CN116911644A - Method and device for determining duration index, electronic equipment and storage medium - Google Patents
Method and device for determining duration index, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN116911644A CN116911644A CN202211510574.4A CN202211510574A CN116911644A CN 116911644 A CN116911644 A CN 116911644A CN 202211510574 A CN202211510574 A CN 202211510574A CN 116911644 A CN116911644 A CN 116911644A
- Authority
- CN
- China
- Prior art keywords
- service
- data
- business
- information
- index
- 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 107
- 230000008569 process Effects 0.000 claims abstract description 61
- 238000004458 analytical method Methods 0.000 claims description 33
- 239000000523 sample Substances 0.000 claims description 20
- 238000012216 screening Methods 0.000 claims description 3
- 230000006870 function Effects 0.000 description 7
- 230000000694 effects Effects 0.000 description 5
- 230000001960 triggered effect Effects 0.000 description 5
- 238000004891 communication Methods 0.000 description 4
- 238000012544 monitoring process Methods 0.000 description 4
- 238000006243 chemical reaction Methods 0.000 description 3
- 238000013480 data collection Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 230000009897 systematic effect Effects 0.000 description 3
- 230000000007 visual effect Effects 0.000 description 3
- 235000008694 Humulus lupulus Nutrition 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 2
- 238000012098 association analyses Methods 0.000 description 2
- 230000006399 behavior Effects 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 230000009191 jumping Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000008447 perception Effects 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 230000002776 aggregation Effects 0.000 description 1
- 238000004220 aggregation Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 238000003780 insertion Methods 0.000 description 1
- 230000037431 insertion Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- 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
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Probability & Statistics with Applications (AREA)
- Strategic Management (AREA)
- General Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Mathematical Physics (AREA)
- General Business, Economics & Management (AREA)
- Operations Research (AREA)
- Marketing (AREA)
- Game Theory and Decision Science (AREA)
- Fuzzy Systems (AREA)
- Quality & Reliability (AREA)
- Software Systems (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application discloses a method, a device, electronic equipment and a storage medium for determining a time index, belonging to the technical field of computers, wherein the method comprises the following steps: acquiring a plurality of business data to be analyzed in the business handling process of a user; acquiring data information of at least one step of handling the service according to the plurality of service data to be analyzed; determining a time length index in the business handling process according to the data information of the at least one step; the method solves the problem that the time length index of the data in the business handling process and the business operation process is not counted in the prior art.
Description
Technical Field
The application belongs to the technical field of computers, and particularly relates to a method and a device for determining a time index, electronic equipment and a storage medium.
Background
In recent years, as market competition is more and more intense, how to make business operation analysis, improve business handling efficiency and meet user experience is more and more important for enterprises. Thus, there is a need for a system for business that can monitor and manage the overall process of the business. In the related art, data of business transaction such as business name, acceptance amount, acceptance success rate, system success rate, etc. is generally monitored and counted. However, the service handling process and various durations of the service operation process are not monitored and counted, such as service call duration, performance time consumption, crash/JS anomaly, handling duration, service conversion rate and the like.
Disclosure of Invention
The embodiment of the application provides a method, a device, electronic equipment and a storage medium for determining a time index, which can solve the problem that the time index of data in a business handling process and a business operation process is not counted in the prior art.
In a first aspect, an embodiment of the present application provides a method for determining a duration indicator, where the method includes: acquiring a plurality of business data to be analyzed in the business handling process of a user; acquiring data information of at least one step of handling the service according to the plurality of service data to be analyzed; and determining a time length index in the business handling process according to the data information of the at least one step.
In a second aspect, an embodiment of the present application provides a device for determining a duration indicator, where the device includes: the acquisition module is used for acquiring a plurality of business data to be analyzed in the business handling process of the user; the analysis module is used for acquiring data information of at least one step of handling the service according to the plurality of service data to be analyzed; and the determining module is used for determining the time length index in the business handling process according to the data information of the at least one step.
In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, and a program or instruction stored on the memory and executable on the processor, the program or instruction implementing the steps of the method according to the first aspect when executed by the processor.
In a fourth aspect, embodiments of the present application provide a readable storage medium having stored thereon a program or instructions which when executed by a processor perform the steps of the method according to the first aspect.
In a fifth aspect, an embodiment of the present application provides a chip, where the chip includes a processor and a communication interface, where the communication interface is coupled to the processor, and where the processor is configured to execute a program or instructions to implement a method according to the first aspect.
In the method for determining the time index provided by the application, the collected service data is analyzed to obtain the data information of at least one step of the service, and each time index in the service handling process and the service operation process can be determined according to the data information, so that systematic monitoring of the time index of the data in the service handling process and the service operation process can be realized.
Drawings
Fig. 1 is a flow chart of a method for determining a duration indicator according to an embodiment of the present application;
fig. 2 is a flowchart of another method for determining a duration indicator according to an embodiment of the present application;
FIG. 3 is a flowchart illustrating a method for determining a duration indicator according to an embodiment of the present application;
fig. 4 is a flowchart of a method for determining a further time index according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a device for determining a duration indicator according to an embodiment of the present application;
fig. 6 is a schematic structural view of an electronic device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The method, the device, the electronic equipment and the storage medium for determining the duration index provided by the embodiment of the application are described in detail through specific embodiments and application scenes thereof with reference to the accompanying drawings.
Fig. 1 illustrates a method for determining a duration indicator according to an embodiment of the present application, where the method may be performed by an electronic device, and the electronic device may include: server and/or terminal device. In other words, the method may be performed by software or hardware installed in an electronic device, the method comprising the following steps.
Step 110: and acquiring a plurality of business data to be analyzed in the business handling process of the user.
In one implementation manner, the obtaining the plurality of service data to be analyzed in the service handling process of the user includes: embedding a data acquisition probe into an application end and a service end; and acquiring service data information existing in the service handling process through the data acquisition probe, wherein the service data information comprises service link information, service calling level information, module information related to a service path and instance information of the module.
The service data information comprises service link information, service call level information, module information related to a service path and instance information of the module. The service link information may be log data of each link in the service link, a plurality of interface information of the service function, and/or call relation information among a plurality of interfaces, where each interface information includes an interface address, a request mode, a request parameter, a response parameter, and the like; the service call level information may be layout architecture information of service entries of each level and/or subordinate correspondence information between levels, etc.; the module information related to the service path and the instance information of the module may be function information of different modules and/or instance information of different function modules related in one service path, etc.
The Application end may include a mobile terminal (Application) and a Web end (Web). Illustratively, the app-end probe may be implemented using a software development kit (Software Development Kit, sdk) technology, the web-end probe may be implemented using a scripting language (JavaScript, js) technology, and the server-end probe may be implemented using a Java Agent technology.
In practical application, the sdk probe is implanted into any system program and/or any application program of the app end in advance, so that service data of the app end can be collected through the sdk probe; the js probe is used for collecting performance data of the web end on the js code part; the agent probe is deployed at a java server of the service system and is used for collecting performance data related to a call link under a heterogeneous architecture of the server in the service operation process. The web server is started by the agent probes when the web server is started, then the probes intercept and modify the returned content when each time a page request is received and the content is returned, after the browser renders the page content, the browser automatically executes the js code, and the automatic acquisition of user behavior data is realized by executing the js code in a non-perception manner at the web server. If the service system also has the C++ server, the logs output by the service system are collected and transmitted to the kafka by adopting a flime, and the data are cleaned and split-packed by a data processing center and are sent to the distributed tracking call chain server.
The data acquisition mode is not needed to be modified on the business side, and the automatic page code insertion is carried out in a non-invasive mode.
In the step, the data of the front end operation business process of the user and the call chain data under the heterogeneous architecture are collected through the data collection probe, so that the accumulation of the user business data and the full-end data can be obtained in a cross-channel, cross-platform, cross-equipment and all-around mode, and the high efficiency and the accuracy of data collection are improved.
Step 120: and acquiring data information of at least one step of handling the service according to the plurality of service data to be analyzed.
In one implementation manner, the obtaining, according to the plurality of service data to be analyzed, data information of at least one step of transacting the service includes: and analyzing the plurality of business data to be analyzed one by one according to business steps preset by the server side to obtain data information of at least one step of transacting the business.
As a possible implementation manner, the implementation process of analyzing the plurality of service data to be analyzed one by one according to the service steps predetermined by the server to obtain the data information of at least one step of handling the service may include the following steps 121 to 123, which are as follows.
Step 121: traversing the plurality of business data to be analyzed.
The service data to be analyzed carries N operation parameters, wherein N is an integer greater than or equal to 0. For example, in a business process, the url address generated from a jump from a first page to a second page may include the following parameters: trigger time of jump button, number of clicks of the first page, dwell time of the first page, etc.
It should be noted that the following steps may be further included before traversing the plurality of service data to be analyzed.
Step 1: and storing the data acquired by the probe into a first queue according to the acquisition sequence.
Step 2: and reporting the data of the first queue.
Step 3: and sequentially dequeuing the reported data of the first queue to store the data in the second queue, and sequentially dequeuing the data of the second queue to traverse.
By means of the queue, consistency and consistency of the collected and analyzed data can be guaranteed.
The reporting mode may adopt a requestIdleCallback/setTimeout delay reporting mode, or report in a before unloading callback function, or buffer the data to be reported, and report after a certain number of data is reached. In a preferred mode, the reported data can be cached first, and after the data is cached to a certain number, the reported data is reported by utilizing the requestIdleCallBack/setTimeout delay, and the unreported data is reported uniformly when the page leaves.
Step 122: comparing the operation parameters with the configuration parameters in the parameter configuration table of the business step, and screening out the operation parameters corresponding to the configuration parameters.
It may be understood that the parameter configuration table corresponding to each predetermined service step should include a plurality of feature parameters, where the feature parameters may include a parameter indicating the start of the service, or a parameter indicating the end of the service, and then the operation parameters corresponding to each processing step are screened from the acquired service data.
Step 123: and obtaining a parameter value corresponding to the operation parameter.
And reporting the parameter values corresponding to the screened operation parameters, receiving data through a flime, caching in a kafka, translating the data through a flink sql, and finally storing the data in a database.
In this step 120, by analyzing the acquired business data, the data can be processed at a minimum cost to the desired result required to determine the time duration indicator.
Step 130: and determining a time length index in the business handling process according to the data information of the at least one step.
Illustratively, the duration index in the business process is determined by analyzing the business handling duration module in business operation analysis.
Based on the page information, the request information and the click information data acquired in the step 110, the acquired service instance id and the service step name are used for triggering the page event and the service duration of the click event when a dimension analysis salesman handles the service.
Specifically, the page event directly uses the loading time of the page as the service duration of the service step; the click event needs to count the valid time of the back-end service request triggered by the click, and because one click may trigger multiple back-end requests, the largest end time of all requests minus the smallest start time of all requests needs to be obtained as the valid time of the click step (the service step duration costTime): max (endTime) -Min (startTime). If the time-consuming summation of all back-end requests is triggered by the click event simply, when the triggered back-end requests are initiated simultaneously, the time-consuming summation of all requests is far greater than the actual time-consuming summation of the steps, so that the simple summation is inaccurate, and the effective time obtained according to the method is the real operation time of the click step.
Extracting page jump step information (page_id, oper_ id, pageName, startTime, endTime, costTime, businessName, businessId) aiming at the collected service loading information; the back-end request event (oper_ id, requestId, costTime, businessName, businessId) for the click event (oper_ id, clickId, stepName, businessName, businessId) and its trigger will be combined into one click step (click_id, oper_ id, stepName, startTime, endTime, costTime, businessName, businessId).
For the collected page skip step and click step data, the data with the following dimensions can be analyzed: total number of steps of operation: and taking the total number of times collected by the page skip step (unique identification PageId) and the click step (unique identification clickId) as the total number of times of operation of the salesman under the service instance according to the dimension of the salesman id and the service instance id.
Page number of hops: and taking the total number of times collected by the page jumping step (uniquely identifying the pageId) as the page jumping number of times of the business operator under the business instance according to the business operator id and the business instance id dimension.
The maximum time-consuming steps are as follows: according to the dimension of the business operator id and the dimension of the business instance id, taking the maximum time-consuming step (Max (costTime)) of the page skip step and the clicking step as the maximum time-consuming step of the business operator under the business instance.
Fastest time-consuming steps: according to the dimension of the business operator id and the dimension of the business instance id, the minimum time-consuming step (Min (costTime)) of the page jump step and the clicking step is taken as the fastest time-consuming step of the business operator under the business instance.
The maximum step interval is time-consuming: according to the dimension of the salesman id and the dimension of the business instance id, sequencing all the steps according to the operation time, respectively calculating the time consumption of the step interval between the current step and the last step (selecting the startTime of the current step and the endTime of the last step), and then taking the maximum time consumption of the step interval as the maximum time consumption of the salesman under the business instance.
The data of the dimension can restore the total number of steps operated, the page jump times, the maximum time-consuming step, the fastest time-consuming step and the time-consuming step interval of the maximum step when a salesman handles a certain business. And (3) carrying out index model convergence of the steps according to the service step data information of the system step name, so as to determine the average processing time index of the service step processing.
In one implementation, the determining the duration indicator in the business handling process according to the data information of the at least one step may include the following steps 131-132.
Step 131: and constructing a time length index analysis model.
The time index analysis model is used for evaluating the efficiency of business handling according to the data in the business handling process of the user. The time length index analysis model refers to combing business from different dimensions, and systematically organizing indexes with interrelation of scattered single points. The dimension is divided into a qualitative dimension and a quantitative dimension, wherein the qualitative dimension is mainly a word description class, such as a most clicked page, a most time-consuming step and the like; the quantitative dimension is mainly a numerical description class, such as the total number of operation steps, service call duration and the like.
Optionally, the constructing a duration index analysis model includes obtaining service index configuration information, where the service index configuration information includes at least one index parameter; and generating the duration index analysis model corresponding to the service index configuration information based on each index parameter.
Wherein, the index parameter can be service name, service start address, service end address, each service step name, etc.
In the face of huge data volume, data analysis personnel are difficult to search data from specific business activities, different businesses of different departments and various operation steps of different businesses can be marked with 'tags' by constructing a time length index analysis model, and after data accumulation is completed, if efficiency evaluation is carried out on business handling according to the data in the business handling process of a user, the data can be directly obtained from the time length index analysis model, so that the method is accurate and rapid.
Step 132: inputting the data information of at least one step into a time length index analysis model, and determining the time length index in the business handling process through the time length index analysis model.
It will be appreciated that the data information of the at least one step refers to a plurality of steps that a user may be involved in handling a service, and each step may include a plurality of data information. For example, the user may include a number of operations in the step of logging into the system: the time of verification when the account number or the password is input, the response time of successful login and the like.
In one implementation, step 132 includes: acquiring a data identifier input by a user, and inquiring data information of an operation corresponding to the data identifier; and analyzing the data information to obtain a multi-dimensional time length index result.
The data identifier may be a data source identifier, and is used for querying data matched with the data source identifier. The multi-dimensional time index result includes, but is not limited to, step call duration, step success rate, step call times, step conversion rate, service call duration, service success rate, service call times, service conversion rate, service step time consumption and/or service step interval average time consumption.
In step 130, through monitoring of the time index analysis model, the user experience change can be monitored end to end, the user behavior track can be captured, and user operation skills, application performance and service handling process experience analysis can be performed, so that the experience of users in handling services can be effectively improved, and system support can be provided for optimizing service flows.
In the method for determining the time index provided by the application, the collected service data is analyzed to obtain the data information of at least one step of the service, and each time index in the service handling process and the service operation process can be determined according to the data information, so that systematic monitoring of the time index of the data in the service handling process and the service operation process can be realized.
Fig. 2 shows a specific embodiment of acquiring app-side service data in the present application, which includes the following steps.
Step 201: and opening the APP, and initializing a probe to judge whether the service name configuration is acquired.
Step 202: and judging whether the service name configuration is acquired.
When judging that the service name configuration is not acquired, remotely acquiring the service name; and when judging that the service name configuration exists in the local database, directly using the service name configuration of the local database.
Step 203: and if the service name configuration is not acquired in the step 202, remotely acquiring the service name.
Step 204: if it is determined in step 202 that the service name configuration has been acquired, the local database name configuration is directly used.
Step 205: based on step 204, the user generates a page path each time the page is opened, and matches a specific service name according to the page path.
And 206, judging whether the page path matches the service name. When the matching is judged to be successful, generating a service instance ID, and storing the configuration into a global variable; and when the matching is judged to be unsuccessful, giving up.
Step 207: and judging the successful service name matching in step 206, generating a service instance ID if the successful service name matching is successful, and storing the configuration into a global variable.
Step 208: and acquiring a click event clickid of the user, converting the click button name into a step name, and simultaneously reporting the acquired service instance id to a server for storage.
Step 209: associating the step name, the service instance and the clickid according to the resource request generated by the button, and realizing the serial connection of pages by the bottom layer through the calling relation among the page id, the request id and the click id; and the probe acquires data to rewrite the request end.
Step 210: and (3) whether the service is finished or not is judged by matching the request, the matching is successful, the global variable data is emptied, and the service end identifier is carried when the service end is reported.
Fig. 3 shows a specific embodiment of acquiring web-side service data in an embodiment of the present application, which includes the following steps.
Step 301: under the condition of being compatible with an ie8 browser, when a user clicks a specific service page of the system, the web terminal carries out service coding information disassembly and service instance id generation on a request head or a request parameter of a user operation initiation request, and carries service information when the server terminal responds.
Step 302: in the execution process of the page js, the generated page information, request information and click information carry service codes and service instance ids.
Step 303: and caching the service codes and the service instance id to the browser SessionStorage by taking the current URL as a key.
And 304, when the browser opens the new label, judging whether url pointed by the reference of the current page exists in the SessionStorage.
When judging that the service information does not exist, the service information needs to be acquired again, and the detail is seen in S305; when it is judged that the value does not exist, the value in the cache is used, see S306 for details.
And 305, acquiring service information.
And aiming at step 304, judging that url pointed by reference of the current page does not exist in the SessionStorage, calling a service query interface by using the page request address, acquiring service information corresponding to the address, and caching the service information in the SessionStorage. The service interface performs service name matching according to the request address, and judges whether the service is a service starting step, if yes, a service instance id is generated (the service instance id is the unique id of the service instance, one service instance id corresponds to a complete service, and each service step carries the service instance id). So as to achieve the effect of acquiring service information.
Step 306, using the data in the cache.
And (3) judging that url pointed by reference of the current page exists in the SessionStorage according to the step (304), and reading service information cached in the SessionStorage, wherein the service information comprises a service instance id and a service name.
Step 307: and the business step information is used as associated basic data to realize cross-page serial connection.
The business step information acquired by 305 or 306 is used as association basic data. When a click event is triggered on the new tabbed page opened at step 304, two situations occur, one is loading new page content and the other is doing some information loading on the current page. In either case, a clickId field is added to a request event or a page event triggered by a click event, so that the concatenation of the click event with a back-end request and a page is realized, and meanwhile, a pageId field of the page is added to the collected click event data for concatenating the click event with the page; the cross-page concatenation can be realized through the logic. Meanwhile, when the page resource information is acquired, the pageId field of the page is increased, and the association between the page resource and the page is realized. Finally, the operation of a user is restored to a complete operation step track diagram, wherein clickId is the unique identifier of a click event, pageId is the unique identifier id of a page loading event, one page corresponds to a plurality of click events and a plurality of page resource information; a click event may correspond to multiple back-end request events or a page event.
Another embodiment of the present application will be described with reference to fig. 4. As shown in fig. 4, this embodiment may include: the data acquisition end 410, the data association analysis end 420, the service model generation end 430 and the visual interface display end 440.
The data collection end 410 is configured to collect user front-end operation business process data and call chain data under heterogeneous architecture, and report the collected data through a probe.
The data association analysis end 420 is configured to analyze and store the collected original data by the server.
The service model generating end 430 is configured to construct a duration index analysis model according to the service operation analysis scene index model by using fields such as a service name and an instance id as aggregation dimensions.
The visual interface display end 440 is configured to display, through the front-end visual interface, the business handling process, the performance thereof, and the duration index of the operation analysis.
In this embodiment, based on page information, request information and click information data collected in the user service handling process, page, step and request resource association relations are established, a time index analysis model for handling the service of a service person is constructed, and when a service person handles a certain service, information such as the total number of steps operated, the number of page hops, the maximum time-consuming step, the fastest time-consuming step, the maximum time-consuming step interval time-consuming and the like is restored, so that the time index systematic monitoring is realized, and meanwhile, the service flow is further optimized, the system support is enhanced, the front-end operation and maintenance handling efficiency is improved, and good customer perception is ensured.
The method for determining the time length index according to the embodiment of the present specification is described in detail above with reference to fig. 1 to 4, and a device for determining the time length index according to the embodiment of the present specification is described in detail below with reference to fig. 5.
Fig. 5 shows a schematic structural diagram of a device for determining a duration indicator according to an embodiment of the present disclosure, where, as shown in fig. 5, the device for determining a duration indicator may include: an acquisition module 510, a parsing module 520, a determination module 530.
An obtaining module 510, configured to obtain a plurality of service data to be analyzed in a service handling process of a user; the parsing module 520 is configured to obtain data information of at least one step of handling the service according to the plurality of service data to be analyzed; a determining module 530, configured to determine a duration indicator in the business handling process according to the data information of the at least one step.
In one implementation manner, the parsing module 520 is further configured to parse the plurality of service data to be analyzed one by one according to a service step predetermined by the server, so as to obtain data information of at least one step of handling the service.
In one implementation, the determining module 530 is further configured to construct a duration indicator analysis model, where the duration indicator analysis model is configured to perform efficiency evaluation on service transaction according to data in the service transaction process of the user; inputting the data information of at least one step into a time length index analysis model, and determining the time length index in the business handling process through the time length index analysis model.
In one implementation manner, the parsing module 520 is further configured to traverse the plurality of service data to be analyzed, where the service data to be analyzed carries N operation parameters, and N is an integer greater than or equal to 0; comparing the operation parameters with the configuration parameters in the parameter configuration table of the business step, and screening out the operation parameters corresponding to the configuration parameters; and obtaining a parameter value corresponding to the operation parameter.
In one implementation, the determining module 530 is further configured to obtain service indicator configuration information, where the service indicator configuration information includes at least one indicator parameter; and generating the duration index analysis model corresponding to the service index configuration information based on each index parameter.
In one implementation, the determining module 530 is further configured to obtain a data identifier input by a user, and query data information of a step corresponding to the data identifier; and analyzing the data information to obtain a multi-dimensional time length index result.
In one implementation, the obtaining module 510 is further configured to embed the data acquisition probe into the application end and the server end; and acquiring service data information existing in the service handling process through the data acquisition probe, wherein the service data information comprises service link information, service calling level information, module information related to a service path and instance information of the module.
The device for determining the duration index in the embodiment of the application can be a device, and can also be a component, an integrated circuit or a chip in electronic equipment. The embodiment of the present application is not particularly limited.
The device for determining a duration indicator in the embodiment of the application may be a device with an operating system. The operating system may be an Android operating system, an ios operating system, or other possible operating systems, and the embodiment of the present application is not limited specifically.
The device for determining the duration index provided by the embodiment of the application can realize each process realized in the embodiment of the method of fig. 1, and in order to avoid repetition, the description is omitted here.
Optionally, as shown in fig. 6, an embodiment of the present application further provides an electronic device 600, including a processor 610, a memory 620, and a program or an instruction stored in the memory 620 and capable of running on the processor 610, where the program or the instruction implements each process of the above embodiment of the method when executed by the processor 610, and the process can achieve the same technical effect, and for avoiding repetition, a detailed description is omitted herein.
The embodiment of the application also provides a readable storage medium, and the readable storage medium stores a program or an instruction, which when executed by a processor, implements each process of the above-mentioned embodiment of the method for determining a duration indicator, and can achieve the same technical effects, so that repetition is avoided, and no further description is given here.
Wherein the processor is a processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium such as a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk or an optical disk, and the like.
The embodiment of the application further provides a chip, the chip comprises a processor and a communication interface, the communication interface is coupled with the processor, the processor is used for running a program or instructions, the processes of the embodiment of the method for determining the duration index can be realized, the same technical effects can be achieved, and the repetition is avoided, and the description is omitted here.
It should be understood that the chips referred to in the embodiments of the present application may also be referred to as system-on-chip chips, chip systems, or system-on-chip chips, etc.
It should be noted that, in this document, 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. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. Furthermore, it should be noted that the scope of the methods and apparatus in the embodiments of the present application is not limited to performing the functions in the order shown or discussed, but may also include performing the functions in a substantially simultaneous manner or in an opposite order depending on the functions involved, e.g., the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present application.
The embodiments of the present application have been described above with reference to the accompanying drawings, but the present application is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present application and the scope of the claims, which are to be protected by the present application.
Claims (10)
1. The method for determining the duration index is characterized by comprising the following steps of:
acquiring a plurality of business data to be analyzed in the business handling process of a user;
acquiring data information of at least one step of handling the service according to the plurality of service data to be analyzed;
and determining a time length index in the business handling process according to the data information of the at least one step.
2. The method of claim 1, wherein the obtaining data information of at least one step of transacting the service according to the plurality of service data to be analyzed comprises:
and analyzing the plurality of business data to be analyzed one by one according to business steps preset by the server side to obtain data information of at least one step of transacting the business.
3. The method of claim 1, wherein determining the duration indicator in the business process according to the data information of the at least one step comprises:
constructing a time length index analysis model, wherein the time length index analysis model is used for evaluating the efficiency of business handling according to the data in the business handling process of the user;
inputting the data information of at least one step into a time length index analysis model, and determining the time length index in the business handling process through the time length index analysis model.
4. The method according to claim 2, wherein the step of analyzing the plurality of service data to be analyzed one by one according to the service step predetermined by the server side to obtain data information of at least one step of handling the service includes:
traversing the plurality of business data to be analyzed, wherein the business data to be analyzed carries N operation parameters, and N is an integer greater than or equal to 0;
comparing the operation parameters with the configuration parameters in the parameter configuration table of the business step, and screening out the operation parameters corresponding to the configuration parameters;
and obtaining a parameter value corresponding to the operation parameter.
5. The method of claim 3, wherein said constructing a time duration indicator analysis model comprises:
acquiring service index configuration information, wherein the service index configuration information comprises at least one index parameter;
and generating the duration index analysis model corresponding to the service index configuration information based on each index parameter.
6. The method of claim 3, wherein said inputting the data information of the at least one step into a time length indicator analysis model, and determining the time length indicator in the business process by the time length indicator analysis model comprises:
acquiring a data identifier input by a user, and inquiring data information of a step corresponding to the data identifier;
and analyzing the data information to obtain a multi-dimensional time length index result.
7. The method of claim 1, wherein the obtaining a plurality of business data to be analyzed during business transaction of the user comprises:
embedding a data acquisition probe into an application end and a service end;
and acquiring service data information existing in the service handling process through the data acquisition probe, wherein the service data information comprises service link information, service calling level information, module information related to a service path and instance information of the module.
8. A time length index determining apparatus, comprising:
the acquisition module is used for acquiring a plurality of business data to be analyzed in the business handling process of the user;
the analysis module is used for acquiring data information of at least one step of handling the service according to the plurality of service data to be analyzed;
and the determining module is used for determining the time length index in the business handling process according to the data information of the at least one step.
9. An electronic device comprising a processor, a memory and a program or instruction stored on the memory and executable on the processor, which when executed by the processor, implements the steps of the method for determining a time index according to any one of claims 1 to 7.
10. A readable storage medium, wherein a program or instructions is stored on the readable storage medium, which when executed by a processor, implements the steps of the method for determining a time length indicator according to any one of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211510574.4A CN116911644A (en) | 2022-11-29 | 2022-11-29 | Method and device for determining duration index, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211510574.4A CN116911644A (en) | 2022-11-29 | 2022-11-29 | Method and device for determining duration index, electronic equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116911644A true CN116911644A (en) | 2023-10-20 |
Family
ID=88353668
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211510574.4A Pending CN116911644A (en) | 2022-11-29 | 2022-11-29 | Method and device for determining duration index, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116911644A (en) |
-
2022
- 2022-11-29 CN CN202211510574.4A patent/CN116911644A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107562620B (en) | Automatic buried point setting method and device | |
| US20210216339A1 (en) | Generation of bots based on observed behavior | |
| CN110428127B (en) | Automatic analysis method, user equipment, storage medium and device | |
| CN105446706B (en) | Method and device for evaluating form page use effect and providing original data | |
| CN106815125A (en) | A kind of log audit method and platform | |
| CN109885496B (en) | Test log management method and system | |
| JP6823265B2 (en) | Analytical instruments, analytical systems, analytical methods and analytical programs | |
| CN106293891B (en) | Multidimensional investment index monitoring method | |
| CN112491611A (en) | Fault location system, method, apparatus, electronic device and computer readable medium | |
| CN111552633A (en) | Interface abnormal call testing method and device, computer equipment and storage medium | |
| CN112559306B (en) | User behavior track obtaining method and device and electronic equipment | |
| CN109409948B (en) | Transaction abnormity detection method, device, equipment and computer readable storage medium | |
| CN111124791A (en) | System testing method and device | |
| CN111352969A (en) | Buried point data analysis method and device and electronic equipment | |
| CN111124891A (en) | Access state detection method and device, storage medium and electronic device | |
| US20170109640A1 (en) | Generation of Candidate Sequences Using Crowd-Based Seeds of Commonly-Performed Steps of a Business Process | |
| CN112416800A (en) | Intelligent contract testing method, device, equipment and storage medium | |
| CN110825609B (en) | Service testing method, device and system | |
| CN111506455A (en) | Checking method and device for service release result | |
| CN116911644A (en) | Method and device for determining duration index, electronic equipment and storage medium | |
| CN111045983A (en) | Nuclear power station electronic file management method and device, terminal equipment and medium | |
| CN113609202B (en) | Data processing method and device | |
| CN116109322A (en) | Data acquisition method, data acquisition device, and computer-readable storage medium | |
| CN112579833A (en) | Service association relation obtaining method and device based on user operation data | |
| CN109685662A (en) | Investment data processing method, device, computer equipment and its 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 |