A method, system and medium for processing Flink jobs

Through the combination of cloud platform and container orchestration engine, Flink job requests and execution plans are automatically managed, which solves the problem of inefficient Flink job management and improves job execution efficiency and resource utilization.

CN118260036BActive Publication Date: 2025-01-14QINGDAO ZHONGKE SHUGUANG TECH SERVICE CO LTD
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Patent Information

Application Number
CN202211698464.5
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2022-12-28
Publication Date
2025-01-14
Estimated Expiration
2042-12-28

AI Technical Summary

Technical Problem

The existing Flink job management is inefficient, especially because it requires manual login to the remote server for management, which leads to low efficiency.

Method used

Job requests are generated through the cloud platform, and the job requests are forwarded to the workbench through the setting components in the container orchestration engine. The execution plan is determined based on the job content and sent to the corresponding Flink cluster to realize automatic deployment and resource isolation of the Flink cluster. Avoid manually logging into remote servers to manage jobs.

Benefits of technology

It improves Flink job management efficiency, reduces operation and maintenance difficulties, avoids problems in code stability and readability, improves code readability, and realizes automatic deployment and resource scalability of Flink clusters.

✦ Generated by Eureka AI based on patent content.

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Abstract

The present invention discloses a method, system and medium for processing Flink jobs. The method comprises generating a job request according to job configuration parameters and job content through a cloud platform, forwarding the job request to a workbench in a container orchestration engine through a setting component in a container orchestration engine; determining an execution plan based on the job content through a setting interface in the workbench, sending the execution plan to a corresponding Flink cluster in the workbench according to the job configuration parameters; and executing the Flink job based on the execution plan through a Flink cluster. The present invention solves the problem of low job management efficiency caused by manually logging into a remote server to manage jobs, and determines the execution plan before handing the job to a Flink cluster, which can avoid problems in code stability and readability caused by calling related components in the Flink cluster, improves code readability, reduces the difficulty of operation and maintenance, and further improves job management efficiency.
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