponding to the index items to be calculated of the object to be assessed.
A third aspect of embodiments of the present application provides an electronic apparatus, including: a memory, a processor, and a bus; the bus is used for realizing the connection communication between the memory and the processor; a processor for executing a computer program stored on the memory; when the processor executes the computer program, the steps in the performance assessment method provided by the first aspect of the embodiment of the present application are implemented.
A fourth aspect of the embodiments of the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps in the performance assessment method provided in the first aspect of the embodiments of the present application.
According to the performance assessment method, the performance assessment device and the computer readable storage medium, each subtask processing node of the distributed task system extracts service data with corresponding identification fields from the original database according to the node identification of the subtask processing node; normalizing all the extracted service data according to the preset key type field to generate a normalized data table; selecting corresponding service data from the normalized data table according to the index item to be calculated to perform combined operation to obtain an index calculation value; and calculating a performance assessment result by combining all index calculation values to be calculated of the object to be assessed. Through the implementation of the scheme, each task node calls the corresponding business data according to the assessment requirements, then the index values corresponding to the subdivided index items are calculated, and the assessment results are calculated by combining the index values, so that the data source is clear and stable, the calculation model hierarchy is complete, the diversity of the performance assessment projects is expanded, and the effectiveness of the performance assessment results is improved.
Drawings
Fig. 1 is a basic flow chart of a performance assessment method according to a first embodiment of the present application;
fig. 2 is a schematic structural diagram of a distributed task system according to a first embodiment of the present application;
fig. 3 is a detailed flowchart of a performance assessment method according to a second embodiment of the present application;
FIG. 4 is a schematic diagram of program modules of a performance assessment apparatus provided in a third embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present application.
Detailed Description
In order to make the objects, features and advantages of the present invention more apparent and understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments of the present application. 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 application.
In order to solve the problems that the assessment rules of the performance assessment method provided in the related art are limited, the number of the supported assessment items is small, and the objectivity of the assessment result cannot be guaranteed in a scene with complex service data, a first embodiment of the present application provides a performance assessment method, which is applied to subtask processing nodes of a distributed task system, for example, fig. 1 is a basic flow diagram of the performance assessment method provided in this embodiment, and the performance assessment method includes the following steps:
In the related art, data statistics is generally processed in a single task and single service mode, program logic is simple, and implementation is easy, but with application of non-relational databases such as micro-services and big data, a traditional program mode cannot meet the current actual use requirements. It should be noted that the task center of this embodiment may be in a stand-alone mode, a main standby mode, or a cluster mode, and the task center may provide type interfaces such as API and TCP externally according to the characteristics of different languages, without forcibly supporting a web protocol in each language, so as to ensure that other task programs are easily integrated, and additionally, the Redis of this embodiment is used as a cache of the task center. Based on the distributed task system of the embodiment, efficient extraction and use of various data can be realized under the condition of complicated data sources, and the application expansion capability is enhanced.
It should be understood that, in the embodiment, the original database is built based on the summary of the service data from a plurality of different sources, each service data in the database has a specific identification field, and is adapted to the corresponding subtask processing node according to the identification field, and in practical applications, the identification field of the service data may correspond to the node identification of at least one subtask processing node. It should also be noted that each subtask processing node of the present embodiment may be customized according to different projects, and each subtask processing node has a customized performance assessment rule.
And 102, carrying out normalization processing on all the extracted service data according to the preset key type field to generate a normalized data table.
Specifically, the key type field of this embodiment includes at least one of the following: the system comprises a data statistics period, data types and data statistics dimensions, wherein the data statistics period can be set according to days, months, quarters and years, the data types comprise usage, yield and the like, and the data statistics dimensions comprise departments, regions and the like. In this embodiment, through data normalization processing, service data from different sources are summarized, so as to facilitate logic processing of subsequent index calculation. It should be understood that, in the embodiment, various data normalization processes are performed through sub-task processing, which facilitates the customized development by a third party.
In an implementation manner of this embodiment, before the step of performing normalization processing on all extracted service data according to the preset key type field to generate the normalized data table, the method further includes: identifying missing data from all the service data; predicting missing data based on existing data in all service data; completing missing data according to the prediction result; and/or matching all the service data based on the key type field; and carrying out deduplication on the plurality of matched and consistent service data.
Specifically, in practical applications, data anomalies such as data loss and duplication may exist in the service data collected from each subtask processing node, so that data cleaning may be performed before data normalization processing, so as to achieve the purpose of data error correction. On one hand, the missing data can be identified in the embodiment, for example, the missing data can be identified according to whether the data is Null or None, and then the missing data is predicted as a target variable based on the existing data, so as to obtain the most possible complement value, and in practical application, the missing data can be complemented by adopting a regression model, a classification model and other manners; on the other hand, the embodiment can also remove the duplicate redundant data, that is, duplicate data is identified by matching the same key information, and then deduplication is performed.
It should be noted that, in practical applications, the data may also have format errors, content errors, logic errors, and other exceptions, so that the data exception handling of the embodiment may further include data correction, that is, data format correction, data content correction, data logic correction, and the like. It should be understood that all the embodiments provided in this embodiment are only typical embodiments, and do not constitute the only limitation to this embodiment.
And 103, selecting corresponding service data from the normalized data table according to the index item to be calculated to perform combined operation to obtain an index calculation value.
Specifically, in practical application, the service data associated with different index items are different, in this embodiment, the corresponding service data type and the operation mode are determined according to the index item, and then the determined operation mode is adopted to perform the combination operation on the corresponding service data in the normalized data table, so as to calculate the index calculation value of each index item. It should be understood that the operation manner of the present embodiment includes mathematical value calculation, custom function operation, four-rule mixed operation, and the like.
In an implementation manner of this embodiment, before the step of selecting corresponding service data from the normalized data table according to the index item to be calculated to perform a combination operation to obtain the index calculation value, the method further includes: grouping all the index items and establishing an index theme management table; and aiming at the target index theme in the index theme management table, creating an index item to be calculated belonging to the target index theme.
Specifically, the data processing modes of each service index are different, and if the data processing modes are unified into one data structure, data redundancy and code mandatory performance are undoubtedly increased.
In an implementation manner of this embodiment, after the step of selecting corresponding service data from the normalized data table according to the index item to be calculated to perform a combination operation to obtain the index calculation value, the method further includes: acquiring index calculation values of index items with the same index time dimension; and inputting all index calculation values into a preset index prediction model, and outputting an index prediction result.
Specifically, in this embodiment, after the index calculation value is obtained through calculation, index value prediction may be performed on the index item according to the historical index calculation value, and the index calculation value needs to be associated, that is, the index items with the same time dimension need to be selected for prediction calculation.
In an implementation manner of this embodiment, after the step of selecting corresponding service data from the normalized data table according to the index item to be calculated to perform a combination operation to obtain the index calculation value, the method further includes: acquiring an index threshold range corresponding to an index item to be calculated; comparing the index calculated value with an index threshold range; and when the index calculation value exceeds the index threshold range, outputting an abnormal alarm aiming at the index item to be calculated.
Specifically, the embodiment may evaluate the calculated index calculation value with reference to an index threshold range, determine that the index of the corresponding index item is abnormal when the index calculation value exceeds the index threshold range, and then output an abnormal alarm.
And 104, calculating a performance assessment result by combining the index calculation values corresponding to all the index items to be calculated of the object to be assessed.
Specifically, the object to be examined generally needs to combine multiple index items to evaluate the performance thereof, the performance assessment result of the embodiment may be a performance score and/or a performance level, and the performance level may be evaluated according to the performance score in practical applications.
In an embodiment of the present invention, the step of calculating the performance assessment result by combining the index calculation values corresponding to all the index items to be calculated of the object to be assessed includes: calculating index scores according to index calculated values corresponding to index items to be calculated of the objects to be assessed; and carrying out weighted summation on all the index scores to obtain a performance assessment result.
Specifically, in practical applications, the indexes of different types of index items have different relevance to the index value, for example, for some index items, the index is better when the index value is larger, and the index is better when the index value is smaller for some other index items, so that the accuracy of the performance assessment result cannot be ensured if the performance assessment result is directly calculated by using the index calculation value. Based on this, in the embodiment, the index score is calculated for the index calculation value of each index item, and then the performance assessment result is calculated based on the index score.
Further, in an embodiment of this embodiment, the specific implementation manners of calculating the index score for the index calculation value corresponding to each index item to be calculated of the object to be assessed include, but are not limited to, the following three types:
determining the value range of the index calculation value corresponding to each index item to be calculated of the object to be assessed; and determining the corresponding index score of each index calculation value according to the value range.
Specifically, in this embodiment, different index scores are respectively and correspondingly set for different value ranges of each index item, for example, when the index value of the index item a is in the interval range of [2,7], the corresponding index score is 30, when the index value of the index item a is in the interval range of [15,20], the corresponding index score is 80, when the index value of the index item B is in the interval range of [2,7], the corresponding index score is 80, and when the index value of the index item B is in the interval range of [15,20], the corresponding index score is 30, that is, different types of index items are unified to the same good and bad evaluation criterion through the index scores, so as to ensure the accuracy of the performance assessment result.
And calculating index scores based on index calculation values corresponding to the index items to be calculated of the objects to be assessed and preset historical index calculation values.
Specifically, in practical application, the index calculation is performed continuously, and a plurality of index calculation values in different periods may exist in the same index item, and this embodiment may obtain a historical index calculation value of the current index calculation value, and then score the current index calculation value with reference to the historical index calculation value, as a preferred implementation, the index score calculation formula may be expressed as: index score ═ (| index calculated value-historical index calculated value |)/historical index calculated value.
And calculating index scores based on index calculation values corresponding to the index items to be calculated of the objects to be assessed and preset standard index values.
Specifically, in practical application, when the current index calculation value is scored, the current index calculation value may not be provided with the historical index calculation value, so that the difference is that the index scoring is performed by using the historical index calculation value as reference data in the second mode, in this embodiment, the current index calculation value may be scored by using a preset standard index value as reference, and the index scoring calculation formula may be represented as: the index score is (| index calculation value-standard index value |)/standard index value.
Based on the technical scheme of the embodiment of the application, each subtask processing node of the distributed task system extracts service data with corresponding identification fields from an original database according to the node identification of the subtask processing node; normalizing all the extracted service data according to the preset key type field to generate a normalized data table; selecting corresponding service data from the normalized data table according to the index item to be calculated to perform combined operation to obtain an index calculation value; and calculating a performance assessment result by combining all index calculation values to be calculated of the object to be assessed. Through the implementation of the scheme, each task node calls the corresponding business data according to the assessment requirements, then the index values corresponding to the subdivided index items are calculated, and the assessment results are calculated by combining the index values, so that the data source is clear and stable, the calculation model hierarchy is complete, the diversity of the performance assessment projects is expanded, and the effectiveness of the performance assessment results is improved.
The method in fig. 3 is a detailed performance assessment method provided in a second embodiment of the present application, and is applied to subtask processing nodes of a distributed task system, where the performance assessment method includes:
And 303, grouping all the index items, establishing an index theme management table, and aiming at a target index theme in the index theme management table, creating an index item to be calculated belonging to the target index theme.
And 304, selecting corresponding service data from the normalized data table according to the index item to be calculated to perform combined operation to obtain an index calculated value.
And 305, determining the value range of the index calculation value corresponding to each index item to be calculated of the object to be assessed.
And step 306, determining the corresponding index score of each index calculation value according to the value range.
And 307, weighting and summing all the index scores to obtain a performance assessment result.
It should be understood that, the size of the serial number of each step in this embodiment does not mean the execution sequence of the step, and the execution sequence of each step should be determined by its function and inherent logic, and should not be limited uniquely to the implementation process of the embodiment of the present application.
Based on the technical scheme of the embodiment of the application, each subtask processing node of the distributed task system extracts service data with corresponding identification fields from an original database according to the node identification of the subtask processing node; normalizing all the extracted service data according to the preset key type field to generate a normalized data table; selecting corresponding service data from the normalized data table according to the index item to be calculated to perform combined operation to obtain an index calculation value; and calculating a performance assessment result by combining all index calculation values to be calculated of the object to be assessed. Through the implementation of the scheme, each task node calls corresponding business data according to the assessment requirements, then index values corresponding to the subdivided index items are calculated, and the assessment results are calculated by combining the index values, so that the data source is clear and stable, the calculation model hierarchy is complete, the diversity of performance assessment projects is expanded, and the effectiveness of the performance assessment results is improved.
Fig. 4 is a performance assessment device according to a third embodiment of the present application. The performance assessment apparatus can be used to implement the performance assessment method in the foregoing embodiments. As shown in fig. 4, the performance assessment apparatus mainly includes:
an extraction module 401, configured to extract service data with a corresponding identification field from an original database according to a node identifier of the extraction module;
a processing module 402, configured to perform normalization processing on all extracted service data according to a preset key type field, and generate a normalized data table; wherein the key type field comprises at least one of: data statistics period, data type and data statistics dimension;
the first calculation module 403 is configured to select, according to the index item to be calculated, corresponding service data from the normalized data table for performing a combination operation, so as to obtain an index calculation value;
and the second calculating module 404 is configured to calculate a performance assessment result by combining the index calculated values corresponding to all the index items to be calculated of the object to be assessed.
In some implementations of this embodiment, the performance assessment apparatus further includes: the creating module is used for grouping all the index items and establishing an index theme management table; and aiming at the target index theme in the index theme management table, creating an index item to be calculated belonging to the target index theme.
In some implementations of this embodiment, the performance assessment apparatus further includes: the output module is used for acquiring index calculation values of index items with the same index time dimension; and inputting all index calculation values into a preset index prediction model, and outputting an index prediction result.
In some embodiments of this embodiment, the processing module is further configured to: identifying missing data from all the service data; predicting missing data based on existing data in all service data; and completing missing data according to the prediction result. In other embodiments of this embodiment, the processing module is further configured to: matching all the service data based on the key type field; and carrying out deduplication on the plurality of matched and consistent service data.
In other embodiments of this embodiment, the output module is further configured to: acquiring an index threshold range corresponding to an index item to be calculated; comparing the index calculated value with an index threshold range; and when the index calculation value exceeds the index threshold range, outputting an abnormal alarm aiming at the index item to be calculated.
In some embodiments of this embodiment, the second calculating module is specifically configured to: calculating index scores according to index calculated values corresponding to the index items to be calculated of the objects to be assessed; and carrying out weighted summation on all the index scores to obtain a performance assessment result.
Further, in some embodiments of this embodiment, when the function of calculating an index score for the index calculation value corresponding to each index item to be calculated of the object to be assessed is executed by the second calculation module, the second calculation module is specifically configured to: determining the value range of the index calculation value corresponding to each index item to be calculated of the object to be assessed; determining the corresponding index score of each index calculation value according to the value range; or, calculating index scores based on index calculation values corresponding to all index items to be calculated of the objects to be assessed and preset historical index calculation values; or, calculating index scores based on index calculation values and preset standard index values corresponding to the index items to be calculated of the objects to be assessed.
It should be noted that, the performance assessment methods in the first and second embodiments can be implemented based on the performance assessment device provided in this embodiment, and persons of ordinary skill in the art can clearly understand that, for convenience and brevity of description, the specific working process of the performance assessment device described in this embodiment may refer to the corresponding process in the foregoing method embodiments, and details are not described here again.
According to the performance assessment device provided by the embodiment, each subtask processing node of the distributed task system extracts service data with corresponding identification fields from the original database according to the node identification of the subtask processing node; normalizing all the extracted service data according to the preset key type field to generate a normalized data table; selecting corresponding service data from the normalized data table according to the index item to be calculated to perform combined operation to obtain an index calculation value; and calculating a performance assessment result by combining all index calculation values to be calculated of the object to be assessed. Through the implementation of the scheme, each task node calls corresponding business data according to the assessment requirements, then index values corresponding to the subdivided index items are calculated, and the assessment results are calculated by combining the index values, so that the data source is clear and stable, the calculation model hierarchy is complete, the diversity of performance assessment projects is expanded, and the effectiveness of the performance assessment results is improved.
Referring to fig. 5, fig. 5 is an electronic device according to a fourth embodiment of the present disclosure. The electronic device can be used for realizing the performance assessment method in the embodiment. As shown in fig. 5, the electronic device mainly includes:
a memory 501, a processor 502, a bus 503, and computer programs stored on the memory 501 and executable on the processor 502, the memory 501 and the processor 502 being connected by the bus 503. The processor 502, when executing the computer program, implements the performance assessment method in the foregoing embodiments. Wherein the number of processors may be one or more.
The Memory 501 may be a high-speed Random Access Memory (RAM) Memory or a non-volatile Memory (non-volatile Memory), such as a disk Memory. The memory 501 is used for storing executable program code, and the processor 502 is coupled to the memory 501.
Further, an embodiment of the present application also provides a computer-readable storage medium, where the computer-readable storage medium may be provided in an electronic device in the foregoing embodiments, and the computer-readable storage medium may be the memory in the foregoing embodiment shown in fig. 5.
The computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the performance assessment method in the foregoing embodiments. Further, the computer-readable storage medium may be various media that can store program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a RAM, a magnetic disk, or an optical disk.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of modules is merely a division of logical functions, and an actual implementation may have another division, for example, a plurality of modules 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 modules, and may be in an electrical, mechanical or other form.
Modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present application may be integrated into one processing module, or each of the modules may exist alone physically, or two or more modules are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode.
The integrated module, if implemented in the form of a software functional module and sold or used as a separate product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a readable 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 of the embodiments of the present application. And the aforementioned readable storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.
It should be noted that, for the sake of simplicity, the above-mentioned method embodiments are described as a series of acts or combinations, but those skilled in the art should understand that the present application is not limited by the described order of acts, as some steps may be performed in other orders or simultaneously according to the present application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In view of the above description of the performance assessment method, apparatus and computer-readable storage medium provided by the present application, those skilled in the art will be able to change the embodiments and applications of the present application based on the idea of the embodiments of the present application, and therefore the content of the present application should not be construed as limiting the present application.
Claims (10)
1. A performance assessment method is applied to subtask processing nodes of a distributed task system, and comprises the following steps:
extracting service data with corresponding identification fields from an original database according to the node identification of the service data;
normalizing all the extracted service data according to a preset key type field to generate a normalized data table; wherein the key type field comprises at least one of: data statistics period, data type and data statistics dimension;
selecting corresponding service data from the normalized data table according to the index item to be calculated to perform combined operation to obtain an index calculation value;
and calculating a performance assessment result by combining the index calculation values corresponding to all the index items to be calculated of the object to be assessed.
2. The performance assessment method according to claim 1, wherein before the step of selecting corresponding service data from the normalized data table according to the index item to be calculated for performing the combination operation to obtain the index calculation value, the method further comprises:
grouping all the index items and establishing an index theme management table;
and aiming at a target index theme in the index theme management table, creating the index item to be calculated which belongs to the target index theme.
3. The performance assessment method according to claim 1, wherein after the step of selecting corresponding service data from the normalized data table according to the index item to be calculated for performing a combination operation to obtain an index calculation value, the method further comprises:
acquiring the index calculation values of index items with the same index time dimension;
and inputting all the index calculation values into a preset index prediction model, and outputting an index prediction result.
4. The performance assessment method according to claim 1, wherein before the step of normalizing all the extracted business data according to the preset key type field and generating the normalized data table, the method further comprises:
identifying missing data from all the service data;
predicting the missing data based on the existing data in all the service data;
completing the missing data according to a prediction result;
and/or matching all the service data based on the key type field;
and carrying out deduplication on the plurality of matched and consistent service data.
5. The performance assessment method according to claim 1, wherein after the step of selecting corresponding service data from the normalized data table according to the index item to be calculated for performing a combination operation to obtain an index calculation value, the method further comprises:
acquiring an index threshold range corresponding to the index item to be calculated;
comparing the indicator calculated value to the indicator threshold range;
and when the index calculation value exceeds the index threshold range, outputting an abnormal alarm aiming at the index item to be calculated.
6. The performance assessment method according to any one of claims 1 to 5, wherein said step of calculating a performance assessment result by combining said index calculation values corresponding to all said index items to be calculated of the object to be assessed comprises:
calculating index scores according to the index calculation values corresponding to the index items to be calculated of the check objects to be checked;
and weighting and summing all the index scores to obtain a performance assessment result.
7. The performance assessment method according to claim 6, wherein said step of calculating an index score for each of said index calculation values corresponding to said index items to be calculated of the object to be assessed comprises:
determining the value range of the index calculation value corresponding to each index item to be calculated of the check object to be checked;
determining the corresponding index score of each index calculation value according to the value range;
or, calculating index scores based on the index calculation value corresponding to each index item to be calculated of the object to be checked and a preset historical index calculation value;
or, calculating index scores based on the index calculation value and the preset standard index value corresponding to each index item to be calculated of the check object.
8. A performance assessment apparatus applied to subtask processing nodes of a distributed task system, the performance assessment apparatus comprising:
the extraction module is used for extracting the service data with the corresponding identification fields from the original database according to the node identification of the extraction module;
the processing module is used for carrying out normalization processing on all the extracted service data according to a preset key type field to generate a normalized data table; wherein the key type field comprises at least one of: data statistics period, data type and data statistics dimension;
the first calculation module is used for selecting corresponding service data from the normalized data table according to the index item to be calculated to perform combined operation to obtain an index calculation value;
and the second calculation module is used for calculating a performance assessment result by combining all the index calculation values corresponding to the index items to be calculated of the object to be assessed.
9. An electronic device, comprising: a memory, a processor, and a bus;
the bus is used for realizing connection communication between the memory and the processor;
the processor is configured to execute a computer program stored on the memory;
the processor, when executing the computer program, performs the steps of the method of any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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| CN (1) | CN114358487A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114971434A (en) * | 2022-08-01 | 2022-08-30 | 广州天维信息技术股份有限公司 | Performance comparison analysis system based on distributed computation |
| CN115759019A (en) * | 2022-11-15 | 2023-03-07 | 广州天维信息技术股份有限公司 | Business data calculation method and device, storage medium and computer equipment |
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2021
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114971434A (en) * | 2022-08-01 | 2022-08-30 | 广州天维信息技术股份有限公司 | Performance comparison analysis system based on distributed computation |
| CN114971434B (en) * | 2022-08-01 | 2022-10-21 | 广州天维信息技术股份有限公司 | Performance comparison analysis system based on distributed computation |
| CN115759019A (en) * | 2022-11-15 | 2023-03-07 | 广州天维信息技术股份有限公司 | Business data calculation method and device, storage medium and computer equipment |
| CN115759019B (en) * | 2022-11-15 | 2023-10-20 | 广州天维信息技术股份有限公司 | Service data calculation method, device, storage medium and computer equipment |
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