CN111628912B - Resource-related data processing method and device, computer equipment and storage medium - Google Patents
Resource-related data processing method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The application relates to a resource-related data processing method, a resource-related data processing device, a computer device and a storage medium. The method comprises the following steps: acquiring a target resource type identifier and rate conversion related information; acquiring a standard rate time sequence corresponding to the target resource type identifier; calculating according to the rate conversion related information and each standard rate in the standard rate time sequence to obtain target rates respectively corresponding to each standard time information, and generating a target rate time sequence; generating a target resource related data set corresponding to the target rate time sequence, wherein the target resource related data set comprises target resource related data corresponding to each standard time information; and according to the target rate time sequence, target resource related data in the target resource related data set are played back, and the played back data are transmitted to the resource related data transmission equipment to be tested so as to test the performance of the resource related data transmission equipment. The method can improve the test accuracy.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a resource-related data processing method and apparatus, a computer device, and a storage medium.
Background
With the rapid development of economy, the financial market has become an important industry in national economy of China, and makes a great contribution to promoting the growth of national economy. In the market transmission process, the market data transmitted by the market transmission system has a large data volume and high requirements on the reliability and low delay of the market transmission system, so that the market transmission system needs to be tested to ensure the reliability, low delay and stability of the system.
At present, a downstream transmission system is tested through real-time market data sent by a market transmission system, however, the problem of insufficient testing often exists, and the testing accuracy is low.
Disclosure of Invention
In view of the above, it is necessary to provide a resource-related data processing method, device, computer device, and storage medium capable of improving the accuracy of the test, in order to solve the technical problem of low accuracy of the test.
A method of resource-related data processing, the method comprising: acquiring a target resource type identifier and rate conversion related information; acquiring a standard rate time sequence corresponding to the target resource type identifier, wherein the standard rate time sequence comprises standard rates corresponding to a plurality of pieces of standard time information respectively; calculating according to the rate conversion related information and each standard rate in the standard rate time sequence to obtain a target rate corresponding to each standard time information, and generating a target rate time sequence; generating a target resource related data set corresponding to the target rate time sequence, wherein the target resource related data set comprises target resource related data corresponding to each standard time information; and replaying the target resource related data in the target resource related data set according to the target rate time sequence, and transmitting the replayed data to resource related data transmission equipment to be tested so as to test the performance of the resource related data transmission equipment.
In some embodiments, the rate conversion related information includes a target characteristic rate, and the obtaining target rates corresponding to the standard time information by performing calculation according to the rate conversion related information and each standard rate in the standard rate time sequence includes: acquiring characteristic parameters; selecting a standard rate meeting the characteristic parameters from the standard rate time sequence as a standard characteristic rate; calculating the corresponding relation between the standard characteristic rate and the target characteristic rate as a target corresponding relation; and calculating according to the target corresponding relation and the standard rate respectively corresponding to each piece of standard time information in the standard rate time sequence to obtain the target rate respectively corresponding to each piece of standard time information.
In some embodiments, the generating a target resource-related data set corresponding to the target rate time series includes: acquiring a standard data volume corresponding to the standard rate time sequence; calculating according to the target corresponding relation and the standard data volume to obtain a target data volume corresponding to the target rate time sequence; and generating resource related data of the target data volume to obtain a target resource related data set corresponding to the target rate time sequence.
In some embodiments, the obtaining the standard data amount corresponding to the standard rate time series includes: respectively calculating the product of each standard time information and the corresponding standard rate to obtain the intermediate data volume respectively corresponding to each standard time information; and calculating the result of the addition of the intermediate data quantities to serve as the standard data quantity corresponding to the standard rate time series.
In some embodiments, the step of obtaining the standard rate time series comprises: acquiring a monitoring resource related data set, wherein the monitoring resource related data set is obtained by monitoring a target resource in real time, and the monitoring resource related data in the monitoring resource related data set corresponds to resource monitoring time; and generating a model according to the monitoring resource related data set and the rate time sequence to obtain the standard rate time information, taking the target resource as the resource type of the standard rate time sequence, and obtaining the standard time information according to the resource monitoring time.
In some embodiments, the step of deriving the rate time series generative model comprises: acquiring a test resource related data set, inputting the test resource related data set into a target machine learning model, and outputting a prediction rate time sequence; acquiring a target rate time sequence corresponding to the test resource related data set; obtaining a model loss value according to the difference between the predicted speed time sequence and the target speed time sequence; and adjusting a target machine learning model according to the model loss value to obtain the rate time series generation model.
In some embodiments, playing back the target resource-related data in the target resource-related data set in the target rate time series includes: selecting first sending resource related data from the target resource related data set, playing back the sending resource related data, and recording a playback time point corresponding to the first sending resource related data as a first playback time point; determining target standard time information corresponding to the current time point from each standard time information according to the current time point and the head playback time point; selecting target resource related data corresponding to the target standard time information from the target resource related data set; and at the current time point corresponding to the target standard time information, replaying the target resource related data corresponding to the target standard time information.
A resource-related data processing apparatus, the apparatus comprising: the rate transformation related information acquisition module is used for acquiring the type identifier of the target resource and the rate transformation related information; a standard rate time sequence obtaining module, configured to obtain a standard rate time sequence corresponding to the target resource type identifier, where the standard rate time sequence includes standard rates corresponding to multiple pieces of standard time information, respectively; a target rate time sequence generation module, configured to calculate according to the rate conversion related information and each standard rate in the standard rate time sequence, to obtain a target rate corresponding to each standard time information, and generate a target rate time sequence; a target resource related data set generating module, configured to generate a target resource related data set corresponding to the target rate time sequence, where the target resource related data set includes target resource related data corresponding to each piece of standard time information; and the target resource related data playback module is used for playing back the target resource related data in the target resource related data set according to the target rate time sequence, and transmitting the played back data to the resource related data transmission equipment to be tested so as to test the performance of the resource related data transmission equipment.
A computer device comprising a memory storing a computer program and a processor implementing the steps of the above-mentioned resource-related data processing method when executing the computer program.
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 above-mentioned resource-related data processing method.
The method, the device, the computer equipment and the storage medium for processing the resource related data acquire a target resource type identifier and rate conversion related information, acquire a standard rate time sequence corresponding to the target resource type identifier, the standard rate time sequence comprises a plurality of standard rates respectively corresponding to the standard time information, calculate according to the rate conversion related information and each standard rate in the standard rate time sequence to acquire a target rate respectively corresponding to each standard time information, generate a target rate time sequence, generate a target resource related data set corresponding to the target rate time sequence, the target resource related data set comprises target resource related data respectively corresponding to each standard time information, replay the target resource related data in the target resource related data set according to the target rate time sequence, and transmitting the played back data to the resource-related data transmission equipment to be tested so as to test the performance of the resource-related data transmission equipment. The standard rate time sequence reflects the real sending condition of the related data of the resources, and the target rate time sequence is obtained by modifying on the basis of the standard rate time sequence and is consistent with the change trend of the standard rate time sequence, so that the related data set of the target resources is played back according to the target rate time sequence, the rationality of the data is ensured on the premise of enriching the test data, and the test accuracy is improved.
Drawings
FIG. 1 is a diagram of an application environment of a resource-related data processing method in some embodiments;
FIG. 2 is a flow diagram illustrating a method for processing resource-related data according to some embodiments;
FIG. 3 is a flow chart illustrating the target rate obtaining step in some embodiments;
FIG. 4 is a flow diagram illustrating a method for processing resource-related data according to some embodiments;
FIG. 5 is a flow diagram illustrating a method for processing resource-related data according to some embodiments;
FIG. 6 is a flowchart illustrating a standard time information obtaining step in some embodiments;
FIG. 7 is a schematic flow chart of the rate time series model generation step in some embodiments;
FIG. 8 is a schematic flow chart of a target resource-related data playback step in some embodiments;
FIG. 9 is a block diagram of an apparatus for resource-related data processing in some embodiments;
FIG. 10 is a diagram of the internal structure of a computer device in some embodiments.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The resource-related data processing method provided by the application can be applied to the application environment shown in fig. 1. Wherein the first server 102 communicates with the second server 104 over a network.
Specifically, the first server 102 may obtain a target resource type identifier and rate conversion related information, obtain a standard rate time sequence corresponding to the target resource type identifier, where the standard rate time sequence includes standard rates corresponding to a plurality of standard time information, perform calculation according to the rate conversion related information and each standard rate in the standard rate time sequence to obtain a target rate corresponding to each standard time information, generate a target rate time sequence, generate a target resource related data set corresponding to the target rate time sequence, where the target resource related data set includes target resource related data corresponding to each standard time information, replay the target resource related data in the target resource related data set according to the target rate time sequence, and transmit the replayed data to the second server 104, to perform performance testing on the second server 104.
The first server 102 and the second server 104 may be implemented by separate servers or a server cluster composed of a plurality of servers. The first server 102 may be a server corresponding to an upstream resource data transfer facility (e.g., a dealer's market gateway), and the second server 104 may be a server corresponding to a downstream resource data transfer facility (e.g., a dealer's market gateway).
In some embodiments, as shown in fig. 2, a resource-related data processing method is provided, which is described by taking the method as an example applied to the first server 102 in fig. 1, and includes the following steps:
s202, obtaining the type identification of the target resource and the related information of rate conversion.
In particular, the resource may be electronic data, such as a virtual item or a physical item, such as stock, that may be transferred over the internet. The resource type is, for example, a type of market data of a stock, wherein the type of market data includes at least one of a deal market or a quote market. The resource type identifier is used to uniquely identify the resource. The target resource type identification may be selected as desired. The rate conversion related information includes information for converting a rate for increasing the rate or decreasing the rate. The resource type identifier may correspond to a rate time sequence, and the rate transformation related information is used to transform a rate in the rate time sequence corresponding to the target resource type identifier.
S204, a standard rate time sequence corresponding to the target resource type identification is obtained, and the standard rate time sequence comprises standard rates corresponding to a plurality of pieces of standard time information respectively.
Specifically, the standard rate time series is obtained according to the transmission rate of the real resource-related data. The standard time information may be a time range, and the standard rate refers to a rate in the time range corresponding to the standard time information. The standard time information may be set as needed, and may be absolute time or relative time. The resource-related data is, for example, net valuations of funds, which are changing over time.
In some embodiments, the first server may store standard rate time sequences corresponding to a plurality of resource types in advance. The first server may select a standard rate time sequence corresponding to the target resource type identifier from standard rate time sequences corresponding to the multiple resource types, respectively.
In some embodiments, the standard rate time series corresponding to the resource type is obtained according to the monitored resource-related data corresponding to the resource type. Specifically, the first server may perform real-time monitoring on resource-related data of multiple resource types, obtain at least one monitoring resource-related data set corresponding to each of the multiple resource types, and record time information corresponding to the resource-related data. For example, the first server may monitor in real time data sent by a sending device of resource-related data, such as a market gateway of an exchange. The first server may divide the total monitoring time period into a plurality of sub-monitoring time periods, where the time lengths of the sub-monitoring time periods may be the same or different. The first server can count the data volume respectively monitored in each sub-monitoring time period to obtain the sub-data volume respectively corresponding to each sub-monitoring time period. The first server can calculate the ratio of the sub-data amount to the corresponding sub-monitoring time period to obtain the rate corresponding to the sub-monitoring time period, arrange the rates corresponding to the sub-monitoring time periods according to the time sequence to obtain a standard rate time sequence, and take the rate corresponding to the sub-monitoring time period as the standard rate. The first server may obtain the standard time information according to the time information corresponding to the sub-monitoring time period, and specifically, the first server may use the time information corresponding to the sub-monitoring time period as the standard time information, or the first server may calculate a relative time period corresponding to the sub-monitoring time period, and use the time information corresponding to the relative time period as the standard time information, where the first server may calculate a difference between a start time point of the sub-monitoring time period and a start time point of the total monitoring time period, as a start time point of the relative time period, and calculate a difference between an end time point of the sub-monitoring time period and an end time point of the total monitoring time period, as an end time point of the relative time period.
In some embodiments, the first server may analyze a rate time sequence corresponding to at least one monitoring resource related data set corresponding to each resource type, to obtain at least one rate time sequence corresponding to each resource type, and determine a standard rate time sequence corresponding to the resource type according to the at least one rate time sequence corresponding to the resource type. Specifically, the first server may calculate rate time sequences corresponding to a plurality of monitoring resource related data sets corresponding to the resource type a, respectively, and perform calculation according to the rate time sequences to determine a standard rate time sequence corresponding to the resource type a. For example, the first server may count average rates corresponding to the sub-monitoring time periods, use a time sequence formed by the average rates corresponding to the time periods as a standard rate time sequence corresponding to the resource type a, and use the average rate corresponding to the sub-monitoring time periods as a standard rate.
In some embodiments, the first server may input at least one monitoring resource-related data set corresponding to a resource type into the rate time series generation model, and the rate time series generation model may process the monitoring resource-related data set to obtain a standard rate time series corresponding to the resource type.
In some embodiments, the first server may write the resource-related data in the sub-monitoring period and the corresponding sub-monitoring period into a preset data structure template, so as to obtain a resource data structure corresponding to each sub-monitoring period.
And S206, calculating according to the rate conversion related information and each standard rate in the standard rate time sequence to obtain target rates respectively corresponding to each standard time information, and generating a target rate time sequence.
Specifically, the first server may calculate, according to the rate conversion related information, a multiple of a standard rate corresponding to each piece of standard time information, and generate the target rate time series by using the calculated multiple of the standard rate as the target rate.
In some embodiments, the rate transformation related information may include a target characteristic rate corresponding to the characteristic parameter. The characteristic parameter may be a parameter corresponding to a rate type, and the quantity type may include at least one of a maximum rate, a minimum rate, or a flat rate. Wherein, the steady rate refers to a rate in the rate time sequence, the rate of which is kept unchanged for a preset time duration. For example, parameters corresponding to the maximum rate, the minimum rate, and the stationary rate may be denoted by a, b, and c, respectively. The target characteristic rate may be set as desired.
In some embodiments, the first server may obtain a standard feature rate corresponding to the feature parameter from the standard rate time sequence, and obtain target rates corresponding to the respective standard time information according to a relationship between the standard feature rate and the target feature rate. Wherein the target rate is a simulated rate and the target rate time series is a simulated sequence. For example, the stationary rate of the a data is 5 ten thousand per second (w/s), the maximum rate is 10 w/s, the minimum rate is 3 w/s, when the target rate time sequence of the a data is simulated, the target stationary rate corresponding to the target rate time sequence may be set, the first server may calculate the correspondence between the target stationary rate and the stationary rate of the a data, and the target rate is obtained by using the rates of the a data in other time periods according to the correspondence. For example, the target flat rate is set to 10 w/s, since the target flat rate is set to 2 times the flat rate of the a data, the target maximum rate becomes 20 w/s, and the minimum rate is 36 w/s, that is, the rate at any time of the simulated sequence will automatically adapt according to the ratio of the set target characteristic rate to the corresponding real standard characteristic rate, so that the data amount of the total monitoring time length (for example, 24 hours) can be controlled by one characteristic parameter that needs to be set. The generation efficiency of the simulation data is improved.
And S208, generating a target resource related data set corresponding to the target rate time sequence, wherein the target resource related data set comprises target resource related data corresponding to each standard time information.
In particular, the asset-related data refers to data related to an asset, such as market data of a stock market, which may include at least one of a big-disc index or a fluctuation ratio.
In some embodiments, the first server may obtain a standard total data amount of the resource-related data set corresponding to the standard rate time sequence, determine a target total data amount of the resource-related data corresponding to the target rate time sequence according to the standard total data amount, generate resource-related data of the target total data amount, and obtain the target resource-related data set.
In some embodiments, the first server may further calculate the target total data amount according to the target rate time series. Specifically, the first server may further calculate a product of the standard time information and the corresponding target rate to obtain data amounts corresponding to each standard time information, and add the data amounts corresponding to each standard time information to obtain a target total data amount.
S210, replaying the target resource related data in the target resource related data set according to the target rate time sequence, and transmitting the replayed data to the resource related data transmission equipment to be tested so as to perform performance test on the resource related data transmission equipment.
In particular, a resource data transmission device refers to a device that transmits resource-related data, for example, a market gateway. The performance test may include at least one of a stability, latency, and real-time test of the resource data transfer device. The first server may determine data volumes corresponding to each standard time information in the target rate time sequence, select resource-related data corresponding to the data volumes from the target resource-related data set, form each resource-related data corresponding to each standard time information, and send each resource-related data. The first server can uniformly send the relevant data of each resource corresponding to the standard time information.
In some embodiments, the first server may calculate data amounts corresponding to the respective standard time information according to the target rate time sequence, select respective resource-related data corresponding to the first standard time information from the target resource-related data set according to the data amount corresponding to the first standard time information, play back the respective resource-related data corresponding to the first standard time information, and record a start time point of playing back the data corresponding to the first standard time information as a first playback time point.
In some embodiments, the first server may calculate a difference between a start time point of the non-first standard time information and a start time point of the first standard time information, obtain a start time point difference corresponding to each of the non-first standard time information, calculate a sum of the first playback time point and the start time point difference, as a target playback time point of the non-first standard time information, and play back data of the corresponding non-first standard time information at the target playback time point.
In the resource-related data processing method, a target resource type identifier and rate conversion related information are obtained, a standard rate time sequence corresponding to the target resource type identifier is obtained, the standard rate time sequence comprises a plurality of standard rates respectively corresponding to the standard time information, calculation is performed according to the rate conversion related information and each standard rate in the standard rate time sequence to obtain a target rate respectively corresponding to each standard time information, a target rate time sequence is generated, a target resource-related data set corresponding to the target rate time sequence is generated, the target resource-related data set comprises target resource-related data respectively corresponding to each standard time information, the target resource-related data in the target resource-related data set are played back according to the target rate time sequence, and the played back data are transmitted to resource-related data transmission equipment to be tested, so as to perform performance test on the resource-related data transmission equipment. The standard rate time sequence reflects the real sending condition of the related data of the resources, and the target rate time sequence is obtained by modifying on the basis of the standard rate time sequence and is consistent with the change trend of the standard rate time sequence, so that the related data set of the target resources is played back according to the target rate time sequence, the rationality of the data is ensured on the premise of enriching the test data, and the test accuracy is improved.
The data volume corresponding to the data sent by the market gateway of the exchange has a special variation trend, for example, the data volume increases rapidly when the market is opened, and then the increase of the data volume gradually decreases to a relatively stable value, that is, the variation trend of the data sending rate of the market gateway is first increased and then stabilized. By adopting the scheme of the application, the data rate sent in each time period can be simultaneously increased or decreased on the basis of keeping the real rate change trend, namely, the data volume in each time period can be simultaneously decreased or increased under the condition of keeping the real data volume change trend. And the total transmitted data volume can be increased and decreased by a specific multiple on the basis of consistent data volume change trend.
In some embodiments, the rate conversion related information includes a target characteristic rate, and as shown in fig. 3, the calculating according to the rate conversion related information and each standard rate in the standard rate time sequence in step S206 to obtain the target rate corresponding to each standard time information includes:
s302, obtaining characteristic parameters.
Specifically, the characteristic parameter may be a parameter corresponding to a rate type, and the number type may include at least one of a maximum rate, a minimum rate, or a flat rate. The characteristic parameters can be set as required. The characteristic parameter may be preset by the first server, for example, the characteristic parameter may be preset to correspond to a maximum rate. The characteristic parameter may be acquired by the first server from a corresponding terminal, the user may input or select the characteristic parameter on the terminal corresponding to the first server, and the terminal may transmit the characteristic parameter input or selected by the user to the first server.
S304, selecting the standard rate meeting the characteristic parameters from the standard rate time sequence as the standard characteristic rate.
Specifically, the first server may obtain, from the standard rate time series, a standard rate that meets the characteristics of the rate type corresponding to the characteristic parameter, as the standard characteristic rate. For example, when the characteristic parameter corresponds to a steady rate, the first server may obtain a standard rate that meets the characteristics of the steady rate from the standard rate time series as the standard characteristic rate.
S306, calculating the corresponding relation between the standard characteristic rate and the target characteristic rate as the target corresponding relation.
Specifically, the target correspondence may include a multiple relationship between the standard feature rate and the target feature rate. The first server may calculate a ratio of the standard feature rate to the target feature rate, and determine the target correspondence relationship according to the calculated ratio, for example, when the ratio of the standard feature rate to the target feature rate is 2, determine that the target correspondence relationship is that the standard feature rate is 2 times the target feature rate.
And S308, calculating according to the target corresponding relation and the standard rate respectively corresponding to each piece of standard time information in the standard rate time sequence to obtain the target rate respectively corresponding to each piece of standard time information.
Specifically, the first server may determine multiples of the standard feature rate and the target feature rate according to the target correspondence, record the multiples as standard multiples, and calculate products of the standard multiples and each standard rate in the standard rate time sequence, respectively, as target rates corresponding to each standard time information, respectively.
In the above embodiment, the corresponding relationship between the standard characteristic rate and the target characteristic rate is calculated as the target corresponding relationship, and the target speed corresponding to each standard time information in the standard speed time sequence is obtained by calculating according to the target corresponding relationship and the standard speed corresponding to each standard time information in the standard speed time sequence.
In some embodiments, as shown in fig. 4, the step S208 of generating the target resource related data set corresponding to the target rate time series includes:
s402, acquiring a standard data volume corresponding to the standard rate time sequence.
Specifically, the standard data amount refers to the total data amount of the resource-related data set corresponding to the standard rate time series. The first server may store standard data amounts corresponding to the standard rate time series in advance.
S404, calculating according to the target corresponding relation and the standard data quantity to obtain the target data quantity corresponding to the target rate time sequence.
Specifically, the first server may calculate a product of the standard multiple and the standard data amount as a target data amount corresponding to the target rate time series.
S406, generating resource related data of the target data volume to obtain a target resource related data set corresponding to the target rate time sequence.
Specifically, the first server may generate a target amount of resource-related data, and use a set of the target amount of resource-related data as a target resource-related data set. The corresponding relation between each resource related data in the target resource related data set and the marked time information system may not be set, or may be set.
In the above embodiment, the standard data volume corresponding to the standard rate time sequence is obtained, calculation is performed according to the target correspondence and the standard data volume to obtain the target data volume corresponding to the target rate time sequence, resource-related data of the target data volume is generated, and the target resource-related data set corresponding to the target rate time sequence is obtained, so that the target data volume can be automatically generated according to the standard data volume, the resource-related data of the target data volume is rapidly generated, and the generation efficiency of the target resource-related data set is improved.
In some embodiments, as shown in fig. 5, the step S402 of obtaining the standard data amount corresponding to the standard rate time series includes:
and S502, respectively calculating the product of each standard time information and the corresponding standard rate to obtain the intermediate data volume respectively corresponding to each standard time information.
And S504, calculating the result of the addition of the intermediate data quantities to be used as the standard data quantity corresponding to the standard rate time series.
Specifically, the first server may calculate a product of each standard time information and the corresponding standard rate, respectively, to obtain intermediate data volumes corresponding to each standard time information, and use a sum of each intermediate data volume as the standard data volume.
In the above embodiment, the product of each standard time information and the corresponding standard rate is calculated respectively to obtain the intermediate data volume corresponding to each standard time information, and the result of adding each intermediate data volume is calculated to be used as the standard data volume corresponding to the standard rate time sequence, so that the standard data volume can be automatically calculated according to the standard time information and the standard rate, and the efficiency of calculating the standard data volume is improved.
In some embodiments, as shown in fig. 6, the step of obtaining the standard rate time series comprises:
s602, acquiring a monitoring resource related data set, wherein the monitoring resource related data set is obtained by monitoring a target resource in real time, and the monitoring resource related data in the monitoring resource related data set corresponds to resource monitoring time.
S604, generating a model according to the monitoring resource related data set and the rate time sequence to obtain a standard rate time sequence, taking the target resource as the resource type of the standard rate time sequence, and obtaining standard time information according to the resource monitoring time.
Specifically, the resource monitoring time refers to a sub-monitoring period. The rate time series generation model may be pre-trained. The first server may input the monitoring resource-related data set into a rate time series generation model, and the rate time series generation model may process the monitoring resource-related data set to obtain a standard rate time series.
In some embodiments, the first server may use the resource monitoring time as the standard time information, or use a relative time period corresponding to the resource monitoring time as the standard time information. The first server may calculate a difference between a start time point of the sub-monitoring period and a start time point of the total monitoring period as a start time point of the relative period, and calculate a difference between an end time point of the sub-monitoring period and an end time point of the total monitoring period as an end time point of the relative period.
In the above embodiment, the monitoring resource related data set is obtained, the model is generated according to the monitoring resource related data set and the rate time sequence to obtain the standard rate time sequence, the target resource is used as the resource type of the standard rate time sequence, and the monitoring resource related data set is obtained by monitoring the target resource in real time, so that the obtained standard rate time sequence reflects the real sending condition of the resource related data, the authenticity and the validity of the obtained standard rate time sequence are ensured, and the validity of the generated simulated rate time sequence (i.e., the target rate time sequence) is guaranteed.
In some embodiments, as shown in fig. 7, the step of obtaining a rate time series generative model comprises:
s702, acquiring a test resource related data set, inputting the test resource related data set into a target machine learning model, and outputting a predicted rate time sequence, wherein the test resource related data set is a monitoring resource related data set.
In particular, the target machine learning model may include one or more of a variety of neural network models. The first server may use the plurality of monitored resource-related data sets as the test resource-related data sets.
S704, a target rate time sequence corresponding to the relevant data set of the test resource is obtained.
In particular, the target rate time series refers to the true rate time series of the test resource-related data set.
And S706, obtaining a model loss value according to the difference between the predicted rate time sequence and the target rate time sequence.
And S708, adjusting the target machine learning model according to the model loss value to obtain a rate time series generation model.
Specifically, the first server may adjust parameters of the target machine learning model toward a direction in which the model loss value decreases by using a gradient descent method, obtain parameters of the target machine learning model that minimize the overall model loss value, and use the target machine learning model corresponding to the parameters as the rate time series generation model.
In the above embodiment, the test resource-related data set is used to train the target machine learning model, and since the test resource-related data set is the monitoring resource-related data set, the accuracy of the trained model in processing the resource-related data set can be improved, that is, the accuracy of the obtained rate time sequence generation model is high.
In some embodiments, as shown in fig. 8, the playing back the target resource related data in the target resource related data set according to the target rate time sequence in step S210 includes:
s802, selecting the first sending resource related data from the target resource related data set, playing back the first sending resource related data, and recording a playback time point corresponding to the first sending resource related data as a first playback time point.
Specifically, the first sending resource-related data refers to the resource-related data corresponding to the first standard time information. The quantity of the first sending resource related data is the product of the first standard time information and the corresponding target rate.
And S804, determining target standard time information corresponding to the current time point from each piece of standard time information according to the current time point and the first playback time point.
Specifically, the current time point refers to a time point corresponding to the current time, the first server may record the current time point and a first playback time point, calculate a time difference between the current time point and the first playback time point, compare the start time point and the time difference of the standard time information, and use the standard time information corresponding to the comparison when the comparison is consistent as target standard time information corresponding to the current time point.
S806, selecting target resource related data corresponding to the target standard time information from the target resource related data set.
And S808, replaying the target resource related data corresponding to the target standard time information at the current time point corresponding to the target standard time information.
Specifically, the first server may obtain, according to the data size corresponding to the target standard time information, data of a corresponding data size from the target resource-related data set, and play back the obtained data at a current time point corresponding to the target standard time information.
In the above embodiment, the target standard time information corresponding to the current time point is determined from each piece of standard time information according to the current time point and the head playback time point, and the target resource-related data corresponding to the target standard time information is played back at the current time point corresponding to the target standard time information, so that the head playback time point is used as a reference point, and therefore, the target resource-related data corresponding to each piece of target standard time information can be sequentially played back according to the time sequence, and the data playback accuracy is improved.
It should be understood that, although the steps in the flowcharts of the above embodiments are shown in sequence as indicated by the arrows, the steps are not necessarily executed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts of the above embodiments may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.
In some embodiments, as shown in fig. 9, there is provided a resource-related data processing apparatus including: a rate transformation related information acquisition module 902, a standard rate time series acquisition module 904, a target rate time series generation module 906, a target resource related data set generation module 908, and a target resource related data playback module 910, wherein:
a rate transformation related information obtaining module 902, configured to obtain the target resource type identifier and the rate transformation related information.
A standard rate time sequence obtaining module 904, configured to obtain a standard rate time sequence corresponding to the target resource type identifier, where the standard rate time sequence includes standard rates corresponding to multiple pieces of standard time information respectively.
And a target rate time sequence generating module 906, configured to calculate according to the rate conversion related information and each standard rate in the standard rate time sequence, to obtain a target rate corresponding to each standard time information, and generate a target rate time sequence.
A target resource related data set generating module 908, configured to generate a target resource related data set corresponding to the target rate time sequence, where the target resource related data set includes target resource related data corresponding to each standard time information.
The target resource related data playback module 910 is configured to playback target resource related data in the target resource related data set according to the target rate time sequence, and transmit the played back data to the resource related data transmission device to be tested, so as to perform performance test on the resource related data transmission device.
In some embodiments, the rate transformation related information comprises a target characteristic rate, and the target rate time series generation module 906 comprises:
and the characteristic parameter acquisition unit is used for acquiring the characteristic parameters.
And the standard characteristic rate selecting unit is used for selecting the standard rate meeting the characteristic parameters from the standard rate time sequence as the standard characteristic rate.
And the target corresponding relation calculating unit is used for calculating the corresponding relation between the standard characteristic rate and the target characteristic rate as the target corresponding relation.
And the target rate obtaining unit is used for calculating according to the target corresponding relation and the standard rates respectively corresponding to the standard time information in the standard rate time sequence to obtain the target rates respectively corresponding to the standard time information.
In some embodiments, target resource-related data set generation module 908 comprises:
and the standard data volume acquisition unit is used for acquiring the standard data volume corresponding to the standard rate time sequence.
And the target data volume acquisition unit is used for calculating according to the target corresponding relation and the standard data volume to obtain the target data volume corresponding to the target rate time sequence.
And the target resource related data set obtaining unit is used for generating the resource related data of the target data volume to obtain a target resource related data set corresponding to the target rate time sequence.
In some embodiments, the standard data amount obtaining unit is further configured to calculate a product of each standard time information and the corresponding standard rate, respectively, to obtain an intermediate data amount corresponding to each standard time information; and calculating the result of adding the intermediate data quantities to be used as the standard data quantity corresponding to the standard rate time series.
In some embodiments, the apparatus further comprises a standard rate time series derivation module, the standard rate time series derivation module comprising:
and the monitoring resource related data set acquisition unit is used for acquiring a monitoring resource related data set, the monitoring resource related data set is obtained by monitoring the target resource in real time, and the monitoring resource related data in the monitoring resource related data set corresponds to the resource monitoring time.
And the standard rate time sequence obtaining unit is used for generating a model according to the monitoring resource related data set and the rate time sequence to obtain a standard rate time sequence, using the target resource as the resource type of the standard rate time sequence, and obtaining standard time information according to the resource monitoring time.
In some embodiments, the apparatus further comprises a rate-time series generative model obtaining module, the rate-time series generative model obtaining module comprising:
and the test resource related data set acquisition unit is used for acquiring the test resource related data set, inputting the test resource related data set into the target machine learning model and outputting a predicted rate time sequence, wherein the test resource related data set is a monitoring resource related data set.
And the target rate time sequence acquisition unit is used for acquiring a target rate time sequence corresponding to the test resource related data set.
And the model loss value obtaining unit is used for obtaining a model loss value according to the difference between the predicted rate time sequence and the target rate time sequence.
And the rate time sequence generation model obtaining unit is used for adjusting the target machine learning model according to the model loss value to obtain a rate time sequence generation model.
In some embodiments, target resource-related data playback module 910 includes:
and the head playback time point obtaining unit is used for selecting head transmission resource related data from the target resource related data set, playing back the head transmission resource related data, and recording a playback time point corresponding to the head transmission resource related data as a head playback time point.
And the target standard time information determining unit is used for determining target standard time information corresponding to the current time point from each piece of standard time information according to the current time point and the head playback time point.
And the target resource related data selecting unit is used for selecting the target resource related data corresponding to the target standard time information from the target resource related data set.
And the target resource related data playback unit is used for playing back the target resource related data corresponding to the target standard time information at the current time point corresponding to the target standard time information.
For specific limitations of the resource-related data processing apparatus, reference may be made to the above limitations of the resource-related data processing method, which are not described herein again. The respective modules in the resource-related data processing apparatus described above may be implemented in whole or in part by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In some embodiments, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 10. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a resource-related data processing method.
Those skilled in the art will appreciate that the architecture shown in fig. 10 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In some embodiments, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the above-described resource-related data processing method when executing the computer program.
In some embodiments, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, realizes the steps of the above-mentioned resource-related data processing method.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for processing resource-related data, the method comprising:
acquiring a target resource type identifier and rate conversion related information; the rate conversion related information includes information for converting a rate; the rate conversion related information is used for increasing or decreasing the rate; the rate transformation related information is used for transforming the rate in the rate time sequence corresponding to the target resource type identifier;
acquiring a standard rate time sequence corresponding to the target resource type identifier, wherein the standard rate time sequence comprises standard rates corresponding to a plurality of pieces of standard time information respectively; the standard rate is a rate in a time range corresponding to the standard time information;
calculating according to the rate conversion related information and each standard rate in the standard rate time sequence to obtain a target rate corresponding to each standard time information, and generating a target rate time sequence;
generating a target resource related data set corresponding to the target rate time sequence, wherein the target resource related data set comprises target resource related data corresponding to each standard time information;
and replaying the target resource related data in the target resource related data set according to the target rate time sequence, and transmitting the replayed data to resource related data transmission equipment to be tested so as to test the performance of the resource related data transmission equipment.
2. The method according to claim 1, wherein the rate conversion related information includes a target characteristic rate, and the obtaining the target rates respectively corresponding to the standard time information by performing the calculation according to the rate conversion related information and each standard rate in the standard rate time series includes:
acquiring characteristic parameters;
selecting a standard rate meeting the characteristic parameters from the standard rate time sequence as a standard characteristic rate;
calculating the corresponding relation between the standard characteristic rate and the target characteristic rate as a target corresponding relation;
and calculating according to the target corresponding relation and the standard rate respectively corresponding to each piece of standard time information in the standard rate time sequence to obtain the target rate respectively corresponding to each piece of standard time information.
3. The method of claim 2, wherein the generating the target resource-related data set corresponding to the target rate time series comprises:
acquiring a standard data volume corresponding to the standard rate time sequence;
calculating according to the target corresponding relation and the standard data volume to obtain a target data volume corresponding to the target rate time sequence;
and generating resource related data of the target data volume to obtain a target resource related data set corresponding to the target rate time sequence.
4. The method of claim 3, wherein the obtaining the standard data amount corresponding to the standard rate time series comprises:
respectively calculating the product of each standard time information and the corresponding standard rate to obtain the intermediate data volume respectively corresponding to each standard time information;
and calculating the result of the addition of the intermediate data quantities to serve as the standard data quantity corresponding to the standard rate time series.
5. The method of claim 1, wherein the step of obtaining the standard rate time series comprises:
acquiring a monitoring resource related data set, wherein the monitoring resource related data set is obtained by monitoring a target resource in real time, and the monitoring resource related data in the monitoring resource related data set corresponds to resource monitoring time;
and generating a model according to the monitoring resource related data set and the rate time sequence to obtain the standard rate time sequence, taking the target resource as the resource type of the standard rate time sequence, and obtaining the standard time information according to the resource monitoring time.
6. The method of claim 5, wherein the step of deriving the rate-time series generative model comprises:
acquiring a test resource related data set, inputting the test resource related data set into a target machine learning model, and outputting a predicted rate time sequence, wherein the test resource related data set is a monitoring resource related data set;
acquiring a target rate time sequence corresponding to the test resource related data set;
obtaining a model loss value according to the difference between the predicted speed time sequence and the target speed time sequence;
and adjusting a target machine learning model according to the model loss value to obtain the rate time series generation model.
7. The method of claim 1, wherein the playing back the target resource-related data in the target resource-related data set in the target rate time sequence comprises:
selecting first sending resource related data from the target resource related data set, playing back the first sending resource related data, and recording a playback time point corresponding to the first sending resource related data as a first playback time point;
determining target standard time information corresponding to the current time point from each standard time information according to the current time point and the head playback time point;
selecting target resource related data corresponding to the target standard time information from the target resource related data set;
and at the current time point corresponding to the target standard time information, replaying the target resource related data corresponding to the target standard time information.
8. A resource-related data processing apparatus, characterized in that the apparatus comprises:
the rate transformation related information acquisition module is used for acquiring the type identifier of the target resource and the rate transformation related information; the rate conversion related information includes information for converting a rate; the rate conversion related information is used for increasing or decreasing the rate; the rate transformation related information is used for transforming the rate in the rate time sequence corresponding to the target resource type identifier;
a standard rate time sequence obtaining module, configured to obtain a standard rate time sequence corresponding to the target resource type identifier, where the standard rate time sequence includes standard rates corresponding to multiple pieces of standard time information, respectively; the standard rate is a rate in a time range corresponding to the standard time information;
a target rate time sequence generation module, configured to calculate according to the rate conversion related information and each standard rate in the standard rate time sequence, to obtain a target rate corresponding to each standard time information, and generate a target rate time sequence;
a target resource related data set generating module, configured to generate a target resource related data set corresponding to the target rate time sequence, where the target resource related data set includes target resource related data corresponding to each piece of standard time information;
and the target resource related data playback module is used for playing back the target resource related data in the target resource related data set according to the target rate time sequence, and transmitting the played back data to the resource related data transmission equipment to be tested so as to test the performance of the resource related data transmission equipment.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any 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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