CN114968504A

CN114968504A - Distributed task scheduling method and device and storage medium

Info

Publication number: CN114968504A
Application number: CN202110217068.5A
Authority: CN
Inventors: 肖甜
Original assignee: China United Network Communications Group Co Ltd
Current assignee: China United Network Communications Group Co Ltd
Priority date: 2021-02-26
Filing date: 2021-02-26
Publication date: 2022-08-30

Abstract

The embodiment of the disclosure provides a distributed task scheduling method, a distributed task scheduling device and a storage medium, relates to the technical field of data processing, and aims to solve the problem that a task scheduling system of a distributed architecture in the prior art is low in applicability. The method specifically comprises the following steps: acquiring tasks to be executed and task information of the service system according to the configured parameter dependent data packet, wherein the dependent data packet is used for capturing the tasks to be executed and the task information of the service system; determining that the task is completed; configuring task information for the registered task; after the task is configured with the task information, searching a service system corresponding to the task, and determining a task node for executing the task; and sending an execution request to the task node, wherein the execution request is used for requesting the task node to execute the task.

Description

Distributed task scheduling method and device and storage medium

Technical Field

The present disclosure relates to the field of data processing technologies, and in particular, to a distributed task scheduling method, an apparatus, and a storage medium.

Background

And batch processing services in batches through a task scheduling system. Most of the existing task scheduling systems are distributed architectures. Such as: crontab, Timer, etc., but these task scheduling systems with distributed architecture have various disadvantages, such as: high coupling degree with a service system, no support of cross-platform and the like.

Disclosure of Invention

The disclosure provides a distributed task scheduling method, a distributed task scheduling device and a storage medium, which are used for solving the problem of low adaptability of a task scheduling system of an existing distributed architecture.

In order to achieve the purpose, the technical scheme adopted by the disclosure is as follows:

in a first aspect, the present disclosure provides a distributed task scheduling method, including the following steps: the distributed task scheduling device acquires tasks to be executed and task information of the service system according to the configured dependent data packet of the parameters, and the dependent data packet is used for capturing the tasks to be executed and the task information of the service system; after the task is determined to be registered, task information is configured for the registered task; after the task is configured with the task information, the distributed task scheduling device searches a service system corresponding to the task and determines a task node for executing the task; and after the task node is determined, sending an execution request to the task node, wherein the execution request is used for requesting the task node to execute the task.

In a second aspect, the present disclosure provides a distributed task scheduling device, the system including: the task processing module is configured to acquire tasks to be executed and task information of the service system according to a dependent data packet of configured parameters, and the dependent data packet is used for capturing the tasks to be executed and the task information of the service system; a task registration module configured to determine that a task has completed registration; the task arranging module is configured to configure task information for the registered tasks; the task scheduling module is configured to search a service system corresponding to the task and determine a task node for executing the task after the task configures the task information; and the task execution module is configured to send an execution request to the task node, and the execution request is used for requesting the task node to execute the task.

In a third aspect, a distributed task scheduling apparatus is provided, including: a processor; a memory for storing the processor-executable instructions; wherein the processor is configured to execute instructions to implement the distributed task scheduling method as provided in the first aspect above.

In a fourth aspect, the present disclosure provides a computer-readable storage medium comprising instructions. The computer instructions, when executed on the server, cause the server to perform the distributed task scheduling method as provided above in the first aspect.

In a fifth aspect, the present disclosure provides a computer program product, which, when run on a server, causes the server to perform the distributed task scheduling method as provided in the first aspect.

It should be noted that all or part of the above computer instructions may be stored on the first computer readable storage medium. The first computer readable storage medium may be packaged with the processor of the access network device, or may be packaged separately from the processor of the access network device, which is not limited in this disclosure.

Reference may be made to the detailed description of the first aspect for the description of the second to fifth aspects of the disclosure; in addition, for the beneficial effects described in the second aspect to the fifth aspect, reference may be made to the beneficial effect analysis of the first aspect, and details are not described here again.

In the present disclosure, the above names do not limit the devices or functional modules themselves, and in actual implementation, the devices or functional modules may appear by other names. Insofar as the functions of the respective devices or functional modules are similar to those of the present disclosure, they are within the scope of the claims of the present disclosure and their equivalents.

The technical scheme provided by the embodiment of the disclosure at least brings the following beneficial effects:

according to the distributed task scheduling method provided by the disclosure, tasks and task information to be executed in a service system are captured according to a data packet, the tasks are registered, the task information is configured for the tasks after the registration, and the execution period and the execution logic of the tasks are determined according to the task information. After the execution period and the execution logic are determined, the search service system determines a task node for executing the task, sends an execution instruction to the task node, and the task node executes the task according to the execution instruction. The distributed task scheduling device disclosed by the disclosure integrally stages the whole task processing process, including task grabbing, task registration, task configuration execution rules and task node determination. The distributed task scheduling device realizes task processing by interacting with the service system, the invasiveness of the whole process to the service system is extremely low, and the access cost of the service system is low; when the distributed task scheduling device acquires data of a plurality of service systems, the execution periods of all tasks are reasonably configured according to the task information, so that the tasks are ensured not to be called again in the execution process. Meanwhile, the method is simple and easy to operate, low in learning cost and wide in applicability.

These and other aspects of the disclosure will be more readily apparent from the following description.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.

FIG. 1 is a schematic diagram of a scheduling system according to an embodiment of the present disclosure;

FIG. 2 is a flowchart illustrating a distributed task scheduling method according to an embodiment of the disclosure;

FIG. 3 is a second flowchart of a distributed task scheduling method according to an embodiment of the disclosure;

FIG. 4 is a schematic structural diagram of a distributed task scheduling apparatus according to an embodiment of the present disclosure;

FIG. 5 is a second schematic structural diagram of a distributed task scheduler according to an embodiment of the disclosure;

fig. 6 is a schematic structural diagram of a computer program product of a distributed task scheduling method provided in accordance with an embodiment of the present disclosure.

Detailed Description

The technical solutions in the embodiments of the present disclosure will be described clearly and completely with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the embodiments described are only some embodiments of the present disclosure, rather than all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.

It should be noted that in the embodiments of the present disclosure, words such as "exemplary" or "for example" are used to mean serving as examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "e.g.," in an embodiment of the present disclosure is not to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.

For the convenience of clearly describing the technical solutions of the embodiments of the present disclosure, in the embodiments of the present disclosure, the terms "first", "second", and the like are used for distinguishing the same or similar items with basically the same functions and actions, and those skilled in the art can understand that the terms "first", "second", and the like are not used for limiting the quantity or the execution sequence.

Firstly, introduction is made to an application scenario of the technical scheme provided by the present disclosure:

at present, batch processing is a common working mode of internet application and enterprise system application, and most batch processing work is realized through a task scheduling system. With the evolution of service architecture, most of the existing task scheduling systems are distributed architecture.

Task scheduling systems supporting distributed architecture are currently used by internet applications, such as: the crontab of the Linux system is used for task scheduling of the Linux system application program in a single machine scene; the Timer in the Java language is used for task scheduling of the Java application in a single machine scene; the method comprises the following steps of realizing a quartz open source framework based on Java language, and using the framework for task time scheduling of Java application; and the elastic-jobframework is used for task scheduling of the Java application in a distributed deployment scene. However, these task scheduling systems suffer from various disadvantages, such as: the method has the problems of no support for task arrangement, high coupling degree with a service system, no support for cross-platform and the like.

In order to solve the foregoing problem, an embodiment of the present disclosure provides a distributed task scheduling method. And automatically capturing a task to be executed according to the dependent data packet, registering the task, configuring task information after the registration is finished, calling a task node according to the task information, and executing the task through the task node. The method disclosed by the invention adopts automatic grabbing to acquire the tasks, has extremely low invasion to the service system, and is suitable for a plurality of service systems. Therefore, the problem of low applicability of the task scheduling system in the prior art is solved.

Fig. 1 shows a scheduling system comprising a distributed task scheduling device, several business systems, an application coordination service device and a database. The distributed task scheduling device is used for processing task scheduling, the service system is used for providing metadata of tasks, the application program coordination service device is used for providing task nodes for executing the tasks, and the database is used for storing data. The distributed task scheduling device, the plurality of business systems, the application program coordination service device and the database are communicated in a wired communication mode or a wireless communication mode.

The service system in the embodiment of the present disclosure may be a mobile phone, a tablet computer desktop, a laptop, a handheld computer, a notebook, an ultra-mobile personal computer (UMPC), a netbook, a cellular phone, a Personal Digital Assistant (PDA), an Augmented Reality (AR) device, a Virtual Reality (VR) device, and the like, which may be installed with an instant messaging application and communicate using the instant messaging application. The service system comprises tasks to be executed.

The distributed task scheduling device in the embodiment of the present disclosure may be one server, or may be a server cluster formed by multiple servers, or one cloud computing service center. The server may include a processor, memory, and network interface, among others.

The application coordination service device in the embodiment of the present disclosure may be one server, or a server cluster composed of multiple servers, or a cloud computing service center.

The database in the embodiment of the present disclosure may be one server, or a server cluster composed of a plurality of servers, or one cloud computing service center. The database can comprise a task database and a log database, wherein the task database is used for storing all tasks, and the log database is used for storing logs generated in the task execution process.

It should be noted that, the distributed task scheduling apparatus shown in fig. 1 is only one implementation manner provided by the embodiment of the present disclosure, and the present disclosure does not limit this. After the application scenario and the implementation environment of the embodiment of the present disclosure are introduced, the distributed task scheduling method provided by the embodiment of the present disclosure is described in detail.

The distributed task scheduling method provided by the embodiment of the disclosure is applicable to a distributed task scheduling device. FIG. 2 is a flowchart illustrating a method of distributed task scheduling, according to an example embodiment, which may include steps 201-204, as shown in FIG. 2:

step 201, the distributed task scheduling device obtains the task to be executed and the task information of the service system according to the configured parameter dependent data packet.

The data packet is used for capturing tasks to be executed and task information of the service system.

In this step, the dependent data packet is a software packet that can be integrated in the service system, and after the service system runs the dependent data packet, the dependent data packet calls an annotation function in the distributed task scheduling device, and the annotation function in the distributed task scheduling device captures tasks and task information in the service system. Specifically, the distributed task scheduling device captures a system identifier to which the task belongs, current machine information (IP, port, and the like) corresponding to the task, an interface method name of the task, and the like.

The task to be executed and the task information are captured by the method, so that the invasion to the service system is extremely low, and the access cost of the service system is very low. Wherein. The annotation function is realized through a Spring framework, and the framework can provide hypertext transfer protocol access to the outside.

Further, the task information includes an execution cycle and execution logic, the execution cycle is an execution time of the tasks to be executed, and the execution logic is an execution sequence of the tasks to be executed.

Illustratively, a task refers to a particular function provided by a business system, such as the business system providing an order system with functionality that aggregates daily sales runs. And packaging the function into an interface for calling. Summarizing the daily sales flow requires 3 steps, the first: summarizing the sales amount of the order, and a second step of: and summarizing the refund amount of the order, and calculating the running water in the third step. These three steps need to be performed sequentially.

The task information refers to an execution cycle and execution logic of task execution. For example, daily sales streams for task summaries. Setting 2 am points of each day as an execution cycle, setting the first step, the second step and the third step as execution logic; the task after the execution cycle and the execution logic are configured is an operation. Wherein, one job comprises at least one task, and the task is taken as a minimum unit.

Further, the configuration parameters include task parameters and development framework parameters.

Wherein, according to the actual grabbing requirement, parameters are configured for the dependent data packet. The task parameters in the configuration parameters comprise: project name, application port number, and application coordination service address, among others. The development framework in this disclosure is a Spring framework. The development frame parameters in the configuration parameters comprise a tangent plane function and a scanning path, the tangent plane function is started to realize serial mode control of task scheduling, and the scanning path comprises a path where the task method is located. Illustratively, the task parameters and development framework parameters are introduced into the dependency package through the POM file of the business system.

Step 202, the distributed task scheduling device determines that the task is registered.

In this step, the distributed task scheduling device registers the captured task and task information through a task registration module in the distributed task scheduling device.

Step 203, the distributed task scheduling device configures task information for the registered task.

In this step, in order to reasonably arrange the execution time of each task, the acquired task information is configured to the corresponding task through the task scheduling module in the distributed task scheduling device, so that the subsequent task cannot be repeatedly called in the execution process.

Further, as shown in fig. 3, after step 203, the method further includes:

step 2031, storing the task configured with the task information.

In this step, the task configured with the task information is stored in the task storage module of the distributed task scheduling device, so that subsequent data search and review are facilitated.

The stored content is not limited to the task of configuring the task information, and also includes a task table, a job table, a task-job table and a scheduling log table generated in the whole task processing process. Specifically, the task table includes a task identity identification number, a trigger type, a parent task identity identification number, and the like; the operation table comprises an operation identity identification number, a service application name, a service application internet interconnection protocol/port, an operation hypertext transfer protocol request path, an operation source and the like; the task-job table comprises a task identity identification number, a job identity identification number, a pre-job identity identification number, job participation, a routing rule, a failure recovery rule and the like; the scheduling log table comprises a log identity identification number, a task identity identification number, a job identity identification number, scheduling time, a scheduling state, scheduling information, execution time, an execution state, execution information and the like.

And step 204, after the task is configured with the task information, the distributed task scheduling device searches a service system corresponding to the task and determines a task node for executing the task.

In this step, after the task is configured with the task information, the task is executed according to the execution period specified in the task information, and the task node for executing the task needs to be determined from the service system corresponding to the task.

The specific determination method comprises the following steps: firstly, each business system is automatically connected to an interface of an application program coordination service device through an integrated dependent software package, and information such as system identification, machine information and the like of the business system is registered through the interface. The distributed task scheduling device can also be connected to the application program coordination service device through a task scheduling module in the distributed task scheduling device. When a task is determined to be executed, the task scheduling module can search a service system needing to execute the task in the application program coordination service device according to the system identification carried by the task and the current machine information (IP, port and the like) corresponding to the task, and then call a corresponding task node of the service system.

The distributed task scheduling device can automatically intercept execution information of task execution and perform single thread control, and ensures that the task cannot be scheduled again during operation and the whole process service system is not aware. The task calling module also applies the task preemption mode technology based on events and the self-adaptive task smooth migration and load balancing technology.

Step 205, the distributed task scheduling device sends an execution request to the task node, where the execution request is used to request the task node to execute the task.

In this step, after the task node is determined, the task execution module of the distributed task scheduling device sends an execution request to the task node, and the task node executes the task according to the execution logic in the execution period according to the execution request.

Further, the distributed task scheduling device further comprises a task monitoring module.

The information monitored by the task monitoring module comprises executed job monitoring information and completed job monitoring information.

Specifically, the executing job monitoring information includes scheduler information, scheduling information, and docking item statistics. The scheduler information comprises the load capacity and the early warning value of the scheduler; the scheduling information comprises job distribution condition, scheduling times triggered by the scheduler and other multi-dimensional scheduling statistics; the statistics of the docking project comprise statistics of a system using the project, the number of jobs and the number of tasks and the like.

The completed job monitoring information includes job status real-time monitoring information and real-time log association information. The real-time monitoring information of the operation state is a panel which takes a project group as a unit and shows the operation running state of the operation; the real-time log association information is real-time association of the log displayed by the painted state icon.

Further, the distributed task scheduling device further comprises an interaction module. The functions that the interactive module can implement include task data entry, task testing, and other operations. The task data entry comprises manual entry and automatic entry; other operations include data modification and data deletion.

According to the distributed task scheduling method provided by the disclosure, tasks and task information to be executed in a service system are captured according to a data packet, the tasks are registered, the task information is configured for the tasks after the registration, and the execution period and the execution logic of the tasks are determined according to the task information. After the execution period and the execution logic are determined, the searching service system determines a task node for executing the task, sends an execution instruction to the task node, and the task node executes the task according to the execution instruction. The distributed task scheduling device disclosed by the disclosure integrally stages the whole task processing process, including task grabbing, task registration, task configuration execution rules and task node determination. The distributed task scheduling device realizes task processing by interacting with the service system, the invasiveness of the whole process to the service system is extremely low, and the access cost of the service system is low; when the distributed task scheduling device acquires data of a plurality of service systems, the execution periods of all tasks are reasonably configured according to the task information, so that the tasks are ensured not to be called again in the execution process. Meanwhile, the method is simple and easy to operate, low in learning cost and wide in applicability.

The foregoing describes the scheme provided by the embodiments of the present disclosure, primarily from a methodological perspective. To implement the above functions, it includes hardware structures and/or software modules for performing the respective functions. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is performed in hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

Fig. 4 is a schematic diagram illustrating a structure of a distributed task scheduler, which may be used to execute the distributed task scheduling method illustrated in fig. 2 according to an exemplary embodiment. As one implementation, the system may include a task processing module 410, a task registration module 420, a task orchestration module 430, a task scheduling module 440, and a task execution module 450.

And the task processing module 410 is configured to obtain the task to be executed by the service system and the task information according to the dependent data packet of the configured parameter, where the dependent data packet is used to capture the task to be executed by the service system and the task information. For example, in conjunction with fig. 2, the task processing module 410 may be used to execute S201.

A task registration module 420 configured to determine that a task has completed registration. For example, in connection with fig. 2, the task registration module 420 may be used to perform S202.

A task orchestration module 430 further configured to configure task information for the registered tasks; for example, in conjunction with FIG. 2, the task orchestration module 430 may be used to perform S203.

The task scheduling module 440 is further configured to search a service system corresponding to the task and determine a task node for executing the task after the task configures the task information; for example, in conjunction with fig. 2, the task scheduling module 440 may be configured to perform S204.

The task execution module 450 is configured to send an execution request to the task node, where the execution request is used to request the task node to execute the task; for example, in conjunction with fig. 2, task execution module 450 may be used to execute S205.

Of course, the distributed task scheduling apparatus provided by the embodiments of the present disclosure includes, but is not limited to, the above modules, for example, the distributed task scheduling apparatus may further include a task storage module 460. The task storage module 460 may be configured to store the program code of the write distributed task scheduling apparatus, and may also be configured to store data generated by the write distributed task scheduling apparatus during operation, such as data in a write request.

Fig. 5 is a schematic structural diagram of a distributed task scheduling apparatus according to an embodiment of the present disclosure, and as shown in fig. 5, the distributed task scheduling apparatus may include: at least one processor 51, a memory 52, a communication interface 53 and a communication bus 54.

The following describes each component of the distributed task scheduling apparatus in detail with reference to fig. 5:

the processor 51 is a control center of the distributed task scheduling apparatus, and may be a single processor or a collective term for a plurality of processing elements. For example, the processor 51 is a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present disclosure, such as: one or more DSPs, or one or more Field Programmable Gate Arrays (FPGAs).

In particular implementations, processor 51 may include one or more CPUs, such as CPU0 and CPU1 shown in FIG. 5, as an example. Also, as an embodiment, the distributed task scheduler may include a plurality of processors, such as the processor 51 and the processor 55 shown in fig. 5. Each of these processors may be a Single-core processor (Single-CPU) or a Multi-core processor (Multi-CPU). A processor herein may refer to one or more devices, circuits, and/or processing cores for processing data (e.g., computer program instructions).

The Memory 52 may be a Read-Only Memory (ROM) or other type of static storage device that can store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that can store information and instructions, an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc Read-Only Memory (CD-ROM) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory 52 may be self-contained and coupled to the processor 51 via a communication bus 54. The memory 52 may also be integrated with the processor 51.

In particular implementations, memory 52 is used to store data in the present disclosure and to execute software programs of the present disclosure. The processor 51 may perform various functions of the air conditioner by running or executing software programs stored in the memory 52 and calling data stored in the memory 52.

The communication interface 53 is a device such as any transceiver, and is used for communicating with other devices or communication Networks, such as a Radio Access Network (RAN), a Wireless Local Area Network (WLAN), a user terminal, and a cloud. The communication interface 53 may include an acquisition unit implementing the acquisition function and a transmission unit implementing the transmission function.

The communication bus 54 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 5, but this is not intended to represent only one bus or type of bus.

As an example, in conjunction with fig. 5, the task processing module in the distributed task scheduling apparatus implements the same function as the processor 51 in fig. 5, and the task storage unit 450 implements the same function as the memory 52 in fig. 5.

Another embodiment of the present disclosure also provides a computer-readable storage medium, which stores instructions that, when executed on a computer, cause the computer to perform the method shown in the above method embodiment.

In some embodiments, the disclosed methods may be implemented as computer program instructions encoded on a computer-readable storage medium in a machine-readable format or encoded on other non-transitory media or articles of manufacture.

Fig. 6 schematically illustrates a conceptual partial view of a computer program product comprising a computer program for executing a computer process on a computing device provided by an embodiment of the present disclosure.

In one embodiment, the computer program product is provided using a signal bearing medium 610. The signal bearing medium 610 may include one or more program instructions that, when executed by one or more processors, may provide the functions or portions of the functions described above with respect to fig. 2. Thus, for example, referring to the embodiment shown in fig. 2, one or more features of S201-S205 may be undertaken by one or more instructions associated with the signal bearing medium 610. Further, the program instructions in FIG. 6 also describe example instructions.

In some examples, signal bearing medium 610 may include a computer readable medium 611, such as, but not limited to, a hard disk drive, a Compact Disc (CD), a Digital Video Disc (DVD), a digital tape, a memory, a read-only memory (ROM), a Random Access Memory (RAM), or the like.

In some implementations, the signal bearing medium 610 may include a computer recordable medium 612 such as, but not limited to, memory, read/write (R/W) CDs, R/W DVDs, and the like.

In some implementations, the signal bearing medium 610 may include a communication medium 613 such as, but not limited to, a digital and/or analog communication medium (e.g., a fiber optic cable, a waveguide, a wired communications link, a wireless communication link, etc.).

The signal bearing medium 610 may be conveyed by a wireless form of communication medium 613, such as a wireless communication medium that complies with the IEEE602.61 standard or other transmission protocols. The one or more program instructions may be, for example, computer-executable instructions or logic-implementing instructions.

In some examples, a data writing device, such as that described with respect to fig. 2, may be configured to provide various operations, functions, or actions in response to one or more program instructions via computer-readable medium 611, computer-recordable medium 612, and/or communication medium 613.

Through the above description of the embodiments, it is clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules to complete the above-described full-classification part or part of the functions.

In the several embodiments provided in the present disclosure, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, a module or a unit may be divided into only one logic function, and may be implemented in other ways, for example, a plurality of units or components may be combined or integrated into another apparatus, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

Units described as separate parts may or may not be physically separate, and parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed to a plurality of different places. The partial or full classification units can be selected according to actual needs to achieve the purpose of the scheme of the embodiment.

In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present disclosure may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, etc.) or a processor (processor) to execute the whole classification part or part of the steps of the methods according to the embodiments of the present disclosure. And the aforementioned storage medium includes: a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk or an optical disk, and various media capable of storing program codes.

The above is only a specific embodiment of the present disclosure, but the scope of the present disclosure is not limited thereto, and any changes or substitutions within the technical scope of the present disclosure should be covered within the scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.

Claims

1. A distributed task scheduling method, comprising:

acquiring tasks to be executed and task information of a service system according to a dependent data packet with configured parameters, wherein the dependent data packet is used for capturing the tasks to be executed and the task information of the service system;

determining that the task has completed registration;

configuring the task information for the registered task;

after the task is configured with the task information, searching a business system corresponding to the task, and determining a task node for executing the task;

and sending an execution request to the task node, wherein the execution request is used for requesting the task node to execute the task.

2. The method according to claim 1, wherein after configuring the task information for the registered task, further comprising:

and storing the tasks configuring the task information.

3. The method according to claim 2, wherein the task information includes an execution cycle and execution logic, the execution cycle is an execution time of the tasks to be executed, and the execution logic is an execution sequence of the tasks to be executed.

4. The method of any of claims 1-3, wherein the configuration parameters include task parameters and development framework parameters.

5. A distributed task scheduler, comprising:

the task processing module is configured to acquire tasks to be executed and task information of the service system according to a dependent data packet of configured parameters, wherein the dependent data packet is used for capturing the tasks to be executed and the task information of the service system;

a task registration module configured to determine that the task has completed registration;

a task orchestration module configured to configure the task information for the registered tasks;

the task scheduling module is configured to search a service system corresponding to the task and determine a task node for executing the task after the task configures the task information;

and the task execution module is configured to send an execution request to the task node, wherein the execution request is used for requesting the task node to execute the task.

6. The apparatus of claim 5, further comprising a task storage module;

the task storage module is configured to store the task configuring the task information.

7. The apparatus of claim 6,

the task information comprises an execution cycle and execution logic, wherein the execution cycle is the execution time of the tasks to be executed, and the execution logic is the execution sequence of the tasks to be executed.

8. The apparatus of any of claims 5-7, wherein the configuration parameters comprise task parameters and development framework parameters.

9. A distributed task scheduler, comprising:

a processor;

a memory for storing the processor-executable instructions;

wherein the processor is configured to execute the instructions to implement the distributed task scheduling method of any of claims 1 to 4.

10. A computer-readable storage medium comprising computer instructions which, when run on a distributed task scheduler, cause the distributed task scheduler to perform the distributed task scheduling method of any of claims 1-4.