CN117555913A - Object data updating method and device based on third party platform - Google Patents
Object data updating method and device based on third party platform Download PDFInfo
- Publication number
- CN117555913A CN117555913A CN202311713458.7A CN202311713458A CN117555913A CN 117555913 A CN117555913 A CN 117555913A CN 202311713458 A CN202311713458 A CN 202311713458A CN 117555913 A CN117555913 A CN 117555913A
- Authority
- CN
- China
- Prior art keywords
- data
- monitoring data
- factors
- party platform
- update
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 47
- 238000012544 monitoring process Methods 0.000 claims abstract description 105
- 230000003993 interaction Effects 0.000 description 20
- 238000012545 processing Methods 0.000 description 11
- 230000006870 function Effects 0.000 description 8
- 238000010586 diagram Methods 0.000 description 7
- 230000008569 process Effects 0.000 description 7
- 230000000694 effects Effects 0.000 description 5
- 238000010606 normalization Methods 0.000 description 4
- 230000001960 triggered effect Effects 0.000 description 4
- 238000004891 communication Methods 0.000 description 3
- 238000004590 computer program Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000007246 mechanism Effects 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 230000003247 decreasing effect Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000010295 mobile communication Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000002829 reductive effect Effects 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 230000002776 aggregation Effects 0.000 description 1
- 238000004220 aggregation Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 230000008094 contradictory effect Effects 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 230000003862 health status Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 230000000670 limiting effect Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 235000019633 pungent taste Nutrition 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/23—Updating
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/302—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a software system
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3065—Monitoring arrangements determined by the means or processing involved in reporting the monitored data
- G06F11/3072—Monitoring arrangements determined by the means or processing involved in reporting the monitored data where the reporting involves data filtering, e.g. pattern matching, time or event triggered, adaptive or policy-based reporting
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Computing Systems (AREA)
- Quality & Reliability (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Mathematical Physics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The embodiment of the application provides an object data updating method based on a third party platform, which is applied to a target platform and comprises the following steps: acquiring service state monitoring data and object monitoring data; determining a plurality of factors according to the service state monitoring data and the object monitoring data, wherein each factor is associated with a weight; acquiring indication parameters of the object according to the factors and the corresponding weights; determining an update frequency of the object based on the indication parameter of the object; and acquiring the latest data of the object from the third party platform according to the update frequency of the object so as to execute object data update. According to the technical scheme, the updating frequency of the object data can be intelligently adjusted by integrating the characteristics of the object and various external factors, the application scene is wide, the instantaneity and the effectiveness of the object data can be effectively improved, and therefore the user experience is improved.
Description
Technical Field
The embodiment of the application relates to the technical field of data processing, in particular to an object data updating method, device, computer equipment and computer readable storage medium based on a third party platform.
Background
With the rapid development of live technology and electronic commerce, live platforms can display and promote objects (such as merchandise) from third party platforms for users to browse and select. In this process, if the object data displayed by the live platform and the actual object data in the third party platform are not consistent, the use experience of the user is seriously affected. Thus, the live platform needs to update the object data from the third party platform in time. However, the related update mechanism is relatively single, the real-time performance is poor, and the applicable scene is limited, so that the object data is difficult to obtain and update effectively.
It should be noted that the foregoing is not necessarily prior art, and is not intended to limit the scope of the patent protection of the present application.
Disclosure of Invention
Embodiments of the present application provide a method, an apparatus, a computer device, and a computer readable storage medium for updating object data based on a third party platform, so as to solve or alleviate one or more of the technical problems set forth above.
An aspect of an embodiment of the present application provides an object data updating method based on a third party platform, which is applied to a target platform, and the method includes:
acquiring service state monitoring data and object monitoring data;
Determining a plurality of factors according to the service state monitoring data and the object monitoring data, wherein each factor is associated with a weight;
acquiring indication parameters of the object according to the factors and the corresponding weights;
determining an update frequency of the object based on the indication parameter of the object;
and acquiring the latest data of the object from the third party platform according to the update frequency of the object so as to execute object data update.
Optionally, the plurality of factors includes:
a first set of factors associated with the service status monitoring data; and
A second set of factors associated with the object monitoring data;
the service state monitoring data comprise resource monitoring data of the target platform and database monitoring data of the target platform.
Optionally, the service status monitoring data further includes resource monitoring data of the third party platform.
Optionally, the weight of each factor in the first set of factors is determined by:
acquiring a system idle resource factor of the target platform according to the resource monitoring data of the target platform and the database monitoring data of the target platform;
acquiring a system load factor of the third party platform according to the resource monitoring data of the third party platform;
And respectively configuring weights for the system idle resource factors of the target platform and the system load factors of the third party platform according to preset rules.
Optionally, the weight of each factor in the second set of factors is determined by:
acquiring a plurality of attribute factors of an object according to the object monitoring data;
and respectively configuring weights for each attribute factor according to the attribute type corresponding to each attribute factor and the preset importance degree.
Optionally, determining the update frequency of the object based on the indication parameter of the object includes:
and determining the update frequency of the object according to the indication parameter of the object and a preset time attenuation factor.
Optionally, the method for updating object data based on the third party platform further comprises the following steps:
matching the update frequency of the object with a preset threshold value;
and setting the preset threshold value as the update frequency of the object under the condition that the update frequency of the object is smaller than the preset threshold value.
Optionally, the obtaining, according to the update frequency of the object, the latest data of the object from the third party platform to perform object data update includes:
storing the object into a corresponding delay queue according to the update frequency of the object;
And under the condition that the number of the objects in the delay queue meets a preset value, acquiring the latest data of each object in the delay queue from the third party platform to execute object data updating.
Optionally, the obtaining, according to the update frequency of the object, the latest data of the object from the third party platform to perform object data update includes:
storing the object into a corresponding delay queue according to the update frequency of the object;
and acquiring the latest data of each object in the delay queue from the third party platform at a preset frequency to execute object data updating.
Another aspect of the embodiments of the present application provides an object data updating device based on a third party platform, applied to a target platform, where the device includes:
the first acquisition module is used for acquiring service state monitoring data and object monitoring data;
the first determining module is used for determining a plurality of factors according to the service state monitoring data and the object monitoring data, and each factor is associated with a weight;
the second acquisition module is used for acquiring the indication parameters of the object according to the factors and the corresponding weights;
a second determining module, configured to determine an update frequency of the object based on the indication parameter of the object;
And the updating module is used for acquiring the latest data of the object from the third party platform according to the updating frequency of the object so as to execute object data updating.
Another aspect of an embodiment of the present application provides a computer device, comprising:
at least one processor; and
A memory communicatively coupled to the at least one processor;
wherein: the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method as described above.
Another aspect of the embodiments provides a computer-readable storage medium having stored therein computer instructions which, when executed by a processor, implement a method as described above.
The technical scheme adopted by the embodiment of the application can comprise the following advantages:
service state monitoring data and object monitoring data are collected first, and a plurality of factors affecting update frequency are identified. And acquiring the indication parameters of the object through the factors and the corresponding weights, and further determining the update frequency of the object. And acquiring the latest data of the object from the third party platform according to the determined updating frequency so as to execute the data updating operation. It can be known that the embodiment of the application can intelligently adjust the update frequency of the object data by integrating the characteristics of the object and various external factors, has wide application scene, and can effectively improve the instantaneity and the effectiveness of the object data, thereby improving the user experience.
Drawings
The accompanying drawings illustrate exemplary embodiments and, together with the description, serve to explain exemplary implementations of the embodiments. The illustrated embodiments are for exemplary purposes only and do not limit the scope of the claims. Throughout the drawings, identical reference numerals designate similar, but not necessarily identical, elements.
FIG. 1 schematically illustrates an operation environment diagram of a third party platform based object data updating method according to an embodiment of the present application;
FIG. 2 schematically illustrates a flowchart of a third party platform based object data update method according to an embodiment of the present application;
FIG. 3 is a flow chart schematically illustrating an additional method for updating object data based on a third party platform according to the first embodiment of the present application;
FIG. 4 is an exemplary diagram of an application of a third party platform based object data update method according to an embodiment of the present application;
FIG. 5 schematically illustrates a block diagram of a third party platform based object data updating apparatus according to a second embodiment of the present application; and
Fig. 6 schematically shows a hardware architecture diagram of a computer device according to a third embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
It should be noted that the descriptions of "first," "second," etc. in the embodiments of the present application are for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be regarded as not exist and not within the protection scope of the present application.
In the description of the present application, it should be understood that the numerical references before the steps do not identify the order of performing the steps, but are only used for convenience in describing the present application and distinguishing each step, and thus should not be construed as limiting the present application.
First, a term explanation is provided in relation to the present application:
system load: refers to the workload and resource usage carried by the system.
Normalization: the data is scaled to fall within a specified range. Normalization can be applied to the data preprocessing stage in order to eliminate dimensional differences between the data, so that different features or indices are comparable and help to improve the performance and convergence speed of the model.
Attenuation factor: for measuring the extent of the influence of the creation time on the current situation. The attenuation factor may be based on a time attenuation model, quantifying the attenuation effect of time by modeling a function of time.
Next, in order to facilitate understanding of the technical solutions provided in the embodiments of the present application by those skilled in the art, the following description is made on related technologies:
with the rapid development of live technology and electronic commerce, live platform can show and promote object data from third party platform for user to browse and select. In this process, if the object data displayed by the live platform and the object data in the third party platform are not consistent, the use experience of the user is seriously affected. Thus, the live platform needs to acquire and synchronize object data from the third party platform in time.
However, the related art update mechanism and corresponding drawbacks known to the applicant are as follows:
(1) Timing task full update: this non-differentiated full-scale update strategy is only applicable to objects of limited orders of magnitude, and it is difficult to support tens of millions of levels of synchronous updates. With the continuous increase of the number of objects, problems such as task timeout and the like easily occur, so that the real-time performance is poor and the delay is high. In addition, the old and new objects cannot be distinguished, so that the old objects still occupy service resources in the traffic peak period, and resource waste is caused.
(2) Inert update mechanism: depending on event triggering to update, the passive update needs to be triggered by anchor or operation manual, and is suitable for updating small-scale objects. However, there is hysteresis for old data, and failure to update data effectively may cause a series of problems.
Therefore, the embodiment of the application provides an object data updating technical scheme based on a third party platform. In the technical scheme, the method comprises the following steps: (1) Objective influence factors of all dimensions are comprehensively considered, weights are dynamically adjusted by combining actual scenes and features of the business, and comprehensive scores (indicating parameters) are calculated in a normalized mode. Meanwhile, the time attenuation factor is considered to gradually decrease the update frequency, so that the high-frequency update of hot data and the low-frequency update of cold data are realized, the instantaneity and the effectiveness of object data are effectively improved, and the use experience of a user is further improved. (2) The update strategy is dynamically adjusted according to the system load capacity, and service stability and object data synchronization capacity are considered, so that the problem of object data synchronization of large data volume can be effectively solved, and the potential problem of series service risks caused by large-scale non-differentiated update operation of timing script tasks can be solved. (3) And feeding back data according to actual conditions, running for a period of time, dynamically adjusting and improving parameters, and distributing proper weight ranges to achieve better effects and system performance. Meanwhile, the importance of different factors and the relation between the factors are balanced, and the influence of the factors is ensured to be comprehensively considered. See in particular below.
Finally, for ease of understanding, an exemplary operating environment is provided below.
As shown in fig. 1, the running environment diagram includes: a target platform 2, a third party platform 4 and a network 6. Wherein the target platform 2 and the third party platform 4 may communicate via a network 6.
The target platform 2 may provide data collection computing services, data update services, message queue services, database services, cache services, and the like. For example: the target platform 2 may be configured to send a request to the third party platform 4 according to the update frequency of the object, and perform an object data update operation according to the latest data returned by the third party platform 4.
The third party platform 4 may be a third party e-commerce platform configured to: in response to the request of the target platform 2, the latest data of the object (article) is fed back.
The following describes the technical solution of the present application through a plurality of embodiments, taking the target platform 2 as an execution subject. It should be understood that these embodiments may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein.
Example 1
Fig. 2 schematically shows a flowchart of a third party platform based object data updating method according to an embodiment of the present application.
As shown in fig. 2, the method for updating object data based on the third party platform may include steps S200 to S208, wherein:
step S200, service status monitoring data and object monitoring data are acquired.
Step S202, determining a plurality of factors according to the service state monitoring data and the object monitoring data, wherein each factor is associated with a weight.
Step S204, according to the factors and the corresponding weights, the indication parameters of the object are obtained.
Step S206, based on the indication parameter of the object, determining the update frequency of the object.
Step S208, according to the update frequency of the object, the latest data of the object is obtained from the third party platform to execute object data update.
According to the object data updating method based on the third-party platform, service state monitoring data and object monitoring data are collected first, a plurality of factors affecting updating frequency are identified, and each factor corresponds to one weight. And acquiring the indication parameters of the object through the factors and the corresponding weights, and further determining the update frequency of the object. And acquiring the latest data of the object from the third party platform according to the determined updating frequency so as to execute the data updating operation. It can be known that the embodiment of the application can intelligently adjust the update frequency of the object data by integrating the characteristics of the object (a plurality of factors obtained by analyzing the object monitoring data) and a plurality of external factors (a plurality of factors obtained by analyzing the service state monitoring data), has wide application scene, and can effectively improve the real-time performance and the effectiveness of the object data, thereby improving the user experience.
Each of steps S200 to S208 and optionally other steps are described in detail below in conjunction with fig. 2.
Step S200Service state monitoring data and object monitoring data are acquired.
The service status monitoring data may be a set of monitoring data reported by a plurality of services, and may include, for example, resource utilization monitoring data reported by a system service, resource usage monitoring data reported by a database service, and the like. The service status monitoring data can be used to measure the workload and resource usage of the system bearer.
The object monitoring data may be data that is tracked and collected for attributes, features, and related triggering events of the object for differentiating between the objects.
Step S202And determining a plurality of factors according to the service state monitoring data and the object monitoring data, wherein each factor is associated with a weight.
In practical applications, the update frequency of an object is affected not only by the attribute of the object, but also by other factors such as service states (e.g., load, idle resources, service anomalies). Taking the service state as an example, when the system load is high, the update frequency of the object needs to be properly reduced to reduce the influence on the system performance. Therefore, in this embodiment, multiple factors affecting the update frequency may be identified according to the service status monitoring data and the object monitoring data, where each factor corresponds to a weight, and the influencing factors of each dimension may be comprehensively considered, so as to optimize decision quality and reliability.
There are various schemes for determining factors and assigning weights, for example: and determining each factor and weight thereof according to the actual scene of the service, the service type, the specific requirement of the service, the characteristics of service data, the importance degree of the service and the like. Several exemplary schemes are provided below.
In an alternative embodiment, the plurality of factors may include: a first set of factors associated with the service status monitoring data; and a second set of factors associated with the object monitoring data. The service state monitoring data comprise resource monitoring data of the target platform and database monitoring data of the target platform.
In this embodiment, the service state monitoring data includes resource monitoring data and database monitoring data of the target platform 2, and through these data, the resource utilization condition and processing capability of the target platform 2 can be evaluated, so as to ensure that the update of the object data is performed within a reasonable performance range of the system, and alleviate the influence of the update of the object data on the system performance.
Since it is necessary to rely on the third party platform 4 for object data updates, it is also necessary to consider the availability and limitations of the third party platform 4 at certain specific time periods and activity time points. Thus, in an alternative embodiment, the service status monitoring data may also include resource monitoring data of the third party platform 4 for evaluating the system pressure of the third party platform 4 to reduce over-requests or exceed limits.
The above embodiment can understand the system loads of the target platform 2 and the third party platform 4 by analyzing the service status monitoring data, which is helpful for flexibly deciding the update frequency of the object, adapting to the load change and improving the service stability.
As in the previous embodiments, the plurality of factors may include a first set of factors associated with the service status monitoring data and a second set of factors associated with the object monitoring data. An exemplary process of acquiring each set of factors and their weights is provided below.
In an alternative embodiment, as shown in fig. 3, the weights of the individual factors in the first set of factors are determined by:
and step S300, acquiring a system idle resource factor of the target platform according to the resource monitoring data of the target platform and the database monitoring data of the target platform.
Step S302, according to the resource monitoring data of the third party platform, a system load factor of the third party platform is obtained.
Step S304, respectively configuring weights for the system idle resource factors of the target platform and the system load factors of the third party platform according to preset rules.
Illustratively, the resource monitoring data may include CPU usage of the service, memory usage of the service, disk IO usage of the service, disk usage of the service, and the like. These resource monitoring data may be used to evaluate the resource utilization and processing power of the service. The database monitoring data can comprise database connection number pressure and database update time r t Database master slave delay conditions, database load pressure, etc. These database monitoring data can evaluate the current load and response time of the databaseAnd health status, etc. From the resource monitoring data and the database monitoring data of the target platform 2, a system idle resource factor of the target platform 2 may be determined, which may represent the load-bearing capacity of the target platform 2. From the resource monitoring data of the third party platform 4, a system pressure factor of the third party platform 4 may be determined, which may be representative of the system load of the third party platform 4. And respectively configuring weights for the system idle resource factors of the target platform 2 and the system load factors of the third party platform 4 according to preset rules, such as business requirements, application scenes, service problems and the like. The weight coefficient can be adjusted according to actual conditions. For example: when the conditions of abnormal database or abnormal system service and the like occur, the corresponding weight can be adjusted to 100%, namely, the updating work is stopped temporarily, and the system operation problem is relieved.
In this embodiment, the idle system resource factor of the target platform 2 and the system load factor of the third party platform 4 are respectively determined, and dynamically adjustable weights are respectively configured according to preset rules, so that the decision result can give consideration to both service stability and object data update. And the self-adaptive system load change is adopted, and the object data update with high priority is preferentially ensured when the load pressure is high or the peak period is long, so that the user experience is improved.
In an alternative embodiment, the weights of the individual factors of the second set of factors are determined by: and acquiring a plurality of attribute factors of the object according to the object monitoring data. And respectively configuring weights for each attribute factor according to the attribute type corresponding to each attribute factor and the preset importance degree.
The plurality of attribute factors may include a creation time factor, an access heat factor, an interaction status factor, an interaction anchor level factor, and the like. Wherein, the newer the creation time, the more new the object indicates that the anchor may be adding use or presentation, and may be updated frequently. Thus, the creation time can be taken as one of the factors, and the more new the creation time, the higher the object update priority. The access popularity of the object can represent the popularity of the object, can be determined according to the access quantity or the click quantity of the object, and can be frequently updated. The interaction state factor can represent the heat of a certain object, and can be determined according to the related interaction condition of the object, and the priority of updating the object with more interaction is correspondingly improved. The interactive anchor level factor can be the level and influence of anchor for displaying and popularizing a certain object, and the objects displayed by anchor with higher level can be updated frequently. In some embodiments, the attribute factors may also include update events or the like where the object is manually triggered, and the attribute factors may be determined according to actual requirements to account for more comprehensive influencing factors. According to the attribute type corresponding to each attribute factor and the preset importance degree, the weight can be respectively configured for each attribute factor. For example, the weight of the creation time factor may be configured to be 0.2, the weight of the access heat factor may be configured to be 0.3, the weight of the interaction state factor may be configured to be 0.2, and the interaction host level factor may be configured to be 0.2. Accordingly, the sum of the weights of the system idle resource factor of the target platform 2 and the system load factor of the third party platform 4 is 0.2.
In this embodiment, multiple attribute factors of the object are acquired and weights are allocated, and each attribute is comprehensively considered in the dimension of the object, so that the differentiated update frequency of the object can be obtained, and the series service risk caused by large-scale non-differential update is relieved.
It should be noted that the weight of each factor can be dynamically adjusted according to the actual situation and the feedback data. By continuously adjusting and improving the parameters, proper weights are allocated to each factor so as to achieve better effects and system performance. The weight range of each factor can be comprehensively considered according to the importance of different factors and the relation among the factors, so that the system performance is further improved.
The above embodiments describe schemes and processes for determining a plurality of factors and their weights, and how to determine the update frequency of an object based on the plurality of factors and the corresponding weights will be described below.
Step S204And acquiring the indication parameters of the object according to the factors and the corresponding weights.
A plurality of factors may also be preprocessed before the indicative parameters of the object are acquired. For example, the values of each factor may be normalized so that they fall within the same range of values for subsequent operations. In particular, the method can be realized by linear scaling or other normalization methods.
In practical application, the method of weighted summation, weighted average, multi-factor optimization model and the like can be selected according to the service requirement to obtain the indication parameters of the object. For example, in the case of a glass, the indication parameters of the object = (normalized creation time factor weight) + (normalized access heat x access heat factor weight) + (normalized interaction state x interaction state factor weight) + (normalized interaction anchor level x interaction anchor level weight) + (normalized system free resource x system free resource weight) + (normalized system load x system load factor weight) +.
In the present embodiment, according to a plurality of factors and weights thereof, an indication parameter of an object may be obtained, which may indicate update priority of the object to some extent.
Step S206An update frequency of the object is determined based on the indication parameter of the object.
After the indication parameters of the object are obtained, the update frequency of the object can be finally calculated based on the service requirement, the resource cost and the manual intervention, so that the intelligent management of the update frequency of the object data is realized, and the real-time performance and the effectiveness of the object are improved.
An exemplary scheme is provided below.
In an alternative embodiment, step S206 may include: and determining the update frequency of the object according to the indication parameter of the object and a preset time attenuation factor.
Based on the difference of the creation time of different objects, a time attenuation factor can be introduced to reduce the update priority of the older object and improve the update priority of the new object so as to meet the actual demands. The time decay factor may be a decreasing function over time, for example: an exponential decay function or a logarithmic decay function. For example: from the product of the indication parameter and the time decay factor, the update frequency of the object can be finally calculated. The higher the product of the indication parameter and the time decay factor, the higher the update frequency of the indication object, and the update priority of the plurality of objects can be determined by sorting based on the update frequency. Illustratively, the update frequency calculation formula of the object may be expressed as follows:
update frequency = (α subject dimension + β target platform service system dimension + γ third party platform service system dimension + δ database load dimension) time decay factor.
The alpha, beta, gamma and delta are weight coefficients of all factors, specific weight values can be flexibly adjusted according to actual conditions, and the selection of time attenuation factors can be optimized according to specific service requirements and data characteristics.
In this embodiment, the update frequency of the object is determined by comprehensively considering the time attenuation factor, so that the update frequency of the new object is improved, and the real-time performance and the user experience of the update of the object data are improved.
In an alternative embodiment, the method for updating object data based on the third party platform may further include: matching the update frequency of the object with a preset threshold value; and setting the preset threshold value as the update frequency of the object under the condition that the update frequency of the object is smaller than the preset threshold value.
In this embodiment, if the calculated update frequency of the object is smaller than the preset threshold, it indicates that the update frequency of the object is lower, which may cause untimely or inflexible update of the information. In order to alleviate the problem caused by overlong update interval, the update frequency of the object can be set to be a preset threshold value, so that timeliness and flexibility of information are ensured. The method can ensure that the object data can be updated within a certain time, and can ensure the timeliness of information update even if the original calculation result is lower than the threshold value.
The above embodiments introduce a method and a process for obtaining the update frequency of an object, and a data update scheme of the object will be described below.
Step S208And acquiring the latest data of the object from the third party platform according to the updating frequency of the object so as to execute object data updating.
After determining the update frequency of the object, the update of the object data may be performed by acquiring the latest data of the object from the third party platform based on the update frequency in combination with various manners of periodic acquisition, time-triggered acquisition, condition-triggered acquisition, incremental update, and the like.
In this embodiment, the latest data of the object is obtained according to the update frequency of the object, so that the object data can be updated timely and effectively, and meanwhile, the stability of the service can be considered.
An exemplary scheme for multiple data updates is provided below.
In an alternative embodiment, the step S208 may include: and storing the object into a corresponding delay queue according to the update frequency of the object. And under the condition that the number of the objects in the delay queue meets a preset value, acquiring the latest data of each object in the delay queue from the third party platform to execute object data updating.
For example, a plurality of message delay queues may be pre-established. The plurality of delay queues may be partitioned according to different update frequencies (e.g., multiple levels of minutes, hours, days, weeks, etc.). And determining a time point of next update according to the update frequency of the object, storing the object into a corresponding delay queue, and waiting for processing. In this embodiment, when the number of objects in the delay queue satisfies the preset value X, aggregation processing, that is, batch request update, may be performed, so as to improve the processing capability.
In an alternative embodiment, the step S208 may further include: and storing the object into a corresponding delay queue according to the update frequency of the object. And acquiring the latest data of each object in the delay queue from the third party platform at a preset frequency to execute object data updating.
In this embodiment, when a certain time is satisfied, the aggregate request batch update is performed on each object in the delay queue, so that the data processing cost can be effectively reduced, the flexibility can be improved, and the resources can be saved.
To make this application easier to understand, an exemplary application is provided below in connection with fig. 4.
S11, acquiring service state monitoring data and object monitoring data.
And acquiring the creation time, access heat data, interaction state, interaction anchor level of each object, the bearing capacity of the current service (target platform 2), the system pressure of the third party platform 4 service and the like.
S12, determining each factor and normalizing the data.
For each factor, the value is normalized so as to be within the same value range. This may be achieved by linear scaling or other normalization methods.
S13, determining weights.
Each factor is assigned a weight according to traffic demand and importance. For example, assume that the weight of the creation time is 0.2, the weight of the access hotness is 0.3, the weight of the interaction state is 0.2, the weight of the interaction anchor level is 0.1, and the weight of the load capacity of the current service and the system pressure of the third party service is 0.2.
S14, calculating comprehensive scores (indicating parameters).
For each object, multiplying each normalized factor value by a corresponding weight and adding them to obtain the composite score of the object.
Comprehensive scoring: (normalized creation time x creation time factor weight) + (normalized access heat x access heat factor weight) + (normalized interaction state x interaction state factor weight) + (normalized interaction anchor level x interaction anchor level weight) + (normalized system free resources x system free resources weight) + (normalized system load x system load factor weight) +.
And S15, introducing a time attenuation factor, and determining the update frequency according to the product of the comprehensive score and the time attenuation factor.
The time decay factor may be introduced to account for differences in creation time of objects, such that newer objects are weighted higher. The attenuation factor may be a decreasing function over time, such as an exponential or logarithmic attenuation function.
And sorting all the objects according to the comprehensive scores of the objects multiplied by the time attenuation factors. The higher the product of the score multiplied by the time decay factor, the higher the update frequency of the object.
S16, adding the target data into a delay message queue, and triggering the update of the target data based on preset conditions.
Calculating the update frequency of the object and the next update time point of the object, distinguishing the dimensions, putting the dimensions into delay queues with different dimensions, waiting for processing, and repeating the steps.
The delay queues are divided into a plurality of levels of minutes, hours, days, weeks, etc. according to different update dimensions. And the delay queue updates the aggregate batch request according to a certain time or when a preset number of objects are met.
In this exemplary application: (1) Objective influence factors of all dimensions are comprehensively considered, weights are dynamically adjusted by combining actual scenes and features of the business, and comprehensive scores (indicating parameters) are calculated in a normalized mode. Meanwhile, the time attenuation factor is considered to gradually decrease the update frequency, so that the high-frequency update of hot data and the low-frequency update of cold data are realized, the instantaneity and the effectiveness of object data are effectively improved, and the use experience of a user is further improved. (2) The update strategy is dynamically adjusted according to the system load capacity, and service stability and object data synchronization capacity are considered, so that the problem of object data synchronization of large data volume can be effectively solved, and the potential problem of series service risks caused by a large number of non-differentiated update operations of the timing script job can be solved. (3) And feeding back data according to actual conditions, running for a period of time, dynamically adjusting and improving parameters, and distributing proper weight ranges to achieve better effects and system performance. Meanwhile, the importance of different factors and the relation between the factors are balanced, and the influence of the factors is ensured to be comprehensively considered.
Example two
Fig. 5 schematically shows a block diagram of an object data updating apparatus based on a third party platform according to a second embodiment of the present application, which is applied to a target platform and may be divided into one or more program modules, which are stored in a storage medium and executed by one or more processors, to complete the embodiments of the present application. Program modules in the embodiments of the present application refer to a series of computer program instruction segments capable of implementing specific functions, and the following description specifically describes the functions of each program module in the embodiment. As shown in fig. 5, the apparatus 1000 may include: a first acquisition module 1100, a first determination module 1200, a second acquisition module 1300, a second determination module 1400, and an update module 1500, wherein:
a first obtaining module 1100, configured to obtain service status monitoring data and object monitoring data;
a first determining module 1200, configured to determine a plurality of factors according to the service status monitoring data and the object monitoring data, where each factor is associated with a weight;
a second obtaining module 1300, configured to obtain an indication parameter of the object according to the multiple factors and the corresponding weights;
a second determining module 1400, configured to determine an update frequency of the object based on the indication parameter of the object;
An updating module 1500, configured to obtain, according to the update frequency of the object, the latest data of the object from the third party platform to perform object data updating.
As an alternative embodiment, the plurality of factors includes:
a first set of factors associated with the service status monitoring data; and
A second set of factors associated with the object monitoring data;
the service state monitoring data comprise resource monitoring data of the target platform and database monitoring data of the target platform.
As an alternative embodiment, the service status monitoring data further includes resource monitoring data of the third party platform.
As an alternative embodiment, the first determining module 1200 is further configured to:
acquiring a system idle resource factor of the target platform according to the resource monitoring data of the target platform and the database monitoring data of the target platform;
acquiring a system load factor of the third party platform according to the resource monitoring data of the third party platform;
and respectively configuring weights for the system idle resource factors of the target platform and the system load factors of the third party platform according to preset rules.
As an alternative embodiment, the first determining module 1200 is further configured to:
acquiring a plurality of attribute factors of an object according to the object monitoring data;
and respectively configuring weights for each attribute factor according to the attribute type corresponding to each attribute factor and the preset importance degree.
The second determining module 1400 is further configured to:
and determining the update frequency of the object according to the indication parameter of the object and a preset time attenuation factor.
As an alternative embodiment, the apparatus 1000 is further configured to:
matching the update frequency of the object with a preset threshold value;
and setting the preset threshold value as the update frequency of the object under the condition that the update frequency of the object is smaller than the preset threshold value.
As an alternative embodiment, the update module 1500 is further configured to:
storing the object into a corresponding delay queue according to the update frequency of the object;
and under the condition that the number of the objects in the delay queue meets a preset value, acquiring the latest data of each object in the delay queue from the third party platform to execute object data updating.
As an alternative embodiment, the update module 1500 is further configured to:
Storing the object into a corresponding delay queue according to the update frequency of the object;
and acquiring the latest data of each object in the delay queue from the third party platform at a preset frequency to execute object data updating.
Example III
Fig. 6 schematically illustrates a hardware architecture diagram of a computer device 10000 adapted to implement a third party platform based object data updating method according to a third embodiment of the present application. In some embodiments, computer device 10000 may be a smart phone, a wearable device, a tablet, a personal computer, a vehicle terminal, a gaming machine, a virtual device, a workstation, a digital assistant, a set top box, a robot, or the like. In other embodiments, the computer device 10000 may be a rack server, a blade server, a tower server, or a rack server (including a stand-alone server, or a server cluster composed of multiple servers), or the like. As shown in fig. 6, the computer device 10000 includes, but is not limited to: the memory 10010, processor 10020, network interface 10030 may be communicatively linked to each other via a system bus. Wherein:
memory 10010 includes at least one type of computer-readable storage medium including flash memory, hard disk, multimedia card, card memory (e.g., SD or DX memory), random Access Memory (RAM), static Random Access Memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, and the like. In some embodiments, memory 10010 may be an internal storage module of computer device 10000, such as a hard disk or memory of computer device 10000. In other embodiments, the memory 10010 may also be an external storage device of the computer device 10000, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the computer device 10000. Of course, the memory 10010 may also include both an internal memory module of the computer device 10000 and an external memory device thereof. In this embodiment, the memory 10010 is generally used to store an operating system and various application software installed on the computer device 10000, such as program codes of an object data updating method based on a third party platform. In addition, the memory 10010 may be used to temporarily store various types of data that have been output or are to be output.
The processor 10020 may be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor, or other chip in some embodiments. The processor 10020 is typically configured to control overall operation of the computer device 10000, such as performing control and processing related to data interaction or communication with the computer device 10000. In this embodiment, the processor 10020 is configured to execute program codes or process data stored in the memory 10010.
The network interface 10030 may comprise a wireless network interface or a wired network interface, which network interface 10030 is typically used to establish a communication link between the computer device 10000 and other computer devices. For example, the network interface 10030 is used to connect the computer device 10000 to an external terminal through a network, establish a data transmission channel and a communication link between the computer device 10000 and the external terminal, and the like. The network may be a wireless or wired network such as an Intranet (Intranet), the Internet (Internet), a global system for mobile communications (Global System of Mobile communication, abbreviated as GSM), wideband code division multiple access (Wideband Code Divi sion Multiple Access, abbreviated as WCDMA), a 4G network, a 5G network, bluetooth (bluetooth), wi-Fi, etc.
It should be noted that fig. 6 only shows a computer device having components 10010-10030, but it should be understood that not all of the illustrated components are required to be implemented, and that more or fewer components may be implemented instead.
In this embodiment, the method for updating object data based on the third party platform stored in the memory 10010 may be further divided into one or more program modules and executed by one or more processors (such as the processor 10020) to complete the embodiments of the present application.
Example IV
The present application further provides a computer readable storage medium having a computer program stored thereon, wherein the computer program when executed by a processor implements the steps of the third party platform based object data updating method in the embodiments.
In this embodiment, the computer-readable storage medium includes a flash memory, a hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEP ROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, and the like. In some embodiments, the computer readable storage medium may be an internal storage unit of a computer device, such as a hard disk or a memory of the computer device. In other embodiments, the computer readable storage medium may also be an external storage device of a computer device, such as a plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash memory Card (Flash Card), etc. that are provided on the computer device. Of course, the computer-readable storage medium may also include both internal storage units of a computer device and external storage devices. In this embodiment, the computer readable storage medium is typically used to store an operating system and various application software installed on the computer device, for example, program code of an object data updating method based on a third party platform in the embodiment, and the like. Furthermore, the computer-readable storage medium may also be used to temporarily store various types of data that have been output or are to be output.
It will be apparent to those skilled in the art that the modules or steps of the embodiments of the present application described above may be implemented in a general-purpose computer device, they may be concentrated on a single computer device, or distributed across a network of multiple computer devices, or they may alternatively be implemented in program code executable by a computer device, so that they may be stored in a storage device for execution by a computer device, and in some cases, the steps shown or described may be performed in an order different from that shown or described herein, or they may be separately fabricated into individual integrated circuit modules, or a plurality of modules or steps in them may be fabricated into a single integrated circuit module. Thus, embodiments of the present application are not limited to any specific combination of hardware and software.
It should be noted that the foregoing is only a preferred embodiment of the present application, and is not intended to limit the scope of the patent protection of the present application, and all equivalent structures or equivalent processes using the descriptions and the contents of the present application or direct or indirect application to other related technical fields are included in the scope of the patent protection of the present application.
Claims (12)
1. An object data updating method based on a third party platform, which is applied to a target platform, the method comprising:
acquiring service state monitoring data and object monitoring data;
determining a plurality of factors according to the service state monitoring data and the object monitoring data, wherein each factor is associated with a weight;
acquiring indication parameters of the object according to the factors and the corresponding weights;
determining an update frequency of the object based on the indication parameter of the object;
and acquiring the latest data of the object from the third party platform according to the update frequency of the object so as to execute object data update.
2. The method of claim 1, wherein the plurality of factors comprises:
a first set of factors associated with the service status monitoring data; and
A second set of factors associated with the object monitoring data;
the service state monitoring data comprise resource monitoring data of the target platform and database monitoring data of the target platform.
3. The method of claim 2, wherein the service status monitoring data further comprises resource monitoring data of the third party platform.
4. A method according to claim 3, wherein the weight of each factor in the first set of factors is determined by:
acquiring a system idle resource factor of the target platform according to the resource monitoring data of the target platform and the database monitoring data of the target platform;
acquiring a system load factor of the third party platform according to the resource monitoring data of the third party platform;
and respectively configuring weights for the system idle resource factors of the target platform and the system load factors of the third party platform according to preset rules.
5. The method of claim 2, wherein the weights of the individual factors in the second set of factors are determined by:
acquiring a plurality of attribute factors of an object according to the object monitoring data;
and respectively configuring weights for each attribute factor according to the attribute type corresponding to each attribute factor and the preset importance degree.
6. The method according to any one of claims 1 to 5, wherein determining the update frequency of the object based on the indication parameter of the object comprises:
and determining the update frequency of the object according to the indication parameter of the object and a preset time attenuation factor.
7. The method according to any one of claims 1 to 5, further comprising:
matching the update frequency of the object with a preset threshold value;
and setting the preset threshold value as the update frequency of the object under the condition that the update frequency of the object is smaller than the preset threshold value.
8. The method according to any one of claims 1 to 5, wherein the obtaining the latest data of the object from the third party platform to perform object data update according to the update frequency of the object comprises:
storing the object into a corresponding delay queue according to the update frequency of the object;
and under the condition that the number of the objects in the delay queue meets a preset value, acquiring the latest data of each object in the delay queue from the third party platform to execute object data updating.
9. The method according to any one of claims 1 to 5, wherein the obtaining the latest data of the object from the third party platform to perform object data update according to the update frequency of the object comprises:
storing the object into a corresponding delay queue according to the update frequency of the object;
and acquiring the latest data of each object in the delay queue from the third party platform at a preset frequency to execute object data updating.
10. An object data updating apparatus based on a third party platform, applied to a target platform, the apparatus comprising:
the first acquisition module is used for acquiring service state monitoring data and object monitoring data;
the first determining module is used for determining a plurality of factors according to the service state monitoring data and the object monitoring data, and each factor is associated with a weight;
the second acquisition module is used for acquiring the indication parameters of the object according to the factors and the corresponding weights;
a second determining module, configured to determine an update frequency of the object based on the indication parameter of the object;
and the updating module is used for acquiring the latest data of the object from the third party platform according to the updating frequency of the object so as to execute object data updating.
11. A computer device, comprising:
at least one processor; and
A memory communicatively coupled to the at least one processor; wherein:
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 9.
12. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein computer instructions which, when executed by a processor, implement the method of any of claims 1 to 9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311713458.7A CN117555913A (en) | 2023-12-13 | 2023-12-13 | Object data updating method and device based on third party platform |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311713458.7A CN117555913A (en) | 2023-12-13 | 2023-12-13 | Object data updating method and device based on third party platform |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117555913A true CN117555913A (en) | 2024-02-13 |
Family
ID=89812682
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311713458.7A Pending CN117555913A (en) | 2023-12-13 | 2023-12-13 | Object data updating method and device based on third party platform |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117555913A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117950703B (en) * | 2024-03-26 | 2024-05-31 | 成都赛力斯科技有限公司 | Self-adaptive updating method and device for dimension data, electronic equipment and storage medium |
-
2023
- 2023-12-13 CN CN202311713458.7A patent/CN117555913A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117950703B (en) * | 2024-03-26 | 2024-05-31 | 成都赛力斯科技有限公司 | Self-adaptive updating method and device for dimension data, electronic equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106959894B (en) | Resource allocation method and device | |
| US7668703B1 (en) | Determining required capacity for a resource | |
| US20090077235A1 (en) | Mechanism for profiling and estimating the runtime needed to execute a job | |
| US9292336B1 (en) | Systems and methods providing optimization data | |
| CN108459905B (en) | Resource pool capacity planning method and server | |
| CN114500339B (en) | Node bandwidth monitoring method and device, electronic equipment and storage medium | |
| CN108833592A (en) | Cloud host schedules device optimization method, device, equipment and storage medium | |
| CN110569170A (en) | method, device and equipment for evaluating utilization rate of server and storage medium thereof | |
| CN116701001B (en) | Target task allocation method and device, electronic equipment and storage medium | |
| CN112565391A (en) | Method, apparatus, device and medium for adjusting instances in an industrial internet platform | |
| CN111258854B (en) | Model training method, alarm method based on prediction model and related device | |
| CN117555913A (en) | Object data updating method and device based on third party platform | |
| CN113553180B (en) | Container scheduling method and device and electronic equipment | |
| CN111796934B (en) | Task issuing method and device, storage medium and electronic equipment | |
| CN114676177A (en) | Financial index determination method, device, equipment, medium and product | |
| CN114490078A (en) | Dynamic capacity reduction and expansion method, device and equipment for micro-service | |
| CN114612037A (en) | Warehouse information management method and system | |
| CN114090201A (en) | Resource scheduling method, device, equipment and storage medium | |
| CN112069017A (en) | Business system monitoring method and device | |
| CN115242626B (en) | Cloud resource allocation prediction method, device, equipment, storage medium and program product | |
| CN116069513B (en) | Cost determination method, device, electronic equipment and storage medium | |
| TW202402088A (en) | Prediction system for 5g dedicated network slicing resource, method and computer readable medium thereof | |
| CN114218325A (en) | Data synchronization method and device, electronic equipment and storage medium | |
| CN112181647A (en) | Method, device and system for updating node state in container cluster | |
| CN113919903A (en) | Method and device for determining resource information, server and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |