CN117149389A - Distributed job scheduling method, device, equipment and medium - Google Patents
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Abstract
The application discloses a distributed job scheduling method, a device, equipment and a medium, and relates to the field of big data or finance. The method comprises the following steps: acquiring an operation with an operable operation type from an operation driving relation table; and executing distributed job scheduling according to a scheduling strategy based on the driving mode of the executable job. Therefore, according to the driving mode set by the job correspondence, the job scheduling such as report processing is scientifically, uniformly and comprehensively performed on the business data according to the scheduling strategy, so that the timeliness of the report data processing is ensured, and the exertion of the digital data asset value of the bank is ensured.
Description
Technical Field
The present application relates to the field of big data or finance, and in particular, to a distributed job scheduling method, apparatus, device, and medium.
Background
With the increase of the number of foreign banks, a domestic and foreign bank system distributed architecture taking domestic general banks as a management center is formed, and the distributed architecture enables all domestic and foreign bank system nodes to be independent.
However, since domestic banks and foreign banks are usually in different time zones, the foreign banks cannot be seamlessly connected in the process of performing job scheduling such as report processing according to service data sent by the domestic banks, and it is also difficult for a certain foreign bank to receive service data of a plurality of banks in different time zones at the same time. Therefore, timeliness of report data processing is affected, and exertion of bank digital data asset value is also affected.
Disclosure of Invention
The embodiment of the application provides a distributed job scheduling method, a device, equipment and a medium, which can ensure the timeliness of report data processing and the exertion of the digital data asset value of a bank.
The embodiment of the application discloses the following technical scheme:
in a first aspect, the present application provides a distributed job scheduling method, the method including:
acquiring an operation with an operable operation type from an operation driving relation table;
and executing distributed job scheduling according to a scheduling strategy based on the driving mode of the executable job.
Optionally, before the job with the executable job type is acquired in the job driving relation table, the method further includes:
constructing parameter table information according to report batch processing operation in a banking system;
constructing a job scheduling model;
and maintaining the parameter table information according to the job scheduling model to obtain a parameter table, wherein the parameter table comprises a job driving relation table.
Optionally, the report batch processing job includes one or more of a banking system job name, a dependency relationship, a time zone area in which the job is located, a file dependency relationship, whether a holiday is involved, a job period, a job type, and a program name to which the job is involved.
Optionally, the executing distributed job scheduling according to a scheduling policy based on the driving manner of the executable job includes:
judging whether the operable job is in a false diary or not;
if not, based on the driving mode of the executable job, executing distributed job scheduling according to a scheduling strategy.
Optionally, the method further comprises:
and monitoring the distributed job scheduling process.
In a second aspect, the present application provides a distributed job scheduling apparatus, the apparatus comprising: the device comprises an acquisition module and an execution module;
the acquisition module is used for acquiring the operation with the operable operation type in the operation driving relation table;
and the execution module is used for executing distributed job scheduling according to a scheduling strategy based on the driving mode of the executable job.
Optionally, the apparatus further includes: the first building module, the second building module and the third building module;
the first construction module is used for constructing parameter table information according to report batch processing operation in the banking system;
the second construction module is used for constructing a job scheduling model;
the third construction module is configured to maintain the parameter table information according to the job scheduling model to obtain a parameter table, where the parameter table includes a job driving relationship table.
Optionally, the report batch processing job includes one or more of a banking system job name, a dependency relationship, a time zone area in which the job is located, a file dependency relationship, whether a holiday is involved, a job period, a job type, and a program name to which the job is involved.
Optionally, the execution module specifically includes: the first execution sub-module and the second execution sub-module;
the first execution sub-module is used for judging whether the executable job is in a false daily list or not;
and the second construction submodule is used for executing distributed job scheduling according to a scheduling strategy based on the driving mode of the executable job if not.
Optionally, the apparatus further includes: a monitoring module;
and the monitoring module is used for monitoring the distributed job scheduling process.
In a third aspect, the present application provides a distributed job scheduling apparatus, comprising: a memory and a processor;
the memory is used for storing programs;
the processor is configured to implement the steps of the distributed job scheduling method when executing the computer program.
In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the above-described distributed job scheduling method.
Compared with the prior art, the application has the following beneficial effects:
the application discloses a distributed job scheduling method, a device, equipment and a medium, wherein the method comprises the following steps: acquiring an operation with an operable operation type from an operation driving relation table; and executing distributed job scheduling according to a scheduling strategy based on the driving mode of the executable job. Therefore, according to the driving mode set by the job correspondence, the job scheduling such as report processing is scientifically, uniformly and comprehensively performed on the business data according to the scheduling strategy, so that the timeliness of the report data processing is ensured, and the exertion of the digital data asset value of the bank is ensured.
Drawings
In order to more clearly illustrate this embodiment or the technical solutions of the prior art, the drawings that are required for the description of the embodiment or the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a distributed report processing procedure according to an embodiment of the present application;
FIG. 2 is a flowchart of a distributed job scheduling method according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a background job scheduling model according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a front-end job scheduling model according to an embodiment of the present application;
FIG. 5 is a schematic diagram of a scheduling policy according to an embodiment of the present application;
FIG. 6 is a schematic diagram of another scheduling policy according to an embodiment of the present application;
fig. 7 is a deployment architecture diagram of a distributed job scheduling device according to an embodiment of the present application;
FIG. 8 is a schematic diagram of a distributed job scheduling apparatus according to an embodiment of the present application;
FIG. 9 is a schematic diagram of a computer readable medium according to an embodiment of the present application;
fig. 10 is a schematic hardware structure of a server according to an embodiment of the present application.
Detailed Description
With the increase of the number of foreign banks, a domestic and foreign bank system distributed architecture taking domestic general banks as a management center is formed, and the distributed architecture enables all domestic and foreign bank system nodes to be independent.
However, since domestic banks and foreign banks are usually in different time zones, the foreign banks cannot be seamlessly connected in the process of performing job scheduling such as report processing according to service data sent by the domestic banks, and it is also difficult for a certain foreign bank to receive service data of a plurality of banks in different time zones at the same time. Therefore, timeliness of report data processing is affected, and exertion of bank digital data asset value is also affected.
In view of this, the present application provides a distributed job scheduling method, apparatus, device and medium, where the method includes: acquiring an operation with an operable operation type from an operation driving relation table; and executing distributed job scheduling according to a scheduling strategy based on the driving mode of the executable job. Therefore, according to the driving mode set by the job correspondence, the job scheduling such as report processing is scientifically, uniformly and comprehensively performed on the business data according to the scheduling strategy, so that the timeliness of the report data processing is ensured, and the exertion of the digital data asset value of the bank is ensured.
In order to make the present application better understood by those skilled in the art, the following description will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be noted that the distributed job scheduling method, device, equipment and medium provided by the application can be used in the big data field or the financial field. The foregoing is merely an example, and the application fields of the distributed job scheduling method, the device, the equipment and the medium provided by the present application are not limited.
It is understood that a job refers to all applications that can be scheduled by a job control process. The job control process refers to a process of scheduling the job according to a set driving relationship to realize automatic loading when the service data is loaded and circulated in each level. Illustratively, report processing is a job control process. For ease of understanding, the following description will be given with respect to report processing as an example.
Referring to fig. 1, a schematic diagram of a distributed report processing procedure according to an embodiment of the present application is shown. After data acquisition, the complete distributed report processing process needs to execute links of the total line business system for downloading text processing, processing the common indexes of the data lake, storing total line report data of a total line report processing platform and storing the characteristic line reports of a characteristic line report processing platform. To manage the comprehensive centralized scheduling of the multi-time zone distributed report processing batch job, a distributed job scheduling method is constructed to perform omnibearing management by starting from each link.
Referring to fig. 2, a flowchart of a distributed job scheduling method according to an embodiment of the present application is shown. The method comprises the following steps:
s201: and acquiring a job driving relation table.
Firstly, all reports related to strong dependency relationships in a bank system need to be combed to process batch jobs. For example, the report processing batch job may include contents such as a job name of a banking system, a dependency relationship, a time zone area in which the dependency relationship is located, a file dependency relationship, whether a holiday is involved, a job period, a job type, a program name (including a program developer) involved in the job, and the like, and based on the report processing batch job, various parameter table information may be constructed to prepare for subsequent parameter import or maintenance.
And then, designing a job scheduling model, and maintaining the parameter table information according to the job scheduling model to acquire a parameter table. By way of example, the parameter table may include one or more of a holiday code, a curve code table, a node area comparison table, a job driving relationship table, and a download file control information table.
It should be noted that, the present application is not limited to a specific report processing batch job and parameter table.
In some specific implementations, a background job scheduling model and a front job scheduling model may be respectively constructed according to the difference between the background parameter table information and the front parameter table information, and the background parameter table information and the front parameter table information may be respectively maintained according to the background job scheduling model and the front job scheduling model. Specifically, the background job scheduling model is mainly a database table deployed on a database server and a job control server, and is a report processing batch job of the whole banking system, and information control tables of report batch processing conditions of all levels are used for unified control. The front-end job scheduling model is mainly a database table required by front-end management application scenes of each hierarchical organization, and is a database table facing a front-end interface so as to manage information input by a front-end user.
Referring to fig. 3, the diagram is a schematic diagram of a background job scheduling model according to an embodiment of the present application. For example, the parameter table acquired by maintaining the parameter table information by the background scheduling model may include: a job false daily table, a job return value table, a region code table, a job running detailed log table, a job running state table, a job running log table, a node region comparison table, a job driving relation table, a download file control information table and the like.
Referring to fig. 4, a schematic diagram of a front-end job scheduling model according to an embodiment of the present application is shown. Illustratively, the parameter table obtained by maintaining parameter table information by the front-end job scheduling model may include: user behavior log table, user information table, user role corresponding relation table, import and export configuration table, program type table, role information table, decision area comparison table, system function table and role function corresponding relation table, etc.
It will be appreciated that the above parameter table information may be imported through an Excel file, or may be manually added by a related technician, which is not limited to the present application.
S202: and selecting the job with the operable job type from the job driving relation table.
After the job driving relationship table is acquired in step S201, first, a job whose job type is operable is selected. Referring to table 1, the table is a job type classification table provided in an embodiment of the present application.
TABLE 1
| R | Actual operation, actual operation |
| V | Virtual job, not actually run |
| ALL_SUC class | Sign type operation |
It should be noted that, the above-mentioned executable job is an R-type job, that is, an actual job, an actually executed job.
It is understood that a virtual job refers to a job defined to satisfy inter-job drive relationship logic that does not require actual execution, and must be a root node job. Virtual jobs and not actually running refer to: the virtual operation is used as an initial root operation, has no leading operation, does not judge the operation state of a decision area, is successfully placed in the system initialization without considering the period and holidays, does not run, and is only used for driving other operations. The leading job refers to a job that must be executed prior to a certain job, that is, a leading job called this job.
It is understood that the marking type job refers to marking that a batch system has been executed in a certain period, the all_suc type job is a flag job, and marks whether the jobs of a certain area are ALL completed, and when setting, each area needs to have a corresponding all_suc type job, and only two states INI (initial) and SUC (successful). The naming convention of the job is all_suc_system name. all_SUC type jobs will not succeed until ALL non-ALL_SUC type jobs and jobs that do not contain ALL_SUC in the preamble are successful.
S203: and executing distributed job scheduling according to a scheduling strategy based on the driving mode of the executable job.
After acquiring the executable job, it is necessary to first determine the driving method of the executable job. Referring to table 2, the table is a driving mode classification table provided in an embodiment of the present application.
TABLE 2
And then, according to different driving modes of the executable jobs, performing distributed job scheduling according to a scheduling strategy. Illustratively, the scheduling policy may include: the plurality of jobs are processed in parallel in accordance with the regional parallel parameters, or the first target job may be processed after the second target job processing is completed, or the like.
For example, if the Job driving method is F-class, for example, F-class driving Job job_f1 of the area 40142, the leading FILE is FILE01|, the determination area is 40142, and when the FILE status of the FILE 40142FILE01| corresponding to the FILE control information table area 40142 is 5000, job_f1 (40142) conforms to the scheduling policy.
For example, if the Job driving method is a type a, for example, the type a driving Job job_a1 of the area 40142, the leading FILE thereof is FILE03, the leading Job is job_j1, and the area is 40142, then the Job job_a1 (40142) conforms to the scheduling policy if and only if the FILE state of the FILE 40142FILE03 corresponding to the FILE control information table area 40142 is 5000, and the Job state of Job job_j1 (40142) is SUC.
For example, if the Job driving method is J-class, for example, J-class driving Job job_j1 of the area 40142, its leading Job is job_f1|job_t1|job_v1|job_b1|, and the area is 40004, if and only if Job states of job_f1 (40142), job_t1 (40142), job_b1 (40142), job_v1 (40142), and job_j1 (40004) are SUC, the present Job job_j1 (40142) conforms to the scheduling policy.
It will be appreciated that in addition to the above-described class T, class J, class B, class a, class F jobs, there is a special job node: a root node. The root node job may be a virtual job, or a job of a job type F, T, B, and is used as a starting job in the running system to drive a subsequent job, and no preceding job is used. The scheduling policy corresponding to the root node is as follows: the virtual operation is successfully set when the system is initialized; if the current period number of the current operation in the current area is holidays or non-period, setting the current operation to be successful in system initialization; other cases operate according to a core driven relationship.
For example, reference may be made to fig. 5, which is a schematic diagram of a scheduling policy provided by an embodiment of the present application. The figure shows the processing logic steps associated with the root node. Referring to fig. 6, a schematic diagram of another scheduling policy according to an embodiment of the present application is shown. The figure illustrates the processing logic steps of a non-root node. It should be noted that, the present application is not limited to a specific scheduling policy.
In one possible implementation, it may also be determined first whether the executable job is in a false daily list. Referring to table 3, the table is a schematic representation of a pseudo daily chart provided in an embodiment of the present application. The function of the false daily watch is to enable a user to set any one job as a holiday, and when the job meets a scheduling policy, the job is not actually scheduled up, but is directly set as successful.
TABLE 3 Table 3
| Sequence number | Job ID | Whether or not it is a holiday | Determination area | Time zone |
| 1 | Job_A1 | 0 | 40142 | 20121001 |
| 2 | Job_A1 | 0 | 40142 | 20121002 |
| 3 | Job_A1 | 0 | 40142 | 20121003 |
As shown in table 3, job job_a1 (40142) can be maintained as holidays in the holiday table as Job 1, 10 month 2, and 10 month 3 in 2012, and then as Job 20121001, 20121002, and 20121003. When the system performs the batch for three days, job_a1 (40142) can be directly successful as long as the leader Job job_j1 (40142) is successful.
It will be appreciated that if the parameter value 0 in the column "whether it is holiday" may indicate that it is not holiday, and the parameter value 1 may indicate that it is holiday, the application is not limited to specific parameter values.
In some specific implementations, during the execution of the distributed job scheduling, the process may also be monitored.
In the monitoring process, the process of suspending the operation may be performed on a certain job or the whole batch job operation condition during the operation as needed. When the batch processing is stopped, the system records the batch processing stopping time, records the processing breakpoint in real time, and updates the information to a background operation detailed log table in real time.
In the monitoring process, the system may restart the stopped batch job, and after restarting, the system may run the rest batch processing job from the record according to the processing breakpoint record recorded in the batch log when stopping the batch.
In another possible implementation manner, the log of the batch job may also be checked, for example, to query running information of the batch job, running time, and job error type query. Specifically, the operation information may include: job name, running status, running area, period number, developer, start time, end time, and detailed information. The runtime may include: program name, region, number of weeks, developer, start time, end time, minutes run, success, etc. The error type details may include: program name, area, number of weeks, detailed error information, etc.
In another possible implementation, the established batch job schedule may also be evaluated and modified according to the batch job schedule operation condition and the resource consumption condition, and the batch scheduling policy may be adjusted and optimized accordingly.
In summary, the embodiment of the application discloses a distributed job scheduling method, which comprises the following steps: acquiring an operation with an operable operation type from an operation driving relation table; and executing distributed job scheduling according to a scheduling strategy based on the driving mode of the executable job. Therefore, according to the driving mode set by the job correspondence, the job scheduling such as report processing is scientifically, uniformly and comprehensively performed on the business data according to the scheduling strategy, so that the timeliness of the report data processing is ensured, and the exertion of the digital data asset value of the bank is ensured.
Referring to fig. 7, the deployment architecture diagram of a distributed job scheduling apparatus according to an embodiment of the present application is shown. The distributed job scheduling device is deployed by adopting a background part and a front end part.
Specifically, the background part adopts global unified and centralized deployment to unify all report processing batch jobs, and comprises a batch job control server and a driving relation database, wherein the batch job control server can be operated by an administrator. The front ends are respectively deployed at a headquarter level and a branching level, and are the front end management application scenes of pigeons of all hierarchical mechanisms. The front-end includes a front-end system server on which operators and developers can perform operations over the network.
It will be appreciated that the batch job control server, the drive relationship database, and the front-end system server all establish a connection with a Connector (Connector) through an application program interface (Application Program Interface, API).
Referring to fig. 8, a schematic diagram of a distributed job scheduling apparatus according to an embodiment of the present application is shown. The distributed job scheduling apparatus 800 includes: an acquisition module 801 and an execution module 802.
Specifically, the acquiring module 801 is configured to acquire, in the job driving relationship table, a job whose job type is operable; an execution module 802, configured to execute distributed job scheduling according to a scheduling policy based on a driving manner of the executable job.
In some possible implementations, the distributed job scheduling apparatus 800 further includes: the first building module, the second building module and the third building module;
specifically, the first construction module is used for constructing parameter table information according to report batch processing operation in the banking system; the second construction module is used for constructing a job scheduling model; and the third construction module is used for maintaining parameter table information according to the job scheduling model to acquire a parameter table, wherein the parameter table comprises a job driving relation table.
In some possible implementations, the report batch job includes one or more of a banking system job name, a dependency, a time zone region in which the job is located, a file dependency, whether holidays are involved, a job period, a job type, and a program name to which the job is related.
In some possible implementations, the execution module 802 specifically includes: the first execution sub-module and the second execution sub-module;
specifically, the first execution submodule is used for judging whether the executable job is in a false japanese or not; and the second construction sub-module is used for executing distributed job scheduling according to a scheduling strategy based on a driving mode of the executable job if not.
In some possible implementations, the distributed job scheduling apparatus 800 further includes: a monitoring module;
specifically, the monitoring module is used for monitoring the distributed job scheduling process.
In summary, the embodiment of the application discloses a distributed job scheduling device, which includes: the device comprises an acquisition module and an execution module. Therefore, according to the driving mode set by the job correspondence, the job scheduling such as report processing is scientifically, uniformly and comprehensively performed on the business data according to the scheduling strategy, so that the timeliness of the report data processing is ensured, and the exertion of the digital data asset value of the bank is ensured.
The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.
Referring to FIG. 9, a schematic diagram of a computer readable medium according to an embodiment of the present application is shown. The computer readable medium 300 has stored thereon a computer program 311, which computer program 311 when executed by a processor implements the steps of the distributed job scheduling method of fig. 2 described above.
It should be noted that in the context of the present application, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
It should be noted that the machine-readable medium according to the present application may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the above. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.
The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device.
Referring to fig. 10, which is a schematic diagram of a hardware structure of a server according to an embodiment of the present application, the server 400 may have a relatively large difference due to different configurations or performances, and may include one or more central processing units (central processing units, CPU) 422 (e.g., one or more processors) and a memory 432, and one or more storage media 430 (e.g., one or more mass storage devices) storing application programs 440 or data 444. Wherein memory 432 and storage medium 430 may be transitory or persistent storage. The program stored on the storage medium 430 may include one or more modules (not shown), each of which may include a series of instruction operations on a server. Still further, the central processor 422 may be configured to communicate with the storage medium 430 and execute a series of instruction operations in the storage medium 430 on the server 400.
The server 400 may also include one or more power supplies 426, one or more wired or wireless network interfaces 450, one or more input/output interfaces 458, and/or one or more operating systems 441, such as Windows ServerTM, mac OS XTM, unixTM, linuxTM, freeBSDTM, and the like.
The steps performed by the distributed job scheduling method in the above embodiments may be based on the server structure shown in fig. 10.
It should also be noted that, according to an embodiment of the present application, the procedure of the distributed job scheduling method described in the flowchart of fig. 2 may be implemented as a computer software program. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a non-transitory computer readable medium, the computer program comprising program code for performing the method shown in the flow diagram of fig. 2 described above.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are example forms of implementing the claims.
While several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the application. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
The above description is only illustrative of the preferred embodiments of the present application and of the principles of the technology employed. It will be appreciated by persons skilled in the art that the scope of the disclosure referred to in the present application is not limited to the specific combinations of technical features described above, but also covers other technical features formed by any combination of the technical features described above or their equivalents without departing from the spirit of the disclosure. Such as the above-mentioned features and the technical features disclosed in the present application (but not limited to) having similar functions are replaced with each other.
Claims (10)
1. A method for distributed job scheduling, the method comprising:
acquiring an operation with an operable operation type from an operation driving relation table;
and executing distributed job scheduling according to a scheduling strategy based on the driving mode of the executable job.
2. The method of claim 1, wherein prior to the acquiring the job of which the job type is runnable in the job drive relationship table, the method further comprises:
constructing parameter table information according to report batch processing operation in a banking system;
constructing a job scheduling model;
and maintaining the parameter table information according to the job scheduling model to obtain a parameter table, wherein the parameter table comprises a job driving relation table.
3. The method of claim 2, wherein the report batch job includes one or more of a banking system job name, a dependency, a time zone area in which the job is located, a file dependency, whether a holiday is involved, a job period, a job type, and a program name to which the job is related.
4. The method of claim 1, wherein the performing distributed job scheduling according to a scheduling policy based on the driving manner of the executable job comprises:
judging whether the operable job is in a false diary or not;
if not, based on the driving mode of the executable job, executing distributed job scheduling according to a scheduling strategy.
5. The method according to claim 1, wherein the method further comprises:
and monitoring the distributed job scheduling process.
6. A distributed job scheduling device, the device comprising: the device comprises an acquisition module and an execution module;
the acquisition module is used for acquiring the operation with the operable operation type in the operation driving relation table;
and the execution module is used for executing distributed job scheduling according to a scheduling strategy based on the driving mode of the executable job.
7. The apparatus of claim 6, wherein the apparatus further comprises: the first building module, the second building module and the third building module;
the first construction module is used for constructing parameter table information according to report batch processing operation in the banking system;
the second construction module is used for constructing a job scheduling model;
the third construction module is configured to maintain the parameter table information according to the job scheduling model to obtain a parameter table, where the parameter table includes a job driving relationship table.
8. The apparatus of claim 7, wherein the report batch job includes one or more of a banking system job name, a dependency, a time zone area in which the job is located, a file dependency, whether a holiday is involved, a job period, a job type, and a program name to which the job is related.
9. A distributed job scheduling apparatus, comprising: a memory and a processor;
the memory is used for storing programs;
the processor being adapted to execute the program to carry out the steps of the method according to any one of claims 1 to 5.
10. A computer storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method according to any of claims 1 to 5.
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| CN202311165312.3A CN117149389A (en) | 2023-09-11 | 2023-09-11 | Distributed job scheduling method, device, equipment and medium |
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| CN202311165312.3A CN117149389A (en) | 2023-09-11 | 2023-09-11 | Distributed job scheduling method, device, equipment and medium |
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