CN111815200A - Task scheduling method and device, computer equipment and storage medium - Google Patents
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Abstract
The invention relates to an artificial intelligence technology, can be applied to the field of smart cities, and discloses a task scheduling method and device, computer equipment and a storage medium, wherein the method comprises the following steps: determining an investment type of a target enterprise according to a preset rule, wherein the preset rule is used for calculating a heat value of the target enterprise concerned by an investor according to enterprise data of the target enterprise, and the investment type is divided based on the heat value of the target enterprise concerned by the investor; generating a task time schedule corresponding to the investment type, wherein the task time schedule is used for representing an execution plan of a task issued by the first public stock raising IPO of the target enterprise; and scheduling the tasks to be executed according to the task time schedule and executing the tasks to be executed. The invention also relates to blockchain techniques, the task time schedule being stored in a blockchain. By the method and the device, the technical problem of low task scheduling efficiency in the related technology is solved.
Description
Technical Field
The invention relates to the field of computers, in particular to a task scheduling method and device, computer equipment and a storage medium.
Background
In the related technology, there are many links of issuing IPOs (called Initial Public offices, first Public stock raising), and there are many participants, and there are also links of manually uploading files, confirming results, manually approving, and auditing. At present, in hong Kong, the IPO issuing and settlement process is currently T +5 to T +8 days, because the interactive communication of various participants still has an offline mode, and a lot of data comparison work and manual approval work are needed, the process is long; the long issuing process not only affects the task scheduling efficiency of the issuing link, but also brings some losses to enterprises, for example, the capital utilization rate is low because the capital occupation time of investors is long; for publishers, long issue times mean an uncontrolled risk, such as an emergency or a clear message, that IPO issues may be cold or fail. Therefore, how to more efficiently schedule the publishing task to shorten the flow of the publishing link is a crucial issue.
In view of the above problems in the related art, no effective solution has been found at present.
Disclosure of Invention
The embodiment of the invention provides a task scheduling method and device, computer equipment and a storage medium, which at least solve the technical problem of low task scheduling efficiency in the related technology.
According to an embodiment of the present invention, a task scheduling method is provided, which is applied to a web server, and includes: determining an investment type of a target enterprise according to a preset rule, wherein the preset rule is used for calculating a heat value of the target enterprise concerned by an investor according to enterprise data of the target enterprise, and the investment type is divided based on the heat value of the target enterprise concerned by the investor; generating a task time schedule corresponding to the investment type, wherein the task time schedule is used for representing an execution plan of a task issued by the first public stock raising IPO of the target enterprise; and scheduling the tasks to be executed according to the task time schedule and executing the tasks to be executed.
Optionally, determining the investment type of the target enterprise according to the preset rule includes: acquiring enterprise data of the target enterprise, wherein the enterprise data at least comprises: the asset size of the target enterprise, the release shares of the target enterprise, the industry market share of the target enterprise; calculating the heat value of the target enterprise by the following formula: heat value ═ a × asset size + b × issued shares + c × industry market share; wherein a represents the preset weight of the asset scale in the first public stock raising, b represents the preset weight of the issued shares in the first public stock raising, and c represents the preset weight of the market share in the first public stock raising; and determining a target type of the target enterprise by comparing the heat value with a preset value, wherein the target type represents the IPO success rate of the target enterprise.
Optionally, the generating a task time schedule corresponding to the investment type includes: generating a task time reference table of the target enterprise according to the historical execution duration of the issued tasks associated with the investment types; generating a risk task association table of the target enterprise according to the risk task of the issuing task and the execution duration of the risk task; and generating a task time schedule of the target enterprise based on the task time reference table and the risk task association table.
Optionally, the generating a task time reference table of the target enterprise according to the historical execution duration of the issued tasks associated with the investment types includes: recording the participants of the issued tasks and the processing timeliness of the issued tasks according to the historical execution duration of the issued tasks; generating the task time reference table based on the participants who issue the tasks and the processing aging, wherein the task time reference table at least comprises the following field contents: the type of the enterprise, the task name, the task code, the execution time and the participating party.
Optionally, the generating a risk task association table of the target enterprise according to the risk task of the issue task and the execution duration of the risk task includes: recording a risk task of the issuing task and the execution duration of the risk task; generating a risk task association table of the target enterprise based on the risk task and the execution duration of the risk task, wherein the risk task association table is used for associating the issue task with the risk task corresponding to the issue task, and the risk task association table at least comprises the following field contents: a type of enterprise, a task name of the release task, a task code of the release task, a task name of the risky task, and a task code of the risky task.
Optionally, the generating a task time schedule of the target enterprise based on the task time reference table and the risk task association table includes: generating a planned time table of the issued tasks according to the task time reference table, the preset sequence of the issued tasks and the dependency relationship of the issued tasks; and adding risk tasks to the schedule based on the risk task association table, and correspondingly adjusting the execution duration of the issued tasks to obtain the task time schedule.
Optionally, the task time schedule is stored in a block chain, and scheduling a task to be executed according to the task time schedule and executing the task to be executed includes: acquiring the task time schedule through a workflow scheduler; calling a first task in the task time schedule and executing the first task; and if a risk task corresponding to the first task needs to be added in a directed acyclic graph mode based on the execution condition of the first task, delaying the execution time of a second task by preset time, wherein the second task is the next task depending on the first task in the task time schedule.
According to an embodiment of the present invention, there is provided a task scheduling apparatus applied to a web server, including: the system comprises a determining module, a judging module and a judging module, wherein the determining module is used for determining the investment type of a target enterprise according to a preset rule, the preset rule is used for calculating the heat value of the target enterprise concerned by investors according to enterprise data of the target enterprise, and the investment type is divided based on the heat value of the target enterprise concerned by the investors; the generating module is used for generating a task time schedule corresponding to the investment type, wherein the task time schedule is used for representing an execution plan of a task issued by the first public offering IPO of the target enterprise; and the execution module is used for scheduling the tasks to be executed according to the task time schedule and executing the tasks to be executed.
Optionally, the determining module includes: a first obtaining unit, configured to obtain enterprise data of the target enterprise, where the enterprise data at least includes: the asset size of the target enterprise, the release shares of the target enterprise, the industry market share of the target enterprise; a calculating unit, configured to calculate a heat value of the target enterprise according to the following formula: heat value ═ a × asset size + b × issued shares + c × industry market share; wherein a represents the preset weight of the asset scale in the first public stock raising, b represents the preset weight of the issued shares in the first public stock raising, and c represents the preset weight of the market share in the first public stock raising; and the determining unit is used for determining the target type of the target enterprise by comparing the heat value with a preset value, wherein the target type represents the IPO success rate of the target enterprise.
Optionally, the generating module includes: the first generation unit is used for generating a task time reference table of the target enterprise according to the historical execution duration of the release tasks associated with the investment types; a second generating unit, configured to generate a risk task association table of the target enterprise according to the risk task of the issue task and the execution duration of the risk task; and the third generating unit is used for generating a task time schedule of the target enterprise based on the task time reference table and the risk task association table.
Optionally, the first generating unit includes: the first recording subunit is used for recording the participants of the issued task and the processing timeliness of the issued task according to the historical execution duration of the issued task; a first generating subunit, configured to generate the task time reference table based on the participants who issue the tasks and the processing timeliness, where the task time reference table includes at least the following field contents: the type of the enterprise, the task name, the task code, the execution time and the participating party.
Optionally, the second generating unit includes: the second recording subunit is used for recording the risk task of the release task and the execution duration of the risk task; a second generating subunit, configured to generate a risk task association table of the target enterprise based on the risk task and the execution duration of the risk task, where the risk task association table is used to associate the issue task with a risk task corresponding to the issue task, and the risk task association table at least includes the following field contents: a type of enterprise, a task name of the release task, a task code of the release task, a task name of the risky task, and a task code of the risky task.
Optionally, the second generating unit includes: the third generation subunit is used for generating a planned time table of the issued tasks according to the task time reference table, the preset order of the issued tasks and the dependency relationship of the issued tasks; and the fourth generation subunit is used for adding risk tasks to the schedule based on the risk task association table and correspondingly adjusting the execution duration of the release tasks to obtain the task time schedule.
Optionally, the task time schedule is stored in a block chain, and the execution module includes: a second obtaining unit, configured to obtain the task time schedule through a workflow scheduler; the calling unit is used for calling a first task in the task time schedule and executing the first task; and the execution unit is used for adding a risk task corresponding to the first task in a directed acyclic graph manner if necessary based on the execution condition of the first task, and delaying the execution time of a second task by preset time, wherein the second task is a next task depending on the first task in the task time schedule.
According to yet another embodiment of the present invention, there is also provided a computer device comprising a memory having a computer program stored therein and a processor configured to execute the computer program to perform the steps of any of the above method embodiments.
According to a further embodiment of the present invention, there is also provided a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps in any of the apparatus embodiments described above when executed.
According to the invention, the investment type of the enterprise is determined according to the enterprise data of the target enterprise so as to determine the attention degree of the target enterprise to investors; aiming at each investment type, automatically generating a task time schedule corresponding to the investment type; and scheduling and executing the tasks to be executed according to the task time schedule without manually planning to arrange IPO issuing tasks, thereby solving the technical problem of low task scheduling efficiency in the related technology and improving the accuracy of workflow planning time points.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a block diagram of a hardware structure of a computer terminal to which a task scheduling method according to an embodiment of the present invention is applied;
FIG. 2 is a flow chart of a method of task scheduling according to an embodiment of the present invention;
FIG. 3 is a flow chart of task execution providing a task schedule according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating specific task scheduling steps according to an embodiment of the present invention;
fig. 5 is a block diagram of a task scheduling apparatus according to an embodiment of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
Example 1
The method provided by the first embodiment of the present application may be executed in a mobile terminal, a server, a computer terminal, or a similar computing device. Taking the operation on a computer terminal as an example, fig. 1 is a hardware structure block diagram of a task scheduling method applied to a computer terminal according to an embodiment of the present invention. As shown in fig. 1, the computer terminal may include one or more (only one shown in fig. 1) processors 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, and optionally, a transmission device 106 for communication functions and an input-output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration and is not intended to limit the structure of the computer terminal. For example, the computer terminal may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
The memory 104 may be used to store computer programs, for example, software programs and modules of application software, such as computer programs corresponding to the task scheduling method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, so as to implement the method described above. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely from the processor 102, which may be connected to a computer terminal over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the computer terminal. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
In order to solve the technical problems in the related art, it is necessary to construct an intelligent workflow planning system to help the exchange to perform coordinated scheduling of each link of issue, centralize and transparent issue flow processing, and achieve the purpose of shortening the IPO issue time and ensuring the successful IPO issue.
In this embodiment, a task scheduling method is provided, where the method is applied to a web server, and fig. 2 is a flowchart of a task scheduling method according to an embodiment of the present invention, and as shown in fig. 2, the flowchart includes the following steps:
step S202, determining the investment type of the target enterprise according to a preset rule, wherein the preset rule is used for calculating the heat value of the target enterprise, which is concerned by the investor, according to enterprise data of the target enterprise, and the investment type is divided based on the heat value of the target enterprise, which is concerned by the investor;
in this embodiment, the enterprise data may be obtained in the form of IPO endorsements, financial data, and the like provided by the enterprise; the heat value indicates how attractive the company is to investors or whether it is a popular investment target.
Step S204, generating a task time schedule corresponding to the investment type, wherein the task time schedule is used for representing an execution plan of a task issued by a first public stock raising IPO of a target enterprise;
and step S206, scheduling the tasks to be executed according to the task time schedule and executing the tasks to be executed.
According to the embodiment of the invention, the investment type of the enterprise is determined according to the enterprise data of the target enterprise to determine the attention degree of the target enterprise to investors; aiming at each investment type, automatically generating a task time schedule corresponding to the investment type; and scheduling and executing the tasks to be executed according to the task time schedule without manually planning to arrange IPO issuing tasks, thereby solving the technical problem of low task scheduling efficiency in the related technology and improving the accuracy of workflow planning time points.
In an alternative embodiment, the determining the investment type of the target enterprise according to the preset rule comprises: acquiring enterprise data of a target enterprise, wherein the enterprise data at least comprises: the asset scale of the target enterprise, the release shares of the target enterprise, and the industry market share of the target enterprise; calculating the heat value of the target enterprise by the following formula: heat value ═ a × asset size + b × issued shares + c × industry market share; wherein a represents the preset weight of the asset scale in the first public stock raising, b represents the preset weight of the issued shares in the first public stock raising, and c represents the preset weight of the market share in the first public stock raising; and determining the target type of the target enterprise by comparing the heat value with a preset value, wherein the target type represents the IPO success rate of the target enterprise.
In one embodiment of the present disclosure, a classification prediction model formula is used: type _ score (type _ score) ═ a × company asset size + b × issued shares + c × industry market share; wherein a, b and c are weight coefficients; optionally, the parameters a, b, and c are obtained by a classification method of logistic regression based on historical IPO release data.
Optionally, the IPO issues are classified into 3 bins according to type _ score: hot IPO, ordinary IPO, may encounter cold IPO (i.e., the success rate of the above-mentioned IPO issuance); in one example, type _ score is normalized to between 0 and 1, and a threshold value of 0.8 or higher is set as a hot IPO and a threshold value of 0.3 or lower is set as a cold IPO.
In an alternative embodiment of the present disclosure, generating a mission schedule corresponding to the investment type includes: generating a task time reference table of the target enterprise according to the historical execution duration of the issued tasks associated with the investment types; generating a risk task association table of the target enterprise according to the risk tasks of the issued tasks and the execution duration of the risk tasks; and generating a task time schedule of the target enterprise based on the task time reference table and the risk task association table.
In this embodiment, for each file (i.e. hot IPO, normal IPO, and cold IPO), there will be at least 2 task template tables in the system, including: the system comprises a task time prediction basis table (namely the task time reference table) and issue handling risk tasks (namely the risk task association table), wherein the task time prediction basis table is used for recording IPO issue task prediction time, and the IPO risk task association table is used for associating IPO issue tasks with risk tasks needing to be additionally added.
Optionally, the generating a task time reference table of the target enterprise according to the historical execution duration of the issued tasks associated with the investment types includes: recording the participants of the issued tasks and the processing timeliness of the issued tasks according to the historical execution duration of the issued tasks; generating a task time reference table based on the participants who issue the tasks and the processing time effectiveness, wherein the task time reference table at least comprises the following field contents: the type of the enterprise, the task name, the task code, the execution time and the participating party.
In an optional example of the above embodiment, different participants are recorded according to the time of the previous task execution for the task time prediction basis table, and if there is no classification data for the first time and the task prediction basis data for different task processing, default data is given. As shown in table 1, taking the heat IPO as an example, the purchase requisition data cleaning task and the distribution data upload, as well as the respective execution time length, the respective task id, and the participating party are recorded.
Table 1:
alternatively, the total processing time period of the entire IPO is usually predetermined (e.g. 2 days), and the start time point and the end time point of the task execution are arranged according to the task processing duration, wherein the task execution time is also determined by the task average execution time according to the historical IPO issue data.
In an optional embodiment of the present disclosure, generating the risk task association table of the target enterprise according to the risk task of the issue task and the execution duration of the risk task includes: recording a risk task of an issuing task and the execution duration of the risk task; generating a risk task association table of the target enterprise based on the risk tasks and the execution duration of the risk tasks, wherein the risk task association table is used for associating the issuing tasks and the risk tasks corresponding to the issuing tasks, and the risk task association table at least comprises the following field contents: the type of business, the task name of the release task, the task code of the release task, the task name of the risk task, and the task code of the risk task.
In this embodiment, risk tasks corresponding to different types of IPO issuance tasks are recorded, where fields of the task association table are as follows: the issue classification, task name, and task id deal with the risky task.
Preferably, the task id can be automatically generated by a system or designated by manual setting and serves as a unique identifier of one task; the IPO risk task association table is used for associating IPO issuing tasks with risk tasks needing to be additionally added. As shown in table 2:
table 2:
| distribution classification | Task name | Task id | Risk task id | Risk tasks |
| Heat IPO | Procurement data cleansing | 123 | 11 | De-weighting cleaning inspection |
| Heat IPO | Procurement data cleansing | 123 | 22 | Payment data file splitting |
According to the above embodiment, the method further comprises a risk task table, wherein the fields of the risk task table are as follows: task id, task name, inspector, inspection presentation parameter (for Dashboard list presentation) notification mode (sms email, etc.).
Optionally, the generating a task time schedule of the target enterprise based on the task time reference table and the risk task association table includes: generating a planned time table of the issuing tasks according to the task time reference table, the preset sequence of the issuing tasks and the dependency relationship of the issuing tasks; and adding risk tasks to the schedule based on the risk task association table, and correspondingly adjusting the execution duration of the issued tasks to obtain a task time schedule.
In the embodiment, the predicted time of each issue task is obtained according to the issue classification and the IPO task template table, and the schedule of each participant and each task of the IPO issue tasks is automatically discharged according to the order of the IPO issue tasks and the dependency relationship of each issue task; preferably, the task plan list is used for generating a workflow plan, and the workflow plan can be displayed for each participant on a web page to form a todolist checklist, so that the participant can conveniently view and plan.
Optionally, the task time schedule is stored in the block chain, and scheduling the task to be executed according to the task time schedule and executing the task to be executed includes: acquiring a task time schedule through a workflow scheduler; calling a first task in the task time schedule and executing the first task; based on the execution condition of the first task, if a risk task corresponding to the first task needs to be added in a directed acyclic graph mode, the execution time of a second task is delayed for a preset time, wherein the second task is the next task depending on the first task in a task time schedule.
Optionally, to further ensure the privacy and security of the task time schedule, the task time schedule may also be stored in a node of a block chain.
In one example, according to the release classification and risk task table, the risk checking task is automatically added, the task time is automatically adjusted, and the time prediction of the time consumed by the risk task is given. For example, for the popularity IPO, due to the large number of procurement people and the large data volume, for the procurement data cleaning task, the deduplication cleaning inspection needs to be added, and the data file splitting inspection task needs to be paid; tasks which are dependent behind the procurement data cleaning task are automatically arranged after the payment data file splitting and checking task, so that the planning time point is correspondingly adjusted.
The invention is further illustrated below with reference to a specific embodiment:
an embodiment of the present invention provides an intelligent workflow planning system to help an exchange perform coordinated scheduling of each issue link, and centralize and transparentize issue flow processing to achieve the purposes of shortening IPO issue time and ensuring successful IPO issue, and fig. 3 is a task execution flow chart for providing task scheduling according to an embodiment of the present invention, as shown in fig. 3.
Further, fig. 4 is a flowchart of specific task scheduling steps according to an embodiment of the present invention, and as shown in fig. 4, the method includes the following steps:
IPO issuer classification prediction. By using the formula: the heat value, a asset size + b issuance share + c industry market share, is calculated and the IPO issuer is classified and forecasted based on heat ratings.
And 2, obtaining data of an IPO task template table, wherein the template comprises an IPO issuing task, time consumption (namely the execution time length), a risk task needing to be added, time consumption/detector information and the like. And then generating a task time reference table and a risk task association table. Wherein, IPO tasks of different classifications have different execution time lengths and different risk subtasks.
3. And acquiring manually adjusted task information, wherein the task information comprises a manually specified task sequence, a task timing time point, newly increased or decreased risk task information and the like.
4. And generating an actual IPO task plan list and determining the task dependency relationship. The method comprises the following steps: and sequentially traversing IPO tasks in the template task time prediction table and the risk task association table, and adding the IPO tasks into the actual IPO task plan list. For example, if the task A in the template table is checked to be related to the risk task, the task A is sequentially added into an actual IPO task plan list, and the preorder dependent task id of the risk task is set to be the id of the task A; 4.2, taking down a task from the template table, and obtaining the id of the preorder dependent task, if the task A finds the related risk task in the IPO task list, setting the preorder dependent task id as the last risk task of the task A, thereby establishing the task dependency relationship.
In an embodiment of the present disclosure, a Task is initialized according to a Task time prediction basis table and a Task dependency relationship is determined, a risk Task is added or deleted based on a workflow diagram (i.e., the Task time schedule table), an IPO scheduling object is generated, and a timing Task is set. The method specifically comprises the following steps:
1) and in a risk point task link, executing risk response task check to ensure that the execution is error-free.
Optionally, at the same time, the IPO participant is reminded of the risk of needing to be checked through a trigger message notification (e.g., a standing email, an email, or a short message), and corresponding data statistics are displayed in real time.
In one example, the process of adding a task is as follows:
a) initializing a Task according to the previous predicted Task data; the field contents include:
the Task has time attributes such as id number, name, state, plan start time, plan finish time, and the like.
b) Generation of a workflow diagram (i.e., the task time schedule described above):
the workflow graph contains tasks and task dependencies (edges of a DAG (directed acyclic graph)), and tasks may be added/deleted or deleted. the task is maintained in a LIST, the task dependency is maintained in a map mapping table, the task name is used as a key, and the pre-dependent task is used as a value. After the tasks and the dependency relationships are initialized, workflow diagram objects corresponding to the IPOs can be generated.
5. And acquiring IPO participant information and specific user information, and binding the IPO participant information and the specific user information with the task (for displaying the task which needs to be executed and concerned by the user on a page in the following step). And according to the heat of issuing IPO, the adjustment of issuing task time and task dependency relationship, adding risk task in a targeted manner and automatically adjusting the dependency relationship, and automatically refreshing the adjusted workflow diagram.
And if the actual completion time point of the task is deviated, automatically adjusting the subsequent task planning time point.
For example, if the execution start time of the previous task a is delayed by 15 minutes from the previously planned delay, an empirical completion delay time, for example, 30 minutes, is calculated according to the historical task execution data, and at this time, the DAG scheduler refreshes and adjusts, and automatically sets the start time delay of the later dependent task B by 30 minutes. If the final delay time of the task A is 20 minutes, the scheduler automatically triggers and executes the subsequent dependent task B, and releases the previously set timing task without waiting for the timing time to execute again, so that the flow time is saved.
Alternatively, if there is no regulation to mark a reasonable task time period within 24 hours, for example, the payment task has a fixed time window such as 2 pm, when the payment task is executed after 2 pm because of the delayed processing of the previous task, the subsequent IPO task will be automatically scheduled again according to the time period T +2, the payment task will be scheduled to be executed tomorrow afternoon, and the human intervention check will be notified, if there is no reasonable place to make corresponding adjustment.
6. The task start time start _ time/end time end _ time is automatically calculated.
The system automatically records the actual execution time of each task, records badcase (bad case) with large prediction deviation and provides the badcase for subsequent verification so as to adjust the automatic workflow prediction and scheduling strategy.
And the actual execution time of each task comprises the start time and the end time of the task, and the task execution time is recorded into an actual IPO task plan list.
Specifically, a first task start time is taken first, and the task end time is the start time plus the task time; recording the starting time/the ending time into an actual IPO task plan list;
then, calculating the task starting time, wherein whether the service fixed starting time exists in the template table is required to be referred, if so, comparing the ending time of the pre-order task with the service fixed starting time, and selecting which is the latest time as the starting time; or adjusting to be executed the next day according to the service requirement;
further, taking down a task, acquiring a preorder dependent task id of the task, and taking the end time of the preorder dependent task from the actual IPO task plan list as the start time of the task; the end time is calculated from the task time consumption of this task.
7. Loading a task time plan list to a workflow scheduler;
and the workflow scheduler loads the generated workflow diagrams, takes out tasks needing to be operated one by one and executes the tasks, and adjusts the task execution time according to the actual execution condition so as to achieve the effect of automatic planning of the workflow.
8. And adjusting the starting time and the ending time of the subsequent task plan according to the actual execution condition of the preorder task.
And searching whether historical task time consumption of the pre-order task is stored in the template table, if so, comparing the actual execution time of each task with the recorded actual execution time, predicting the planned execution time of the subsequent task, then adjusting the starting time and the ending time of the subsequent task plan according to the business requirements, adjusting the automatic scheduling execution of the IPO issuing task, and coordinating the risk task scheduling of each link issued by the IPO.
Through the steps, the following beneficial effects can be achieved: 1. the planning work does not need to be done manually, the checking and rechecking are only done when necessary, and the workflow time of each task issued is automatically adjusted ipo; 2. the method comprises the steps that information of historically executed participator tasks, time consumption, data scale and the like is recorded, and an issuing enterprise issuing classification model identifies that excessive subscription or cold subscription is possible to be carried out on the IPO issuing at this time, and the time consumption of the tasks is predicted and estimated, so that the workflow time is adjusted more accurately and automatically, and the whole process is predicted more accurately and reliably; 3. aiming at different issuing classifications, a risk point inspection task is added, the exchange is reminded of where a risk point is in advance, prevention and control are well done, and an issuing participant is enabled to make a corresponding coping plan to help an IPO issue to succeed; 4. the possible future working time consumption can be estimated according to the historical task time consumption situation, and the accuracy of the workflow planning time point is improved; 5. this scheme belongs to wisdom city field, can promote the construction in wisdom city through this scheme.
Example 2
In this embodiment, a task scheduling device is further provided, and the device is used to implement the foregoing embodiments and preferred embodiments, and details are not described again after the description is given. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 5 is a block diagram of a task scheduling apparatus according to an embodiment of the present invention, and as shown in fig. 5, the apparatus is applied to a web server, and the apparatus includes: the determining module 52 is configured to determine an investment type of the target enterprise according to preset rules, where the preset rules are used to calculate a popularity value of the target enterprise, which is focused by the investor, according to enterprise data of the target enterprise, and the investment type is divided based on the popularity value of the target enterprise, which is focused by the investor; a generating module 54, connected to the determining module 52, configured to generate a mission time schedule corresponding to the investment type, where the mission time schedule is used to represent an execution plan of a first time public recruitment IPO issue mission of a target enterprise; and the execution module 56 is connected to the generation module 54 and is used for scheduling the tasks to be executed according to the task time schedule and executing the tasks to be executed.
Optionally, the determining module 52 includes: the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring enterprise data of a target enterprise, and the enterprise data at least comprises: the asset scale of the target enterprise, the release shares of the target enterprise, and the industry market share of the target enterprise; the calculating unit is used for calculating the heat value of the target enterprise through the following formula: heat value ═ a × asset size + b × issued shares + c × industry market share; wherein a represents the preset weight of the asset scale in the first public stock raising, b represents the preset weight of the issued shares in the first public stock raising, and c represents the preset weight of the market share in the first public stock raising; and the determining unit is used for determining the target type of the target enterprise by comparing the heat value with a preset value, wherein the target type represents the IPO success rate of the target enterprise.
Optionally, the generating module 54 includes: the first generation unit is used for generating a task time reference table of the target enterprise according to the historical execution duration of the issued tasks associated with the investment types; the second generation unit is used for generating a risk task association table of the target enterprise according to the risk tasks of the issuing tasks and the execution duration of the risk tasks; and the third generation unit is used for generating a task time schedule of the target enterprise based on the task time reference table and the risk task association table.
Optionally, the first generating unit includes: the first recording subunit is used for recording the participants of the issued task and the processing timeliness of the issued task according to the historical execution duration of the issued task; the first generation subunit is used for generating a task time reference table based on the participants who issue the tasks and the processing timeliness, wherein the task time reference table at least comprises the following field contents: the type of the enterprise, the task name, the task code, the execution time and the participating party.
Optionally, the second generating unit includes: the second recording subunit is used for recording the risk task of the issuing task and the execution duration of the risk task; the second generation subunit is configured to generate a risk task association table of the target enterprise based on the risk task and the execution duration of the risk task, where the risk task association table is used to associate the issue task and the risk task corresponding to the issue task, and the risk task association table at least includes the following field contents: the type of business, the task name of the release task, the task code of the release task, the task name of the risk task, and the task code of the risk task.
Optionally, the second generating unit includes: the third generation subunit is used for generating a planned time table of the issuing tasks according to the task time reference table, the preset sequence of the issuing tasks and the dependency relationship of the issuing tasks; and the fourth generation subunit is used for adding the risk tasks to the schedule based on the risk task association table and correspondingly adjusting the execution duration of the release tasks to obtain the task time schedule.
Optionally, the task time schedule is stored in the block chain, and the execution module 56 includes: a second obtaining unit, configured to obtain the task time schedule through the workflow scheduler; the calling unit is used for calling a first task in the task time schedule and executing the first task; and the execution unit is used for adding a risk task corresponding to the first task in a directed acyclic graph mode if necessary based on the execution condition of the first task, and delaying the execution time of a second task by a preset time, wherein the second task is the next task depending on the first task in the task time schedule.
It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.
Example 3
Embodiments of the present invention also provide a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
Alternatively, in the present embodiment, the storage medium may be configured to store a computer program for executing the steps of:
s1, determining the investment type of a target enterprise according to preset rules, wherein the preset rules are used for calculating the heat value of the target enterprise concerned by investors according to enterprise data of the target enterprise, and the investment type is divided based on the heat value of the target enterprise concerned by investors;
s2, generating a task time schedule corresponding to the investment type, wherein the task time schedule is used for representing an execution plan of a first time public recruitment IPO issue task of the target enterprise;
and S3, scheduling the tasks to be executed according to the task time schedule and executing the tasks to be executed.
Optionally, in this embodiment, the storage medium may include, but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:
s1, determining the investment type of a target enterprise according to preset rules, wherein the preset rules are used for calculating the heat value of the target enterprise concerned by investors according to enterprise data of the target enterprise, and the investment type is divided based on the heat value of the target enterprise concerned by investors;
s2, generating a task time schedule corresponding to the investment type, wherein the task time schedule is used for representing an execution plan of a first time public recruitment IPO issue task of the target enterprise;
and S3, scheduling the tasks to be executed according to the task time schedule and executing the tasks to be executed.
Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and this embodiment is not described herein again.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A task scheduling method is applied to a web server and comprises the following steps:
determining an investment type of a target enterprise according to a preset rule, wherein the preset rule is used for calculating a heat value of the target enterprise concerned by an investor according to enterprise data of the target enterprise, and the investment type is divided based on the heat value of the target enterprise concerned by the investor;
generating a task time schedule corresponding to the investment type, wherein the task time schedule is used for representing an execution plan of a task issued by the first public stock raising IPO of the target enterprise;
and scheduling the tasks to be executed according to the task time schedule and executing the tasks to be executed.
2. The method of claim 1, wherein determining the investment type of the target enterprise according to the predetermined rules comprises:
acquiring enterprise data of the target enterprise, wherein the enterprise data at least comprises: the asset size of the target enterprise, the release shares of the target enterprise, the industry market share of the target enterprise;
calculating the heat value of the target enterprise by the following formula:
heat value ═ a × asset size + b × issued shares + c × industry market share; wherein a represents the preset weight of the asset scale in the first public stock raising, b represents the preset weight of the issued shares in the first public stock raising, and c represents the preset weight of the market share in the first public stock raising;
and determining a target type of the target enterprise by comparing the heat value with a preset value, wherein the target type represents the IPO success rate of the target enterprise.
3. The method of claim 1, wherein generating a mission schedule corresponding to the investment type comprises:
generating a task time reference table of the target enterprise according to the historical execution duration of the issued tasks associated with the investment types;
generating a risk task association table of the target enterprise according to the risk task of the issuing task and the execution duration of the risk task;
and generating a task time schedule of the target enterprise based on the task time reference table and the risk task association table.
4. The method of claim 3, wherein generating a task schedule for the target business based on historical execution duration of release tasks associated with the investment type comprises:
recording the participants of the issued tasks and the processing timeliness of the issued tasks according to the historical execution duration of the issued tasks;
generating the task time reference table based on the participants who issue the tasks and the processing aging, wherein the task time reference table at least comprises the following field contents: the type of the enterprise, the task name, the task code, the execution time and the participating party.
5. The method of claim 3, wherein generating the risk task association table for the target enterprise based on the risk tasks of the release tasks and the execution duration of the risk tasks comprises:
recording a risk task of the issuing task and the execution duration of the risk task;
generating a risk task association table of the target enterprise based on the risk task and the execution duration of the risk task, wherein the risk task association table is used for associating the issue task with the risk task corresponding to the issue task, and the risk task association table at least comprises the following field contents: a type of enterprise, a task name of the release task, a task code of the release task, a task name of the risky task, and a task code of the risky task.
6. The method of claim 3, wherein generating a task time schedule for the target enterprise based on the task time reference table and the risk task association table comprises:
generating a planned time table of the issued tasks according to the task time reference table, the preset sequence of the issued tasks and the dependency relationship of the issued tasks;
and adding risk tasks to the schedule based on the risk task association table, and correspondingly adjusting the execution duration of the issued tasks to obtain the task time schedule.
7. The method of claim 1, wherein the task time schedule is stored in a blockchain, and wherein scheduling tasks to be performed and executing the tasks to be performed according to the task time schedule comprises:
acquiring the task time schedule through a workflow scheduler;
calling a first task in the task time schedule and executing the first task;
and if a risk task corresponding to the first task needs to be added in a directed acyclic graph mode based on the execution condition of the first task, delaying the execution time of a second task by preset time, wherein the second task is the next task depending on the first task in the task time schedule.
8. A task scheduling device applied to a web server includes:
the system comprises a determining module, a judging module and a judging module, wherein the determining module is used for determining the investment type of a target enterprise according to a preset rule, the preset rule is used for calculating the heat value of the target enterprise concerned by investors according to enterprise data of the target enterprise, and the investment type is divided based on the heat value of the target enterprise concerned by the investors;
the generating module is used for generating a task time schedule corresponding to the investment type, wherein the task time schedule is used for representing an execution plan of a task issued by the first public offering IPO of the target enterprise;
and the execution module is used for scheduling the tasks to be executed according to the task time schedule and executing the tasks to be executed.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.
10. A computer storage medium on which a computer program is stored, characterized in that the computer program, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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