CN117575358A - Big data-based data processing management method and system - Google Patents
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Abstract
The invention provides a data processing management method and system based on big data, and relates to the technical field of big data analysis. Acquiring engineering result management parameter data, and carrying out validity analysis based on data management to form engineering management parameter analysis result data; acquiring extraction processing information and flow processing information of each engineering result management parameter, and analyzing the optimized comparison parameters to form optimized comparison analysis information; and carrying out optimization analysis based on data management according to the optimization comparison analysis to form flow efficiency optimization guide data. The method realizes the efficient and accurate control, optimization and guidance of engineering management information by reasonably managing the engineering management result data.
Description
Technical Field
The invention relates to the technical field of big data analysis, in particular to a data processing management method and system based on big data.
Background
Data Governance (Data Governance) is a complete set of management actions in an organization that involve the use of Data. A series of policies and procedures are initiated and enforced by the enterprise data governance department regarding how business applications and technical management for the data within the entire enterprise are formulated and enforced. Considering the characteristics of data management, the application of data management is increasingly emphasized in engineering management. Thus, the improvement of the efficiency and accuracy of engineering project management with respect to the use of data governance is becoming an important research direction for data governance.
At present, the engineering management data has various and complex contents, and the final engineering management result data is often obtained and integrated with different original parameter data in the forming process. And a reasonable and efficient data acquisition and use mode is formed when the engineering management result data are not acquired by combining different original parameter data.
Therefore, designing a data processing management method and system based on big data, which realizes efficient and accurate control, optimization and guidance of engineering management information by reasonable data management of engineering management result data is a problem to be solved at present.
Disclosure of Invention
The invention aims to provide a data processing management method based on big data, which is characterized in that the data processing management method is used for carrying out validity analysis aiming at forming engineering result management data by acquiring engineering result management parameter data, further dividing the types of processing flows corresponding to different engineering result management parameters, comprehensively knowing the forming efficiency and the specific conditions of the original data of the engineering result management parameters on the basis of fully acquiring the using processing information of the engineering result management parameters, further carrying out optimization analysis to acquire the guiding parameters for carrying out high-efficiency and accurate acquisition on the engineering result management data, helping to realize high-efficiency management of the engineering result management data, improving the validity and accuracy of the engineering result management parameter data control, and greatly improving the acquisition efficiency of the engineering result management parameter.
The invention also aims to provide a data processing management system based on big data, which acquires basic data for optimizing the engineering result management parameters by utilizing the engineering management parameter acquisition unit and the management parameter processing information acquisition unit, and simultaneously performs reasonable data management analysis by utilizing the optimization analysis unit so as to determine optimized data information for adjusting the processing flow of the engineering result management parameters and improving the acquisition accuracy.
In a first aspect, the invention provides a data processing management method based on big data, which comprises the steps of obtaining engineering result management parameter data, and carrying out validity analysis based on data management to form engineering management parameter analysis result data; acquiring extraction processing information and flow processing information of each engineering result management parameter, and analyzing the optimized comparison parameters to form optimized comparison analysis information; and carrying out optimization analysis based on data management according to the optimization comparison analysis to form flow efficiency optimization guide data.
According to the method, the effectiveness analysis aiming at forming the engineering result management data is carried out by acquiring the engineering result management parameter data, so that the types of processing flows corresponding to different engineering result management parameters are distinguished, the specific conditions of the engineering result management parameters in terms of forming efficiency and original data use are comprehensively known on the basis of fully acquiring the use processing information of the engineering result management parameters, and further, the guidance parameters for efficiently and accurately acquiring the engineering result management data can be obtained through optimization analysis, the efficient management of the engineering result management data is facilitated, the effectiveness and the accuracy of the engineering result management parameter data control are improved, and the efficiency of acquiring the engineering result management parameters is greatly improved.
As one possible implementation manner, obtaining engineering result management parameter data, and performing validity analysis based on data management to form engineering management parameter analysis result data, including: determining the processing flow of different engineering result management parameters, and setting an effective analysis period; counting the output frequency of all engineering result management parameters in the effective analysis period to form a flow output frequency A n Wherein n represents the number of different engineering result management parameters; in the effective analysis period, counting the utilized quantities of different engineering real-time parameters acquired by all engineering result management parameters on corresponding processing flows to form a parameter utilization percentageWherein c represents the number of different engineering real-time parameters utilized in the generation process of the engineering result management parameter with the number n; process output frequency according to different engineering result management parametersSecondary A n And parameter utilization percentage->And analyzing based on the effective processing of the data to form analysis result data of the engineering management parameters.
In the invention, the data management model is mainly used for reasonably adjusting and controlling the use and utilization conditions of data in the process of forming result management parameters. Two main considerations here are the evaluation of engineering result management parameters. The method is characterized in that the collected original engineering management data is utilized to analyze and output engineering result management parameters to form the speed of the engineering result management parameters, so that the efficiency of data analysis and extraction in the data analysis process is determined to a certain extent, and the processing efficiency of a processing flow for forming the engineering result management parameters can be reflected to a certain extent. The other is the utilization of all the original parameters used in the engineering result management parameters in the processing mileage. Often, the utilization rate of the original parameters determines the availability of the original data acquisition on one hand, and determines the efficiency of effective data extraction of the original parameters on the other hand, and the excessive collection of the original data can cause the increase of the workload of corresponding engineering real-time parameter processing during the process of engineering result management, thereby reducing the efficiency of engineering result management parameter acquisition to a certain extent. For example, in terms of engineering quality management, the material content data of the target engineering material needs to be acquired, if a reasonable sample acquisition range is not defined, the sample extraction performed in a large range can cause that the acquisition point is not in a reasonable position, so that the acquisition amount is increased, and meanwhile, the acquisition efficiency of effective data is reduced because of the need of processing excessive useless sample point data, namely, the effective utilization rate of the acquired original data is lower, so that the time for acquiring the final material content data is increased, and the efficiency is reduced. By examining the data processing parameters in the two aspects, the analysis and judgment of the processing efficiency and the effective accuracy can be well carried out on the management object.
As a oneIn a possible implementation manner, the frequency A is output according to the flow of different engineering result management parameters n And the percentage of parameter utilizationPerforming analysis based on effective processing of the data to form analysis result data of engineering management parameters, including: setting an output frequency threshold alpha n Parameter utilization threshold beta n Parameter quantity ratio threshold M n And carrying out analysis and judgment of effective processing of the following data on each engineering result management parameter: if A n ＜α n And in the process of engineering result management parameters, c is exceeded by M n Is>Determining a processing flow corresponding to the corresponding engineering result management parameter as a first processing class; if A n ＜α n In the process of engineering result management parameters, c is not exceeded n Is>Determining a processing flow corresponding to the corresponding engineering result management parameter as a second processing class; if A n ≥α n And in the process of engineering result management parameters, c is exceeded by M n Is>Determining the corresponding processing flow of the corresponding engineering result management parameter as a third processing class; if A n ≥α n In the process of engineering result management parameters, c is not exceeded n Is >And determining the processing flow corresponding to the corresponding engineering result management parameter as a fourth processing class.
In the invention, the classification of the data processing process forming the engineering result management parameters is carried out according to the flow output frequency of the engineering result management parameters and the parameter utilization percentage of the engineering real-time parameters used in the process, so that the flow processing can be reasonably classified and divided, and further, basic, accurate and reasonable classified data information is provided for the follow-up optimization analysis of the output processing flows aiming at the engineering result management parameters of different types. It will be appreciated that for the first class of processes, i.e. in the formation of engineering result management parameters, the frequency of parameter formation is low and there are severe cases of low utilization of engineering real-time parameters used in the process flow. For the processing flow of the second processing class, there is only a case where the frequency of outputting the engineering result management parameter is low. For the third processing class, there are only a certain number of cases where the utilization of engineering real-time parameters is low. For the fourth processing class, the processing flow for basically acquiring the corresponding engineering result management parameter is in a state of efficient operation.
As one possible implementation manner, obtaining the extraction processing information and the flow processing information of each engineering result management parameter, and analyzing the optimization contrast parameter to form optimization contrast analysis information, including: obtaining the average time spent by each time the engineering result management parameters are extracted and utilized forms the time spent by the data extraction processObtaining the average waiting time spent by each time the engineering result management parameters are extracted and utilized, forming data extraction waiting time +.>The time spent by processing each engineering real-time parameter in the processing flow corresponding to the engineering result management parameter after forming the effective parameter is waited, and the time spent by forming the parameter processing wait +.>
In the invention, the purpose of data management is clear, and the efficiency of the data processing process and the optimization of related data processing conditions are improved. For the engineering result management parameters, the target of data management is that the used time and waiting time of the formed engineering result parameters cannot exceed the threshold value, and the excessively long used time and waiting time can be determined as slow formation of the engineering result management parameters, and the engineering result management parameters cannot be extracted at high frequency to carry out subsequent analysis processing. The factor limiting the formation efficiency of the engineering result management parameters is mainly the effective collection of engineering real-time parameters used in the formation process, and the formation of the engineering result management parameters can be seriously reduced due to the overlong waiting of the formation of the engineering real-time parameters.
As a possible implementation manner, according to the optimization contrast analysis, performing optimization analysis based on data management to form flow efficiency optimization guide data, including: setting a data extraction time-consuming thresholdAnd parameter processing wait time threshold +.>And processing time-consuming according to the data extraction>Data extraction latency +.>Parameter processing latency +.>And analyzing the result data by the engineering management parameters, performing the following optimization judgment based on data management to form flow efficiency optimization guide data, including: for engineering result management parameters corresponding to the first processing class: when->And is also provided withThen form the first type frequency adjustment quantity J n For flow output frequency A n Performing range-based utilization rate adjustment analysis according to the order of the parameter utilization percentages of different engineering real-time parameters in the processing flow from small to large to form parameter utilization rate adjustment information, wherein +_>When->And->Then form the first type frequency adjustment quantity J n For flow output frequency A n Wherein->When (when)And->The parameter utilization percentage according to different engineering real-time parameters in the processing flow is->And performing range-based utilization adjustment analysis from small to large to form parameter utilization adjustment information.
In the invention, for different types of processing, when the optimization guidance of the data management of the engineering result management parameters is carried out, the reference analysis data of the guidance is different because of different comparison and judgment results. For the first processing class, there are cases where the data trip frequency is low and the utilization rate of the engineering real-time parameters in the processing flow is low during the formation of the engineering result management parameters. Therefore, when the extraction time consumption and the processing waiting time consumption both exceed the threshold value, the difference between the extraction time consumption and the threshold value can be used as a reference quantity for frequency adjustment, and the efficiency of the whole processing flow can be improved by adjusting the utilization rate of the real-time engineering parameters under the condition that the total extraction time sum of the objective quantity of the real-time engineering parameters on the processing flow exceeds the time threshold value.
As a possible implementation manner, according to the optimization contrast analysis, performing optimization analysis based on data management to form flow efficiency optimization guide data, including: setting a data extraction time-consuming thresholdAnd parameter processing wait time threshold +.>And processing time-consuming according to the data extraction>Data extraction latency +.>Parameter processing latency +. >And analyzing the result data by the engineering management parameters, performing the following optimization judgment based on data management to form flow efficiency optimization guide data, including: and for engineering result management parameters corresponding to the second processing class: when->Then form the second class frequency adjustment quantity J n For flow output frequency A n Wherein->
In the invention, for the engineering result management data corresponding to the second processing class, as the processing flow only has low frequency of forming the engineering result management data, the guiding of improving the efficiency of the engineering result management data processing is mainly realized through adjusting the frequency, and the influence of the engineering real-time parameter validity acquisition time on the processing flow on the engineering result management data acquisition efficiency is not considered any more.
As a possible implementation manner, according to the optimization contrast analysis, performing optimization analysis based on data management to form flow efficiency optimization guide data, including: setting a data extraction time-consuming thresholdAnd parameter processing wait time threshold +.>And processing time-consuming according to the data extraction>Data extraction latency +.>Parameter processing latency +.>And analyzing the result data by the engineering management parameters, performing the following optimization judgment based on data management to form flow efficiency optimization guide data, including: and for engineering result management parameters corresponding to the third processing class: when- >The parameter utilization percentage according to different engineering real-time parameters in the processing flow is->And performing range-based utilization adjustment analysis from small to large to form parameter utilization adjustment information.
In the present invention, for the third processing class, only the engineering real-time parameters required for acquiring the engineering result management data exist, and the effective acquisition efficiency is low. The corresponding optimization guidance can only consider the adjustment of the effective data acquisition time of engineering real-time parameters in the processing flow. Of course, for the engineering result management data of the fourth processing class, since both the time and the engineering real-time parameters meet the requirements, it can be determined that the adjustment is not required for the data management.
As a possible implementation, the percentage of parameter utilization according to different engineering real-time parameters in the process flowPerforming range-based utilization adjustment analysis from a large order to a small order to form parameter utilization adjustment information, including: parameter utilization percentage according to different engineering real-time parameters in the processing flow>The utilization rate of engineering real-time parameters is sequentially adjusted and defined from big to small, and the parameter range is adjusted and defined after each adjustment and definition >And->Is determined by: if it isThe number of different engineering real-time parameters of (a) can be satisfied +.>Then at the judgment that it meetsStopping adjusting and demarcating; if->The number of different engineering real-time parameters of (a) cannot be satisfiedFoot supportThen all +.>Carrying out an adjustment definition of different engineering real-time parameters of (1) and determining +.>
In the invention, the efficiency of extracting the engineering real-time parameters in the processing flow is mainly adjusted by considering that the lower the utilization rate is, the less effective data can be extracted, and a large amount of invalid data needs to be processed, so that the greater the effective data acquisition time of the engineering real-time parameters is. Therefore, the adjustment is performed in order of small utilization rate, which has positive and obvious influence on the improvement of the efficiency of the whole treatment process.
As one possible implementation manner, the defining the parameter range for adjusting the utilization rate of the engineering real-time parameter includes: obtaining the range of engineering real-time parameters in effective analysis periodAnd +.>The statistics of the frequency of use is carried out on the parameters in the process; setting a use frequency threshold value, and extracting parameters of which the use frequency exceeds the use frequency threshold value to form an adjustment range quantity; and re-determining the adjustment acquisition range of the engineering real-time parameters according to the adjustment range quantity.
In the invention, the definition of the parameter range mainly considers that when the effective data of the engineering real-time parameters are acquired, screening is carried out in the original data, and the excessive range of the original data can lead to the increase of the screening workload, so that the adjustment based on the original data acquisition range can be carried out on the existing data, thereby reducing the volume of data processing and greatly increasing the efficiency of acquiring the effective data of the engineering real-time parameters.
In a second aspect, the present invention provides a data processing management system based on big data, which is applied to the data processing management method based on big data in the first aspect, and includes an engineering management parameter acquisition unit, configured to acquire engineering result management parameter data; the management parameter processing information acquisition unit is used for acquiring the extraction processing information and the flow processing information of the engineering result management parameters; the optimization analysis unit is used for acquiring the engineering result management parameter data of the engineering management parameter acquisition unit to perform validity analysis to form engineering management parameter analysis result data, and is used for acquiring the extraction processing information and the flow processing information of the engineering result management parameter of the management parameter processing information acquisition unit to perform optimization analysis to form flow efficiency optimization guide data.
In the invention, the system acquires basic data for optimizing the engineering result management parameters by utilizing the engineering management parameter acquisition unit and the management parameter processing information acquisition unit, and simultaneously performs reasonable data management analysis by utilizing the optimization analysis unit, so as to further determine optimized data information for adjusting the processing flow of the engineering result management parameters and improving the acquisition accuracy.
The data processing management method and system based on big data provided by the invention have the beneficial effects that:
according to the method, the effectiveness analysis aiming at forming the engineering result management data is carried out by acquiring the engineering result management parameter data, so that the types of processing flows corresponding to different engineering result management parameters are distinguished, the specific conditions of the engineering result management parameters in terms of forming efficiency and use of original data are comprehensively known on the basis of fully acquiring the use processing information of the engineering result management parameters, and further, the guidance parameters for efficiently and accurately acquiring the engineering result management data can be obtained through optimization analysis, the efficient management of the engineering result management data is facilitated, the effectiveness and accuracy of the engineering result management parameter data control are improved, and meanwhile, the efficiency of acquiring the engineering result management parameter is greatly improved.
According to the system, basic data for optimizing the engineering result management parameters are acquired by utilizing the engineering management parameter acquisition unit and the management parameter processing information acquisition unit, and meanwhile, reasonable data management analysis is performed by utilizing the optimization analysis unit, so that optimized data information for adjusting the processing flow of the engineering result management parameters and improving the acquisition accuracy is determined.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments of the present invention will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and should not be considered as limiting the scope, and other related drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a step diagram of a data processing management method based on big data according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described below with reference to the accompanying drawings in the embodiments of the present invention.
Data Governance (Data Governance) is a complete set of management actions in an organization that involve the use of Data. A series of policies and procedures are initiated and enforced by the enterprise data governance department regarding how business applications and technical management for the data within the entire enterprise are formulated and enforced. Considering the characteristics of data management, the application of data management is increasingly emphasized in engineering management. Thus, the improvement of the efficiency and accuracy of engineering project management with respect to the use of data governance is becoming an important research direction for data governance.
At present, the engineering management data has various and complex contents, and the final engineering management result data is often obtained and integrated with different original parameter data in the forming process. And a reasonable and efficient data acquisition and use mode is formed when the engineering management result data are not acquired by combining different original parameter data.
Referring to fig. 1, an embodiment of the present invention provides a data processing management method based on big data, where the method performs validity analysis aimed at forming engineering result management data by obtaining engineering result management parameter data, so as to further divide types of processing flows corresponding to different engineering result management parameters, comprehensively understand specific situations of forming efficiency and use of original data of the engineering result management parameters on the basis of fully obtaining use processing information of the engineering result management parameters, and further perform optimization analysis to obtain guiding parameters for efficiently and accurately obtaining the engineering result management data, thereby helping to realize efficient management of the engineering result management data, improving validity and accuracy of data control of the engineering result management parameters, and greatly improving efficiency of obtaining the engineering result management parameters.
The data processing management method based on big data specifically comprises the following steps:
s1: and acquiring engineering result management parameter data, and carrying out validity analysis based on data management to form engineering management parameter analysis result data.
Acquiring engineering result management parameter data, and carrying out validity analysis based on data management to form engineering management parameter analysis result data, wherein the engineering result management parameter analysis result data comprises: determining the processing flow of different engineering result management parameters, and setting an effective analysis period; counting the output frequency of all engineering result management parameters in the effective analysis period to form a flow output frequency A n Wherein n represents the number of different engineering result management parameters; in the effective analysis period, counting the utilized quantities of different engineering real-time parameters acquired by all engineering result management parameters on corresponding processing flows to form a parameter utilization percentageWherein c represents the number of different engineering real-time parameters utilized in the generation process of the engineering result management parameter with the number n; flow output frequency A according to different engineering result management parameters n And parameter utilization percentage->And analyzing based on the effective processing of the data to form analysis result data of the engineering management parameters.
The data management model is mainly used for reasonably adjusting and controlling the use and utilization conditions of data in the process of forming result management parameters. Two main considerations here are the evaluation of engineering result management parameters. The method is characterized in that the collected original engineering management data is utilized to analyze and output engineering result management parameters to form the speed of the engineering result management parameters, so that the efficiency of data analysis and extraction in the data analysis process is determined to a certain extent, and the processing efficiency of a processing flow for forming the engineering result management parameters can be reflected to a certain extent. The other is the utilization of all the original parameters used in the engineering result management parameters in the processing mileage. Often, the utilization rate of the original parameters determines the availability of the original data acquisition on one hand, and determines the efficiency of effective data extraction of the original parameters on the other hand, and the excessive collection of the original data can cause the increase of the workload of corresponding engineering real-time parameter processing during the process of engineering result management, thereby reducing the efficiency of engineering result management parameter acquisition to a certain extent. For example, in terms of engineering quality management, the material content data of the target engineering material needs to be acquired, if a reasonable sample acquisition range is not defined, the sample extraction performed in a large range can cause that the acquisition point is not in a reasonable position, so that the acquisition amount is increased, and meanwhile, the acquisition efficiency of effective data is reduced because of the need of processing excessive useless sample point data, namely, the effective utilization rate of the acquired original data is lower, so that the time for acquiring the final material content data is increased, and the efficiency is reduced. By examining the data processing parameters in the two aspects, the analysis and judgment of the processing efficiency and the effective accuracy can be well carried out on the management object.
Flow for managing parameters according to different engineering resultsOutput frequency A n And the percentage of parameter utilizationPerforming analysis based on effective processing of the data to form analysis result data of engineering management parameters, including: setting an output frequency threshold alpha n Parameter utilization threshold beta n Parameter quantity ratio threshold M n And carrying out analysis and judgment of effective processing of the following data on each engineering result management parameter: if A n ＜α n And in the process of engineering result management parameters, c is exceeded by M n Engineering real-time parameter presence of (2)Determining a processing flow corresponding to the corresponding engineering result management parameter as a first processing class; if A n ＜α n In the process of engineering result management parameters, c is not exceeded n Is>Determining a processing flow corresponding to the corresponding engineering result management parameter as a second processing class; if A n ≥α n And in the process of engineering result management parameters, c is exceeded by M n Is>Determining the corresponding processing flow of the corresponding engineering result management parameter as a third processing class; if A n ≥α n In the process of engineering result management parameters, c is not exceeded n Is>And determining the processing flow corresponding to the corresponding engineering result management parameter as a fourth processing class.
The data processing process forming the engineering result management parameters is classified according to the process output frequency of the engineering result management parameters and the parameter utilization percentage of the engineering real-time parameters used in the process, so that the process processing can be classified reasonably, and further basic, accurate and reasonable classified data information is provided for the follow-up optimization analysis of the output processing processes of the engineering result management parameters of different types. It will be appreciated that for the first class of processes, i.e. in the formation of engineering result management parameters, the frequency of parameter formation is low and there are severe cases of low utilization of engineering real-time parameters used in the process flow. For the processing flow of the second processing class, there is only a case where the frequency of outputting the engineering result management parameter is low. For the third processing class, there are only a certain number of cases where the utilization of engineering real-time parameters is low. For the fourth processing class, the processing flow for basically acquiring the corresponding engineering result management parameter is in a state of efficient operation.
S2: and acquiring the extraction processing information and the flow processing information of each engineering result management parameter, and analyzing the optimized comparison parameters to form optimized comparison analysis information.
Acquiring the extraction processing information and the flow processing information of each engineering result management parameter, and analyzing the optimized comparison parameters to form optimized comparison analysis information, wherein the method comprises the following steps: obtaining the average time spent by each time the engineering result management parameters are extracted and utilized forms the time spent by the data extraction processObtaining the average waiting time spent by each time the engineering result management parameters are extracted and utilized, forming data extraction waiting time +.>The time spent by processing each engineering real-time parameter in the processing flow corresponding to the engineering result management parameter after forming the effective parameter is waited, and the time spent by forming the parameter processing wait +.>
The method has definite purposes for data management and aims at improving the efficiency of the data processing process and the optimization of related data processing conditions. For the engineering result management parameters, the target of data management is that the used time and waiting time of the formed engineering result parameters cannot exceed the threshold value, and the excessively long used time and waiting time can be determined as slow formation of the engineering result management parameters, and the engineering result management parameters cannot be extracted at high frequency to carry out subsequent analysis processing. The factor limiting the formation efficiency of the engineering result management parameters is mainly the effective collection of engineering real-time parameters used in the formation process, and the formation of the engineering result management parameters can be seriously reduced due to the overlong waiting of the formation of the engineering real-time parameters.
According to the optimization comparison analysis, performing optimization analysis based on data management to form flow efficiency optimization guide data, wherein the optimization guide data comprises: setting a data extraction time-consuming thresholdAnd parameter processing wait time threshold +.>And processing time-consuming according to the data extraction>Data extraction latency +.>Parameter processing latency +.>And analyzing the result data by the engineering management parameters, performing the following optimization judgment based on data management to form flow efficiency optimization guide data, including: for engineering result management parameters corresponding to the first processing class: when->And->Then form the first type frequency adjustment quantity J n For flow output frequency A n And performing range-based utilization rate adjustment analysis according to the order of the parameter utilization percentages of different engineering real-time parameters in the processing flow from small to large to form parameter utilization rate adjustment information, wherein,when->And->Then form the first type frequency adjustment quantity J n For flow output frequency A n Wherein->When->And->The parameter utilization percentage according to different engineering real-time parameters in the processing flow is->And performing range-based utilization adjustment analysis from small to large to form parameter utilization adjustment information.
For different types of processing, when the optimization guidance of the data management of the engineering result management parameters is carried out, the reference analysis data of the guidance is different because the comparison and judgment results are different. For the first processing class, there are cases where the data trip frequency is low and the utilization rate of the engineering real-time parameters in the processing flow is low during the formation of the engineering result management parameters. Therefore, when the extraction time consumption and the processing waiting time consumption both exceed the threshold value, the difference between the extraction time consumption and the threshold value can be used as a reference quantity for frequency adjustment, and the efficiency of the whole processing flow can be improved by adjusting the utilization rate of the real-time engineering parameters under the condition that the total extraction time sum of the objective quantity of the real-time engineering parameters on the processing flow exceeds the time threshold value.
According to the optimization contrast analysis, performing optimization analysis based on data management to form flow efficiency optimization guide data, including: setting a data extraction time-consuming thresholdAnd parameter processing wait time threshold +.>And time consuming according to data extraction processData extraction latency +.>Parameter processing latency +.>And analyzing the result data by the engineering management parameters, performing the following optimization judgment based on data management to form flow efficiency optimization guide data, including: and for engineering result management parameters corresponding to the second processing class: when-> Then form the second class frequency adjustment quantity J n For flow output frequency A n Wherein, the method comprises the steps of, wherein,
for the engineering result management data corresponding to the second processing class, as the processing flow only has low frequency of forming the engineering result management data, the guiding of improving the efficiency of processing the engineering result management data is mainly realized through adjusting the frequency, and the influence of the engineering real-time parameter validity acquisition time on the processing flow on the engineering result management data acquisition efficiency is not considered any more.
S3: and carrying out optimization analysis based on data management according to the optimization comparison analysis to form flow efficiency optimization guide data.
According to the optimization contrast analysis, performing optimization analysis based on data management to form flow efficiency optimization guide data, including: setting a data extraction time-consuming threshold And parameter processing wait time threshold +.>And time consuming according to data extraction processData extraction latency +.>Parameter processing latency +.>And analyzing the result data by the engineering management parameters, performing the following optimization judgment based on data management to form flow efficiency optimization guide data, including: and for engineering result management parameters corresponding to the third processing class: when->The parameter utilization percentage according to different engineering real-time parameters in the processing flow is->And performing range-based utilization adjustment analysis from small to large to form parameter utilization adjustment information.
For the third processing class, only the engineering real-time parameters required for acquiring engineering result management data exist, so that the effective acquisition efficiency is low. The corresponding optimization guidance can only consider the adjustment of the effective data acquisition time of engineering real-time parameters in the processing flow. Of course, for the engineering result management data of the fourth processing class, since both the time and the engineering real-time parameters meet the requirements, it can be determined that the adjustment is not required for the data management.
Percentage utilization of parameters according to different engineering real-time parameters in a process flowPerforming range-based utilization adjustment analysis from a large order to a small order to form parameter utilization adjustment information, including: parameter utilization percentage according to different engineering real-time parameters in the processing flow >The utilization rate of engineering real-time parameters is sequentially adjusted and defined from big to small, and the parameter range is adjusted and defined after each adjustment and definition>And->Is determined by: if->The number of different engineering real-time parameters of (a) can be satisfied +.>Then at decision satisfied->After stoppingAdjusting and demarcating; if it isThe number of different engineering real-time parameters of (a) cannot be met +.>Then for all of the process flowsCarrying out an adjustment definition of different engineering real-time parameters of (1) and determining +.>
The efficiency of extracting the engineering real-time parameters in the processing flow is adjusted mainly by considering that the lower the utilization rate is, the less effective data can be extracted, and a large amount of invalid data needs to be processed, so that the greater the effective data acquisition time of the engineering real-time parameters is. Therefore, the adjustment is performed in order of small utilization rate, which has positive and obvious influence on the improvement of the efficiency of the whole treatment process.
The method for defining the parameter range of the utilization ratio of the engineering real-time parameters comprises the following steps: obtaining the range of engineering real-time parameters in effective analysis periodAnd +.>The statistics of the frequency of use is carried out on the parameters in the process; setting a use frequency threshold value, and extracting parameters of which the use frequency exceeds the use frequency threshold value to form an adjustment range quantity; and re-determining the adjustment acquisition range of the engineering real-time parameters according to the adjustment range quantity.
The definition of the parameter range mainly considers that when effective data of engineering real-time parameters are acquired, screening is performed in original data, and the excessive range of the original data can cause the increase of screening workload, so that adjustment based on the original data acquisition range can be performed on existing data, the volume of data processing is further reduced, and the efficiency of acquiring the effective data of the engineering real-time parameters is greatly increased.
The invention also provides a data processing management system based on big data, which is applied to the data processing management method based on big data, and comprises an engineering management parameter acquisition unit for acquiring engineering result management parameter data; the management parameter processing information acquisition unit is used for acquiring the extraction processing information and the flow processing information of the engineering result management parameters; the optimization analysis unit is used for acquiring the engineering result management parameter data of the engineering management parameter acquisition unit to perform validity analysis to form engineering management parameter analysis result data, and is used for acquiring the extraction processing information and the flow processing information of the engineering result management parameter of the management parameter processing information acquisition unit to perform optimization analysis to form flow efficiency optimization guide data.
According to the system, basic data for optimizing the engineering result management parameters are acquired by utilizing the engineering management parameter acquisition unit and the management parameter processing information acquisition unit, and meanwhile, reasonable data management analysis is performed by utilizing the optimization analysis unit, so that optimized data information for adjusting the processing flow of the engineering result management parameters and improving the acquisition accuracy is determined.
In summary, the data processing management method and system based on big data provided by the embodiment of the invention have the beneficial effects that:
according to the method, the effectiveness analysis aiming at forming the engineering result management data is carried out by acquiring the engineering result management parameter data, so that the types of processing flows corresponding to different engineering result management parameters are distinguished, the specific conditions of the engineering result management parameters in terms of forming efficiency and use of original data are comprehensively known on the basis of fully acquiring the use processing information of the engineering result management parameters, and further, the guidance parameters for efficiently and accurately acquiring the engineering result management data can be obtained through optimization analysis, the efficient management of the engineering result management data is facilitated, the effectiveness and accuracy of the engineering result management parameter data control are improved, and meanwhile, the efficiency of acquiring the engineering result management parameter is greatly improved.
According to the system, basic data for optimizing the engineering result management parameters are acquired by utilizing the engineering management parameter acquisition unit and the management parameter processing information acquisition unit, and meanwhile, reasonable data management analysis is performed by utilizing the optimization analysis unit, so that optimized data information for adjusting the processing flow of the engineering result management parameters and improving the acquisition accuracy is determined.
In the present invention, "at least one" means one or more, and "a plurality" means two or more. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b, or c may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or plural.
It should be understood that, in various embodiments of the present invention, the sequence numbers of the foregoing processes do not mean the order of execution, and the order of execution of the processes should be determined by the functions and internal logic thereof, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
Those of ordinary skill in the art will appreciate that the elements and method steps of the examples described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or as a combination of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the system, system and unit described above may refer to the corresponding process in the foregoing method embodiment, which is not repeated herein.
In the several embodiments provided by the present invention, it should be understood that the disclosed systems, and methods may be implemented in other ways. For example, the system embodiments described above are merely illustrative, e.g., the division of the elements is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interface, system or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform 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 (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the invention, which are described in detail and are not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (10)
1. A data processing management method based on big data, characterized by comprising:
acquiring engineering result management parameter data, and carrying out validity analysis based on data management to form engineering management parameter analysis result data;
acquiring the extraction processing information and the flow processing information of each engineering result management parameter, and analyzing the optimized comparison parameters to form optimized comparison analysis information;
and carrying out optimization analysis based on data management according to the optimization comparison analysis to form flow efficiency optimization guide data.
2. The big data based data processing management method according to claim 1, wherein the obtaining the engineering result management parameter data and performing validity analysis based on data management to form engineering management parameter analysis result data includes:
Determining different processing flows of the engineering result management parameters, and setting an effective analysis period;
counting the output frequency of all the engineering result management parameters in the effective analysis period to formFlow output frequency A n Wherein n represents the number of different engineering result management parameters;
counting the utilized quantities of different engineering real-time parameters acquired by all engineering result management parameters on corresponding processing flows in the effective analysis period to form a parameter utilization percentageWherein c represents the number of different engineering real-time parameters utilized in the generation process of the engineering result management parameter with the number n;
the flow output frequency A according to different engineering result management parameters n And the percentage of utilization of the parameterAnd analyzing based on the effective processing of the data to form the analysis result data of the engineering management parameters.
3. The big data based data processing management method according to claim 2, wherein the flow output frequency a according to the different engineering result management parameters n And the percentage of utilization of the parameterPerforming analysis based on effective processing of the data to form analysis result data of the engineering management parameters, including:
Setting an output frequency threshold alpha n Parameter utilization threshold beta n Parameter quantity ratio threshold M n And carrying out analysis and judgment of effective processing of the following data on each engineering result management parameter:
if A n ＜α n And in the process of the engineering result management parameter, exceeding c×M n Engineering real-time parameter presence of (2)Determining a corresponding processing flow corresponding to the engineering result management parameter as a first processing class;
if A n ＜α n And in the process of the engineering result management parameter, c is not exceeded n Engineering real-time parameter presence of (2)Determining the corresponding processing flow corresponding to the engineering result management parameter as a second processing class;
if A n ≥α n And in the process of the engineering result management parameter, exceeding c×M n Engineering real-time parameter presence of (2)Determining the corresponding processing flow of the engineering result management parameter as a third processing class;
if A n ≥α n And in the process of the engineering result management parameter, c is not exceeded n Engineering real-time parameter presence of (2)And determining the corresponding processing flow corresponding to the engineering result management parameter as a fourth processing class.
4. The big data based data processing management method according to claim 3, wherein the obtaining the extraction processing information and the flow processing information of each of the engineering result management parameters and analyzing the optimization contrast parameters to form the optimization contrast analysis information comprises:
Obtaining the average time consumption of each extracted and utilized engineering result management parameter, and forming time consumption of data extraction processing
Obtaining the average waiting time of each extracted and utilized engineering result management parameter to form the waiting time of data extraction
The time spent by processing after each engineering real-time parameter in the processing flow corresponding to the engineering result management parameter is obtained to form an effective parameter, and the time spent by processing the formation parameter is spent
5. The big data based data processing management method according to claim 4, wherein the performing an optimization analysis based on data governance according to the optimization comparison analysis to form flow efficiency optimization guide data includes:
setting a data extraction time-consuming thresholdAnd parameter processing wait time threshold +.>And extracting the time-consuming +.>The data extraction waits for a time consuming->The parameter processing waits for a time consuming->And analyzing the result data by the engineering management parameters, performing the following optimization judgment based on data management, and forming the flow efficiency optimization guide data, wherein the method comprises the following steps of:
and for the engineering result management parameters corresponding to the first processing class:
when (when) And->Then form the first type frequency adjustment quantity J n Outputting frequency A to the flow n Performing range-based utilization rate adjustment analysis according to the sequence of the parameter utilization percentages of different engineering real-time parameters in the processing flow from large to small to form parameter utilization rate adjustment information, wherein +_>
When (when)And->Then form the first type frequency adjustment quantity J n Outputting frequency A to the flow n Wherein->
When (when)And->The parameter utilization percentage according to different engineering real-time parameters in the processing flow is->Range-based utilization adjustment partitioning in order of small to largeAnd analyzing to form parameter utilization rate adjustment information.
6. The big data based data processing management method according to claim 4, wherein the performing an optimization analysis based on data governance according to the optimization comparison analysis to form flow efficiency optimization guide data includes:
setting a data extraction time-consuming thresholdAnd parameter processing wait time threshold +.>And extracting the time-consuming +.>The data extraction waits for a time consuming->The parameter processing waits for a time consuming->And analyzing the result data by the engineering management parameters, performing the following optimization judgment based on data management, and forming the flow efficiency optimization guide data, wherein the method comprises the following steps of:
And for the engineering result management parameters corresponding to the second processing class:
when (when)Then form the second class frequency adjustment quantity J n Outputting frequency A to the flow n Wherein, the method comprises the steps of, wherein,
7. the big data based data processing management method according to claim 4, wherein the performing an optimization analysis based on data governance according to the optimization comparison analysis to form flow efficiency optimization guide data includes:
setting a data extraction time-consuming thresholdAnd parameter processing wait time threshold +.>And extracting the time-consuming +.>The data extraction waits for a time consuming->The parameter processing waits for a time consuming->And analyzing the result data by the engineering management parameters, performing the following optimization judgment based on data management, and forming the flow efficiency optimization guide data, wherein the method comprises the following steps of:
and for the engineering result management parameters corresponding to the third processing class:
when (when)The parameter utilization percentage according to different engineering real-time parameters in the processing flow is->And performing range-based utilization adjustment analysis from small to large to form parameter utilization adjustment information.
8. According to claim 5 orThe data processing and management method based on big data as described in 7, wherein the method is characterized in that the parameter utilization percentage of different engineering real-time parameters in the processing flow is calculated Performing range-based utilization adjustment analysis from small to large to form parameter utilization adjustment information, including:
percentage utilization of parameters according to different engineering real-time parameters in a process flowThe utilization rate of engineering real-time parameters is sequentially adjusted and defined from small to large, and the parameter range is adjusted and defined after each adjustment and definition>And->Is determined by:
if it isThe number of different engineering real-time parameters of (a) can be satisfied +.>Then at the judgment that it meetsStopping adjusting and demarcating;
if it isThe number of different engineering real-time parameters of (a) cannot be met +.>Then for all of the process flowsCarrying out an adjustment definition of different engineering real-time parameters of (1) and determining +.>
9. The big data based data processing management method according to claim 8, wherein the defining the parameter range for adjusting the utilization rate of the engineering real-time parameter includes:
obtaining the range of the engineering real-time parameters in the effective analysis periodAnd +.>The statistics of the frequency of use is carried out on the parameters in the process;
setting a use frequency threshold value, and extracting parameters with use frequency exceeding the use frequency threshold value to form an adjustment range quantity;
and re-determining the adjustment acquisition range of the engineering real-time parameters according to the adjustment range quantity.
10. A big data based data processing management system employing the big data based data processing management method of any one of claims 1 to 9, comprising:
the engineering management parameter acquisition unit is used for acquiring engineering result management parameter data;
the management parameter processing information acquisition unit is used for acquiring the extraction processing information and the flow processing information of the engineering result management parameters;
and the optimization analysis unit is used for acquiring the engineering result management parameter data of the engineering management parameter acquisition unit to perform validity analysis to form engineering management parameter analysis result data, and is used for acquiring the extraction processing information and the flow processing information of the engineering result management parameter of the management parameter processing information acquisition unit to perform optimization analysis to form flow efficiency optimization guide data.
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