CN115185666A

CN115185666A - Task scheduling method and device, computer equipment and storage medium

Info

Publication number: CN115185666A
Application number: CN202210927820.XA
Authority: CN
Inventors: 雷望春
Original assignee: Ping An Property and Casualty Insurance Company of China Ltd
Current assignee: Ping An Property and Casualty Insurance Company of China Ltd
Priority date: 2022-08-03
Filing date: 2022-08-03
Publication date: 2022-10-14

Abstract

The embodiment of the application belongs to the field of artificial intelligence and relates to a task scheduling method, a task scheduling device, computer equipment and a storage medium, wherein the method comprises the following steps: acquiring 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; searching a related task of the task to be scheduled according to a pre-established task map when the task to be scheduled is determined to be an off-line task according to the task value evaluation result; and performing offline scheduling on the tasks to be scheduled and the associated tasks. In addition, the application also relates to a block chain technology, and the task value evaluation information can be stored in the block chain. The method and the device improve the accuracy of task scheduling.

Description

Task scheduling method and device, computer equipment and storage medium

Technical Field

The present application relates to the field of artificial intelligence technologies, and in particular, to a task scheduling method and apparatus, a computer device, and a storage medium.

Background

With the development of computer technology, the production and operation activities of various organizations increasingly adopt an online management form, and various online tasks are distributed. However, the life cycle of each task is very different, some projects may run for a long time, and some projects may be gradually wasted due to business iteration, personnel change, access amount reduction and the like. These obsolete tasks continue to occupy platform resources, which can result in a significant amount of wasted resources if not discovered and cleaned in time.

However, scheduling of these tasks is typically based on manual implementation, i.e., relying on manual experience to determine which tasks are less valuable, can be downlinked, and manually search for other tasks associated with the downlinked tasks to downline together. As the number of tasks increases, the accuracy of manually scheduling the tasks decreases.

Disclosure of Invention

The embodiment of the application aims to provide a task scheduling method, a task scheduling device, a computer device and a storage medium, so as to improve the accuracy of task scheduling.

In order to solve the foregoing technical problem, an embodiment of the present application provides a task scheduling method, which adopts the following technical solutions:

acquiring 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;

searching a related task of the task to be scheduled according to a pre-established task map when the task to be scheduled is determined to be an off-line task according to the task value evaluation result;

and performing offline scheduling on the task to be scheduled and the associated task.

In order to solve the foregoing technical problem, an embodiment of the present application further provides a task scheduling apparatus, which adopts the following technical solutions:

the information acquisition module is used for acquiring task value evaluation information of the task to be scheduled;

the value evaluation module is used for inputting the task value evaluation information into a task value evaluation model to obtain a task value evaluation result;

the correlation searching module is used for searching the correlation task of the task to be scheduled according to a pre-established task map when the task to be scheduled is determined to be an off-line task according to the task value evaluation result;

and the offline scheduling module is used for performing offline scheduling on the tasks to be scheduled and the associated tasks.

In order to solve the above technical problem, an embodiment of the present application further provides a computer device, which adopts the following technical solutions:

acquiring task value evaluation information of a task to be scheduled;

In order to solve the above technical problem, an embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solutions:

acquiring task value evaluation information of a task to be scheduled;

Compared with the prior art, the embodiment of the application mainly has the following beneficial effects: acquiring task value evaluation information of a task to be scheduled, wherein the task value evaluation information comprises multi-dimensional information related to task value; automatically evaluating the task value of the task to be scheduled by the task value evaluation model according to the task value evaluation information to obtain a task value evaluation result; and when the task value is smaller, the task to be scheduled is determined as an offline task, and the downstream associated task influenced by the task to be scheduled is accurately searched through the task map, so that the offline operation is performed on the task to be scheduled and the associated task, the automatic evaluation of the task value and the automatic determination and search of the task needing to be offline are realized, the wrong judgment and omission are avoided, and the task scheduling efficiency and accuracy are improved.

Drawings

In order to more clearly illustrate the solution of the present application, the drawings needed for describing the embodiments of the present application will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and that other drawings can be obtained by those skilled in the art without inventive effort.

FIG. 1 is an exemplary system architecture diagram to which the present application may be applied;

FIG. 2 is a flow diagram for one embodiment of a task scheduling method according to the present application;

FIG. 3 is a schematic block diagram illustrating an embodiment of a task scheduler according to the application;

FIG. 4 is a schematic block diagram of one embodiment of a computer device according to the present application.

Detailed Description

Unless defined otherwise, 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 belongs; the terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "including" and "having," and any variations thereof in the description and claims of this application and the description of the figures above, are intended to cover non-exclusive inclusions. The terms "first," "second," and the like in the description and claims of this application or in the above-described drawings are used for distinguishing between different objects and not for describing a particular order.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein may be combined with other embodiments.

In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

As shown in fig. 1, the system architecture 100 may include

terminal devices

101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the

terminal devices

101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.

The user may use the

terminal devices

101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. Various communication client applications, such as a web browser application, a shopping application, a search application, an instant messaging tool, a mailbox client, social platform software, etc., may be installed on the

terminal devices

101, 102, 103.

The

terminal devices

101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to a smart phone, a tablet computer, an e-book reader, an MP3 player (Moving Picture experts Group Audio Layer III, motion Picture experts compression standard Audio Layer 3), an MP4 player (Moving Picture experts Group Audio Layer IV, motion Picture experts compression standard Audio Layer 4), a laptop portable computer, a desktop computer, and the like.

The server 105 may be a server providing various services, such as a background server providing support for pages displayed on the

terminal devices

101, 102, 103.

It should be noted that, the task scheduling method provided in the embodiments of the present application is generally executed by a server, and accordingly, the task scheduling device is generally disposed in the server.

It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

With continuing reference to FIG. 2, a flowchart of one embodiment of a task scheduling method according to the present application is shown. The task scheduling method comprises the following steps:

step S201, task value evaluation information of the task to be scheduled is obtained.

In this embodiment, the electronic device (for example, the server shown in fig. 1) on which the task scheduling method operates may communicate with the terminal through a wired connection manner or a wireless connection manner. It should be noted that the wireless connection means may include, but is not limited to, a 3G/4G/5G connection, a WiFi connection, a bluetooth connection, a WiMAX connection, a Zigbee connection, an UWB (ultra wideband) connection, and other wireless connection means now known or developed in the future.

Specifically, a plurality of tasks can be run online, and when the plurality of running tasks need to be scheduled offline, each task can be processed one by one to obtain a task to be scheduled.

The task to be scheduled has task value evaluation information, and the task value evaluation information can be multidimensional information and is used for measuring and evaluating the task value of the task to be scheduled.

Step S202, inputting the task value evaluation information into the task value evaluation model to obtain a task value evaluation result.

Specifically, the task value evaluation information is input into a trained task value evaluation model, the task value evaluation model processes multidimensional information in the task value evaluation information, and a task value evaluation result is output. The task value evaluation result can be a numerical value, and the numerical value is used for measuring the task value; or a classification result, and the task value is measured by the task category to which the task to be scheduled belongs.

The task value evaluation model can be built based on a neural network, the task value evaluation information is input into the task value evaluation model, the task value is predicted and evaluated through the neural network, and a task value evaluation result is output. In one embodiment, the task value evaluation model can be a tree model such as a random forest, an XGBOOST, a GBDT, a LightGBM and the like, and multidimensional information in the task value evaluation model is input into the tree model to obtain a task value evaluation result.

And step S203, searching the associated task of the task to be scheduled according to the pre-established task map when the task to be scheduled is determined to be the off-line task according to the task value evaluation result.

Specifically, the task value evaluation result is used for displaying the task value of the task to be scheduled, and if the task value of the task to be scheduled is judged to be low through the task value evaluation result, the task to be scheduled can be marked as an offline task. The offline scheduling can be performed on the offline tasks, so that the waste of system resources is avoided.

A plurality of tasks can be run on the system, and a dependency relationship exists between the tasks, for example, a task a generates a data table B, a task C needs to read data in the data table B during running, and then the task C depends on the data table B, and the task C depends on the task a, the task a is an upstream task of the task C, and the task C is a downstream task of the task a.

The dependency and incidence relation between tasks can be stored and inquired through the task map. The knowledge graph is constructed according to each task on the system, and can record the dependence and incidence relation among the tasks and record other attributes of the tasks.

The task graph can be a Neo4j knowledge graph, neo4j is a high-performance NOSQL graph database which stores structured data on a network (called a graph from a mathematical perspective) instead of tables, and Neo4j can also be regarded as a high-performance graph engine.

When the task to be scheduled is an off-line task, the task to be scheduled can be used as a searching condition, searching is carried out through a task map, and a task related to the task to be scheduled is searched; the related task can be a downstream task of the task to be scheduled, which is found through the task map; in one embodiment, after finding the downstream task of the task to be scheduled through the task map, the downstream task can be used as a new starting point to continuously find a new downstream task; and continuously searching according to the mode until a new downstream task cannot be found, and marking all the found tasks as related tasks influenced by the task to be scheduled.

And step S204, performing offline scheduling on the task to be scheduled and the associated task.

Specifically, the task value of the task to be scheduled is low, and offline operation can be performed. When offline operation is carried out, besides the tasks to be scheduled, downstream related tasks influenced by the tasks to be scheduled can be all subjected to offline scheduling.

In the embodiment, task value evaluation information of a task to be scheduled is obtained, wherein the task value evaluation information comprises multi-dimensional information related to task value; automatically evaluating the task value of the task to be scheduled by the task value evaluation model according to the task value evaluation information to obtain a task value evaluation result; and the task value evaluation result is used for displaying the task value of the task to be scheduled, when the task value is smaller, the task to be scheduled is determined as an offline task, and a downstream associated task influenced by the task to be scheduled is accurately searched through a task map, so that the task to be scheduled and the associated task are offline, the automatic evaluation of the task value and the automatic determination and searching of the offline task are realized, the misjudgment and omission are avoided, and the task scheduling efficiency and accuracy are improved.

Further, the step S201 may include: acquiring access object information, access time information and resource consumption information of a task to be scheduled; and determining the access object information, the access time information and the resource consumption information as task value evaluation information of the task to be scheduled.

Specifically, access object information, access time information, and resource consumption information of the task to be scheduled are obtained. The task has an access object, the access object is a user of the task, for example, for an approval task, the access object can be an approver, and generally, the more the access objects, the higher the level of the access objects, and the higher the task value; the access object information records information such as an access object, a level of the access object, and the number of access objects of the task.

Each time the access object accesses the task, the access time is left; generally, the more times a task is accessed, the higher the value of the task; meanwhile, the number of times that the task is accessed is combined with the access time, for example, the number of times that the task is accessed is large when the task is just online, but the number of times that the task is accessed becomes very small after a period of time, and at this time, the task value is not necessarily high. The access time information may be an access time at which the task is accessed, or an access time of the task within a preset time period, or a time at which the task is last accessed.

When running, a task occupies certain hardware resources, such as the running time of a central processing unit CPU, the storage space consumed by the task, and the like, which are consumption resource information of the task.

The access object information, the access time information, and the resource consumption information may be determined as task value evaluation information of the task to be scheduled.

In the embodiment, the access object information, the access time information and the resource consumption information of the task to be scheduled are determined as the task value evaluation information, so that the task value can be comprehensively measured.

Further, before step S203, the method may further include: acquiring task dependency relationship information and task value evaluation information of each task; determining a node object, relationship information and attribute information based on the task dependency relationship information and the task value evaluation information; and establishing a task map according to the node object, the relationship information and the attribute information.

Specifically, a task map needs to be established in advance before searching, task dependency relationships of tasks and task value evaluation information need to be acquired when the task map is established, and the task dependency relationships record dependency relationships among the tasks.

The task graph in this application may be a Neo4j knowledge graph. A graph is a common data structure used to represent objects and relationships between them. The object is also called node or vertex, and the relationship is described by edge. Mathematically, a graph is generally represented by G = (V, E, A, X), where V = { V1, V2 \8230;, vn } is a set of nodes, E = E _ ij represents a set of edges, A is an adjacency matrix of size | V | × | V |, used to represent the connection relationship between nodes, if E _ ij ∈ E, A _ ij =1, X is a feature matrix of size | V | × d, and the ith row X _ i of X represents the attribute feature of the ith node, where d is the dimension of the attribute.

The task dependency relationship information and the task value evaluation information may be parsed based on artificial intelligence to determine node objects, relationship information, and attribute information. The node objects can be tasks, access objects and the like, the tasks have dependency relationships with each other, the dependency relationships form relationship information, and the access objects can also have relationship information with the tasks. The access object and the task have attribute information in the form of key/value, for example, the access object has access time and the task has resource consumption information.

After the node object, the relationship information and the attribute information are determined, the task graph can be established according to a knowledge graph construction algorithm.

In the embodiment, the node object, the relationship information and the attribute information required by the construction map are determined according to the task dependency relationship information and the task value evaluation information of each task, and the task map is established, so that accurate searching of the associated task can be realized through the task map.

Further, before the step of obtaining the task dependency relationship information and the task value evaluation information of each task, the method may further include: acquiring a task script of each task; analyzing each task script to identify an access statement in each task script; and determining the dependency relationship between the tasks according to the access statement to generate task dependency relationship information.

Specifically, a task script of each task is obtained, and the task script is analyzed to identify an access statement in the task script. The access statement may be an SQL statement and may indicate where the data table/task acquires data from the data table/task, so that a dependency relationship between the data table and the data table may be obtained, the data table belongs to the task, and a dependency relationship between the data table and the task and a dependency relationship between the task and the task may be obtained, so that task dependency relationship information may be obtained.

In one embodiment, the task dependency relationship information may be manually filled in, or a task script of each task may be obtained. The task script can record the upstream task on which the task depends, so that the task dependency relationship information is generated according to each task script.

In the embodiment, the task script of each task is obtained, the access statement in the task script is identified, and the dependency relationship between the tasks can be judged according to the access relationship, so that the task dependency relationship information can be accurately generated.

Further, the step S203 may include: when determining that the task to be scheduled is an off-line task according to the task value evaluation result, acquiring a preset search strategy; and taking the task to be scheduled as a search condition, and searching the associated task of the task to be scheduled in a pre-established task map based on a search strategy.

Specifically, when the task to be scheduled is determined to be an offline task according to the task value evaluation result, a preset search strategy is obtained. The search strategy is used for indicating how to search the task map for the associated task of the task to be scheduled. The search strategy can be configured in advance or can be configured immediately before the search is started, and the configuration comprises that whether the depth-first search is carried out or the breadth-first search is carried out; meanwhile, the number of association levels can be configured, for example, the task A is a downlinlable task, the downstream task of the task A is a task B, the downstream task of the task B is a task C and a task D, the number of association levels is configured, the depth of searching downstream can be controlled, if the number of association levels is 1, only 1 layer is searched downstream, and the searching can be stopped when the task B is found; and if the correlation series is 2, searching the 2 layers downstream to find the task B, the task C and the task D.

And then, taking the task to be scheduled as a starting condition for searching, and searching in the task map based on a searching strategy to obtain a related task influenced by the task to be scheduled.

In this embodiment, a preset search policy is obtained, and the search policy is used to control a search operation, so that personalized search of the associated task can be implemented.

Further, the step S204 may include: sending the task to be scheduled and the associated task to a terminal logged in by a preset management account; receiving a scheduling confirmation instruction returned by the terminal; and performing offline scheduling on the task to be scheduled and the associated task according to the scheduling confirmation instruction.

Specifically, after the task to be scheduled and the associated task are obtained, a task identifier of the task to be scheduled and the associated task may be sent to a terminal logged in by a preset management account. The management account can be an account of a worker responsible for task scheduling, and the worker can view, modify or reject the task to be scheduled or the associated task through the terminal.

When the staff agrees to perform offline scheduling on the tasks to be scheduled and the associated tasks, a scheduling confirmation instruction can be triggered through the terminal. And after receiving the scheduling confirmation instruction, the server performs offline scheduling on the scheduling task and the associated task.

In the embodiment, the tasks to be scheduled and the associated tasks are sent to the terminal logged by the management account so as to be checked manually, and after the manual checking is passed, the offline scheduling is performed according to the scheduling confirmation instruction, so that the accuracy of the offline scheduling is ensured.

Further, the task scheduling method may further include: acquiring access object information; searching the associated task of the access object information in the task map by taking the access object information as a search condition; and performing offline scheduling on the associated tasks.

Specifically, access object information of the task may also be obtained, specifically, the access object in the access object information may be obtained, a task graph is used to query an associated task of the access object, and the queried associated task is subjected to offline scheduling. For example, the employee name or the employee number of the employee forms an access object in the system, when the employee leaves, the task in charge of the employee can be offline, and at this time, the access object information representing the employee can be used as a query condition to query the associated task in the task map and perform offline operation.

In the embodiment, the access object information can be used as a search condition, the associated task is searched in the task map, and offline scheduling is performed, so that offline scheduling modes are enriched.

It is emphasized that, in order to further ensure the privacy and security of the task value evaluation information, the task value evaluation information may also be stored in a node of a block chain.

The block chain referred by the application 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 string of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, which is used for verifying the validity (anti-counterfeiting) of the information and generating a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.

The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.

The artificial intelligence base technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware that is configured to be instructed by computer-readable instructions, which can be stored in a computer-readable storage medium, and when executed, the programs may include the processes of the embodiments of the methods described above. The storage medium may be a non-volatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a Random Access Memory (RAM).

It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless otherwise indicated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

With further reference to fig. 3, as an implementation of the method shown in fig. 2, the present application provides an embodiment of a task scheduling apparatus, where the embodiment of the apparatus corresponds to the embodiment of the method shown in fig. 2, and the apparatus may be specifically applied to various electronic devices.

As shown in fig. 3, the task scheduling device 300 according to this embodiment includes: an information acquisition module 301, a value evaluation module 302, an association search module 303, and a offline scheduling module 304, wherein:

the information obtaining module 301 is configured to obtain task value evaluation information of a task to be scheduled.

And the value evaluation module 302 is used for inputting the task value evaluation information into the task value evaluation model to obtain a task value evaluation result.

And the association searching module 303 is configured to search an association task of the task to be scheduled according to a task map established in advance when the task to be scheduled is determined to be an off-line task according to the task value evaluation result.

And the offline scheduling module 304 is configured to perform offline scheduling on the task to be scheduled and the associated task.

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

and the information acquisition submodule is used for acquiring the access object information, the access time information and the resource consumption information of the task to be scheduled.

And the information determining submodule is used for 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.

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

and the acquisition module is used for acquiring the task dependency relationship information and the task value evaluation information of each task.

And the determining module is used for determining the node object, the relationship information and the attribute information based on the task dependency relationship information and the task value evaluation information.

And the establishing module is used for establishing a task map according to the node object, the relationship information and the attribute information.

In some optional implementations of this embodiment, the task scheduling device 300 may further include: the system comprises a script acquisition module, a statement identification module and a dependence generation module, wherein:

and the script acquisition module is used for acquiring the task scripts of each task.

And the statement identification module is used for analyzing each task script so as to identify the access statement in each task script.

And the dependency generation module is used for determining the dependency relationship among the tasks according to the access statement so as to generate task dependency relationship information.

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

and the strategy acquisition submodule is used for acquiring a preset search strategy when the task to be scheduled is determined to be an off-line task according to the task value evaluation result.

And the association searching submodule is used for searching the association tasks of the tasks to be scheduled in a pre-established task map based on a searching strategy by taking the tasks to be scheduled as searching conditions.

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

and the task sending submodule is used for sending the tasks to be scheduled and the associated tasks to a terminal logged by a preset management account.

And the instruction receiving submodule is used for receiving the scheduling confirmation instruction returned by the terminal.

And the offline scheduling submodule is used for performing offline scheduling on the task to be scheduled and the associated task according to the scheduling confirmation instruction.

In the embodiment, the tasks to be scheduled and the associated tasks are sent to the terminal logged by the management account so as to be manually checked, and after the manual checking is passed, the offline scheduling is performed according to the scheduling confirmation instruction, so that the accuracy of the offline scheduling is ensured.

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

and the object acquisition module is used for acquiring the access object information.

And the task searching module is used for searching the associated tasks of the access object information in the task map by taking the access object information as a searching condition.

And the task offline module is used for performing offline scheduling on the associated tasks.

In the embodiment, the access object information can be used as a search condition, the associated tasks are searched in the task map, and offline scheduling is performed, so that offline scheduling modes are enriched.

In order to solve the technical problem, an embodiment of the present application further provides a computer device. Referring to fig. 4 in particular, fig. 4 is a block diagram of a basic structure of a computer device according to the embodiment.

The computer device 4 comprises a memory 41, a processor 42, a network interface 43 communicatively connected to each other via a system bus. It is noted that only computer device 4 having components 41-43 is shown, but it is understood that not all of the shown components are required to be implemented, and that more or fewer components may be implemented instead. As will be understood by those skilled in the art, the computer device is a device capable of automatically performing numerical calculation and/or information processing according to instructions set or stored in advance, and the hardware thereof includes but is not limited to a microprocessor, an Application Specific Integrated Circuit (ASIC), a Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), an embedded device, and the like.

The computer device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The computer equipment can carry out man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch panel or voice control equipment and the like.

The memory 41 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 41 may be an internal storage unit of the computer device 4, such as a hard disk or a 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, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the computer device 4. Of course, the memory 41 may also include both internal and external storage devices of the computer device 4. In this embodiment, the memory 41 is generally used for storing an operating system and various application software installed on the computer device 4, such as computer readable instructions of a task scheduling method. Further, the memory 41 may also be used to temporarily store various types of data that have been output or are to be output.

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

The network interface 43 may comprise a wireless network interface or a wired network interface, and the network interface 43 is generally used for establishing communication connection between the computer device 4 and other electronic devices.

The computer device provided in this embodiment may execute the task scheduling method. Here, the task scheduling method may be the task scheduling method of the above embodiments.

The present application further provides another embodiment, which is to provide a computer-readable storage medium storing computer-readable instructions executable by at least one processor to cause the at least one processor to perform the steps of the task scheduling method as described above.

In the embodiment, task value evaluation information of a task to be scheduled is obtained, wherein the task value evaluation information comprises multi-dimensional information related to task value; automatically evaluating the task value of the task to be scheduled by the task value evaluation model according to the task value evaluation information to obtain a task value evaluation result; and when the task value is smaller, the task to be scheduled is determined as an offline task, and the downstream associated task influenced by the task to be scheduled is accurately searched through the task map, so that the offline operation is performed on the task to be scheduled and the associated task, the automatic evaluation of the task value and the automatic determination and search of the task needing to be offline are realized, the wrong judgment and omission are avoided, and the task scheduling efficiency and accuracy are improved.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present application.

It is to be understood that the above-described embodiments are merely illustrative of some, but not restrictive, of the broad invention, and that the appended drawings illustrate preferred embodiments of the invention and do not limit the scope of the invention. This application is capable of embodiments in many different forms and the embodiments are provided so that this disclosure will be thorough and complete. Although the present application has been described in detail with reference to the foregoing embodiments, it will be apparent to one skilled in the art that the present application may be practiced without modification or with equivalents of some of the features described in the foregoing embodiments. All equivalent structures made by using the contents of the specification and the drawings of the present application are directly or indirectly applied to other related technical fields and are within the protection scope of the present application.

Claims

1. A task scheduling method, comprising the steps of:

acquiring task value evaluation information of a task to be scheduled;

2. The task scheduling method according to claim 1, wherein the step of obtaining task value evaluation information of the task to be scheduled comprises:

acquiring access object information, access time information and resource consumption information of a task to be scheduled;

and determining the access object information, the access time information and the resource consumption information as task value evaluation information of the task to be scheduled.

3. The task scheduling method according to claim 1, wherein before the step of searching for the associated task of the task to be scheduled according to the pre-established task map, the method further comprises:

acquiring task dependency relationship information and task value evaluation information of each task;

determining a node object, relationship information and attribute information based on the task dependency relationship information and the task value evaluation information;

and establishing a task graph according to the node object, the relationship information and the attribute information.

4. The task scheduling method according to claim 3, further comprising, before the step of obtaining the task dependency relationship information and the task value evaluation information of each task:

acquiring a task script of each task;

analyzing each task script to identify an access statement in each task script;

and determining the dependency relationship between the tasks according to the access statement to generate task dependency relationship information.

5. The task scheduling method according to claim 1, wherein the step of searching for the task associated with the task to be scheduled according to a pre-established task map when the task to be scheduled is determined to be an offline task according to the task value evaluation result comprises:

when the task to be scheduled is determined to be an off-line task according to the task value evaluation result, acquiring a preset search strategy;

and searching the related tasks of the tasks to be scheduled in a pre-established task map based on the search strategy by taking the tasks to be scheduled as search conditions.

6. The task scheduling method according to claim 1, wherein the step of performing offline scheduling on 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 preset management account;

receiving a scheduling confirmation instruction returned by the terminal;

and performing offline scheduling on the task to be scheduled and the associated task according to the scheduling confirmation instruction.

7. The method of task scheduling according to claim 1, wherein the method further comprises:

acquiring access object information;

searching the associated task of the access object information in the task map by taking the access object information as a search condition;

and performing offline scheduling on the associated tasks.

8. A task scheduling apparatus, comprising:

9. A computer device comprising a memory having computer readable instructions stored therein and a processor which when executed implements the steps of a task scheduling method as claimed in any one of claims 1 to 7.

10. A computer readable storage medium having computer readable instructions stored thereon which, when executed by a processor, implement the steps of a task scheduling method as claimed in any one of claims 1 to 7.