CN115794339A - Cloud computing task tracking processing method and system - Google Patents
Cloud computing task tracking processing method and system Download PDFInfo
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Abstract
The invention is applicable to the technical field of cloud computing, and particularly relates to a cloud computing task tracking processing method and a cloud computing task tracking processing system, wherein the method comprises the following steps: acquiring a cloud computing task; carrying out calculation sequence decomposition on the cloud calculation tasks to obtain a plurality of groups of functional tasks; performing task decomposition on the functional task, dividing the functional task into a serial task and a parallel task, and generating a progress tracking task; and sending the serial task, the parallel task and the progress tracking task to a cloud server for calculation, receiving feedback information, generating a scheduling task, and sending the scheduling task. The invention divides the overall task according to the processing sequence, so that the divided tasks are divided in parallel to obtain the parallel task and the serial task, and the completion condition of the small program is tracked in the process of completing the task, so that the distribution of the tasks is actively adjusted according to the task completion condition, and the overall task completion time is ensured to the maximum extent.
Description
Technical Field
The invention belongs to the technical field of cloud computing, and particularly relates to a cloud computing task tracking processing method and system.
Background
Cloud computing is one of distributed computing, and refers to decomposing a huge data computing processing program into countless small programs through a network cloud, and then processing and analyzing the small programs through a system consisting of a plurality of servers to obtain results and returning the results to a user.
In the current cloud computing process, in order to count the completion condition of the current cloud computing task, the cloud computing task is usually tracked, and the task completion progress is judged by analyzing the execution condition of each xiao Cheng sequence on the assigned task.
However, in the current cloud computing task tracking process, flexible adjustment cannot be performed according to the execution condition of the task, so that the overall task completion time is prolonged when the applet cannot complete the task.
Disclosure of Invention
The embodiment of the invention aims to provide a cloud computing task tracking processing method, and aims to solve the problem that the overall task completion time is prolonged when an applet cannot complete a task.
The embodiment of the invention is realized in such a way that a cloud computing task tracking processing method comprises the following steps:
acquiring a cloud computing task;
carrying out calculation sequence decomposition on cloud calculation tasks to obtain a plurality of groups of functional tasks, wherein the functional tasks are sequentially associated;
performing task decomposition on the functional task, dividing the functional task into a serial task and a parallel task, and generating a progress tracking task;
the method comprises the steps of sending a serial task, a parallel task and a progress tracking task to a cloud server for calculation, receiving feedback information, generating a scheduling task according to the feedback information, and sending the scheduling task, wherein the cloud server comprises a parallel small program, a serial small program and a supervision small program.
Preferably, the step of performing calculation sequence decomposition on the cloud calculation tasks to obtain multiple groups of functional tasks specifically includes:
determining a data computing sequence according to the cloud computing task;
dividing the cloud computing task into a plurality of parts according to a computing sequence to obtain a plurality of groups of functional tasks, wherein the functional tasks have a sequential relationship which is completed in sequence;
and dividing the functional task into a plurality of subtasks according to the preset task division granularity.
Preferably, the step of performing task decomposition on the functional task, dividing the functional task into a serial task and a parallel task, and generating a progress tracking task specifically includes:
determining the processing sequence of the functional tasks according to the sequence association among the functional tasks;
dividing subtasks contained in each functional task into a non-sequential task and a sequential task;
and dividing unordered tasks contained in all the functional tasks into parallel tasks, sequentially dividing the ordered tasks in each functional task into serial tasks according to the order, and generating a progress tracking task according to the division condition of the tasks.
Preferably, the steps of sending the serial task, the parallel task and the progress tracking task to the cloud server for computation, receiving feedback information, generating a scheduling task according to the feedback information, and sending the scheduling task include:
distributing the parallel tasks to the parallel small programs in the cloud server, and sending the serial tasks to the serial small programs in batches;
sending the progress tracking task to the supervisory applet and receiving feedback information from the supervisory applet;
and determining the allocation scheme of the serial tasks and/or the parallel tasks based on the feedback information, generating scheduling tasks, and sending the scheduling tasks to the corresponding parallel small programs and/or the serial small programs.
Preferably, when the serial task, the parallel task and the progress tracking task are sent out, the serial task, the parallel task and the progress tracking task are encrypted by adopting a preset encryption algorithm, and a corresponding decryption algorithm is stored in the cloud server.
Preferably, the supervision applet calculates a theoretical time-consuming value according to the serial task and/or the parallel task and the computing power of the corresponding parallel applet and/or the serial applet, records an actual time-consuming value, and sends back the actual time-consuming value as feedback information when the deviation of the increase progress of the actual time-consuming value exceeds a preset value.
Another object of an embodiment of the present invention is to provide a cloud computing task tracking processing system, where the system includes:
the task obtaining module is used for obtaining a cloud computing task;
the task decomposition module is used for carrying out calculation sequence decomposition on the cloud calculation tasks to obtain a plurality of groups of functional tasks, and the functional tasks are sequentially associated;
the task division module is used for performing task decomposition on the functional tasks, dividing the functional tasks into serial tasks and parallel tasks and generating progress tracking tasks;
and the task tracking module is used for sending the serial task, the parallel task and the progress tracking task to the cloud server for calculation, receiving feedback information, generating a scheduling task according to the feedback information and sending the scheduling task, wherein the cloud server comprises a parallel small program, a serial small program and a monitoring small program.
Preferably, the task decomposition module includes:
the sequence determining unit is used for determining a data computing sequence according to the cloud computing task;
the cloud computing system comprises a task dividing unit, a task processing unit and a task processing unit, wherein the task dividing unit is used for dividing a cloud computing task into a plurality of parts according to a computing sequence to obtain a plurality of groups of functional tasks, and the functional tasks have sequential relations which are completed in sequence;
and the subtask division unit is used for dividing the functional task into a plurality of subtasks according to the preset task division granularity.
Preferably, the task dividing module includes:
the task association unit is used for determining the processing sequence of the functional tasks according to the sequence association among the functional tasks;
the subtask sequence dividing unit is used for dividing the subtasks contained in each functional task into a non-sequence task and a sequence task;
and the task mode dividing unit is used for dividing unordered tasks contained in all the functional tasks into parallel tasks, dividing ordered tasks in each functional task into serial tasks according to the order, and generating a progress tracking task according to the division condition of the tasks.
Preferably, the task tracking module includes:
the task processing unit is used for distributing the parallel tasks to the parallel small programs in the cloud server and sending the serial tasks to the serial small programs in batches;
the task supervision unit is used for sending the progress tracking task to the small supervision program and receiving feedback information sent by the small supervision program;
and the task adjusting unit is used for determining a serial task and/or a parallel task distribution scheme based on the feedback information, generating a scheduling task and sending the scheduling task to the corresponding parallel small program and/or the serial small program.
According to the cloud computing task tracking processing method provided by the embodiment of the invention, the overall task is divided according to the processing sequence, so that the divided tasks are divided in parallel to obtain the parallel task and the serial task, and the completion condition of the small program is tracked in the process of completing the task, so that the distribution of the task is actively adjusted according to the completion condition of the task, and the overall task completion time is ensured to the greatest extent.
Drawings
Fig. 1 is a flowchart of a cloud computing task tracking processing method according to an embodiment of the present invention;
fig. 2 is a flowchart of a step of performing calculation sequence decomposition on cloud calculation tasks to obtain multiple groups of functional tasks according to an embodiment of the present invention;
FIG. 3 is a flowchart of the steps of performing task decomposition on a functional task, dividing the task into a serial task and a parallel task, and generating a progress tracking task according to an embodiment of the present invention;
fig. 4 is a flowchart for sending a serial task, a parallel task, and a progress tracking task to a cloud server for computation, receiving feedback information, generating a scheduling task according to the feedback information, and sending the scheduling task according to the embodiment of the present invention;
fig. 5 is an architecture diagram of a cloud computing task tracking processing system according to an embodiment of the present invention;
FIG. 6 is an architecture diagram of a task decomposition module according to an embodiment of the present invention;
FIG. 7 is an architecture diagram of a task partitioning module according to an embodiment of the present invention;
fig. 8 is an architecture diagram of a task tracking module according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It will be understood that, as used herein, the terms "first," "second," and the like may be used herein to describe various elements, but these elements should not be limited by these terms unless otherwise specified. These terms are only used to distinguish one element from another. For example, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script, without departing from the scope of the present application.
In the current cloud computing process, in order to count the completion condition of the current cloud computing task, the cloud computing task is usually tracked, and the task completion progress is judged by analyzing the execution condition of each xiao Cheng sequence on the assigned task. However, in the current cloud computing task tracking process, flexible adjustment cannot be performed according to the execution condition of the task, so that the overall task completion time is prolonged when the applet cannot complete the task.
The invention divides the overall task according to the processing sequence, thereby dividing the divided tasks in parallel to obtain the parallel task and the serial task, and tracking the completion condition of the small program in the process of completing the task, thereby actively adjusting the distribution of the tasks according to the task completion condition and ensuring the overall task completion time to the maximum extent.
As shown in fig. 1, a flowchart of a cloud computing task tracking processing method provided in an embodiment of the present invention is shown, where the method includes:
s100, acquiring a cloud computing task.
In this step, a cloud computing task is obtained, and in the same cloud computing task, a plurality of processes such as data analysis, data classification, data transcoding, data statistics, data compression and the like exist, and some processes have a precedence relationship, so that when cloud computing is performed, all processes having the precedence relationship need to be processed according to the order, and if an output result of the process a is input to the process B, the process B needs to be performed after the process a is completed.
S200, carrying out calculation sequence decomposition on the cloud calculation tasks to obtain a plurality of groups of functional tasks, wherein the functional tasks are sequentially associated.
In this step, the cloud computing task is subjected to computation order decomposition, that is, the process of analyzing the cloud computing task is divided into a plurality of processes, each process is an individual function, for example, one cloud computing task is divided into five processes, that is, a process a, a process B, a process C, a process D and a process E, the processes a, the processes B, the process C, the process D and the process E are a plurality of groups of functional tasks, each process realizes an independent function, such as data analysis, data classification and the like, and the process C and the process D can be performed after the process B, and the process a and the process B have no order relationship, and are independent processes, and order association can be determined by the order relationship between the processes.
And S300, performing task decomposition on the functional tasks, dividing the functional tasks into serial tasks and parallel tasks, and generating a progress tracking task.
In the step, the functional tasks are decomposed, for a process, the process can be divided into a plurality of specific steps, for example, for a data classification process, the data classification process comprises the steps of data screening, keyword setting, data searching, data classification and storage, the specific steps have precedence relations and parallel relations, for example, the data screening and the keyword setting have no precedence relation, the data screening and the keyword setting are performed before the data searching, the data searching and the data classification and storage steps need to perform data searching first and then perform data classification and storage, so that each specific step can be divided into a serial task and a parallel task, the serial task and the parallel task are used as the sequence of execution of each small program, the progress tracking task is generated, and the parameters of the execution progress of each task are determined according to the progress tracking task.
And S400, sending the serial task, the parallel task and the progress tracking task to a cloud server for calculation, receiving feedback information, generating a scheduling task according to the feedback information, and sending the scheduling task, wherein the cloud server comprises a parallel small program, a serial small program and a monitoring small program.
In the step, the serial tasks, the parallel tasks and the progress tracking tasks are sent to the cloud server for calculation, and in the calculation, the serial tasks, the parallel tasks and the progress tracking tasks are respectively calculated by different applets, wherein the serial tasks have a precedence relationship, so that the next serial task is sent only when the current task is completed, the parallel tasks are sent and processed simultaneously, the precision tracking tasks comprise execution progress parameters for determining the serial tasks and the parallel tasks for supervision of the supervision applets, the supervision applets obtain corresponding data according to the applets which execute the serial tasks and the parallel tasks under the parameters, and compare the data with the set parameters to determine the progress, when the progress is delayed, the delay condition is sent back through feedback information, at the moment, the tasks are scheduled according to the feedback information, sent to the corresponding applets, and a new applet synchronously executes the delayed serial tasks or the parallel tasks.
As shown in fig. 2, as a preferred embodiment of the present invention, the step of decomposing the computing sequence of the cloud computing task to obtain a plurality of groups of functional tasks specifically includes:
s201, determining a data computing sequence according to the cloud computing task.
In the step, a data computing sequence is determined according to the cloud computing task, the cloud computing task is wholly analyzed, main processes contained in the cloud computing task are analyzed, and when the processes are divided, all steps for achieving independent functions are an independent process.
S202, dividing the cloud computing task into a plurality of parts according to the computing sequence to obtain a plurality of groups of functional tasks, wherein the functional tasks have sequential relation which is finished in sequence.
In this step, the cloud computing task is divided into a plurality of parts according to the computing sequence, an independent process is a plurality of parts, that is, the cloud computing task is divided into a combination body composed of a plurality of parts, and the sequence among the main processes is determined according to the execution sequence relation of each functional task.
S203, dividing the functional task into a plurality of subtasks according to the preset task division granularity.
In this step, the functional task is divided into a plurality of sub-tasks according to the preset task division granularity, specifically, for any process, the functional task can be divided into a plurality of small steps, so that each small step is divided into one sub-task, and for the complexity of different processes, different task division granularities can be set.
As shown in fig. 3, as a preferred embodiment of the present invention, the step of performing task decomposition on a functional task, dividing the functional task into a serial task and a parallel task, and generating a progress tracking task specifically includes:
s301, determining the processing sequence of the functional tasks according to the sequence association among the functional tasks.
S302, dividing subtasks contained in each functional task into unordered tasks and ordered tasks.
In this step, the processing order of the functional tasks is determined according to the order association between the functional tasks, and due to the precedence relationship between the functional tasks, when the ordered tasks and the unordered tasks are determined, the unordered tasks refer to absolutely unordered tasks, that is, subtasks of the tasks which are not affected by the precedence order of the functional tasks, the partial subtasks are regarded as unordered tasks, and then the rest subtasks are ordered tasks.
And S303, dividing unordered tasks contained in all the functional tasks into parallel tasks, sequentially dividing the ordered tasks in each functional task into serial tasks, and generating a progress tracking task according to the division condition of the tasks.
In the step, unordered tasks contained in all functional tasks are divided into parallel tasks, the parallel tasks are independent and are not affected by sequence, sequential tasks in all the functional tasks are divided into serial tasks according to the sequence, before the serial tasks are determined, the execution first-hand sequence among all the serial tasks needs to be determined, then respective calculated amount is determined according to the parallel tasks and the serial tasks, and the calculated amount is recorded into a progress tracking task.
As shown in fig. 4, as a preferred embodiment of the present invention, the steps of sending the serial task, the parallel task, and the progress tracking task to the cloud server for computation, receiving feedback information, generating a scheduling task according to the feedback information, and sending the scheduling task specifically include:
s401, distributing the parallel tasks to the parallel small programs in the cloud server, and sending the serial tasks to the serial small programs in batches.
In this step, the parallel tasks and the serial tasks are respectively sent to the parallel small programs and the serial small programs, and for the parallel tasks, the parallel tasks are not related, so the overall progress of the whole task processing is not affected by the sequence of the parallel tasks, and for the serial tasks, the parallel tasks need to be completed one by one, so that after the execution of one serial task is finished, the other serial task is executed.
S402, sending the progress tracking task to the small monitoring program and receiving feedback information sent by the small monitoring program.
In this step, the progress tracking task is sent to the supervisory applet, the progress tracking task records the data processing amount of each serial task and each parallel task, and the supervisory applet determines the time to be spent according to the computing power of the current corresponding parallel applet or serial applet, and counts the actually spent time, for example, if 60% of a certain task is completed through calculation, 10ms is spent, and 20ms is spent actually, the supermarket takes 10ms, and records the 10ms in the feedback information and sends the feedback information back.
And S403, determining a serial task and/or parallel task allocation scheme based on the feedback information, generating a scheduling task, and sending the scheduling task to the corresponding parallel small program and/or serial small program.
In this step, whether task adjustment is needed or not is judged based on feedback information, specifically, a threshold value is set, when the time over-value exceeds 50%, it is indicated that the applet executes the task abnormally, the applet can be switched or the same task is sent to the same applet, the applet and the applet run synchronously, the calculation result obtained firstly is taken as the standard, the applet which generates the calculation result firstly is continuously adopted subsequently, when the abnormality exists, the applet which has the same function as the applet but has a different specific implementation method can be switched for replacement; when the serial task, the parallel task and the progress tracking task are sent out, the serial task, the parallel task and the progress tracking task are encrypted by adopting a preset encryption algorithm, and a corresponding decryption algorithm is stored in the cloud server.
As shown in fig. 5, a cloud computing task tracking processing system provided in an embodiment of the present invention includes:
the task obtaining module 100 is configured to obtain a cloud computing task.
In the system, the task obtaining module 100 obtains the cloud computing task, and in the same cloud computing task, the cloud computing task includes a plurality of processes, such as data analysis, data classification, data transcoding, data statistics, data compression, and the like, wherein some processes have a precedence relationship, so that when cloud computing is performed, all processes having the precedence relationship need to be processed according to the order thereof, and if an output result of the process a is input of the process B, the process B needs to be performed after the process a is completed.
The task decomposition module 200 is configured to perform calculation sequence decomposition on the cloud calculation tasks to obtain multiple groups of functional tasks, where the functional tasks have sequence association.
In the system, the task decomposition module 200 decomposes the cloud computing task in a computing order, that is, analyzes the process of the cloud computing task, and divides the cloud computing task into a plurality of processes, each process is an individual function, for example, a cloud computing task is divided into five processes, which are respectively an a process, a B process, a C process, a D process, and an E process, the a process, the B process, the C process, the D process, and the E process are a plurality of groups of functional tasks, each process implements an independent function, such as data analysis, data classification, and the like, and wherein the C process and the D process can be performed after the B process, and the a process and the B process have no order relationship, and are independent processes, and order association can be determined through the order relationship between the processes.
The task division module 300 is configured to perform task decomposition on the functional task, divide the functional task into a serial task and a parallel task, and generate a progress tracking task.
In the system, the task dividing module 300 performs task decomposition on a functional task, and for a process, the process may be divided into a plurality of specific steps, for example, for a data classification process, the process includes steps of data screening, keyword setting, data searching, data classification and storage, some of the specific steps have precedence relationships and some of the specific steps are parallel relationships, and for example, the data screening and the keyword setting have no precedence relationship, both of the specific steps are performed before data searching, and data searching and data classification and storage need to be performed first and then data classification and storage are performed between the data searching and data classification and storage steps, so each specific step may be divided into a serial task and a parallel task, and thus the specific steps are used as an execution sequence of each applet, and a progress tracking task is generated, and the applet determines a parameter for determining an execution progress of each task according to the progress tracking task.
The task tracking module 400 is configured to send the serial task, the parallel task, and the progress tracking task to a cloud server for computation, receive feedback information, generate a scheduling task according to the feedback information, and send the scheduling task, where the cloud server includes a parallel applet, a serial applet, and a supervisory applet.
In the system, a task tracking module 400 sends serial tasks, parallel tasks and progress tracking tasks to a cloud server for calculation, and in the calculation, different applets are used for calculating the serial tasks, the parallel tasks and the progress tracking tasks respectively, wherein the serial tasks have a precedence relationship, so that the next serial task is sent only when the current task is completed, the parallel tasks are sent and processed simultaneously, the precision tracking tasks comprise execution progress parameters for determining the serial tasks and the parallel tasks so as to be supervised by a supervision applet, the supervision applet obtains corresponding data according to the applet which executes the serial tasks and the parallel tasks under the parameters and compares the data with the set parameters so as to determine the progress, when the progress is delayed, the delay condition is sent back through feedback information, at the moment, the tasks are scheduled according to the feedback information and sent to the corresponding applets, and a new applet synchronously executes the delayed serial tasks or the parallel tasks.
As shown in fig. 6, as a preferred embodiment of the present invention, the task decomposition module 200 includes:
an order determination unit 201, configured to determine a data computation order according to the cloud computing task.
In this module, the sequence determining unit 201 determines a data computing sequence according to the cloud computing task, analyzes a main process included in the cloud computing task by analyzing the whole cloud computing task, and divides the process to realize all steps of an individual function as an independent process.
The task dividing unit 202 is configured to divide the cloud computing task into multiple parts according to a computing sequence to obtain multiple groups of functional tasks, where the functional tasks have a sequential relationship that is completed sequentially.
In this module, the task partitioning unit 202 divides the cloud computing task into multiple parts according to the computing sequence, where an independent process is a combination of the multiple parts, that is, the cloud computing task is divided into multiple parts, and the sequence between the main processes is determined according to the execution precedence of each functional task.
The subtask dividing unit 203 is configured to divide the functional task into a plurality of subtasks according to a preset task division granularity.
In this module, the sub-task dividing unit 203 divides the functional task into a plurality of sub-tasks according to a preset task division granularity, specifically, for any process, it can divide the functional task into a plurality of small steps, so that each small step is divided into one sub-task, and for the complexity of different processes, different task division granularities can be set.
As shown in fig. 7, as a preferred embodiment of the present invention, the task dividing module 300 includes:
a task associating unit 301, configured to determine a processing order of the functional tasks according to the order association between the functional tasks.
A subtask sequence dividing unit 302, configured to divide the subtasks included in each functional task into an unordered task and an ordered task.
In this module, the task association unit 301 determines the processing order of the functional tasks according to the order association between the functional tasks, and since there is a precedence relationship between the functional tasks, when determining a sequential task and an unordered task, the unordered task refers to an absolutely unordered task, that is, a subtask of which the task is not affected by the precedence order of the functional tasks, and the partial subtasks are regarded as unordered tasks, and then the remaining partial subtasks are ordered tasks.
The task mode dividing unit 303 is configured to divide unordered tasks included in all the functional tasks into parallel tasks, divide ordered tasks in each functional task into serial tasks in order, and generate a progress tracking task according to the division condition of the tasks.
In this module, the task mode dividing unit 303 divides unordered tasks included in all functional tasks into parallel tasks, the parallel tasks are independent and are not affected by a sequence, the ordered tasks in each functional task are divided into serial tasks according to the sequence, before the serial tasks are determined, the execution first-hand sequence among the serial tasks needs to be determined, then respective calculated amount is determined according to the parallel tasks and the serial tasks, and the calculated amount is recorded into the progress tracking task.
As shown in fig. 8, as a preferred embodiment of the present invention, the task tracking module 400 includes:
and the task processing unit 401 is configured to allocate the parallel tasks to the parallel applets in the cloud server, and send the serial tasks to the serial applets in batches.
In this module, the task processing unit 401 sends the parallel tasks and the serial tasks to the parallel applet and the serial applet respectively, and for the parallel tasks, there is no relationship between the parallel tasks, so the sequence of the parallel tasks does not affect the total processing progress of the whole task, and for the serial tasks, the tasks need to be completed one by one, so that after the execution of one serial task is finished, another serial task is executed.
A task supervision unit 402 for sending the progress tracking task to the supervisory applet and receiving feedback information from the supervisory applet.
In this module, the task supervision unit 402 sends the progress tracking task to the supervision applet, where the progress tracking task records the data processing amount of each serial task and parallel task, and the supervision applet determines the time to be spent according to the calculation power of the current corresponding parallel applet or serial applet, and counts the actually spent time, where if 60% of a certain task is completed by calculation, it takes 10ms, and actually it takes 20ms, it indicates that the supermarket takes 10ms, and records it in the feedback information and sends it back.
And the task adjusting unit 403 is configured to determine an allocation scheme of the serial task and/or the parallel task based on the feedback information, generate a scheduling task, and send the scheduling task to the corresponding parallel applet and/or the serial applet.
In this module, the task adjusting unit 403 determines whether task adjustment is needed based on the feedback information, specifically, a threshold is set, when the time over-value exceeds 50%, it indicates that the applet executes the task abnormally, and the applet can be switched or the same task is sent to the same applet, and the two are run synchronously, on the basis of the calculation result obtained first, the applet which generates the calculation result first is continuously used subsequently, and when the abnormality exists, the applet which has the same function as the applet but has a different specific implementation method can be switched for replacement; when the serial task, the parallel task and the progress tracking task are sent out, the serial task, the parallel task and the progress tracking task are encrypted by adopting a preset encryption algorithm, and a corresponding decryption algorithm is stored in the cloud server.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in various embodiments may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
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 a computer program, which may be stored in a non-volatile computer readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
All possible combinations of the technical features of the above embodiments may not be described for the sake of brevity, but should be considered as within the scope of the present disclosure as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A cloud computing task tracking processing method is characterized by comprising the following steps:
acquiring a cloud computing task;
carrying out calculation sequence decomposition on cloud calculation tasks to obtain a plurality of groups of functional tasks, wherein the functional tasks are sequentially associated;
performing task decomposition on the functional task, dividing the functional task into a serial task and a parallel task, and generating a progress tracking task;
the method comprises the steps of sending a serial task, a parallel task and a progress tracking task to a cloud server for calculation, receiving feedback information, generating a scheduling task according to the feedback information, and sending the scheduling task, wherein the cloud server comprises a parallel small program, a serial small program and a monitoring small program.
2. The cloud computing task tracking processing method according to claim 1, wherein the step of performing computation order decomposition on the cloud computing tasks to obtain a plurality of groups of functional tasks specifically comprises:
determining a data computing sequence according to the cloud computing task;
dividing the cloud computing task into a plurality of parts according to a computing sequence to obtain a plurality of groups of functional tasks, wherein the functional tasks have a sequential relationship which is completed in sequence;
and dividing the functional task into a plurality of subtasks according to the preset task division granularity.
3. The cloud computing task tracking processing method according to claim 2, wherein the step of performing task decomposition on the functional task, dividing the task into a serial task and a parallel task, and generating the progress tracking task specifically includes:
determining the processing sequence of the functional tasks according to the sequence association among the functional tasks;
dividing subtasks contained in each functional task into unordered tasks and ordered tasks;
and dividing unordered tasks contained in all functional tasks into parallel tasks, sequentially dividing the ordered tasks in each functional task into serial tasks according to the sequence, and generating a progress tracking task according to the division condition of the tasks.
4. The cloud computing task tracking processing method according to claim 1, wherein the steps of sending the serial task, the parallel task, and the progress tracking task to a cloud server for computation, receiving feedback information, generating a scheduling task according to the feedback information, and sending the scheduling task specifically include:
distributing the parallel tasks to parallel small programs in the cloud server, and sending the serial tasks to the serial small programs in batches;
sending the progress tracking task to the small supervision program and receiving feedback information sent by the small supervision program;
and determining the allocation scheme of the serial tasks and/or the parallel tasks based on the feedback information, generating scheduling tasks, and sending the scheduling tasks to the corresponding parallel small programs and/or the serial small programs.
5. The cloud computing task tracking processing method according to claim 1, wherein when the serial task, the parallel task, and the progress tracking task are sent out, the serial task, the parallel task, and the progress tracking task are encrypted by using a preset encryption algorithm, and a corresponding decryption algorithm is stored in the cloud server.
6. The cloud computing task tracking processing method according to claim 1, wherein the supervisory applet calculates a theoretical time-consuming value according to the computing power of the serial task and/or the parallel task and the corresponding parallel applet and/or the serial applet, records an actual time-consuming value, and sends back the actual time-consuming value as feedback information when a deviation of a growth progress of the actual time-consuming value exceeds a preset value.
7. A cloud computing task tracking processing system, the system comprising:
the task obtaining module is used for obtaining a cloud computing task;
the task decomposition module is used for carrying out calculation sequence decomposition on the cloud calculation tasks to obtain a plurality of groups of functional tasks, and the functional tasks are sequentially associated;
the task division module is used for performing task decomposition on the functional tasks, dividing the functional tasks into serial tasks and parallel tasks and generating progress tracking tasks;
and the task tracking module is used for sending the serial task, the parallel task and the progress tracking task to the cloud server for calculation, receiving feedback information, generating a scheduling task according to the feedback information and sending the scheduling task, wherein the cloud server comprises a parallel small program, a serial small program and a monitoring small program.
8. The cloud computing task tracking processing system of claim 7, wherein the task decomposition module comprises:
the sequence determining unit is used for determining a data computing sequence according to the cloud computing task;
the cloud computing system comprises a task dividing unit, a task processing unit and a task processing unit, wherein the task dividing unit is used for dividing a cloud computing task into a plurality of parts according to a computing sequence to obtain a plurality of groups of functional tasks, and the functional tasks have sequential relations which are completed in sequence;
and the subtask division unit is used for dividing the functional task into a plurality of subtasks according to the preset task division granularity.
9. The cloud computing task tracking processing system of claim 8, wherein the task partitioning module comprises:
the task association unit is used for determining the processing sequence of the functional tasks according to the sequence association among the functional tasks;
the subtask sequence dividing unit is used for dividing the subtasks contained in each functional task into a non-sequence task and a sequence task;
and the task mode dividing unit is used for dividing the unordered tasks contained in all the functional tasks into parallel tasks, dividing the ordered tasks in each functional task into serial tasks according to the order, and generating the progress tracking task according to the division condition of the tasks.
10. The cloud computing task tracking processing system of claim 7, wherein the task tracking module comprises:
the task processing unit is used for distributing the parallel tasks to the parallel small programs in the cloud server and sending the serial tasks to the serial small programs in batches;
the task supervision unit is used for sending the progress tracking task to the small supervision program and receiving feedback information sent by the small supervision program;
and the task adjusting unit is used for determining the distribution scheme of the serial tasks and/or the parallel tasks based on the feedback information, generating scheduling tasks and sending the scheduling tasks to the corresponding parallel small programs and/or the serial small programs.
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