CN110297693B - Distributed software task allocation method and system - Google Patents
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Abstract
The application discloses a method and a system for distributing distributed software tasks, wherein the method for distributing the distributed software tasks specifically comprises the following steps: responding to the starting of the distributed software, and establishing a distributed software task; establishing at least one task group according to the distributed software tasks; and selecting a physical machine according to the task group, and establishing a virtual machine group on the physical machine to complete each task in the task group. According to the method and the device, the corresponding physical machine and the server thereof can be effectively selected for the task in the distributed software, instead of randomly selecting the physical machine to execute the task, so that the resource consumption of the physical machine and the server thereof is reduced, and the normal operation of the distributed software is ensured.
Description
Technical Field
The present application relates to the field of software, and in particular, to a method and a system for distributing distributed software tasks.
Background
In the prior art, distributed computers have been developed along with the ubiquitous idea of interconnection, the scale of software is continuously increased, more distributed application programs are provided, and the mode of a single server in the past cannot meet the use requirement, so that multitask parallel processing by using a distributed software system is generated. However, although the efficiency of the distributed software processing task is improved, executing a parallel program in the distributed software requires distributing the task to different physical machines for execution, thereby obtaining higher system performance. Then, in task allocation, the conventional distributed software does not consider the allocation situation of tasks in the physical machine, which may cause excessive resources operated by a certain server in the physical machine, and cause excessive consumption of the server resources of the physical machine to affect the processing performance of the physical machine. Therefore, a more powerful task allocation method is needed, which can ensure and improve the task execution efficiency without affecting the excessive resource consumption of the physical machine.
Disclosure of Invention
The purpose of the present application is to provide a method and a system for distributing distributed software tasks, which can reasonably distribute and execute tasks in distributed software, reduce resource consumption of a physical machine corresponding to a server, increase execution speed of tasks, and ensure normal operation of distributed software.
In order to achieve the above object, the present application provides a distributed software task allocation method, which specifically includes the following steps: responding to the starting of the distributed software, and establishing a distributed software task; establishing at least one task group according to the distributed software tasks; and selecting a physical machine according to the task group, and establishing a virtual machine group on the physical machine to complete each task in the task group.
As above, the distributed software tasks are established according to the types of the distributed software and the tasks included in the corresponding distributed software, and the distributed software tasks include at least one task.
As above, wherein multiple tasks exceeding a specified traffic are distributed among the same distributed software task.
As above, among others, the establishment of the task group is performed according to the task information included in the distributed software task.
As described above, the task information includes the number of task groups required by the distributed software tasks, the number of distributed software tasks in each task group, the execution condition of the tasks, the type of the server required for executing the tasks, and the upper limit value of the resources consumed when executing the tasks.
As above, wherein before selecting the physical machine according to the task group, the following sub-steps are further included: acquiring task information in a task group; and searching a physical machine corresponding to the task information.
As above, before executing the task by using the virtual machine, the following sub-steps are further included: selecting a plurality of tasks in the task group to execute; creating a work schedule according to historical completion time of tasks in a certain task group; the execution time that each task ideally needs is calculated.
As above, the work schedule is represented by a matrix, and if there are a plurality of tasks, the work schedule matrix A is represented as
a11…a13Representing the historical time of completion of task 1 in the task group, am1…amnRepresenting the historical time of completion of the last task in the task group, a is a constant, m represents a row in the matrix a, and n represents a column in the matrix a.
As above, wherein the respective tasks are in an ideal situationCalculating the next required execution time according to the time in the working time table; execution time tmIs particularly shown as
Wherein t ismRepresents the minimum time required for task 1, m represents a row in the matrix, n represents a column in the matrix, t represents a column in the matrixm1Representing the value of the first column in the mth row in the matrix, k representing the number of tasks included in the task group, tn2A value representing the second number in the nth column of the matrix, min { t }mnDenotes the smallest value in m rows and n columns,
indicates that n ≠ m, t is always set for any integer n, mmkRepresenting the value of the mth row and the kth column.
A distributed software task allocation system has a structure of a universal server and specifically comprises a physical machine, a task group and a virtual machine group; the physical machine runs distributed software, and the distributed software comprises distributed software tasks; a task group for planning and managing one or more tasks included in the plurality of distributed software; the virtual machine set executes one or more tasks in the task group; the processor of the system performs a method of distributed software task distribution as described above, stored in the form of computer instructions on a storage medium of the system.
The application has the following beneficial effects:
(1) the method and the system for distributing the distributed software tasks can select the corresponding physical machine and the server thereof according to the tasks in the distributed software effectively, and the physical machine is not selected randomly to execute the tasks, so that the resource consumption of the physical machine and the server thereof is reduced, and the normal operation of the distributed software is ensured.
(2) The distributed software task allocation method and the distributed software task allocation system can establish the virtual machine group in the physical machine to complete the execution of the tasks, and can revise the corresponding relation between the virtual machine group and the tasks at the specified time interval, thereby ensuring the effectiveness of the task execution and improving the speed of the task execution.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained by those skilled in the art according to the drawings.
FIG. 1 is a flow chart of a method of distributed software task distribution provided according to an embodiment of the present application;
fig. 2 is a system internal structure diagram of distributed software task allocation provided according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application are clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The application relates to a distributed software task allocation method and a system thereof. According to the method and the device, the tasks in the distributed software can be reasonably distributed and executed, the resource consumption of the physical machine corresponding to the server is reduced, the execution speed of the tasks is increased, and the normal operation of the distributed software is guaranteed.
Fig. 1 is a flowchart illustrating a method for distributed software task allocation according to the present application.
Step S110: in response to the initiation of the distributed software, a distributed software task is established.
After the distributed software is started, the distributed software tasks can be established according to the types of the distributed software and the tasks contained in the corresponding distributed software, and specifically, the types of the distributed software can be divided into distributed operation software, distributed programming language and compiling software thereof, distributed file software, distributed database software and the like.
Further, a plurality of distributed software tasks are established according to the distributed software types, and if the distributed software of the same type contains different tasks, a plurality of different distributed software tasks are correspondingly established according to the number of the tasks.
Still further, multiple tasks may also be distributed within the same distributed software task. E.g., large traffic is required between multiple tasks, the multiple tasks may be distributed among the same distributed software task.
Illustratively, if three parallel tasks are included in the distributed operating software, a distributed software task 1, a distributed software task 2, and a distributed software task 3 may be established. If two of the three tasks have large communication traffic, the two tasks can be distributed in the same distributed software task to establish a distributed software task 1 and a distributed software task 2.
Step S120: at least one task group is established based on the distributed software tasks.
And establishing a task group according to task information contained in the distributed software tasks.
Specifically, the task information includes the number of task groups required by the distributed software tasks, the number of distributed software tasks in each task group, the execution condition of the task, the type of the server required for executing the task, and the upper limit value of the resource consumed when executing the task. Wherein a task group may include one or more distributed software tasks.
Step S130: and selecting a physical machine according to the task group, and establishing a virtual machine group on the physical machine to complete each task in the task group.
The method specifically comprises the following sub-steps before the physical machine is selected:
step D1: and acquiring task information in the task group.
Step D2: and searching a physical machine corresponding to the task information.
Specifically, since a plurality of servers are integrated on the physical machine, the corresponding physical machine may be selected according to the type of the server required for executing the task in the task information.
After selecting the physical machine, the following substeps are also included:
step P1: starting a certain task group according to the sequence of the tasks.
For example, if task 1 is requested to be started preferentially, the task group in which the task is located is started preferentially.
Step P2: and judging whether the resources required after the task group is started are overloaded or not. If the consumption of the resource exceeds the upper limit of the resource consumed by executing the task in the task information, step P3 is executed. Otherwise, P4 is executed.
Specifically, the resource consumption condition of the server corresponding to the physical machine after the task group is started is calculated, and the actual consumption condition of the server is compared with the upper limit value of the resource consumed when the task is executed in the task information.
Step P3: the physical machine is again selected and step P2 is performed after the physical machine is selected.
Specifically, if it is determined that there is no selectable physical machine, step P5 is executed.
Step P4: the task group is started on the physical machine and step P6 is performed.
Preferably, after the task group is started, the method further includes determining whether the started task group is the last group, and if not, performing step P1, otherwise, performing step P6.
Step P5: a notification is issued that the task group cannot be started.
Furthermore, after the notification is sent, the notification is also sent to split the task, and the task is split into a plurality of subtasks, so that the resource consumption of the server in the task execution process is reduced. The prior art can be referred to for a specific resolution method.
Step P6: and creating a virtual machine group.
Specifically, a virtual machine group is created on a physical machine to complete each distributed software task in a task group. The virtual machine group comprises at least one virtual machine.
The virtual machine group and the tasks included in the task group have a certain corresponding relationship, which may be a priority order of task execution, and specifically, the corresponding relationship may be redistributed after a certain time interval according to the time of task execution.
For example, since one virtual machine group may execute one or more task groups correspondingly, it is necessary to prioritize each task in each task group and select a task that the virtual machine group executes preferentially, and the virtual machine group and the task that executes preferentially have a preferential correspondence relationship.
Specifically, when a virtual machine group is initially used to execute a task, the task in a certain task group may be randomly executed, and after a specified time, the corresponding relationship between the task and the virtual machine group may be modified again, which specifically includes the following steps:
step Q1: and selecting a plurality of tasks in the task group to execute.
Step Q2: a work schedule is created based on historical completion times of tasks in a certain task group.
Preferably, the work schedule may be represented by a matrix, for example, three tasks in a task group, and the work schedule matrix a corresponding to the three tasks may be represented as:
Preferably, the arrangement order in the work schedule matrix may be arranged according to the chronological order of executing the tasks.
Further, the work schedule matrix may also increase the ordering based on the actual number of tasks in the task group.
For example, if there are more than 3 tasks corresponding to the work schedule matrix, it can be expressed as
Wherein the matrix A ═ amnM denotes a row of the matrix and n denotes a column of the matrix.
Step Q2: the execution time that each task ideally needs is calculated.
Specifically, the calculation may be performed based on the time in the work schedule.
In particular to a method for preparing a high-performance nano-silver alloy,
wherein t ismRepresents the minimum time required for task 1, m represents a row in the matrix, n represents a column in the matrix, t represents a column in the matrixm1Representing the value of the first column in the mth row in the matrix, k representing the number of tasks included in the task group, tn2A value representing the second number in the nth column of the matrix, min { t }mnDenotes the smallest value in m rows and n columns.
Indicates that n ≠ m, t is always set for any integer n, mmkRepresenting the value of the mth row and the kth column.
By the above formula, the execution time required to execute each of the three tasks can be calculated. The three tasks are sequenced according to the required execution time, the task with the least time consumption has a preferential corresponding relation with the virtual machine set, and can be preferentially executed in the virtual machine set.
For example, if the execution time of task 1 is 28 minutes, the execution time of task 2 is 30 minutes, and the execution time of task 3 is 40 minutes, task 1 and the virtual machine group are set to have the first corresponding relationship, task 1 is preferentially executed, and task 2 and task 3 can be executed respectively after task 1 is executed.
The present application further includes a system for providing distributed software task allocation, the system has a structure of a general server, as shown in fig. 2, the management system for distributed software backup includes a physical machine 201, a task group 202, and a virtual machine group 203, where the physical machine 201 runs a distributed software 204, the distributed software 204 includes distributed software tasks (not shown in the figure), and the task group 202 is used for planning and managing one or more tasks included in a plurality of distributed software. The virtual machine group 203 is used to execute one or more tasks in the task group 202, and the processors on the system execute the method of distributed software task assignment as described above, which is stored on the storage medium of the system in the form of computer instructions.
The application has the following beneficial effects:
(1) the method and the system for distributing the distributed software tasks can select the corresponding physical machine and the server thereof according to the tasks in the distributed software effectively, and the physical machine is not selected randomly to execute the tasks, so that the resource consumption of the physical machine and the server thereof is reduced, and the normal operation of the distributed software is ensured.
(2) The distributed software task allocation method and the distributed software task allocation system can establish the virtual machine group in the physical machine to complete the execution of the tasks, and can revise the corresponding relation between the virtual machine group and the tasks at the specified time interval, thereby ensuring the effectiveness of the task execution and improving the speed of the task execution.
Although the present application has been described with reference to examples, which are intended to be illustrative only and not to be limiting of the application, changes, additions and/or deletions may be made to the embodiments without departing from the scope of the application.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (7)
1. A distributed software task allocation method is characterized by specifically comprising the following steps:
responding to the starting of the distributed software, and establishing a distributed software task;
establishing at least one task group according to the distributed software tasks;
selecting a physical machine according to the task group, and establishing a virtual machine group on the physical machine to complete each task in the task group;
before executing tasks by using the virtual machine, the method further comprises the following substeps:
selecting a plurality of tasks in the task group to execute;
creating a work schedule according to historical completion time of tasks in a certain task group;
calculating the execution time required by each task under the ideal condition;
the working schedule is expressed by a matrix, and if a plurality of tasks exist, the working schedule matrix A is expressed as
a11…a13Representing the historical time of completion of task 1 in the task group, am1…amnRepresenting the historical time of the completion of the last task in the task group, wherein a is a constant, m represents a row in the matrix A, and n represents a column in the matrix A;
in which the execution time required by each task in the ideal case is counted according to the time in the working scheduleComputing and executing time tmIs particularly shown as
Wherein t ismRepresents the minimum time required for task 1, m represents a row in the matrix, n represents a column in the matrix, t represents a column in the matrixm1Representing the value of the first column in the mth row in the matrix, k representing the number of tasks included in the task group, tn2A value representing the second number in the nth column of the matrix, min { t }mnDenotes the smallest value in m rows and n columns,
indicates that n ≠ m, t is always set for any integer n, mmkRepresenting the value of the mth row and the kth column.
2. The method for distributed software task distribution according to claim 1, wherein the distributed software tasks are established according to the type of the distributed software and the tasks included in the corresponding distributed software, and the distributed software tasks include at least one task.
3. A method of distributed software task distribution as claimed in claim 2, wherein a plurality of tasks exceeding a specified traffic volume are distributed within the same distributed software task.
4. The method for distributed software task distribution according to claim 1, wherein the establishment of the task group is performed according to task information contained in the distributed software tasks.
5. The method for distributing the software tasks according to claim 4, wherein the task information includes the number of task groups required by the distributed software tasks, the number of the distributed software tasks in each task group, the execution condition of the tasks, the type of the server required for executing the tasks, and the upper limit value of the resources consumed in executing the tasks.
6. The method for distributed software task distribution according to claim 4, further comprising, before selecting a physical machine based on the task group, the substeps of:
acquiring task information in a task group;
and searching a physical machine corresponding to the task information.
7. A distributed software task allocation system is characterized by having a structure of a universal server, and specifically comprising a physical machine, a task group and a virtual machine group;
the physical machine runs distributed software, and the distributed software comprises distributed software tasks;
a task group for planning and managing one or more tasks included in the plurality of distributed software;
the virtual machine set executes one or more tasks in the task group;
a processor of a system performing a method of distributed software task distribution as claimed in any one of claims 1 to 6, the method being in the form of computer instructions stored on a storage medium of the system.
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