Task scheduling methods, devices, computer equipment and storage media

Abstract

This application belongs to the field of artificial intelligence and relates to a task scheduling method, apparatus, computer device, and storage medium. The method includes: acquiring task value assessment information of a task to be scheduled; inputting the task value assessment information into a task value assessment model to obtain a task value assessment result; when the task to be scheduled is determined to be a task that can be taken offline based on the task value assessment result, searching for related tasks of the task to be scheduled according to a pre-established task graph; and taking offline the task to be scheduled and related tasks. Furthermore, this application also relates to blockchain technology, whereby the task value assessment information can be stored in the blockchain. This application improves the accuracy of task scheduling.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of artificial intelligence, and in particular relates to a task scheduling method and device, computer equipment and a storage medium. BACKGROUND

[0002] With the development of computer technology, production and business activities of various institutions are increasingly managed online, and various online tasks are published. However, the life cycles of various tasks are different, some projects may run for a long time, and some projects may be gradually abandoned due to business iteration, personnel changes, and decreased access, etc. These abandoned tasks will continue to occupy platform resources, and if not discovered and cleaned up in time, a large amount of resources will be wasted.

[0003] However, the scheduling of these tasks is usually implemented manually, that is, relying on manual experience to determine which tasks have low value and can be offline, and manually searching for other tasks associated with the offline tasks so as to be offline together. With the increase in the number of tasks, the accuracy of scheduling these tasks by relying on manual experience is also lower and lower. SUMMARY

[0004] The purpose of the embodiments of the present application is to provide a task scheduling method, device, computer equipment and storage medium to improve the accuracy of task scheduling.

[0005] To solve the above technical problems, the embodiments of the present application provide a task scheduling method, which adopts the technical scheme as follows:

[0006] Obtain task value evaluation information of a task to be scheduled;

[0007] Input the task value evaluation information into a task value evaluation model to obtain a task value evaluation result;

[0008] When it is determined according to the task value evaluation result that the task to be scheduled is an offline task, search for associated tasks of the task to be scheduled according to a pre-established task graph;

[0009] Offline schedule the task to be scheduled and the associated tasks.

[0010] To solve the above technical problems, the embodiments of the present application also provide a task scheduling device, which adopts the technical scheme as follows:

[0011] An information obtaining module is configured to obtain task value evaluation information of a task to be scheduled;

[0012] A value evaluation module is configured to input the task value evaluation information into a task value evaluation model to obtain a task value evaluation result;

[0013] The associated search module is used to search for associated tasks of the task to be scheduled based on a pre-established task graph when the task to be scheduled is determined to be a task that can be taken offline based on the task value assessment result.

[0014] The offline scheduling module is used to schedule the task to be scheduled and the associated task offline.

[0015] To address the aforementioned technical problems, this application also provides a computer device that employs the following technical solution:

[0016] Obtain the task value assessment information of the tasks to be scheduled;

[0017] Input the task value assessment information into the task value assessment model to obtain the task value assessment result;

[0018] When the task to be scheduled is determined to be a task that can be taken offline based on the task value assessment result, the associated tasks of the task to be scheduled are searched according to the pre-established task graph.

[0019] The task to be scheduled and the associated task are taken offline and scheduled.

[0020] To address the aforementioned technical problems, this application also provides a computer-readable storage medium, employing the technical solution described below:

[0021] Obtain the task value assessment information of the tasks to be scheduled;

[0022] Input the task value assessment information into the task value assessment model to obtain the task value assessment result;

[0023] When the task to be scheduled is determined to be a task that can be taken offline based on the task value assessment result, the associated tasks of the task to be scheduled are searched according to the pre-established task graph.

[0024] The task to be scheduled and the associated task are taken offline and scheduled.

[0025] Compared with the prior art, the embodiments of this application have the following advantages: They obtain task value assessment information for tasks to be scheduled, including multi-dimensional information related to task value; the task value assessment model automatically assesses the task value of the task to be scheduled based on the task value assessment information, obtaining a task value assessment result; the task value assessment result is used to display the task value of the task to be scheduled; when the task value is low, the task to be scheduled is identified as a task that can be taken offline, and downstream related tasks affected by the task to be scheduled are accurately searched through the task graph, thereby taking the task to be scheduled and related tasks offline. This achieves automatic assessment of task value, automatic identification and search of tasks that need to be taken offline, avoids incorrect judgments and omissions, and improves the efficiency and accuracy of task scheduling. Attached Figure Description

[0026] To more clearly illustrate the solutions in this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is an exemplary system architecture diagram to which this application can be applied;

[0028] Figure 2 This is a flowchart of an embodiment of the task scheduling method according to this application;

[0029] Figure 3 This is a schematic diagram of a structure of an embodiment of the task scheduling device according to this application;

[0030] Figure 4 This is a schematic diagram of the structure of one embodiment of the computer device according to this application. Detailed Implementation

[0031] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application, are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0032] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0033] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0034] like Figure 1 As shown, system architecture 100 may include terminal devices 101, 102, and 103, a network 104, and a server 105. Network 104 serves as the medium for providing communication links between terminal devices 101, 102, and 103 and server 105. Network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0035] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, and 103, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social media platform software, etc.

[0036] Terminal devices 101, 102, and 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III), MP4 players (Moving Picture Experts Group Audio Layer IV), laptops, and desktop computers, etc.

[0037] Server 105 can be a server that provides various services, such as a backend server that supports the pages displayed on terminal devices 101, 102, and 103.

[0038] It should be noted that the task scheduling method provided in this application embodiment is generally executed by the server, and correspondingly, the task scheduling device is generally set in the server.

[0039] It should be understood that Figure 1The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0040] Continue to refer to Figure 2 A flowchart of an embodiment of the task scheduling method according to this application is shown. The task scheduling method includes the following steps:

[0041] Step S201: Obtain the task value assessment information of the task to be scheduled.

[0042] In this embodiment, the task scheduling method runs on an electronic device (e.g., Figure 1 The server shown can communicate with the terminal via wired or wireless connection. It should be noted that the aforementioned wireless connection methods may include, but are not limited to, 3G / 4G / 5G connections, WiFi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (ultra wideband) connections, and other currently known or future wireless connection methods.

[0043] Specifically, multiple tasks can run online. When it is necessary to take multiple running tasks offline, each task can be processed one by one to obtain the task to be scheduled.

[0044] The task to be scheduled has task value assessment information, which can be multi-dimensional and used to measure and evaluate the task value of the task to be scheduled.

[0045] Step S202: Input the task value assessment information into the task value assessment model to obtain the task value assessment result.

[0046] Specifically, the task value assessment information is input into the trained task value assessment model. The model processes the multi-dimensional information in the task value assessment information and outputs the task value assessment result. The task value assessment result can be a numerical value, using the magnitude of the value to measure the task; or it can be a classification result, using the task category to which the task to be scheduled belongs to measure the value of the task.

[0047] The task value assessment model can be built based on a neural network. Task value assessment information is input into the model, and the neural network predicts and evaluates the task value, outputting the assessment result. In one embodiment, the task value assessment model can be a tree model such as Random Forest, XGBoost, GBDT, or LightGBM. Multi-dimensional information from the task value assessment model is input into the tree model to obtain the task value assessment result.

[0048] Step S203: When the task to be scheduled is determined to be a task that can be taken offline based on the task value assessment result, search for related tasks of the task to be scheduled based on the pre-established task graph.

[0049] Specifically, the task value assessment result is used to display the task value of the task to be scheduled. If the task value assessment result indicates that the task value of the task to be scheduled is low, then the task to be scheduled can be marked as a task that can be taken offline. Tasks that can be taken offline can be scheduled offline, thereby avoiding the waste of system resources.

[0050] Multiple tasks can run on the system, and there are dependencies between the tasks. For example, task A generates data table B, and task C needs to read data from data table B when it runs. Therefore, task C depends on data table B, and task C depends on task A. Task A is the upstream task of task C, and task C is the downstream task of task A.

[0051] Dependencies and relationships between tasks can be stored and retrieved using a task graph. A knowledge graph is a graph built based on the tasks in the system. It can record dependencies and relationships between tasks, as well as other attributes of the tasks.

[0052] The task graph can be a Neo4j knowledge graph. Neo4j is a high-performance NoSQL graph database that stores structured data on a network (mathematically called a graph) instead of tables. Neo4j can also be seen as a high-performance graph engine.

[0053] When the task to be scheduled is a task that can be taken offline, the task to be scheduled can be used as a search condition to search through the task graph to find related tasks. Here, the related tasks can be the downstream tasks of the task to be scheduled found through the task graph. In one embodiment, after finding the downstream task of the task to be scheduled through the task graph, the downstream task can be used as a new starting point to continue searching for new downstream tasks. The search is continued in the above manner until no new downstream tasks can be found. All the tasks found are marked as related tasks affected by the task to be scheduled.

[0054] Step S204: Take the task to be scheduled and related tasks offline.

[0055] Specifically, tasks with low value that are pending scheduling can be taken offline. When taking a task offline, in addition to the task itself, downstream related tasks affected by the task can also be taken offline.

[0056] In this embodiment, task value assessment information of the task to be scheduled is obtained, which includes multi-dimensional information related to task value. The task value assessment model automatically assesses the task value of the task to be scheduled based on the task value assessment information, and obtains the task value assessment result. The task value assessment result is used to display the task value of the task to be scheduled. When the task value is small, the task to be scheduled is identified as a task that can be taken offline. The downstream related tasks affected by the task to be scheduled are accurately searched through the task graph, thereby taking the task to be scheduled and related tasks offline. This realizes automatic assessment of task value and automatic identification and search of tasks that need to be taken offline, avoiding misjudgment and omission, and improving the efficiency and accuracy of task scheduling.

[0057] Furthermore, step S201 may include: obtaining access object information, access time information, and resource consumption information of the task to be scheduled; and determining the access object information, access time information, and resource consumption information as task value assessment information of the task to be scheduled.

[0058] Specifically, the system obtains the access object information, access time information, and resource consumption information of the task to be scheduled. Each task has an access object, which is the user of the task. For example, for an approval task, the access object could be the approver. Generally, the more access objects and the higher their level, the higher the value of the task. The access object information records details such as the task's access objects, their levels, and the number of access objects.

[0059] Each time an accessed object accesses a task, the access time is recorded. Generally, the more times a task is accessed, the higher its value. However, the number of accesses must also be considered in conjunction with the access time. For example, a task might be accessed many times when it first goes live, but the number of accesses drops drastically after a period of time; in this case, the task's value may not be very high. Access time information can be the time when the task is accessed, the time when the task is accessed within a preset time period, or the time when the task is last accessed.

[0060] When a task runs, it will consume certain hardware resources, such as the CPU's runtime and the storage space consumed by the task. These are the resource consumption information of the task.

[0061] Access object information, access time information, and resource consumption information can be used as task value assessment information for tasks to be scheduled.

[0062] In this embodiment, the access object information, access time information, and resource consumption information of the task to be scheduled are determined as task value assessment information, ensuring that the task value can be comprehensively measured.

[0063] Furthermore, before step S203 above, the process may include: obtaining task dependency information and task value assessment information for each task; determining node objects, relationship information, and attribute information based on the task dependency information and task value assessment information; and establishing a task graph based on the node objects, relationship information, and attribute information.

[0064] Specifically, this application requires the prior establishment of a task graph before the search. The establishment of the task graph requires the acquisition of the task dependency relationships and task value assessment information of each task. Among them, the task dependency relationship records the dependency relationship between tasks.

[0065] The task graph in this application can be a Neo4j knowledge graph. A graph is a common data structure used to represent objects and the relationships between them. Objects are also called nodes or vertices, and relationships are described by edges. Mathematically, a graph is generally represented by G = (V, E, A, X), where V = {v1, v2, ..., vn} is the set of nodes, E = e_ij represents the set of edges, A is an adjacency matrix of size |V| × |V|, used to represent the connections between nodes, and if e_ij ∈ E, then A_ij = 1. X is a feature matrix of size |V| × d, where the i-th row X_i represents the attribute features of the i-th node, and d is the dimension of the attribute.

[0066] Artificial intelligence can be used to analyze task dependency information and task value assessment information to identify node objects, relationship information, and attribute information. Node objects can be tasks, access objects, etc. Tasks have dependencies on each other, and these dependencies constitute relationship information. Relationship information can also exist between access objects and tasks. Access objects and tasks have attribute information in key / value format; for example, access objects have access time, and tasks have resource consumption information.

[0067] Once the node objects, relationship information, and attribute information are determined, the task graph can be built using the knowledge graph construction algorithm.

[0068] In this embodiment, the node objects, relationship information and attribute information required to construct the graph are determined based on the task dependency information and task value assessment information of each task, and a task graph is established to ensure that the accurate search of related tasks can be achieved through the task graph.

[0069] Furthermore, before the steps of obtaining task dependency information and task value assessment information for each task, the method may further include: obtaining the task scripts for each task; parsing each task script to identify data retrieval statements in each task script; and determining the dependencies between tasks based on the data retrieval statements to generate task dependency information.

[0070] Specifically, the task scripts for each task are obtained and parsed to identify the data retrieval statements within them. These data retrieval statements can be SQL statements, indicating which table / task retrieves data from, thus revealing the dependencies between tables, the relationships between tables belonging to tasks, and the dependencies between tasks, thereby obtaining task dependency information.

[0071] In one embodiment, task dependency information can be filled in manually or obtained from the task scripts of each task. The task scripts can record the upstream tasks that a task depends on, thereby generating task dependency information based on each task script.

[0072] In this embodiment, the task scripts of each task are obtained, the data retrieval statements in the task scripts are identified, and the dependency relationships between tasks can be determined based on the data retrieval relationships, thereby accurately generating task dependency information.

[0073] Furthermore, step S203 may include: when the task to be scheduled is determined to be a task that can be taken offline based on the task value assessment result, obtaining a preset search strategy; using the task to be scheduled as a search condition, searching for related tasks of the task to be scheduled in the pre-established task graph based on the search strategy.

[0074] Specifically, when a task to be scheduled is determined to be a task that can be taken offline based on the task value assessment results, a preset search strategy is obtained. The search strategy is used to indicate how to search for related tasks of the task to be scheduled in the task graph. The search strategy can be pre-configured or configured on the spot before the search begins, including configuring whether to perform a depth-first search or a breadth-first search; at the same time, the association level can also be configured. For example, if task A is a task that can be taken offline, task B is the downstream task of task A, and task C and task D are the downstream tasks of task B, configuring the association level can control the depth of the downstream search. If the association level is 1, only one level downstream is searched, and the search stops when task B is found; if the association level is 2, two levels downstream are searched, and tasks B, C, and D are found.

[0075] Then, the task to be scheduled is used as the starting condition for the search, and the search is performed in the task graph based on the search strategy to obtain the related tasks affected by the task to be scheduled.

[0076] In this embodiment, a preset search strategy is obtained. The search strategy is used to control the search operation, thereby enabling personalized search for related tasks.

[0077] Furthermore, step S204 may include: sending the task to be scheduled and related tasks to the terminal logged in by the preset management account; receiving the scheduling confirmation instruction returned by the terminal; and scheduling the task to be scheduled and related tasks offline according to the scheduling confirmation instruction.

[0078] Specifically, after receiving the tasks to be scheduled and related tasks, the task identifiers of the tasks to be scheduled and related tasks can be sent to the terminal logged into by a preset management account. The management account can be the account of the staff member responsible for task scheduling, who can view, modify, or reject the tasks to be scheduled or related tasks through the terminal.

[0079] When staff agree to take a scheduled task and its associated tasks offline, they can trigger a scheduling confirmation command via the terminal. Upon receiving the scheduling confirmation command, the server will take the scheduled task and its associated tasks offline.

[0080] In this embodiment, the task to be scheduled and related tasks are sent to the terminal logged into by the management account for manual review. After the manual review is passed, the task is taken offline according to the scheduling confirmation instruction, thus ensuring the accuracy of the offline scheduling.

[0081] Furthermore, the above task scheduling method may also include: obtaining access object information; using the access object information as a search condition to search for related tasks of the access object information in the task graph; and scheduling the related tasks offline.

[0082] Specifically, it can also obtain the access object information of a task, which can be the access object in the access object information. By querying the task graph, it can find the associated tasks of the access object and schedule the associated tasks offline. For example, an employee's name or employee number constitutes an access object in the system. When an employee leaves the company, the tasks that the employee was responsible for can be taken offline. In this case, the access object information representing the employee can be used as a query condition to find the associated tasks in the task graph and take them offline.

[0083] In this embodiment, access object information can also be used as a search condition to search for related tasks in the task graph and perform offline scheduling, thus enriching the offline scheduling methods.

[0084] It should be emphasized that, in order to further ensure the privacy and security of the aforementioned task value assessment information, the aforementioned task value assessment information can also be stored in a node of a blockchain.

[0085] The blockchain referred to in this application is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Essentially, a blockchain is a decentralized database, a chain of data blocks linked together using cryptographic methods. Each data block contains information about a batch of network transactions, used to verify the validity of the information (anti-counterfeiting) and generate the next block. A blockchain can include an underlying blockchain platform, a platform product service layer, and an application service layer.

[0086] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0087] Foundational technologies for artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0088] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing related hardware with computer-readable instructions. These computer-readable instructions can be stored in a computer-readable storage medium. When executed, the program can include the processes of the embodiments of the above methods. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0089] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0090] Further referenceFigure 3 As a response to the above Figure 2 To implement the method shown, this application provides an embodiment of a task scheduling device, which is similar to... Figure 2 Corresponding to the method embodiments shown, this device can be specifically applied to various electronic devices.

[0091] like Figure 3 As shown, the task scheduling device 300 described in this embodiment includes: an information acquisition module 301, a value assessment module 302, an association search module 303, and an offline scheduling module 304, wherein:

[0092] The information acquisition module 301 is used to acquire the task value assessment information of the task to be scheduled.

[0093] The value assessment module 302 is used to input task value assessment information into the task value assessment model to obtain the task value assessment result.

[0094] The associated search module 303 is used to search for associated tasks of the task to be scheduled based on a pre-established task graph when the task to be scheduled is determined to be a task that can be taken offline based on the task value assessment result.

[0095] The offline scheduling module 304 is used to perform offline scheduling of tasks to be scheduled and related tasks.

[0096] In this embodiment, task value assessment information of the task to be scheduled is obtained, which includes multi-dimensional information related to task value. The task value assessment model automatically assesses the task value of the task to be scheduled based on the task value assessment information, and obtains the task value assessment result. The task value assessment result is used to display the task value of the task to be scheduled. When the task value is small, the task to be scheduled is identified as a task that can be taken offline. The downstream related tasks affected by the task to be scheduled are accurately searched through the task graph, thereby taking the task to be scheduled and related tasks offline. This realizes automatic assessment of task value and automatic identification and search of tasks that need to be taken offline, avoiding misjudgment and omission, and improving the efficiency and accuracy of task scheduling.

[0097] In some optional implementations of this embodiment, the information acquisition module 301 may include: an information acquisition submodule and an information determination submodule, wherein:

[0098] The information acquisition submodule is used to acquire information about the access objects, access times, and resource consumption of the tasks to be scheduled.

[0099] The information determination submodule is used to determine the access object information, access time information, and resource consumption information as the task value assessment information for the task to be scheduled.

[0100] In this embodiment, the access object information, access time information, and resource consumption information of the task to be scheduled are determined as task value assessment information, ensuring that the task value can be comprehensively measured.

[0101] In some optional implementations of this embodiment, the task scheduling device 300 may further include: an acquisition module, a determination module, and an establishment module, wherein:

[0102] The acquisition module is used to acquire task dependency information and task value assessment information for each task.

[0103] The determination module is used to determine node objects, relationship information, and attribute information based on task dependency information and task value assessment information.

[0104] The module is used to build a task graph based on node objects, relationship information, and attribute information.

[0105] In this embodiment, the node objects, relationship information and attribute information required to construct the graph are determined based on the task dependency information and task value assessment information of each task, and a task graph is established to ensure that the accurate search of related tasks can be achieved through the task graph.

[0106] In some optional implementations of this embodiment, the task scheduling device 300 may further include: a script acquisition module, a statement recognition module, and a dependency generation module, wherein:

[0107] The script retrieval module is used to retrieve the task scripts for each task.

[0108] The statement recognition module is used to parse the scripts of each task to identify the data retrieval statements in each script.

[0109] The dependency generation module is used to determine the dependencies between tasks based on the data retrieval statements, and to generate task dependency information.

[0110] In this embodiment, the task scripts of each task are obtained, the data retrieval statements in the task scripts are identified, and the dependency relationships between tasks can be determined based on the data retrieval relationships, thereby accurately generating task dependency information.

[0111] In some optional implementations of this embodiment, the association search module 303 may include: a strategy acquisition submodule and an association search submodule, wherein:

[0112] The strategy acquisition submodule is used to acquire a preset search strategy when the task to be scheduled is determined to be a task that can be taken offline based on the task value assessment results.

[0113] The associated search submodule is used to search for associated tasks of the task to be scheduled in a pre-established task graph based on the search strategy, using the task to be scheduled as the search condition.

[0114] In this embodiment, a preset search strategy is obtained. The search strategy is used to control the search operation, thereby enabling personalized search for related tasks.

[0115] In some optional implementations of this embodiment, the offline scheduling module 304 may include: a task sending submodule, an instruction receiving submodule, and an offline scheduling submodule, wherein:

[0116] The task sending submodule is used to send the tasks to be scheduled and related tasks to the terminal logged in by the preset management account.

[0117] The instruction receiving submodule is used to receive scheduling confirmation instructions returned by the terminal.

[0118] The offline scheduling submodule is used to take offline the scheduled tasks and related tasks according to the scheduling confirmation instruction.

[0119] In this embodiment, the task to be scheduled and related tasks are sent to the terminal logged into by the management account for manual review. After the manual review is passed, the task is taken offline according to the scheduling confirmation instruction, thus ensuring the accuracy of the offline scheduling.

[0120] In some optional implementations of this embodiment, the task scheduling device 300 may further include: an object acquisition module, a task search module, and a task offline module, wherein:

[0121] The object retrieval module is used to obtain information about the accessed object.

[0122] The task search module is used to search for related tasks in the task graph by using the access object information as search criteria.

[0123] The task offline module is used to schedule the offline operation of associated tasks.

[0124] In this embodiment, access object information can also be used as a search condition to search for related tasks in the task graph and perform offline scheduling, thus enriching the offline scheduling methods.

[0125] To address the aforementioned technical problems, embodiments of this application also provide a computer device. Please refer to [link / reference needed]. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0126] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected via a system bus. It should be noted that only the computer device 4 with components 41-43 is shown in the figure; however, it should be understood that it is not required to implement all the shown components, and more or fewer components can be implemented alternatively. Those skilled in the art will understand that the computer device described here is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0127] The computer device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device can interact with the user via a keyboard, mouse, remote control, touchpad, or voice control.

[0128] The memory 41 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 41 may be an internal storage unit of the computer device 4, such as the hard disk or memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 4. Of course, the memory 41 may also include both the internal storage unit and its external storage device of the computer device 4. In this embodiment, the memory 41 is typically used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions for task scheduling methods. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or will be output.

[0129] In some embodiments, the processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor 42 is typically used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to execute computer-readable instructions stored in the memory 41 or to process data, for example, to execute computer-readable instructions of the task scheduling method.

[0130] The network interface 43 may include a wireless network interface or a wired network interface, which is typically used to establish communication connections between the computer device 4 and other electronic devices.

[0131] The computer device provided in this embodiment can execute the task scheduling method described above. The task scheduling method here can be any of the task scheduling methods described in the various embodiments above.

[0132] In this embodiment, task value assessment information of the task to be scheduled is obtained, which includes multi-dimensional information related to task value. The task value assessment model automatically assesses the task value of the task to be scheduled based on the task value assessment information, and obtains the task value assessment result. The task value assessment result is used to display the task value of the task to be scheduled. When the task value is small, the task to be scheduled is identified as a task that can be taken offline. The downstream related tasks affected by the task to be scheduled are accurately searched through the task graph, thereby taking the task to be scheduled and related tasks offline. This realizes automatic assessment of task value and automatic identification and search of tasks that need to be taken offline, avoiding misjudgment and omission, and improving the efficiency and accuracy of task scheduling.

[0133] This application also provides another embodiment, namely, providing a computer-readable storage medium storing computer-readable instructions that can be executed by at least one processor to cause the at least one processor to perform the steps of the task scheduling method described above.

[0134] In this embodiment, task value assessment information of the task to be scheduled is obtained, which includes multi-dimensional information related to task value. The task value assessment model automatically assesses the task value of the task to be scheduled based on the task value assessment information, and obtains the task value assessment result. The task value assessment result is used to display the task value of the task to be scheduled. When the task value is small, the task to be scheduled is identified as a task that can be taken offline. The downstream related tasks affected by the task to be scheduled are accurately searched through the task graph, thereby taking the task to be scheduled and related tasks offline. This realizes automatic assessment of task value and automatic identification and search of tasks that need to be taken offline, avoiding misjudgment and omission, and improving the efficiency and accuracy of task scheduling.

[0135] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0136] Obviously, the embodiments described above are only some embodiments of this application, not all embodiments. The accompanying drawings show preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms; rather, the purpose of providing these embodiments is to provide a more thorough and comprehensive understanding of the disclosure of this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this application's specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the scope of patent protection of this application.

Claims

1. A task scheduling method, characterized by, The method comprises the following steps: obtaining task value evaluation information of a task to be scheduled; inputting the task value evaluation information into a task value evaluation model to obtain a task value evaluation result; when it is determined according to the task value evaluation result that the task to be scheduled is an offline task, searching for an associated task of the task to be scheduled according to a pre-established task graph; offline scheduling the task to be scheduled and the associated task; before the step of searching for the associated task of the task to be scheduled according to the pre-established task graph, the method further comprises: obtaining task dependency relationship information and task value evaluation information of each task; determining node objects, relationship information and attribute information based on the task dependency relationship information and the task value evaluation information; establishing a task graph according to the node objects, the relationship information and the attribute information, wherein the task graph is a Neo4j knowledge graph; the step of searching for the associated task of the task to be scheduled according to the pre-established task graph when it is determined according to the task value evaluation result that the task to be scheduled is an offline task comprises: when it is determined according to the task value evaluation result that the task to be scheduled is an offline task, obtaining a pre-set search strategy; searching for the associated task of the task to be scheduled in the pre-established task graph based on the search strategy, wherein the search strategy is used to indicate how to search for the associated task of the task to be scheduled in the task graph, and the search strategy is a depth-first search or a breadth-first search.

2. The task scheduling method of claim 1, wherein, the step of obtaining the task value evaluation information of the task to be scheduled comprises: obtaining access object information, access time information and resource consumption information of the task to be scheduled; determining the access object information, the access time information and the resource consumption information as the task value evaluation information of the task to be scheduled.

3. The task scheduling method of claim 1, wherein, before the step of obtaining the task dependency relationship information and the task value evaluation information of each task, the method further comprises: obtaining task scripts of each task; parsing each task script to identify a data obtaining statement in the each task script; determining a dependency relationship between tasks according to the data obtaining statement to generate task dependency relationship information.

4. The task scheduling method of claim 1, wherein, the step of offline scheduling the task to be scheduled and the associated task comprises: sending the task to be scheduled and the associated task to a terminal logged in by a pre-set management account; receiving a scheduling confirmation instruction returned by the terminal; offline scheduling the task to be scheduled and the associated task according to the scheduling confirmation instruction.

5. The task scheduling method of claim 1, wherein, The method further comprises: obtaining access object information; searching for an associated task of the access object information in the task graph by taking the access object information as a search condition; offline scheduling the associated task.

6. A task scheduling apparatus characterized by comprising: The task scheduling device is used to implement the task scheduling method according to any one of claims 1 to 5, and comprises: an information obtaining module configured to obtain task value evaluation information of a task to be scheduled; a value evaluation module configured to input the task value evaluation information into a task value evaluation model to obtain a task value evaluation result; a value evaluation module configured to input the task value evaluation information into a task value evaluation model to obtain a task value evaluation result; The association search module is configured to search for an associated task of the to-be-scheduled task according to a pre-established task graph when it is determined according to the task value evaluation result that the to-be-scheduled task is an offline task. The offline scheduling module is configured to perform offline scheduling on the to-be-scheduled task and the associated task. 7.A computer device, comprising a memory and a processor, wherein the memory stores computer readable instructions, and the processor executes the computer readable instructions to implement the steps of the task scheduling method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer readable instructions, and the computer readable instructions are executed by the processor to implement the steps of the task scheduling method according to any one of claims 1 to 5.

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