CN117076073A - Task scheduling method, system, computer equipment and readable storage medium - Google Patents
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- 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
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Abstract
The application relates to the field of task scheduling of financial science and technology, in particular to a task scheduling method, a task scheduling system, computer equipment and a readable storage medium, wherein the method is applied to a data management system and comprises the following steps: periodically counting the access times of each application in the system; acquiring an information table of each task, a corresponding table access amount and application information of each application; obtaining the task importance of each task based on the access times, the information table, the table access amount and the application information; and scheduling the tasks successively based on the importance of the tasks. The application can improve the task scheduling efficiency on the premise of not increasing the number of nodes.
Description
Technical Field
The present application relates to the field of task scheduling in financial technology, and in particular, to a task scheduling method, system, computer device, and readable storage medium.
Background
In the field of financial science and technology, a large number of financial consumption data tasks need to be executed every day, but existing schemes are mostly aimed at completing more tasks as much as possible by reasonable arrangement with fewer nodes, so that the number of nodes in a consumption data cluster is limited. However, with the expansion of functions and applications, consumption tasks are gradually increased, and further, the situation that task scheduling resources are insufficient often occurs, so that the efficiency of processing the whole consumption data task is greatly reduced. Therefore, a method for improving task scheduling efficiency without increasing the number of nodes is needed.
Disclosure of Invention
In view of the foregoing, the present application proposes a task scheduling method, system, computer device, and readable storage medium.
The embodiment of the application provides a task scheduling method, which is applied to a data management system and comprises the following steps:
periodically counting the access times of each application in the system;
acquiring an information table of each task, a corresponding table access amount and application information of each application;
obtaining the task importance of each task based on the access times, the information table, the table access amount and the application information;
and scheduling the tasks successively based on the importance of the tasks.
Further, in the task scheduling method, the application information includes an application level; the information table comprises the association relation between the corresponding task and the application of which the task is scheduled, and the data quantity which needs to be processed by the corresponding task.
Further, in the task scheduling method, the application level corresponds to a level coefficient, the table access amount corresponds to an access amount coefficient, the access number corresponds to an access number coefficient, and the data amount corresponds to a data amount coefficient; the obtaining the task importance of each task based on the access times, the information table, the table access amount and the application information includes:
and obtaining the task importance of each task based on the access times, the access times coefficient, the application level, the level coefficient, the table access quantity, the access quantity coefficient, the data quantity and the data quantity coefficient.
Further, in the task scheduling method, when one task is associated with only one application, a formula for calculating the importance of the task is:
Q＝c*C+y*Y+f*F-s*S；
wherein Q is the task importance of the task, C is the access times of the application corresponding to the task, C is the access times coefficient of the access times, Y is the application grade corresponding to the task, Y is the grade coefficient of the application grade, F is the table access volume corresponding to the task, F is the access volume coefficient of the table access volume, S is the data volume corresponding to the task, and S is the data volume coefficient of the data volume.
Further, in the task scheduling method, when one task is associated with a plurality of applications, a formula for calculating the importance of the task is:
Q＝(∑c i C i )/n+(∑y i *Y i )/n+f*F-s*S；
wherein Q is the importance of the task, C i C, for the access times of the application i corresponding to the task i For the access number coefficient of application i, Y i Application class, y, for application i corresponding to the task i For the class coefficient of the application i, F is the table access quantity corresponding to the task, F is the access quantity coefficient of the table access quantity, S is the data quantity corresponding to the task, S is the data quantity coefficient of the data quantity, n is the association of the task and n applications, and n is a positive integer greater than 1.
Further, in the task scheduling method, the scheduling the tasks based on the task importance sequentially includes:
forming a task ordering table according to the importance of each task;
and when the task scheduling resources are insufficient, sequentially scheduling corresponding tasks from the high importance level to the low importance level of the tasks according to the task ordering table.
Further, in the task scheduling method, the period is daily, and the periodically counting the number of accesses by each application in the system includes:
the number of accesses by each application within the system within one period is counted at a preset time of day.
Another embodiment of the present application further provides a task scheduling system, which is applied to a data management system, including:
a statistics unit, configured to periodically count the number of accesses by each application in the system;
the acquisition unit is used for acquiring an information table of each task, a corresponding table access amount and application information of each application;
the computing unit is used for obtaining the task importance of each task based on the access times, the information table, the table access quantity and the application information;
and the scheduling unit is used for scheduling the tasks successively based on the importance of the tasks.
Another embodiment of the present application also proposes a computer device, including a storage unit and a processing unit, where the storage unit stores a computer program, and the processing unit executes the steps of the task scheduling method described above by calling the computer program stored in the storage unit.
Another embodiment of the present application also proposes a computer readable storage medium storing a computer program adapted to be loaded by a processor for performing the steps of the task scheduling method described above.
The embodiment of the application has the following beneficial effects:
the embodiment of the application provides a task scheduling method, which comprises the steps of periodically counting the access times of each application in a system, obtaining an information table of each task, a corresponding table access amount and application information of each application according to the access times, obtaining the task importance of each task, and finally scheduling the tasks successively according to the task importance. By quantifying importance of each task according to multiple dimensions, determining execution sequence of the tasks according to the quantified importance of the tasks, and preferentially processing important tasks under the condition that resources are insufficient in task scheduling, efficiency of whole task scheduling is improved, and a direction is provided for transformation of a follow-up scheduling system.
Drawings
In order to more clearly illustrate the technical solutions of the present application, the drawings that are required for the embodiments will be briefly described, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope of the present application. Like elements are numbered alike in the various figures.
FIG. 1 illustrates a first flow diagram of a task scheduling method according to some embodiments of the application;
FIG. 2 illustrates a second flow diagram of a task scheduling method according to some embodiments of the application;
FIG. 3 illustrates a task importance ranking representation intent of a task scheduling method of some embodiments of the present application;
FIG. 4 illustrates a first architectural diagram of a task scheduling system according to some embodiments of the present application;
fig. 5 illustrates a second architectural diagram of a task scheduling system according to some embodiments of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments.
The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
The terms "comprises," "comprising," "including," or any other variation thereof, are intended to cover a specific feature, number, step, operation, element, component, or combination of the foregoing, which may be used in various embodiments of the present application, and are not intended to first exclude the presence of or increase the likelihood of one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing.
Furthermore, the terms "first," "second," "third," and the like are used merely to distinguish between descriptions and should not be construed as indicating or implying relative importance.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which various embodiments of the application belong. The terms (such as those defined in commonly used dictionaries) will be interpreted as having a meaning that is the same as the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein in connection with the various embodiments of the application.
Some embodiments of the present application are described in detail below with reference to the accompanying drawings. The embodiments described below and features of the embodiments may be combined with each other without conflict.
Generally, with the continuous expansion of the system, the improvement of functions and the increase of the number of users increase the daily consumption of tasks, so that the situation that resources are insufficient when the system performs task scheduling is increased, and the situation that the whole task scheduling process is low in efficiency is caused.
Accordingly, in order to solve the above-mentioned problems, the present application provides a task scheduling method applicable to the fields of financial science and technology and other related fields.
Referring to fig. 1, a flow chart of a task scheduling method according to an embodiment of the application is shown. The task scheduling method is exemplarily applied to a related system in the financial and technological field, for example, the system may be a credit card data processing system, a commodity purchase data processing system, etc.
In some embodiments, as shown in fig. 1, the task scheduling method is applied to a data management system, and the method includes:
s110, periodically counting the access times of each application in the system.
Specifically, the data management system includes a plurality of applications, such as knowledge base construction, information release, information security, etc., each of which is accessed by an object external to the data management system, where the external object may be a user side or another system in data communication with the data management system. When an external object accesses an application in a data management system once, an access request is generated, the system counts the access times according to the received access request, and besides each application in the access data management system, all the access requests corresponding to all the systems downstream of the access request for accessing a certain application are counted, and the counted access times belong to the access times corresponding to the application.
For example, if the data management system includes the application a and the application B, the access requests of the access application a are 3 access requests a, an access request a1 and an access request a2, where the access request a is a request of the access application a, the access request a1 is an access request of the system 1 downstream of the access request a, and the access request a2 is an access request of the system 2 downstream of the access request a, so the number of access times of the application a is counted to be 3.
In addition, the periodic statistics means statistics once per period, and the period may be every several hours, every day or every several days, or may be one week, etc., which is not limited herein.
In the task scheduling method of some embodiments, the period is daily, and the periodically counting the access times of each application inside the system includes:
the number of accesses by each application within the system within one period is counted at a preset time of day.
Specifically, if the period is daily, statistics is started at a preset time of each day, that is, the statistics time range is the same time of the previous day to the corresponding access times of each application within the same time of the current day, and the access times counted at the preset time are used as the basis for managing task scheduling in the current period.
For example, if the existing application C and application D are now 20 # for a certain month, assuming that the preset time is 1 am (i.e. 1 am of 20 #), the number of accesses of application C and application D between 1 am of 19 # and 1 am of 20 # should be counted. And then taking the access times counted in the 1 st early morning of 20 as the basis for managing task scheduling in the time period from the 1 st early morning of 20 to the 1 st early morning of 21.
S210, acquiring an information table of each task, a corresponding table access amount and application information of each application.
Specifically, each task (job) corresponds to an information table, and the information table includes a table name, a correlation coefficient of the corresponding task, an association relationship between the corresponding task and an application to which the task is scheduled, and an amount of data to be processed by the corresponding task. The application information comprises data such as application level, application name, application positioning, application responsible person and the like.
Illustratively, applications M, N and W exist, task job1, task job2 and task job3, while application M needs to call task job1 and task job2, application N needs to call task job3, application W needs to call task job2 and task job3. The information table corresponding to the task job1 comprises an association relation with the application M; the information table corresponding to the task job2 comprises an association relation between the application M and the application W; the information table corresponding to the task job3 includes an association relationship with the application N and the application W.
S310, obtaining the importance degree of each task based on the access times, the information table, the table access quantity and the application information.
In particular, since each task involves and is associated with a lot of data during the call, it is a particularly complex matter to calculate the importance of each task, taking into account a number of factors. The number of accesses is required in this embodiment because the higher the number of accesses, the more the application represents the user affected by the application, and the more priority is required. The association relationship in the information table determines how many applications the task corresponding to the information table is associated with, so that the importance level of the task needs to be determined according to the association relationship. The table access amount represents the number of times the information table is accessed, that is, the table access amount of the information table (the number of times the information table is accessed) represents the number of times the task corresponding to the information table is called. The application level in the application information represents the importance degree of the application, and the importance degree of each application is different due to the large number of applications in the data management system, and some application importance courses are very high, so that the importance degree of the task corresponding to the application is also high. The importance degree of the application can be preset and set at first and can be changed at any time, the access times, the table access amount and other data are periodically counted according to actual conditions and change along with time, so that the counted data are more real, and the importance degree for calculating each task is more accurate. It should be considered that the shorter the period is, the farther the data deviates from the real data, because the data in a short time is not referenced, but the longer the period is, the more the calculated importance of the task can represent the actual importance of the task, but only the calculated importance of the task can represent that the task is in the period (long period), but the calculated importance of the task is not applicable to each short period, because the application of each month is updated continuously, and the user in use is changed continuously, the called task is changed continuously, so that the importance of the current task can be reflected more accurately by selecting the appropriate period, and the priority period is daily, of course, the scheme in the embodiment is applied to different scenes, and the corresponding data rule is different, so that the selected period can be changed accordingly, and the method is not limited.
In addition, it should be noted that, in this embodiment, the table access amount is actually covered by the number of accesses, but here, the table access amount is purposely taken out to participate in the calculation, because some other systems do not access the information table through an application in the data processing system, but these access to the information table through other manners are often not core functions, so the importance degree corresponding to the target access amount is not high.
In the task scheduling method of some embodiments, a level coefficient, a table access amount coefficient, an access number coefficient, a data amount coefficient, and a data amount coefficient are applied; based on the access times, the information table, the table access amount and the application information, obtaining the task importance of each task, including:
and obtaining the task importance of each task based on the access times, the access times coefficient, the application level, the level coefficient, the table access quantity, the access quantity coefficient, the data quantity and the data quantity coefficient.
Specifically, in addition to the access times, the information table, the table access amount and the data corresponding to the application information, in order to make the finally calculated task importance closer to the actual situation and more accurate, the present embodiment further increases the access times, the information table, the table access amount and the coefficient corresponding to the application information, and is used for adjusting the weight occupied by each data. The data amount represents the number of lines of data required in the processing process of the corresponding task, and the more the data amount is, the longer the time required for processing the task is.
In the task scheduling method of some embodiments, when a task is associated with only one application, the formula for calculating the importance of the task is:
Q＝c*C+y*Y+f*F-s*S；
wherein Q is the task importance of the task, C is the access times of the application corresponding to the task, C is the access times coefficient of the access times, Y is the application grade corresponding to the task, Y is the grade coefficient of the application grade, F is the table access volume corresponding to the task, F is the access volume coefficient of the table access volume, S is the data volume corresponding to the task, and S is the data volume coefficient of the data volume.
Specifically, some applications call a plurality of tasks, and some applications call one task, so that under the complex call relationship, some tasks are called by only one application, and some tasks are called by a plurality of applications, and therefore, the embodiment distinguishes the two situations and gives different calculation formulas of the importance of the tasks respectively. The reason for subtracting the data amount is that tasks with small data amount need to be processed preferentially, and tasks with large data amount are processed later, so that important tasks with small data amount are not processed when more time is spent processing tasks with large data amount. This disadvantage is more pronounced in the case of several tasks of equal importance, for example if task V1, task V2 and task V3 are of equal importance, the time taken by task V1 is greater than the sum of the time taken by task V2 and task V3, and it is of course optimal to process more tasks in as much time.
Exemplarily, if a task is associated with the application Q, the number of accesses counted by the application Q in the period is 200, and the number of accesses coefficient c is 1.2; the application level of the application Q is 10 (the larger the number is, the higher the representative level is, the higher the importance degree is), and the application level coefficient y is 3; the table access amount F corresponding to the task in the period is 220, the access amount coefficient F is 0.4, the data amount corresponding to the task is 10, the corresponding data amount coefficient s is 0.5, and finally the calculated task importance Q is 353.
In the task scheduling method of some embodiments, when one task is associated with a plurality of applications, a formula for calculating importance of the task is:
Q＝(∑c i C i )/n+(∑y i *Y i )/n+f*F-s*S；
wherein Q is the importance of the task, C i C, for the access times of the application i corresponding to the task i For the access number coefficient of application i, Y i Application class, y, for application i corresponding to the task i For the class coefficient of application i, F is the table access amount corresponding to the task, F is the access amount coefficient of the table access amount, S is the data amount corresponding to the task, S is the data amount coefficient of the data amount, n is the association of the task and n applications, and n is a positive integer greater than 1.
Specifically, part of the tasks are associated by a plurality of applications, so if the tasks are accumulated to represent the importance degree, the importance degree is pulled too high, and thus the embodiment calculates by acquiring the average value of the data corresponding to the plurality of associated applications.
Exemplary, if a task is associated with application H, application J, and application K, the number of accesses counted by application H in the period is 200, and the access number coefficient c is 1.2; the access times counted by the application J in the period are 120 times, and the access times coefficient c is 1.2; the access times counted by the application K in the period are 230 times, and the access times coefficient c is 1.2. The application grade of the application H is 10, and the application grade coefficient y is 3; application ofThe application grade of J is 6, and the application grade coefficient y is 3; the application class of application K is 7 and the application class coefficient y is 3. The table access amount F corresponding to the task in the period is 600, the access amount coefficient F is 0.1, the data amount corresponding to the task is 4, and the corresponding data amount coefficient s is 0.5. Then n is 3 and Σc is obtained i C i ＝200*1.2+120*1.2+230*1.2＝660，∑y i *Y i =10×3+6×3+7×3=69, and the task importance Q calculated last is 301.
S410, scheduling the tasks successively based on the importance of the tasks.
In some embodiments of the task scheduling method, as shown in fig. 2, the task scheduling method sequentially schedules the task based on the importance degree of the task, including:
s411, forming a task ordering table according to the importance of each task.
And S412, when the task scheduling resources are insufficient, scheduling corresponding tasks in sequence from high importance to low importance according to the task ordering table.
Specifically, each task is ordered according to the importance of the task, as shown in fig. 3, from large to small, or from small to large, which is not limited herein. When the task scheduling resources are insufficient, tasks with high importance of the tasks are processed preferentially, and then tasks with low importance of the tasks are processed sequentially. The task scheduling resource is insufficient, and in the running process of the computer, because the supply and demand of system resources (mainly memory) required by program execution are unbalanced, the memory is insufficient, and further the problems of system blocking, program crash and the like occur.
In addition, the present application also proposes a system architecture, as shown in fig. 4, where the data processing system 500 of the present application includes a statistical CMS subsystem 510, a CAT subsystem 520, a storage subsystem 530, and a scheduling subsystem 540. The external system other performs task scheduling by accessing applications in the CMS subsystem 510. First, the external system other sends 510 an access request to the CMS subsystem, where the request includes an application name that needs to be accessed, and the CMS subsystem 510 obtains, from the storage subsystem 530, an information table and a table access amount corresponding to the access request through the application access name. Wherein the storage subsystem 530 stores information (e.g., information table, table access amount, access source, etc.) related to each task; the scheduling subsystem 540 stores an execution program of each task (corresponding data is written into the storage subsystem 530 when the task in the scheduling subsystem executes), and when the task needs to be scheduled, the scheduling subsystem 540 is directly accessed to schedule the corresponding task. The statistics CAT subsystem 520 will keep statistics of the access requests of the external system other to the CMS subsystem 510 at all times.
The embodiment of the application provides a task scheduling method, which comprises the steps of periodically counting the access times of each application in a system, obtaining an information table of each task, a corresponding table access amount and application information of each application according to the access times, obtaining the task importance of each task, and finally scheduling the tasks successively according to the task importance. By quantifying importance of each task according to multiple dimensions, determining execution sequence of the tasks according to the quantified importance of the tasks, and preferentially processing important tasks under the condition that resources are insufficient in task scheduling, efficiency of whole task scheduling is improved, and a direction is provided for transformation of a follow-up scheduling system.
In addition, in the application, the coefficient corresponding to each calculated data is increased, so that the weight occupied by the corresponding data can be adjusted at any time, for example, the application adjusts the data quantity parameter corresponding to the data quantity to the minimum, because the occupied importance degree is less important than other data, but in order to make the scheme more optimal, the application also needs to be used in order to improve the efficiency in the task scheduling process.
Another embodiment of the present application further proposes a task scheduling system, applied to a data management system 600, as shown in fig. 5, the system 600 includes:
a statistics unit 610, configured to periodically count the number of accesses by each application in the system.
The acquiring unit 620 is configured to acquire an information table of each task, a corresponding table access amount, and application information of each application.
The computing unit 630 is configured to obtain a task importance of each task based on the access times, the information table, the table access amount, and the application information.
And a scheduling unit 640 for scheduling the tasks successively based on the importance of the tasks.
Another embodiment of the present application also provides a computer device, including a storage unit and a processing unit, where the storage unit stores a computer program, and the processing unit executes the steps of the task scheduling method by calling the computer program stored in the storage unit.
Another embodiment of the present application also proposes a computer readable storage medium storing a computer program adapted to be loaded by a processor for performing the steps of the task scheduling method described above.
It will be appreciated that the method steps of the present embodiment correspond to the task scheduling method in the above embodiment, and that the options of the task scheduling method described above are equally applicable to the present embodiment, and will not be repeated here.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The apparatus embodiments described above are merely illustrative, for example, of the flow diagrams and block diagrams in the figures, which illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules or units in various embodiments of the application may be integrated together to form a single part, or the modules may exist alone, or two or more modules may be integrated to form a single part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a smart phone, a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application.
Claims (10)
1. A task scheduling method, applied to a data management system, comprising:
periodically counting the access times of each application in the system;
acquiring an information table of each task, a corresponding table access amount and application information of each application;
obtaining the task importance of each task based on the access times, the information table, the table access amount and the application information;
and scheduling the tasks successively based on the importance of the tasks.
2. The task scheduling method of claim 1, wherein the application information includes an application level; the information table comprises the association relation between the corresponding task and the application of which the task is scheduled, and the data quantity which needs to be processed by the corresponding task.
3. The task scheduling method according to claim 2, wherein the application level corresponds to a level coefficient, the table access amount corresponds to an access amount coefficient, the access number corresponds to an access number coefficient, and the data amount corresponds to a data amount coefficient; the obtaining the task importance of each task based on the access times, the information table, the table access amount and the application information includes:
and obtaining the task importance of each task based on the access times, the access times coefficient, the application level, the level coefficient, the table access quantity, the access quantity coefficient, the data quantity and the data quantity coefficient.
4. A task scheduling method according to claim 3, wherein when one of the tasks is associated with only one of the applications, then the formula for calculating the importance of the task is:
Q＝c*C+y*Y+f*F-s*S；
wherein Q is the task importance of the task, C is the access times of the application corresponding to the task, C is the access times coefficient of the access times, Y is the application grade corresponding to the task, Y is the grade coefficient of the application grade, F is the table access volume corresponding to the task, F is the access volume coefficient of the table access volume, S is the data volume corresponding to the task, and S is the data volume coefficient of the data volume.
5. A task scheduling method according to claim 3, wherein when one of the tasks is associated with a plurality of the applications, a formula for calculating importance of the task is:
Q＝(∑c i C i )/n+(∑y i *Y i )/n+f*F-s*S；
wherein Q is the importance of the task, C i C, for the access times of the application i corresponding to the task i For the access number coefficient of application i, Y i Application class, y, for application i corresponding to the task i For the class coefficient of the application i, F is the table access quantity corresponding to the task, F is the access quantity coefficient of the table access quantity, S is the data quantity corresponding to the task, S is the data quantity coefficient of the data quantity, n is the association of the task and n applications, and n is a positive integer greater than 1.
6. The task scheduling method according to claim 1, wherein the scheduling the tasks sequentially based on the task importance degree includes:
forming a task ordering table according to the importance of each task;
and when the task scheduling resources are insufficient, sequentially scheduling corresponding tasks from the high importance level to the low importance level of the tasks according to the task ordering table.
7. The task scheduling method according to claim 1, wherein the period is daily, and the periodically counting the number of accesses by each application inside the system includes:
the number of accesses by each application within the system within one period is counted at a preset time of day.
8. A task scheduling system, for use in a data management system, comprising:
a statistics unit, configured to periodically count the number of accesses by each application in the system;
the acquisition unit is used for acquiring an information table of each task, a corresponding table access amount and application information of each application;
the computing unit is used for obtaining the task importance of each task based on the access times, the information table, the table access quantity and the application information;
and the scheduling unit is used for scheduling the tasks successively based on the importance of the tasks.
9. A computer device comprising a storage unit in which a computer program is stored and a processing unit that performs the steps of the task scheduling method according to any one of claims 1 to 7 by calling the computer program stored in the storage unit.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program adapted to be loaded by a processor for performing the steps of the task scheduling method according to any one of claims 1 to 7.
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