Note:
This topic has been translated from a Chinese forum by GPT and might contain errors.Original topic: DM worker 任务负载均衡
How can I deploy 3 DM workers in a DM cluster with about a thousand tasks to achieve load balancing across all DM workers?
Note:
This topic has been translated from a Chinese forum by GPT and might contain errors.Original topic: DM worker 任务负载均衡
How can I deploy 3 DM workers in a DM cluster with about a thousand tasks to achieve load balancing across all DM workers?
Hello, the task load of the DM worker is only related to the number of upstream sources, because one worker can only be bound to one source (the migration task of one source can only be handled by one worker).
If you have only a few upstream instances, you can also distinguish the same instance with different source-ids. This way, when scheduling tasks, they will be considered different sources, allowing multiple workers to be utilized for the import.
Tasks are distinguished by source, and each source is bound one-to-one with a DM worker.
Isn’t it possible to configure multiple source-ids for a task? The task bound by the worker, am I misunderstanding something?
A worker is not bound to a task; a worker is bound to a source. A single worker can execute multiple tasks from the same source.