CN117389708A - Autopaas-based public number operation data statistics method - Google Patents
Autopaas-based public number operation data statistics method Download PDFInfo
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- CN117389708A CN117389708A CN202311580383.XA CN202311580383A CN117389708A CN 117389708 A CN117389708 A CN 117389708A CN 202311580383 A CN202311580383 A CN 202311580383A CN 117389708 A CN117389708 A CN 117389708A
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- 238000004458 analytical method Methods 0.000 description 26
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- 230000009471 action Effects 0.000 description 3
- 238000007726 management method Methods 0.000 description 3
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- 230000003252 repetitive effect Effects 0.000 description 2
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- 230000009286 beneficial effect Effects 0.000 description 1
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- 238000007405 data analysis Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/48—Program initiating; Program switching, e.g. by interrupt
- G06F9/4806—Task transfer initiation or dispatching
- G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/64—Protecting data integrity, e.g. using checksums, certificates or signatures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
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Abstract
The invention relates to the technical field of natural robots and discloses an Autopaas-based public number operation data statistics method. The public number operation data statistics method based on Autopaas comprises the following steps: the application is executed regularly by using a planning task, the flow capacity is described based on the schema of Autopaas, and the ui operation and execution logic are decoupled, wherein the planning task comprises the following steps: executing tasks, analyzing by a cloud engine, arranging instructions and scheduling instructions, and is characterized in that: the scheduling instruction is used for scheduling the execution task according to the scheduling instruction; the cloud engine is used for realizing the calling of the instruction level, so that the execution time and mode of the task can be controlled, and the accuracy and the integrity of data are ensured. Meanwhile, if errors or failures occur in the execution process, an error result can be returned in time and the flow is terminated, so that the influence on the integrity and accuracy of data is avoided, and the capability of automatically counting public number operation data is realized.
Description
Technical Field
The invention relates to the technical field of natural robots, in particular to an Autopaas-based public number operation data statistics method.
Background
Public number operation data statistics mainly include user analysis, content analysis, menu analysis, and message analysis. User analysis: including user growth and user attribute data analysis. By analyzing the user growth data, the growth trend and the cause of the account fan can be known; by analyzing the user attributes, the situation of the vermicelli can be known more. Content analysis: including mass-distribution analysis and multimedia analysis. The group sending analysis comprises all group sending and single group sending; the multimedia analysis includes all video analysis, a single video analysis, and a single audio analysis. Menu analysis: menu is one way of interacting between public numbers and fans. Message analysis: including message analysis and consumption message keyword analysis.
The current public number operation data statistics are written into or exported from a data table by adopting manual statistics, and the working mode has a plurality of defects: first, the repetitive work is more: the operator is required to repeat the collection, arrangement, statistics and entry of data whenever it is required to collect and analyze public number operation data. This repetitive work is not only inefficient, but is also prone to error. Second, the human cost is higher: with the continuous expansion of the public number operation scale, the amount of data that needs to be counted is also increasing. This means that more operators are required to do this, increasing the manpower cost. Third, data accuracy is difficult to guarantee: in the process of manually counting data, due to the influence of human factors (such as carelessness, fatigue and the like), the accuracy of the data is difficult to ensure. Even some simple data entry errors may lead to errors in subsequent analysis. Fourth, the limiting factor is more: by adopting a mode of manual statistics and data form derivation, operators are required to operate online and by using a computer or a robot. This limits the flexibility and convenience of operation. If a network problem or equipment failure is encountered, the timeliness and integrity of the data may be affected. Therefore, a basic capability based on Autopaas is urgently needed, and the capability of realizing instruction level calling through a cloud engine and helping to realize automatic statistics of public number operation data is realized.
Disclosure of Invention
The invention aims to provide an Autopaas-based public number operation data statistics method for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: an Autopaas-based public number operation data statistics method comprises the following steps:
executing the application at regular time using the planning task;
based on the schema description flow capability of Autopaas, decoupling ui operation and execution logic;
the cloud engine based on Autopaas compiles and analyzes the schema to form an intermediate file, so that the re-execution efficiency is accelerated;
the cloud engine based on Autopaas analyzes the instruction, analyzes the calling link and schedules the instruction;
based on the capacity of Autopaas, relevant type instruction scheduling is configured, and instruction level calling is realized;
the planning task includes: executing tasks, analyzing by a cloud engine, arranging instructions and scheduling instructions, and is characterized in that: the scheduling instruction is connected with the public number connector according to the scheduling instruction.
Preferably, the AIP Gateway is called in the public number connector to judge whether success or not, if failure, an error result is returned and the planned task process is ended.
Preferably, the public number connector invokes AIP Gateway to judge whether the public number connector is successful, and if so, the public number data is imported into the form connector.
Preferably, the table connector calls AIP Gateway to judge whether success or not, if failure, an error result is returned.
Preferably, the form connector invokes AIP Gateway to judge whether success or not, if success, public number data is inserted into the corresponding form.
Preferably, the process of planning the task is ended after the public number data is inserted into the corresponding form.
Preferably, the cloud engine parses the task execution instruction and schedules a corresponding operation.
Compared with the prior art, the invention has the following beneficial effects:
a scheduled task is an application that performs the execution of the task at a specified time, which ensures that the task is triggered and executed at the specified point in time. The execution task is performed in a cloud engine analysis module, which analyzes a preset instruction and performs a corresponding scheduling instruction according to the analysis result. In the scheduling instruction, firstly, AIP Gateway is called in the public number connector to judge whether the scheduling instruction is successful or not. If the connection fails, an erroneous result is returned and the planning task is ended. If the connection is successful, the obtained public number data is imported into the form connector, and then another determination is made in the form connector as to whether the call for AIP Gateway is successful. If the data import fails, an error result is returned. If the data is successfully imported, the public number data is inserted into the corresponding table, and finally the process of the planning task is ended. Through this flow, the ability to automatically count public number operation data can be achieved. The cloud engine is used for realizing the calling of the instruction level, so that the execution time and mode of the task can be controlled, and the accuracy and the integrity of data are ensured. Meanwhile, if errors or failures occur in the execution process, an error result can be returned in time and the flow is terminated, so that the influence on the integrity and accuracy of data is avoided, and the capability of automatically counting public number operation data is realized.
Secondly, the invention adopts a cloud engine to analyze based on Autopaas capability, and then carries out instruction level scheduling, thereby realizing the following capability: the user executes the application at any time without environmental restrictions: the application can be deployed on the cloud, and a user can execute the application at any time by accessing the cloud application through the Internet without installing any environment or configuring any parameters. Thus, the threshold and the operation cost of the user can be greatly reduced, and the usability and convenience of the application are improved; autopaas Yun Jiqun capability scheduling: a large-scale cloud cluster can be constructed and managed to perform efficient resource management and scheduling. Tasks can be distributed to different nodes for parallel processing through analysis of a cloud engine and scheduling of instruction levels, so that the resource advantage of a cloud cluster is fully utilized, and the performance and response speed of an application are improved; autopaas instruction level scheduling, parallel scheduling capability of dependency instructions is not available: for the instructions without correlation, the instructions can be simultaneously distributed to different nodes for parallel processing, so that the execution efficiency of the application is further improved. This capability can help applications better utilize system resources, improving the performance and response speed of the application.
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FIG. 1 is a flow chart of the data flow of the public number based on Autopaas statistics according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, an Autopaas-based public number operation data statistics method includes the following steps:
executing the application at regular time using the planning task;
based on the schema description flow capability of Autopaas, decoupling ui operation and execution logic;
the cloud engine based on Autopaas compiles and analyzes the schema to form an intermediate file, so that the re-execution efficiency is accelerated;
the cloud engine based on Autopaas analyzes the instruction, analyzes the calling link and schedules the instruction;
based on the capacity of Autopaas, relevant type instruction scheduling is configured, and instruction level calling is realized;
the planning task includes: executing tasks, analyzing by a cloud engine, arranging instructions and scheduling instructions, and is characterized in that: the scheduling instruction is connected with a public number connector according to the scheduling instruction, the public number connector is used for calling AIP Gateway to judge whether the scheduling instruction is successful or not, if the scheduling instruction is failed, the public number connector is used for calling AIP Gateway to judge whether the scheduling task is successful or not, if the scheduling instruction is successful, the public number connector is used for leading public number data into a form connector, the form connector is used for calling AIP Gateway to judge whether the scheduling task is successful or not, if the scheduling instruction is failed, the form connector is used for calling AIP Gateway to judge whether the scheduling task is successful or not, if the scheduling instruction is successful, the public number data is inserted into a corresponding form, if the scheduling task is finished, the cloud engine is used for analyzing the execution task instruction and scheduling corresponding operation after the public number data is inserted into the corresponding form.
In embodiment 1 of the present invention, a scheduled task is an application that performs execution tasks at a specified time, which ensures that the task is triggered and executed at the specified point in time. The execution task is performed in a cloud engine analysis module, which analyzes a preset instruction and performs a corresponding scheduling instruction according to the analysis result. In the scheduling instruction, firstly, AIP Gateway is called in the public number connector to judge whether the scheduling instruction is successful or not. If the connection fails, an erroneous result is returned and the planning task is ended. If the connection is successful, the obtained public number data is imported into the form connector, and then another determination is made in the form connector as to whether the call for AIP Gateway is successful. If the data import fails, an error result is returned. If the data is successfully imported, the public number data is inserted into the corresponding table, and finally the process of the planning task is ended. Through this flow, the ability to automatically count public number operation data can be achieved. The cloud engine is used for realizing the calling of the instruction level, so that the execution time and mode of the task can be controlled, and the accuracy and the integrity of data are ensured. Meanwhile, if errors or failures occur in the execution process, an error result can be returned in time and the flow is terminated, so that the influence on the integrity and accuracy of data is avoided, and the capability of automatically counting public number operation data is realized.
In embodiment 2 of the present invention, based on Autopaas capability, a cloud engine is adopted to analyze, and then instruction level scheduling is performed, so that the following capability can be realized: the user executes the application at any time without environmental restrictions: the application can be deployed on the cloud, and a user can execute the application at any time by accessing the cloud application through the Internet without installing any environment or configuring any parameters. Thus, the threshold and the operation cost of the user can be greatly reduced, and the usability and convenience of the application are improved; autopaas Yun Jiqun capability scheduling: a large-scale cloud cluster can be constructed and managed to perform efficient resource management and scheduling. Tasks can be distributed to different nodes for parallel processing through analysis of a cloud engine and scheduling of instruction levels, so that the resource advantage of a cloud cluster is fully utilized, and the performance and response speed of an application are improved; autopaas instruction level scheduling, parallel scheduling capability of dependency instructions is not available: for the instructions without correlation, the instructions can be simultaneously distributed to different nodes for parallel processing, so that the execution efficiency of the application is further improved. This capability can help applications better utilize system resources, improving the performance and response speed of the application.
In embodiment 3 of the present invention, the cloud of the Autopaas execution engine and the establishment of the robot cloud cluster thoroughly change the limitation of the traditional local execution engine. In this way, the user can conduct flow arrangement and execution at the cloud end, and is not limited by local environment and hardware conditions. At the user end, when the user is arranging the flow, the cloud application ipaas instruction can be selected to be used. These instructions can be flexibly inserted into the flow and their order and properties can be recorded in schema. In this way, users are free to define and tailor business processes to meet specific needs. When the cloud engine parses the schema, it will further analyze the input and output dependencies between each instruction. Through the analysis, the cloud engine can accurately judge the dependency between the instructions and rearrange the instructions according to the dependency. This approach helps to optimize the execution efficiency of the process so that tasks can be completed more efficiently. During the cloud engine execution phase, the attributes of each instruction are analyzed in detail. Based on these attributes, the cloud engine can determine the scheduling manner of each instruction. For ipaas instructions, the cloud engine will dispatch them to the api service cluster for processing. This approach enables Autopaas to fully leverage its basic capabilities, enabling instruction level invocation through the cloud engine. In this way, autopaas can help enable the ability to automatically count public number operation data. Through cloud intelligent management, automatic execution and flexible flow arrangement, autopaas can provide powerful data support for public number operation. Autopaas can provide an accurate and efficient solution, both for analysis of user behavior and for insight into market trends.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. An Autopaas-based public number operation data statistics method comprises the following steps:
executing the application at regular time using the planning task;
based on the schema description flow capability of Autopaas, decoupling ui operation and execution logic;
the cloud engine based on Autopaas compiles and analyzes the schema to form an intermediate file, so that the re-execution efficiency is accelerated;
the cloud engine based on Autopaas analyzes the instruction, analyzes the calling link and schedules the instruction;
based on the capacity of Autopaas, relevant type instruction scheduling is configured, and instruction level calling is realized;
the planning task includes: executing tasks, analyzing by a cloud engine, arranging instructions and scheduling instructions, and is characterized in that: the scheduling instruction is connected with the public number connector according to the scheduling instruction.
2. The Autopaas-based public number operation data statistics method of claim 1, wherein: and calling AIP Gateway in the public number connector to judge whether the AIP Gateway is successful or not, and if the AIP Gateway is failed, returning an error result and ending the process of the planned task.
3. The Autopaas-based public number operation data statistics method of claim 1, wherein: and calling AIP Gateway in the public number connector, judging whether the public number connector is successful, and if so, importing the public number data into the form connector.
4. A method for counting public number operation data based on autopas according to claim 3, wherein: and calling AIP Gateway in the form connector, judging whether the AIP Gateway is successful or not, and returning an error result if the AIP Gateway is failed.
5. A method for counting public number operation data based on autopas according to claim 3, wherein: and calling AIP Gateway in the form connector to judge whether the AIP Gateway is successful or not, and if so, inserting public number data into the corresponding form.
6. The method for counting public number operation data based on autopas according to claim 5, wherein: and after the public number data are inserted into the corresponding form, the task scheduling process is ended.
7. The Autopaas-based public number operation data statistics method of claim 1, wherein: and the cloud engine analyzes the instruction for analyzing the execution task and schedules corresponding operation.
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| CN202311580383.XA CN117389708A (en) | 2023-11-23 | 2023-11-23 | Autopaas-based public number operation data statistics method |
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| CN202311580383.XA CN117389708A (en) | 2023-11-23 | 2023-11-23 | Autopaas-based public number operation data statistics method |
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