CN114168304A - MQ-based cloud task scheduling and executing method and system - Google Patents
MQ-based cloud task scheduling and executing method and system Download PDFInfo
- Publication number
- CN114168304A CN114168304A CN202210001176.3A CN202210001176A CN114168304A CN 114168304 A CN114168304 A CN 114168304A CN 202210001176 A CN202210001176 A CN 202210001176A CN 114168304 A CN114168304 A CN 114168304A
- Authority
- CN
- China
- Prior art keywords
- task
- message
- module
- message queue
- task scheduling
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000004519 manufacturing process Methods 0.000 claims abstract description 56
- 230000008878 coupling Effects 0.000 claims abstract description 14
- 238000010168 coupling process Methods 0.000 claims abstract description 14
- 238000005859 coupling reaction Methods 0.000 claims abstract description 14
- 238000012546 transfer Methods 0.000 claims description 18
- 238000012545 processing Methods 0.000 claims description 9
- 238000003780 insertion Methods 0.000 claims description 3
- 230000037431 insertion Effects 0.000 claims description 3
- 238000010276 construction Methods 0.000 claims description 2
- 238000000354 decomposition reaction Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/48—Program initiating; Program switching, e.g. by interrupt
- G06F9/4806—Task transfer initiation or dispatching
- G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
- G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/54—Interprogram communication
- G06F9/546—Message passing systems or structures, e.g. queues
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2209/00—Indexing scheme relating to G06F9/00
- G06F2209/54—Indexing scheme relating to G06F9/54
- G06F2209/547—Messaging middleware
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2209/00—Indexing scheme relating to G06F9/00
- G06F2209/54—Indexing scheme relating to G06F9/54
- G06F2209/548—Queue
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Engineering & Computer Science (AREA)
- Software Systems (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a cloud task scheduling and executing method based on MQ, which comprises the following steps: step S1, setting the message production end of the message queue as an entrance and setting task parameters; step S2, inserting the task parameters into a database; step S3, delivering the task parameter information to the information queue; step S4, the consumption module of the message queue consumes the message of the task parameter in real time; step S5, the consumption module of the message queue hands over the message of the task parameter to the cloud task scheduling center, and an instruction chain of the task parameter is constructed; step S6, taking a production module of the cloud task scheduling center as a production end of the message queue, and delivering the instruction chain to the message queue; step S7, the client side of task instruction execution is used as the consuming side of the message queue, the instruction chain message is consumed and processed, and the message queue is called back in real time after the instruction chain message is processed; the invention can reduce the coupling degree of each component in task scheduling to zero through the message queue.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a cloud task scheduling and executing method and system based on MQ.
Background
Task scheduling capabilities are often involved in somewhat large and complex systems, with the breaking down of size execution units and building a clear task chain being the key points for task scheduling. The traditional task scheduling system is mutually interwoven with Restfull or RPC messages in each scheduling link, so that the development complexity is increased, and the difficulty is caused for constructing a clear task chain; in addition, in the task execution layer, the conventional task scheduling system uses the task as the minimum unit, and cannot schedule the execution unit with finer granularity in the task again, which in principle causes resource waste.
Disclosure of Invention
In order to overcome the problems, the invention aims to provide a method for reducing the coupling degree of each component in task scheduling to zero through a message queue.
The invention is realized by adopting the following scheme: a method for MQ-based cloud task scheduling and execution, the method comprising the steps of:
step S1, setting the message production end of the message queue as an entrance and setting task parameters;
step S2, inserting the task parameters into a database;
step S3, delivering the task parameter information to the information queue;
step S4, the consumption module of the message queue consumes the message of the task parameter in real time;
step S5, the consumption module of the message queue hands over the message of the task parameter to the cloud task scheduling center, and an instruction chain of the task parameter is constructed and transmitted to the production module of the cloud task scheduling center in a serial-parallel mode;
step S6, taking a production module of the cloud task scheduling center as a production end of the message queue, and delivering the instruction chain to the message queue;
and step S7, taking the client side of the task instruction execution as a consuming side of the message queue, consuming and processing the instruction chain message, and calling back to the message queue in real time after the instruction chain message is processed, so that the coupling degree of each component for realizing task scheduling through the message queue is reduced to zero.
Further, the step S2 is further specifically: the task parameters are inserted into the database according to the format, the structures corresponding to the task parameters and the task types are obtained from the database according to the IDs of the task parameters, the structures are subsequently sent to a task disassembling and instruction chain building module of the cloud task scheduling center for use, and the sequence of executing task instructions is built.
Further, the step S3 is further specifically: and delivering a message with a message transfer station as a 'task' to the message queue, providing a specific task parameter ID, and marking as $ { task _ ID }.
Further, the step S5 is further specifically: and the consumption module of the message queue hands over the message with the ID task parameter to a task disassembling and instruction chain constructing module of the cloud task scheduling center, an instruction chain of a topological structure of the task parameter is constructed, and the instruction chain is transmitted to a production module of the cloud task scheduling center in a serial-parallel mode.
Further, the step S6 is further specifically: and taking a production module of the cloud task scheduling center as a production end of the message queue, constructing a message of a message transfer station by the instruction chain, wherein the message is named as $ { command _ ID }, and the message has ID of the task parameter, and delivering the ID to the message queue.
Further, the step S7 is further specifically: and taking the client side for executing the task instruction as a consuming side of the message queue, consuming and processing the instruction chain message of the message transfer station, calling back the result to the message queue in real time after the completion, confirming whether the execution is successful and confirming the storage path of the execution result, thereby reducing the coupling degree of each component for realizing task scheduling to zero through the message queue.
The invention also provides a system for scheduling and executing the cloud task based on the MQ, which comprises a setting module, an inserting module, a delivering module, a consuming module, a constructing module, a producing module and a call-back module, wherein the setting module sets the message producing end of the message queue as an inlet and sets task parameters; the inserting module inserts the task parameters into a database; the delivery module delivers the message of the task parameters to the message queue; the consumption module, namely the consumption module of the message queue, consumes the message of the task parameter in real time; the building module, namely a consumption module of the message queue, hands over the message of the task parameter to the cloud task scheduling center, builds an instruction chain of the task parameter, and transmits the instruction chain to a production module of the cloud task scheduling center in a serial-parallel mode; the production module is used for taking a production module of the cloud task scheduling center as a production end of the message queue and delivering the instruction chain to the message queue; the callback module takes a client side executing the task instruction as a consumption side of the message queue, consumes and processes the instruction chain message, and then calls back to the message queue in real time after the completion of the instruction chain message, so that the coupling degree of each component for realizing task scheduling through the message queue is reduced to zero.
Further, the insertion module further specifically includes: the task parameters are inserted into the database according to the format, the structures corresponding to the task parameters and the task types are obtained from the database according to the IDs of the task parameters, the structures are subsequently sent to a task disassembling and instruction chain building module of the cloud task scheduling center for use, and the sequence of executing task instructions is built.
Further, the delivery module further specifically comprises: and delivering a message with a message transfer station as a 'task' to the message queue, providing a specific task parameter ID, and marking as $ { task _ ID }.
Further, the building module further specifically includes: and the consumption module of the message queue hands over the message with the ID task parameter to a task disassembling and instruction chain constructing module of the cloud task scheduling center, an instruction chain of a topological structure of the task parameter is constructed, and the instruction chain is transmitted to a production module of the cloud task scheduling center in a serial-parallel mode.
Further, the production module further specifically includes: and taking a production module of the cloud task scheduling center as a production end of the message queue, constructing a message of a message transfer station by the instruction chain, wherein the message is named as $ { command _ ID }, and the message has ID of the task parameter, and delivering the ID to the message queue.
Further, the callback module further specifically includes: and taking the client side for executing the task instruction as a consuming side of the message queue, consuming and processing the instruction chain message of the message transfer station, calling back the result to the message queue in real time after the completion, confirming whether the execution is successful and confirming the storage path of the execution result, thereby reducing the coupling degree of each component for realizing task scheduling to zero through the message queue.
The invention has the beneficial effects that: according to the invention, the coupling degree of each component of task scheduling is reduced to zero through the MQ message queue, the internal logic of the task scheduling is concerned, and the development difficulty is greatly reduced; the split execution instruction can be preferentially executed in the first time in a short time to a certain extent, so that the efficiency is greatly improved; from the development perspective, the cloud task scheduling for large-scale complex systems also needs to be decomposed into small-scale tasks and processed, and the invention meets the capacity of splitting large problems into small problems by using the divide-and-conquer thinking.
Drawings
FIG. 1 is a schematic flow diagram of the process of the present invention.
Fig. 2 is a schematic block diagram of the system of the present invention.
FIG. 3 is a task execution flow diagram according to the present invention.
FIG. 4 is a detailed flow chart of the task of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
Referring to fig. 1, a method for MQ-based cloud task scheduling and execution according to the present invention includes the following steps:
step S1, setting the message production end of the message queue as an entrance and setting task parameters;
step S2, inserting the task parameters into a database;
step S3, delivering the task parameter information to the information queue;
step S4, the consumption module of the message queue consumes the message of the task parameter in real time;
step S5, the consumption module of the message queue hands over the message of the task parameter to the cloud task scheduling center, and an instruction chain of the task parameter is constructed and transmitted to the production module of the cloud task scheduling center in a serial-parallel mode;
step S6, taking a production module of the cloud task scheduling center as a production end of the message queue, and delivering the instruction chain to the message queue;
and step S7, taking the client side of the task instruction execution as a consuming side of the message queue, consuming and processing the instruction chain message, and calling back to the message queue in real time after the instruction chain message is processed, so that the coupling degree of each component for realizing task scheduling through the message queue is reduced to zero.
The invention is further illustrated by the following specific examples:
in order to execute the whole task, the whole link involved by the task is divided into a task production component, a task consumption component, an instruction production component and an instruction execution component, and all the components are decoupled through MQ, namely the components do not depend on each other and only need to interact with MQ, so that the complexity is reduced in principle. The task production component acts as a portal and is a pure MQ message production side. The task consumption component and the instruction production component together construct a task scheduling center, the center mainly consumes tasks from MQ, and disassembles the tasks into specified small granularity according to the specific tasks, an executable execution unit execution chain is constructed, and the disassembler in the center delivers the execution unit as the message of MQ. The instruction execution unit, which is the final node, consumes the messages from the MQ and returns the current task state after execution. MQ refers to a message queue service, see in particular the figure below (FIG. 3).
In connection with the embodiment of producing a PPT courseware task in which the part set numbers correspond to implementation modules (see fig. 4), the general steps are divided into seven steps, as follows:
the C1 device is a client of a production task.
The C2 device is a message queue.
The C3 device is a database that stores tasks.
The C4 device is a consumption module of the cloud task scheduling center that receives the task message.
The C5 device is a production module of a production instruction message of the cloud task scheduling center.
The C6 device is a task disassembling and constructing instruction chain module of the cloud task scheduling center.
The C7 device is a client that the instruction executes.
1. The C1 device is an entrance, and is also a Producer end of the C2 device, and parameters and resources necessary for tasks are set; the essential parameters are necessary parameters required for task execution, are part of services, are not much related to the scheduling mechanism of the patent, and are only used for explaining the flow. Such as: task type, resource ID required by the task. Resources are also a parameter on which services depend.
2. Inserting the assembled task data into the C3 device, and then using the C6 device for detailed decomposition; the task data to be assembled is that the mentioned task parameters are in a certain format. Including different contents according to different services, and has little relation with the whole scheduling mechanism. The detailed decomposition refers to that the C6 device obtains details of a task from a database according to the task ID, where the details include task parameters and a structure corresponding to a task type, for example, one task type may require 5 instructions to complete, 2 instructions are parallel, 3 instructions are serial, and the detailed decomposition is to construct an execution sequence of the instructions.
Specific examples of the detailed decomposition include: including the task name task _ name, the task type structure tools, and the required resource id res _ id.
For example, service a needs to output one PPT, which needs 3 tools to complete, and its format is as follows:
res_id:’d075498f-3535-43f8-bd41-1d75806628 ef', the C6 device constructs a command execution chain based on this parameter (where t-C needs to depend on t-a and t-b; and t-a and t-b can be executed in parallel). While service B needs to output a video, it needs a tool to complete it, and its format:
3. delivering a message with exchange of 'TASK' to the C2 device, wherein the message is provided with a specific TASK ID with the name of $ { TASK _ ID }; the delivery is that the message queue producer sends a message to the message queue. The client is connected with a message queue service tcp and actively sends a subject message to the message queue.
4. At this time, the consumption side C4 device, which is a C2 device, consumed $ { task _ id } message immediately; consumption is a general term of a message queue, a client is connected with a message queue service tcp and subscribes a certain subject message of the message queue, when the subject message has data, the subject message is sent to the client through the message queue service tcp, and the client takes the message to perform service processing.
5. The C4 device transfers the message to the C6 device of the internal processor of the task scheduling center, constructs an instruction chain of a topological structure for constructing the task, the chain comprises a plurality of instructions, and the instruction chain is transmitted to the C5 device in a serial-parallel mode; the parallel mode is a mode that the execution sequence is in parity and does not need to depend on a preposed instruction; the serial mode is a mode that the execution sequence is dependent and needs to depend on a preposed instruction.
The instruction chain construction comprises the following specific flows:
1. taking out corresponding task data from the database according to the task _ id;
2. according to the task type, finding out an instruction for executing the task under the type, wherein the instruction at least comprises the following steps: and executing the host and the command execution command.
3. The instructions that execute the tasks have instruction dependencies, and the instruction execution order is set according to the dependencies.
6. The C5 device also serves as a production end of the C2 device, and a message $ { COMMAND _ id } with $ { task _ id } is sent to the C2, wherein the message is formed by an instruction and is changed into 'COMMAND'; exchange: is a message transfer station; COMMAND is the transfer station name; $ command _ ID identifies a placeholder that is an ID;
7. the C7 device is also used as a consuming end of the C2 device, consumes the message with exchange as 'COMMAND', receives and processes the $ { COMMAND _ id } message, and finishes the call back of the horse immediately.
The specific process of callback includes: sending a command execution callback message to a message queue, the message comprising at least: execution identification (success or failure), execution result storage path; the cloud scheduling center receives this status and schedules the next instruction. And writing the task state when judging that all the instructions of the task are executed.
Continuing to refer to fig. 2, the invention further provides a system for scheduling and executing a cloud task based on MQ, which comprises a setting module, an inserting module, a delivering module, a consuming module, a constructing module, a producing module and a callback module, wherein the setting module sets a message producing end of a message queue as an entrance and sets task parameters; the inserting module inserts the task parameters into a database; the delivery module delivers the message of the task parameters to the message queue; the consumption module, namely the consumption module of the message queue, consumes the message of the task parameter in real time; the building module, namely a consumption module of the message queue, hands over the message of the task parameter to the cloud task scheduling center, builds an instruction chain of the task parameter, and transmits the instruction chain to a production module of the cloud task scheduling center in a serial-parallel mode; the production module is used for taking a production module of the cloud task scheduling center as a production end of the message queue and delivering the instruction chain to the message queue; the callback module takes a client side executing the task instruction as a consumption side of the message queue, consumes and processes the instruction chain message, and then calls back to the message queue in real time after the completion of the instruction chain message, so that the coupling degree of each component for realizing task scheduling through the message queue is reduced to zero.
The insertion module is further embodied as follows: the task parameters are inserted into the database according to the format, the structures corresponding to the task parameters and the task types are obtained from the database according to the IDs of the task parameters, the structures are subsequently sent to a task disassembling and instruction chain building module of the cloud task scheduling center for use, and the sequence of executing task instructions is built.
The delivery module is further embodied as follows: and delivering a message with a message transfer station as a 'task' to the message queue, providing a specific task parameter ID, and marking as $ { task _ ID }.
The building module is further specifically: and the consumption module of the message queue hands over the message with the ID task parameter to a task disassembling and instruction chain constructing module of the cloud task scheduling center, an instruction chain of a topological structure of the task parameter is constructed, and the instruction chain is transmitted to a production module of the cloud task scheduling center in a serial-parallel mode.
The production module further comprises: and taking a production module of the cloud task scheduling center as a production end of the message queue, constructing a message of a message transfer station by the instruction chain, wherein the message is named as $ { command _ ID }, and the message has ID of the task parameter, and delivering the ID to the message queue.
The callback module further specifically comprises: and taking the client side for executing the task instruction as a consuming side of the message queue, consuming and processing the instruction chain message of the message transfer station, calling back the result to the message queue in real time after the completion, confirming whether the execution is successful and confirming the storage path of the execution result, thereby reducing the coupling degree of each component for realizing task scheduling to zero through the message queue.
The above description is only a preferred embodiment of the present invention, and all equivalent changes and modifications made in accordance with the claims of the present invention should be covered by the present invention.
Claims (12)
1. An MQ-based cloud task scheduling and executing method, the method comprising the following steps:
step S1, setting the message production end of the message queue as an entrance and setting task parameters;
step S2, inserting the task parameters into a database;
step S3, delivering the task parameter information to the information queue;
step S4, the consumption module of the message queue consumes the message of the task parameter in real time;
step S5, the consumption module of the message queue hands over the message of the task parameter to the cloud task scheduling center, and an instruction chain of the task parameter is constructed and transmitted to the production module of the cloud task scheduling center in a serial-parallel mode;
step S6, taking a production module of the cloud task scheduling center as a production end of the message queue, and delivering the instruction chain to the message queue;
and step S7, taking the client side of the task instruction execution as a consuming side of the message queue, consuming and processing the instruction chain message, and calling back to the message queue in real time after the instruction chain message is processed, so that the coupling degree of each component for realizing task scheduling through the message queue is reduced to zero.
2. The MQ-based cloud task scheduling and execution method of claim 1, wherein: the step S2 further includes: the task parameters are inserted into the database according to the format, the structures corresponding to the task parameters and the task types are obtained from the database according to the IDs of the task parameters, the structures are subsequently sent to a task disassembling and instruction chain building module of the cloud task scheduling center for use, and the sequence of executing task instructions is built.
3. The MQ-based cloud task scheduling and execution method of claim 1, wherein: the step S3 further includes: and delivering a message with a message transfer station as a 'task' to the message queue, providing a specific task parameter ID, and marking as $ { task _ ID }.
4. The MQ-based cloud task scheduling and execution method of claim 1, wherein: the step S5 further includes: and the consumption module of the message queue hands over the message with the ID task parameter to a task disassembling and instruction chain constructing module of the cloud task scheduling center, an instruction chain of a topological structure of the task parameter is constructed, and the instruction chain is transmitted to a production module of the cloud task scheduling center in a serial-parallel mode.
5. The MQ-based cloud task scheduling and execution method of claim 1, wherein: the step S6 further includes: and taking a production module of the cloud task scheduling center as a production end of the message queue, constructing a message of a message transfer station by the instruction chain, wherein the message is named as $ { command _ ID }, and the message has ID of the task parameter, and delivering the ID to the message queue.
6. The MQ-based cloud task scheduling and execution method of claim 1, wherein: the step S7 further includes: and taking the client side for executing the task instruction as a consuming side of the message queue, consuming and processing the instruction chain message of the message transfer station, calling back the result to the message queue in real time after the completion, confirming whether the execution is successful and confirming the storage path of the execution result, thereby reducing the coupling degree of each component for realizing task scheduling to zero through the message queue.
7. A system for scheduling and executing cloud tasks based on MQ is characterized in that: the system comprises a setting module, an inserting module, a delivery module, a consumption module, a construction module, a production module and a callback module, wherein the setting module sets a message production end of a message queue as an inlet and sets task parameters; the inserting module inserts the task parameters into a database; the delivery module delivers the message of the task parameters to the message queue; the consumption module, namely the consumption module of the message queue, consumes the message of the task parameter in real time; the building module, namely a consumption module of the message queue, hands over the message of the task parameter to the cloud task scheduling center, builds an instruction chain of the task parameter, and transmits the instruction chain to a production module of the cloud task scheduling center in a serial-parallel mode; the production module is used for taking a production module of the cloud task scheduling center as a production end of the message queue and delivering the instruction chain to the message queue; the callback module takes a client side executing the task instruction as a consumption side of the message queue, consumes and processes the instruction chain message, and then calls back to the message queue in real time after the completion of the instruction chain message, so that the coupling degree of each component for realizing task scheduling through the message queue is reduced to zero.
8. The MQ-based cloud task scheduling and execution system as claimed in claim 7, wherein: the insertion module is further embodied as follows: the task parameters are inserted into the database according to the format, the structures corresponding to the task parameters and the task types are obtained from the database according to the IDs of the task parameters, the structures are subsequently sent to a task disassembling and instruction chain building module of the cloud task scheduling center for use, and the sequence of executing task instructions is built.
9. The MQ-based cloud task scheduling and execution system as claimed in claim 7, wherein: the delivery module is further embodied as follows: and delivering a message with a message transfer station as a 'task' to the message queue, providing a specific task parameter ID, and marking as $ { task _ ID }.
10. The MQ-based cloud task scheduling and execution system as claimed in claim 7, wherein: the building module is further specifically: and the consumption module of the message queue hands over the message with the ID task parameter to a task disassembling and instruction chain constructing module of the cloud task scheduling center, an instruction chain of a topological structure of the task parameter is constructed, and the instruction chain is transmitted to a production module of the cloud task scheduling center in a serial-parallel mode.
11. The MQ-based cloud task scheduling and execution system as claimed in claim 7, wherein: the production module further comprises: and taking a production module of the cloud task scheduling center as a production end of the message queue, constructing a message of a message transfer station by the instruction chain, wherein the message is named as $ { command _ ID }, and the message has ID of the task parameter, and delivering the ID to the message queue.
12. The MQ-based cloud task scheduling and execution system as claimed in claim 7, wherein: the callback module further specifically comprises: and taking the client side for executing the task instruction as a consuming side of the message queue, consuming and processing the instruction chain message of the message transfer station, calling back the result to the message queue in real time after the completion, confirming whether the execution is successful and confirming the storage path of the execution result, thereby reducing the coupling degree of each component for realizing task scheduling to zero through the message queue.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210001176.3A CN114168304B (en) | 2022-01-04 | 2022-01-04 | MQ-based cloud task scheduling and executing method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210001176.3A CN114168304B (en) | 2022-01-04 | 2022-01-04 | MQ-based cloud task scheduling and executing method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114168304A true CN114168304A (en) | 2022-03-11 |
| CN114168304B CN114168304B (en) | 2024-07-26 |
Family
ID=80488989
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210001176.3A Active CN114168304B (en) | 2022-01-04 | 2022-01-04 | MQ-based cloud task scheduling and executing method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114168304B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2016119521A1 (en) * | 2015-01-30 | 2016-08-04 | Huawei Technologies Co., Ltd. | Asynchronous multiple-core processor |
| CN110134499A (en) * | 2019-03-29 | 2019-08-16 | 新智云数据服务有限公司 | Method for scheduling task, task scheduling system, storage medium and computer equipment |
| CN112379995A (en) * | 2021-01-11 | 2021-02-19 | 北京江融信科技有限公司 | DAG-based unitized distributed scheduling system and method |
-
2022
- 2022-01-04 CN CN202210001176.3A patent/CN114168304B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2016119521A1 (en) * | 2015-01-30 | 2016-08-04 | Huawei Technologies Co., Ltd. | Asynchronous multiple-core processor |
| CN110134499A (en) * | 2019-03-29 | 2019-08-16 | 新智云数据服务有限公司 | Method for scheduling task, task scheduling system, storage medium and computer equipment |
| CN112379995A (en) * | 2021-01-11 | 2021-02-19 | 北京江融信科技有限公司 | DAG-based unitized distributed scheduling system and method |
Non-Patent Citations (2)
| Title |
|---|
| S.SHENG: "A Resource Collaborative Scheduling Strategy Based on Cloud Edge Framework", 《2021 IEEE 5TH ADVANCED INFORMATION TECHNOLOGY，ELECTRONIC AND AUTOMATION CONTROL CONFERENCE》, 5 April 2021 (2021-04-05), pages 1740 - 1744 * |
| 陈红洲: "同时多线程处理器资源共享控制策略研究", 《中国博士学位论文全文数据库 信息科技辑》, no. 07, 15 July 2010 (2010-07-15), pages 137 - 2 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114168304B (en) | 2024-07-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107277083B (en) | Data interaction processing method, device and system | |
| CN109858607A (en) | A kind of application method, management method, system and server | |
| CN101383839A (en) | Data distribution system based on data server and implementation method | |
| CN110503385B (en) | Service processing method, device, computer equipment and storage medium | |
| CN110611707A (en) | Task scheduling method and device | |
| Hwang et al. | Modification of mosquitto broker for delivery of urgent MQTT message | |
| EP2696297A1 (en) | System and method for generating information file based on parallel processing | |
| CN111478839B (en) | Physical bus and operating system decoupled distributed aviation communication system | |
| CN116661978B (en) | Distributed flow processing method and device and distributed business flow engine | |
| CN114168304B (en) | MQ-based cloud task scheduling and executing method and system | |
| CN112905318A (en) | Message priority queue based distributed switching network element calling method and system | |
| CN106886453A (en) | Information processing method, device and system for asynchronous multiple tracks | |
| CN115361382B (en) | Data processing method, device, equipment and storage medium based on data group | |
| CN111988372A (en) | Method and device for decoding and transmitting mobile telephone bill | |
| Lee et al. | A causality based time management mechanism for federated simulation | |
| CN114741167A (en) | Distributed timing task scheduling method and system based on message queue | |
| CN115712572A (en) | Task testing method and device, storage medium and electronic device | |
| CN113835853A (en) | Distributed RPA robot management method, device and storage medium combining AI and RPA | |
| CN108399096A (en) | Multi-task scheduling time sequence monitoring method and system for battery management system | |
| CN113497731B (en) | Centralized control probe scheduling method and centralized control probe management system | |
| CN111786875A (en) | Data processing method and device based on distributed architecture | |
| CN111541759A (en) | Cloud platform communication system and communication method thereof | |
| US7757235B2 (en) | Trigger support for a bi-directional broker | |
| CN116795434B (en) | Pipelined task processing method and device, electronic equipment and storage medium | |
| CN116594784B (en) | Method, device and system for scheduling edges and readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |