Publishing state prediction method and device, equipment, medium and program

Abstract

The embodiment of the invention discloses a publishing state prediction method, which comprises the following steps: acquiring first predicted publishing reference time and real-time publishing reference time of a target publishing task in a target publishing object, the target publishing object comprising at least one target publishing task; determining a task release state of the target release task according to the first predicted release reference time and the real-time release reference time; and predicting the release state of the target release object according to the task release state of the at least one target release task to obtain a predicted release state of the target release object. According to the technical scheme, the publishing state of the publishing object can be predicted, and the publishing efficiency of the publishing object is improved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of computer application technology, and in particular, to a release status prediction method, device, equipment, medium and program. Background Art

[0002] As the business of an enterprise gradually expands, the corresponding business system also needs to be frequently updated to release more new business functions, so that the online business modules can support more functions and the various business functions in the business system can provide more comprehensive services to users. Among them, each object that needs to be published will have one or more subtasks that need to be published, and in the process of publishing the published object, some publishing problems often arise.

[0003] In the existing technology, most companies choose to launch an automated publishing platform to publish objects that need to be published. However, when publishing objects, the existing automated publishing platform can only prompt the publishing tasks that have failed, and cannot predict the overall publishing status of the published objects in advance, which reduces the publishing efficiency of the published objects that need to be published. Summary of the invention

[0004] The embodiments of the present invention provide a publishing status prediction method, device, equipment, medium and program, which can predict the publishing status of a publishing object and improve the publishing efficiency of the publishing object.

[0005] According to one aspect of the present invention, a release status prediction method is provided, comprising:

[0006] Acquire a first estimated release reference time and a real-time release reference time of a target release task in a target release object, wherein the target release object includes at least one target release task;

[0007] Determine the task release state of the target release task according to the first estimated release reference time and the real-time release reference time;

[0008] The release state of the target release object is predicted according to the task release state of at least one of the target release tasks to obtain the predicted release state of the target release object.

[0009] According to another aspect of the present invention, there is provided a release status prediction device, comprising:

[0010] A release reference time acquisition module, used to acquire a first estimated release reference time and a real-time release reference time of a target release task in a target release object, wherein the target release object includes at least one target release task;

[0011] A target publishing task state determination module, configured to determine the task publishing state of the target publishing task according to the first estimated publishing reference time and the real-time publishing reference time;

[0012] The target publishing object state prediction module is used to predict the publishing state of the target publishing object according to the task publishing state of at least one target publishing task, so as to obtain the predicted publishing state of the target publishing object.

[0013] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the release status prediction method described in any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the release status prediction method described in any embodiment of the present invention when executed.

[0018] According to another aspect of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the publishing status prediction method according to any embodiment of the present invention is implemented.

[0019] The technical solution of this embodiment obtains the first estimated release reference time and the real-time release reference time of at least one target release task in the target release object, and determines the task release status of the target release task according to the first estimated release reference time and the real-time release reference time, so as to predict the release status of the target release object according to the task release status of at least one target release task, and obtain the predicted release status of the target release object, which solves the problem in the prior art that the overall release status of the release object cannot be predicted in advance, and can predict the release status of the release object, thereby improving the release efficiency of the release object.

[0020] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 is a flow chart of a release status prediction method provided by Embodiment 1 of the present invention;

[0023] Figure 2 is a flow chart of another release status prediction method provided by Embodiment 2 of the present invention;

[0024] Figure 3 A visual display diagram of the real-time publishing status of the publishing object provided by the second embodiment of the present invention;

[0025] Figure 4 It is a structural diagram of a release status prediction device provided by Embodiment 3 of the present invention;

[0026] Figure 5 A schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] Embodiment 1

[0030] Figure 1This is a flowchart of a publishing status prediction method provided by the first embodiment of the present invention. This embodiment is applicable to the case of predicting the publishing status of a target publishing object. The method can be executed by a publishing status prediction device. The device can be implemented by software and / or hardware and can generally be integrated in an electronic device. The electronic device can be a terminal device or a server device. The embodiment of the present invention does not limit the specific device type of the electronic device. Figure 1 As shown, the method may include the following operations:

[0031] S110: Obtain a first estimated release reference time and a real-time release reference time of a target release task in a target release object, wherein the target release object includes at least one target release task.

[0032] Among them, the target release object may be an object that needs to be launched or updated. For example, the target release object may be a business system that needs to be launched in an enterprise, or a business system that has been launched but needs to be updated. Alternatively, the target release object may also be an APP (Application) or a machine learning model to be launched online. As long as the object type needs to be published online, it can be used as a target release object. The embodiment of the present invention does not limit the specific type of the target release object. The target release object may include one or more target release tasks. The target release task may be a specific release task included in the target release object that needs to be published. For example, the target release task may be each sub-business included in the business system, or the target release task may also be each sub-functional module included in the machine learning model. It can be understood that the type of the target release task is closely related to the target release object, and the embodiment of the present invention also does not limit the specific type of the target release task.

[0033] Among them, the first estimated release reference time can be the estimated release reference time of the target release task, which is used to characterize the release time of completing the release of the target release task. The first estimated release reference time can be a release task reference time determined according to the size of the memory occupied by the target release task or the release difficulty of the target release task. The first estimated release reference time can be the release duration corresponding to the target release task, such as 20 minutes; or it can be the release time interval corresponding to the target release task, such as 10:00-10:15, which means that the start time of the first estimated release reference time of the target release task is 10:00 and the end time is 10:15. The embodiment of the present invention does not limit the method and format for obtaining the first estimated release reference time.

[0034] The real-time publishing reference time may be the time when the target publishing task has been published, which is obtained during the publishing process of the target publishing task, and is used to characterize the real-time publishing time of the target publishing task. The real-time publishing reference time can be obtained by periodically reading the publishing log generated by the target publishing task during the publishing process, or by other means. The embodiment of the present invention does not limit the method for obtaining the real-time publishing reference time.

[0035] Specifically, the task identifier of one or more target release tasks that can be included in the target release object can be obtained, and the first estimated release reference time of each target release task can be obtained according to the task identifier of each target release task. When it is detected that the target release task starts to be released, the start release time of the target release task is recorded, and the release status and release time of the target release task are periodically collected to obtain the real-time release reference time of the target release object.

[0036] S120: Determine a task release status of the target release task according to the first estimated release reference time and the real-time release reference time.

[0037] The task release status may be the release status after the target release task starts to be released, which is used to characterize the task release status of the target release task at the current moment. The task release status may include a normal release status and an abnormal release status.

[0038] Specifically, the real-time release reference time of the target release task collected periodically may be compared with the first estimated release reference time. If the real-time release reference time of the target release task currently collected is less than or equal to the first estimated release reference time, and the target release task has been released, it means that the target release task has been released within the expected time. At this time, it can be determined that the task release status of the target release task is a normal release status. If the real-time release reference time of the target release task currently collected is greater than the first estimated release reference time, and the target release task has not been released, it means that the target release task has not been released within the expected time. At this time, it can be determined that the task release status of the target release task is an abnormal release status.

[0039] S130: predicting a release state of a target release object according to a task release state of at least one target release task, to obtain a predicted release state of the target release object.

[0040] The predicted release status can be a release status that may occur in the target release object within the expected time, which is predicted based on the number of target release tasks in the target release object whose task release status is abnormal and / or the specific abnormal situation of the abnormal release status. For example, if the number of target release tasks in the target release object whose task release status is abnormal is relatively large, it can be predicted that the target release object may have a release failure at a certain point in time, resulting in the failure of the target release object to be released; if the number of target release tasks in the target release object whose task release status is abnormal is relatively small or there is no abnormal release status, it can be predicted that the target release object will not have a release failure within the expected time.

[0041] Specifically, after the release of each target release task is completed, the release status of the target release object can be predicted based on the task release status of one or more target release tasks that have been released in the target release object, so as to obtain the release status of the target release object within the expected time. For example, the target release object contains 10 target release tasks, and the first 5 target release tasks have been completed, and the 6th target release task is being released. Then, after the 6th target release task is completed, the task release status of the 6 target release tasks that have been released can be obtained, and the release status of the target release object can be predicted based on the task release status of the 6 target release tasks that have been released. The embodiment of the present invention does not limit the release status prediction method of the target release object.

[0042] The technical solution of this embodiment obtains the first estimated release reference time and the real-time release reference time of at least one target release task in the target release object, and determines the task release status of the target release task according to the first estimated release reference time and the real-time release reference time, so as to predict the release status of the target release object according to the task release status of at least one target release task, and obtain the predicted release status of the target release object, which solves the problem in the prior art that the overall release status of the release object cannot be predicted in advance, and can predict the release status of the release object, thereby improving the release efficiency of the release object.

[0043] Embodiment 2

[0044] Figure 2It is a flowchart of another release status prediction method provided by the second embodiment of the present invention. This embodiment is specific based on the above embodiment. In this embodiment, the first estimated release reference time and the real-time release reference time of the target release task in the target release object are obtained; the task release status of the target release task is determined according to the first estimated release reference time and the real-time release reference time; the release status of the target release object is predicted according to the task release status of at least one target release task, and the predicted release status of the target release object is further refined. Correspondingly, Figure 2 As shown, the method of this embodiment may include:

[0045] S210: Obtain a first estimated release reference time and a real-time release reference time of a target release task in a target release object, wherein the target release object may include at least one target release task.

[0046] In an optional embodiment of the present invention, obtaining the first estimated release reference time and the real-time release reference time of the target release task in the target release object may include: querying the release object database according to the release object identification information of the target release object to obtain the target release task identification information corresponding to the release object identification information; obtaining the first estimated release reference time of the target release task according to the target release task identification information; and when it is determined that the target release task is in a release state, real-time statistics of the current release time of the target release task are used as the real-time release reference time.

[0047] The publishing object identification information may be identification information of a target publishing object, which is used to uniquely identify the target publishing object. The target publishing task identification information may be identification information of each target publishing task that needs to be published in the target publishing object.

[0048] The publication object database may be constructed based on the target publication object obtained from the user's publication plan and one or more target publication tasks contained in each target publication object, and may store the target publication object identification and one or more target publication task identification information contained in each target publication object. The publication object database may include information associated with the target publication object, such as publication object identification information, target publication task identification information, and publication start time information of the target publication task.

[0049] Exemplarily, before publishing the target publishing task in the target publishing object, the corresponding publishing plan can be specified according to the object to be published. By obtaining the publishing plan formulated by the user, the target publishing objects to be published and the target publishing tasks corresponding to each target publishing object are obtained, and the corresponding identification information is attached to the target publishing object and the target publishing task corresponding to each target publishing object, and stored in the publishing object database, and the publishing start time of each target publishing task is obtained according to the publishing plan formulated by the user as the first estimated publishing reference time, and stored in the database, and associated with the corresponding target publishing task.

[0050] Specifically, when it is detected that the target release task in the target release object starts to execute the release, the release object identification information of the target release task can be obtained, and then the first estimated release reference time corresponding to the target release task is read from the release object database according to the release object identification information, and then the current release time of the target release task is counted as the real-time release reference time.

[0051] S220 , comparing the first estimated release reference time and the real-time release reference time of the target release task to obtain a release time comparison result.

[0052] The release time comparison result may be a comparison result obtained after comparing the first estimated release reference time of the target release task with the real-time release reference time. The release time comparison result may be used to characterize the size of the first estimated release reference time of the target release task and the real-time release reference time. The task release status of the target release task may be determined based on the size of the first estimated release reference time of the target release task and the real-time release reference time.

[0053] S230: Determine the task release status of the target release task according to the release time comparison result.

[0054] In an optional embodiment of the present invention, determining the task release status of the target release task based on the release time comparison result may include: if the real-time release reference time of the target release task is less than or equal to the first estimated release reference time, and the release of the target release task is completed, then determining that the task release status of the target release task is a normal release status; if the real-time release reference time of the target release task is greater than the first estimated release reference time, then determining that the task release status of the target release task is an abnormal release status.

[0055] The normal release state may be the task release state of the target release task when the target release task is completed within the first estimated release reference time. The abnormal release state may be the release state of the target release task when the target release task is not completed within the first estimated release reference time.

[0056] For example, if the first estimated release reference time is 20 minutes, and the target release task is released within 20 minutes, the release status of the target release task can be determined as a normal release status. If the target release task is not released within 20 minutes, the release status of the target release task can be determined as an abnormal release status.

[0057] In an optional embodiment of the present invention, the abnormal publishing status may include a publishing timeout status and a publishing failure status. Determining that the task publishing status of the target publishing task is an abnormal publishing status may include: if the real-time publishing reference time of the target publishing task is greater than the first estimated publishing reference time, and the real-time publishing reference time of the target publishing task is less than or equal to the second estimated publishing reference time, then continue to publish the target publishing task, and determine that the task publishing status of the target publishing task is an abnormal publishing status; if the target publishing task completes publishing before the real-time publishing reference time is less than the second estimated publishing reference time, then determine the task publishing status of the target publishing task as a publishing timeout status; if the target publishing task does not complete publishing before the real-time publishing reference time is less than the second estimated publishing reference time, then stop publishing the target publishing task, and determine the task publishing status of the target publishing task as a publishing failure status.

[0058] Among them, the second estimated release reference time can be a reference time used to judge whether the task release status of the target release task is a release failure status or a release timeout after determining that the real-time release reference time of the target release task is greater than the first estimated release reference time. The second estimated release reference time can be calculated based on the first estimated release reference time, or it can be set by the technical staff according to the needs. The embodiment of the present invention does not limit the second estimated release reference time method. It should be noted that the second estimated release reference time is greater than the first estimated release reference time. Among them, the release timeout status can be the task release status of the target release task when the real-time release reference time of the target release task is greater than the first estimated release reference time and less than or equal to the second estimated release reference time; the release failure status can be the task release status of the target release task when the real-time release reference time of the target release task is greater than the second estimated release reference time.

[0059] For example, if the first estimated release reference time of the target release task is 20 minutes, the second estimated release reference time is 45 minutes, and the real-time release reference time currently obtained is 21 minutes, then the task release status of the target release task can be determined to be the release timeout state in the abnormal release status. At this time, the target release task can continue to be released, and the second estimated release reference time of the target release task can be continuously obtained. If the real-time release reference time of the target release task is completed before 45 minutes, the task release status of the target release task can be determined as the release timeout state; if the target release task exceeds 45 minutes in the real-time release reference time, it indicates that the release of the target release task has failed. At this time, the release of the target release task can be stopped, and the task release status of the target release task can be determined as the release failure state.

[0060] Optionally, after detecting that the target release task has ended, the task release status of the target release task can be updated to the visualization interface, and the task release status of the target release task can be displayed in different display modes, and the associated information of the target release task can also be displayed to the visualization interface, so that the user can more intuitively understand the release status of each target release task in each target release object. For example, a target release task with a task release status of a normal release status is displayed in green, a target release task with a task release status of a timed release status is displayed in yellow or red, and a target release task with a task release status of a failed release status is displayed in gray, etc.

[0061] Optionally, after detecting that the task release status of the target release task is an abnormal release status, the release process data of the target release task can also be obtained from the task release log, and the reason for the abnormal release of the target release task can be analyzed based on the release process data, and the reason for the abnormal release of the target release task can be displayed on the visual interface, so that the staff can obtain the abnormal reason for the target release task in real time.

[0062] S240: predicting a release status of a target release object according to a task release status of at least one target release task to obtain a predicted release status of the target release object.

[0063] In an optional embodiment of the present invention, predicting the release status of a target release object according to the task release status of at least one target release task to obtain the predicted release status of the target release object may include: determining a release abnormality task identifier according to the task release status of the target release task, wherein the release abnormality task identifier is an abnormal identifier of a target release task whose task release status in the target release object is an abnormal release status; calculating a release risk value of the target release object according to the release abnormality task identifier; predicting the release status of the target release object according to the release risk value to obtain the predicted release status of the target release object.

[0064] Among them, the release abnormal task identifier can be the abnormal identification information of the target release task in the target release object whose task release status is the release timeout state and the release failure state, which can be used to calculate the release risk value of the target release object. Among them, the release risk value can be the risk value of the target release object this time calculated based on the abnormal identification information of the target release task in the target release object whose task release status is the release timeout state and the release failure state. Through the release risk value, the release status of the target release object can be predicted.

[0065] Exemplarily, after any target release task in the target release object is completed, the release abnormal task identifiers of all target release tasks in the target release object whose task release status is abnormal release status can be obtained, and the abnormal release status of the target release task is determined to be a release timeout status or a release failure status according to these release abnormal task identifiers, and different risk values ​​are obtained according to different abnormal release statuses, and then these risk values ​​are added to obtain the risk value of the target release object this time, and the release status of the target release object is predicted according to the risk value of the target release object this time. Table 1 is a statistical table of the task release status of the target release object. As shown in Table 1, there are abnormal tasks, yellow tasks, red tasks and normal tasks in the target release object. An abnormal task can be a task whose release time of the target release task is greater than the second expected release reference time, and the target task has not yet been released, that is, a task that has failed to release. Red tasks and yellow tasks can be target release tasks whose release time of the target release task is greater than the first expected release reference time, and the target task has not yet been released, that is, a target release task whose release time has timed out. Among them, yellow tasks can be tasks that have generally timed out, and red tasks can be target release tasks that have seriously timed out. The timeout of red tasks is greater than the timeout of yellow tasks. Normal tasks are target release tasks that are completed and released within the first estimated release reference time. As shown in Table 1, the release status of the target release objects is 10 abnormal tasks, 5 yellow tasks, and 8 red tasks.

[0066] Exemplarily, the risk value of the target release task with a task release status of abnormal task can be assigned 3, the risk value of the target release task with a task release status of red timeout state can be assigned 2, and the risk value of the target release task with a task release status of yellow timeout state can be assigned 1. According to the statistical table of task release status of the target release object in Table 1, the release risk value of the target release object can be calculated. As shown in Table 1, the release status of the target release object is 10 abnormal tasks, 5 yellow tasks, and 8 red tasks. It can be calculated that the release risk value of the target release object is: 3*10+5*5+8*1=63. It can be understood that the release risk value of the target release object is closely related to the release status of the target release task and the corresponding values ​​of different states. The embodiment of the present invention does not limit the specific calculation method of the release risk value.

[0067] Table 1 Statistics of task release status of target release objects

[0068] Task Status quantity Abnormal tasks 10 Yellow Tasks 5 Red Mission 8 Normal tasks 0

[0069] Optionally, the data collection component that comes standard with the existing big data platform can be used to collect data from the database and the publishing object file, and a data index corresponding to each publishing task in the publishing object file can be established based on the collected data, so that users can obtain the required data in real time. Exemplarily, the following data can be collected: 1. Release plan: the scheduling plan before the release object goes online, which is stored in the database, including the name of the release object, the release object ID (identifier), the release task ID in the release object, the release task name, the planned start time of the release task, the planned end time of the release task, the release reference time of the release task, and the number of tasks of the release object; 2. Task overview table: the task status of all release objects released in the database is stored, which can be used to show whether the data release is completed or abnormal or not started, and the start and end time of the release task; 3. Task exception log: when the task is released abnormally, the abnormal reasons of each release task with an abnormal release status are stored in a fixed log path, and the ID of the release object and the ID of the release task corresponding to the release task with an abnormal release status; 4. Task release completion record table: the total release time of different release objects in the database is stored, and the individual release time records of different release tasks of different release objects are recorded; 5. Real-time task status: the real-time status information of the data in the database when it is being released is stored, such as real-time task status information such as task release, task release success, task release not started, task release timeout, and task release abnormality. After the above data is collected, a corresponding data table may be established in the database, the above information may be stored in the corresponding data table, and corresponding associations may be made between the data tables.

[0070] Optionally, after the collected data is stored in the database, the data can be processed and cleaned, key field information can be extracted, and important key fields can be obtained from each data table for the next step of association processing and analysis. Among them, log data can be cleaned by regular processing, and the fields can be grouped and extracted by regular processing to extract key fields. Database data uses json (JavaScript Object Notation, a lightweight data exchange format) data processing method to extract key fields. Then the extracted key fields are associated and displayed.

[0071] Exemplarily, before publishing a publishing object, the publishing plan data can be used to associate the task overview table with the publishing object ID and the publishing task ID to obtain the number of tasks that need to be published on the day for each publishing object, the overall publishing time on the day, and the publishing time required for a single publishing object. Finally, a more complete scheduling plan data before publishing is formed. In the process of publishing a publishing object, the overview plan table generated before publishing can be associated with the real-time publishing status table of each publishing object to obtain whether each publishing object has started publishing at present, and at the same time, it can be compared with the average publishing completion time of the same type of tasks in history to obtain whether the current publishing task of the current publishing object can exceed the historical average publishing time. If it exceeds, it will be marked yellow to indicate that an abnormality may occur. If it exceeds twice the historical average publishing time, it means that there is a serious abnormality and is marked red. If the publishing is completed within the historical average publishing time, it will be marked green. If it exceeds twice the historical average publishing time or other data, it can be determined that the publishing task is abnormal and marked gray. After publishing the publishing object, it can be obtained that the total number of publishing tasks of the publishing object today is compared with the planned number. Missing or extra is an abnormality. The number of task exceptions, the ID of the publishing object, the publishing task ID corresponding to the publishing object, the associated exception information log and the display exception error. The general exception automatically associates the abnormal publishing task ID and the fault library execution repair button and re-publish button through the API (Application Programming Interface). The publishing progress bar can display the above information in a publishing progress bar corresponding to the publishing time of the publishing object, and obtain the real-time changes of the publishing time of each publishing task in the publishing object in the publishing status table.

[0072] For example, Figure 3 A visual display diagram of the real-time publishing status of the publishing object provided by the second embodiment of the present invention, such as Figure 3As shown in the figure, there are 5 publishing objects, namely loan services, operation platform, transaction center, credit card center and mortgage center. In the publishing status page of the publishing object, the publishing object can include the publishing object's person in charge number information, task number information, abnormal task number information, completed task information, publishing progress bar and the publishing object's task start publishing time information. It can also display the publishing object's task completion time information after all the publishing tasks of the publishing object are published without abnormality.

[0073] Exemplarily, the person in charge number information is used to represent the unique number corresponding to the person in charge of the current publishing object. The user can determine the person in charge corresponding to the current publishing object based on the person in charge number information; the number of tasks information is used to represent the number of publishing tasks of the current publishing object. The user can determine the total number of tasks that need to be published by the current publishing object based on the number of tasks information. For example, if the number of tasks of the trading platform is 24, it means that the total number of tasks that need to be published by the trading platform is 24. The number of abnormal tasks information is used to represent the number of tasks whose publishing status of the current publishing object is abnormal. The user can determine how many publishing tasks of the current publishing object have publishing abnormalities based on the number of abnormal tasks information. For example, if the number of abnormal tasks of the trading platform is 2, it means that the trading platform has 2 publishing tasks with publishing abnormalities. The completed task information is used to represent the number of tasks that have been completed for the current publishing object. The user can determine how many publishing tasks of the current publishing object have been completed based on the completed task information. For example, if the number of completed tasks of the credit card center is 16, it means that the credit card center has completed 16 publishing tasks. The release progress bar is used to represent the release status of the task of the current release object through the progress bar. The user can obtain the release status information and release time and other release related information of the released tasks in the current release object by placing the mouse on the progress bar. For example, there are 22 release tasks with normal release status in the transaction, and the color of these 22 tasks in the progress bar can be set to normal color, for example Figure 3The gray color in the progress bar, the user can place the mouse at different positions of the progress bar to obtain the name information and release time information of the release task. There are two release tasks in the transaction whose release status is seriously timed out, then the color of these two tasks in the progress bar can be set to black, and the user can place the mouse at the black position of the progress bar to obtain the name information and release time information of the release task with serious timeout, as well as the reason for the serious timeout of the release task. The time information of the start release of the task of the release object can be the time information of the start release of any release task in the release object, and the time information of the completion release of the task can be the time information after all the release tasks of the release object are completed without exception. It can be understood that the information displayed in the above-mentioned visualization display diagram of the real-time release status of the release object is only an example of the visualization display of the release object, and the embodiment of the present invention does not limit the visualization display method and display form of the release object.

[0074] Optionally, after predicting the release status of the target release object, if the predicted release status of the target release object is failure, the release of the target release object can be actively terminated, and the reasons for the release abnormality of each target release object whose task release status is abnormal in the target release object can be analyzed, and then the release parameters can be modified, and the target release object can be re-released through the restart button; or it can be waited for the release of the target release object to be completed, and the release parameters in the target release object can be automatically adjusted through the preset repair button, and then the target release object can be re-released through the restart button. If the predicted release status of the target release object is normal, the target release task in the target release object can continue to be released, and the release status of the target release object can be predicted in real time, and corresponding processing operations can be performed according to the prediction results.

[0075] Optionally, when all target release objects in the user's release plan are completed or reach the end of release time, the release status of all target release objects in the release plan can be counted and displayed to the user, so that the user can arrange subsequent release plans according to the release status of each target release object.

[0076] Exemplarily, the following data can be counted and displayed based on the collected data through SQL (Structured Query Language, a standard programming language for managing and operating relational databases) functions: Statistics on the number of objects released today: the total number of release objects is calculated based on the total release completion table; The total number of release tasks today: the total number of release tasks that have been completed for all release objects is calculated based on the total release completion table; The number of exceptions today: the total number of release tasks with abnormal release status that appeared today is calculated; Task prediction & real-time monitoring track diagram: a visual display diagram of the real-time release status of the relevant refreshed release objects is displayed based on the association of each data; Statistics on long-time tasks: obtain the IDs of the five or other number of release tasks that take the longest time; Display of abnormal logs associated with abnormal tasks: when the mouse is placed on the abnormal task, a floating window will display the abnormal reason for the abnormal task. The technical solution of this embodiment obtains the first estimated release reference time and the real-time release reference time of at least one target release task in the target release object, and determines the task release status of the target release task according to the first estimated release reference time, the second estimated release reference time and the real-time release reference time, and finally calculates the release risk value of the target release object according to the statistical result by counting the target release tasks whose task release status is an abnormal release status, and finally predicts the release status of the target release object according to the release risk value of the target release object to obtain the predicted release status of the target release object, which solves the problem that the prior art cannot predict the overall release status of the release object in advance, and can predict the release status of the release object in real time, thereby improving the release efficiency of the release object. The task release status of each release task in the release object is displayed to the user in a visual display manner, so that the real-time release status of each release object can be more intuitively understood, thereby improving the user experience.

[0077] In the technical solution disclosed herein, the collection, storage, use, processing, transmission, provision and disclosure of user personal information (such as person in charge, person in charge number, etc.) are in compliance with the relevant laws and regulations and do not violate public order and good morals.

[0078] Embodiment 3

[0079] Figure 4 is a schematic diagram of a release status prediction device provided by Embodiment 4 of the present invention, such as Figure 4 As shown, the apparatus may include: a publishing reference time acquisition module 310 , a target publishing task state determination module 320 , and a target publishing object state prediction module 330 .

[0080] A release reference time acquisition module 310 is used to obtain a first estimated release reference time and a real-time release reference time of a target release task in a target release object, wherein the target release object may include at least one target release task; a target release task status determination module 320 is used to determine a task release status of a target release task according to the first estimated release reference time and the real-time release reference time; a target release object status prediction module 330 is used to predict the release status of a target release object according to the task release status of at least one target release task, and obtain a predicted release status of the target release object.

[0081] Furthermore, the release reference time acquisition module 310 is specifically used to: query the release object database according to the release object identification information of the target release object to obtain the target release task identification information corresponding to the release object identification information; obtain the first estimated release reference time of the target release task according to the target release task identification information; and when it is determined that the target release task is in a release state, real-time statistics of the current release time of the target release task are used as the real-time release reference time.

[0082] Furthermore, the target release task status determination module 320 is specifically used to: compare the first estimated release reference time and the real-time release reference time of the target release task to obtain a release time comparison result; and determine the task release status of the target release task according to the release time comparison result.

[0083] Furthermore, the target release task status determination module 320 is specifically used to: if the real-time release reference time of the target release task is less than or equal to the first estimated release reference time, and the target release task is completed, then the task release status of the target release task is determined to be a normal release status; if the real-time release reference time of the target release task is greater than the first estimated release reference time, then the task release status of the target release task is determined to be an abnormal release status.

[0084] Furthermore, the target release task status determination module 320 is specifically used for: if the real-time release reference time of the target release task is greater than the first estimated release reference time, and the real-time release reference time of the target release task is less than or equal to the second estimated release reference time, then continue to release the target release task, and determine the task release status of the target release task as an abnormal release status; if the target release task is completed before the real-time release reference time is less than the second estimated release reference time, then determine the task release status of the target release task as a release timeout status; if the target release task is not completed before the real-time release reference time is less than the second estimated release reference time, then stop releasing the target release task, and determine the task release status of the target release task as a release failure status.

[0085] Furthermore, the target release object status prediction module 330 is specifically used to: determine a release abnormality task identifier based on the task release status of the target release task, wherein the release abnormality task identifier is an abnormal identifier of the target release task whose task release status in the target release object is an abnormal release status; calculate a release risk value of the target release object based on the release abnormality task identifier; predict the release status of the target release object based on the release risk value to obtain a predicted release status of the target release object.

[0086] The above-mentioned publishing status prediction device can execute the publishing status prediction method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not fully described in this embodiment, please refer to the publishing status prediction method provided by any embodiment of the present invention.

[0087] Since the release status prediction device introduced above is a device that can execute the release status prediction method in the embodiment of the present invention, based on the release status prediction method introduced in the embodiment of the present invention, the technical personnel in the field can understand the specific implementation of the release status prediction device of the present embodiment and its various variations, so how the release status prediction device implements the release status prediction method in the embodiment of the present invention is not described in detail here. As long as the technical personnel in the field implement the device used in the release status prediction method in the embodiment of the present invention, it belongs to the scope of protection of this application.

[0088] Embodiment 4

[0089] Figure 5 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0090] like Figure 5As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0091] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0092] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the release status prediction method.

[0093] In some embodiments, the release status prediction method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the release status prediction method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the release status prediction method in any other appropriate manner (e.g., by means of firmware).

[0094] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0095] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0096] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0097] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0098] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0099] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0100] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0101] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A release status prediction method, characterized in that: include: Acquire a first estimated release reference time and a real-time release reference time of a target release task in a target release object, wherein the target release object includes at least one target release task; Determine the task release state of the target release task according to the first estimated release reference time and the real-time release reference time; The release state of the target release object is predicted according to the task release state of at least one of the target release tasks to obtain the predicted release state of the target release object.

2. The method according to claim 1, characterized in that The step of obtaining the first estimated release reference time and the real-time release reference time of the target release task in the target release object includes: According to the publishing object identification information of the target publishing object, a publishing object database is searched to obtain the target publishing task identification information corresponding to the publishing object identification information; Acquire the first estimated release reference time of the target release task according to the target release task identification information; When it is determined that the target publishing task is in a publishing state, the current publishing time of the target publishing task is counted in real time as the real-time publishing reference time.

3. The method according to claim 1, characterized in that Determining the task release status of the target release task according to the first estimated release reference time and the real-time release reference time includes: Compare the first estimated release reference time of the target release task with the real-time release reference time to obtain a release time comparison result; The task release status of the target release task is determined according to the release time comparison result.

4. The method according to claim 3, characterized in that The determining the task release status of the target release task according to the release time comparison result includes: If the real-time release reference time of the target release task is less than or equal to the first estimated release reference time, and the release of the target release task is completed, then determining that the task release state of the target release task is a normal release state; If the real-time release reference time of the target release task is greater than the first estimated release reference time, it is determined that the task release state of the target release task is an abnormal release state.

5. The method according to claim 4, characterized in that in, The abnormal publishing state includes a publishing timeout state and a publishing failure state, and the step of determining that the task publishing state of the target publishing task is an abnormal publishing state includes: If the real-time release reference time of the target release task is greater than the first estimated release reference time, and the real-time release reference time of the target release task is less than or equal to the second estimated release reference time, continue to release the target release task, and determine that the task release state of the target release task is an abnormal release state; If the target publishing task is completed before the real-time publishing reference time is less than the second estimated publishing reference time, the task publishing state of the target publishing task is determined as a publishing timeout state; If the target publishing task is not completed before the real-time publishing reference time is less than the second estimated publishing reference time, the publishing of the target publishing task is stopped, and the task publishing status of the target publishing task is determined as a publishing failure status.

6. The method according to claim 5, characterized in that The predicting the release status of the target release object according to the task release status of at least one target release task to obtain the predicted release status of the target release object includes: Determine a release abnormal task identifier according to the task release status of the target release task, wherein the release abnormal task identifier is an abnormal identifier of the target release task whose task release status in the target release object is an abnormal release status; Calculating a publishing risk value of the target publishing object according to the publishing abnormality task identifier; The publishing status of the target publishing object is predicted according to the publishing risk value to obtain the predicted publishing status of the target publishing object.

7. A release status prediction device, characterized in that: include: A release reference time acquisition module, used to acquire a first estimated release reference time and a real-time release reference time of a target release task in a target release object, wherein the target release object includes at least one target release task; A target publishing task state determination module, configured to determine the task publishing state of the target publishing task according to the first estimated publishing reference time and the real-time publishing reference time; The target publishing object state prediction module is used to predict the publishing state of the target publishing object according to the task publishing state of at least one target publishing task, so as to obtain the predicted publishing state of the target publishing object.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the release status prediction method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the release status prediction method described in any one of claims 1-6 when executed.

10. A computer program product comprising a computer program / instructions, wherein: When the computer program / instructions are executed by a processor, the release status prediction method according to any one of claims 1 to 6 is implemented.

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