Task scheduling server and task scheduling method

A task scheduling and server technology, applied in the field of communications, can solve problems such as the inability to execute subtasks successfully, the inability to determine whether subtasks are executed successfully, and the inability to determine whether subsystems execute subtasks, etc., to achieve the effect of improving efficiency.

Inactive Publication Date: 2017-09-05
NUBIA TECHNOLOGY CO LTD
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  • Abstract
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  • Claims
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Problems solved by technology

Airflow itself can execute tasks directly, such as Hive SQL tasks. The blocking execution between tasks is to determine whether to execute the next subtask based on the execution results of the subtasks to ensure that the subtasks can be executed in an orderly manner. However, some big data tasks currently For example, the Hive SQL task is completed by a separate subsystem. Therefore, in Airflow, the subtask becomes the hypertext transfer protocol request subsystem execution, and the subsystem executes the subtask in two steps. The success of the hypertext protocol request cannot determine whether the subsystem has executed. For subtasks, the success of the hypertext protocol request cannot be regarded as the real execution success status of the subtask, and the existing technology cannot determine whether the subtask is successfully executed

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  • Task scheduling server and task scheduling method
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  • Task scheduling server and task scheduling method

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Embodiment Construction

[0045] It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0046] An optional task scheduling server implementing various embodiments of the present invention will now be described with reference to the accompanying drawings. In the following description, use of suffixes such as 'module', 'part' or 'unit' for denoting elements is only for facilitating description of the present invention and has no specific meaning by itself. Therefore, "module" and "component" may be used mixedly.

[0047] A task scheduling server can be implemented in various forms. For example, the servers described in the present invention may include, for example, large servers and small servers.

[0048] figure 1 It is a layered schematic diagram of the big data platform where the task scheduling server is located in various embodiments of the present invention. figure 1It includes data analysis lay...

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Abstract

The present invention provides a task scheduling server, which includes: a judgment module, an acquisition module, and a processing module. The judging module is used to judge whether the current subtask is independently executed by the corresponding subsystem. The acquiring module is used to acquire the task script corresponding to the subtask when the current subtask is executed independently by the corresponding subsystem. The processing module is used to execute the task script, send the execution request of the subtask to the corresponding subsystem, monitor the execution result of the subtask, and determine whether the execution of the subtask is completed according to the execution result. The invention also provides a task scheduling method. The task scheduling server and task scheduling method provided by the present invention can determine whether the current subtask is successfully executed by calling the task script of the subtask, and ensure that all subtasks can be executed in an orderly manner.

Description

technical field [0001] The present invention relates to the communication field, and more specifically, to a task scheduling server and a task scheduling method. Background technique [0002] The directed acyclic graph (DAG, Directed Acyclic Graph) task scheduling process in the task scheduling system of the big data platform is maintained by a separate system. The task scheduling process based on the DAG graph is converted into a tool that can be used by the tool flow scheduler. Recognized scripts, for example, use the Airflow tool to convert the task scheduling process based on the DAG graph into a dag.py script that can be recognized by Airflow, where Airflow is an open source workflow project, and dag.py refers to the code written in Python script. Airflow itself can execute tasks directly, such as Hive SQL tasks. The blocking execution between tasks is to determine whether to execute the next subtask based on the execution results of the subtasks to ensure that the sub...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/48
CPCG06F9/4881
Inventor 郭思勇
Owner NUBIA TECHNOLOGY CO LTD
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