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apache-flink

Difference between job, task and subtask in flink

I'm new to flink and try to understand:

  1. job
  2. task
  3. subtask

I searched in the docs but still did not get it. What's the main diffence between them?

Solution

  • Tasks and sub-tasks are explained here -- https://ci.apache.org/projects/flink/flink-docs-release-1.7/concepts/runtime.html#tasks-and-operator-chains:

    enter image description here

    A task is an abstraction representing a chain of operators that could be executed in a single thread. Something like a keyBy (which causes a network shuffle to partition the stream by some key) or a change in the parallelism of the pipeline will break the chaining and force operators into separate tasks. In the diagram above, the application has three tasks.

    A subtask is one parallel slice of a task. This is the schedulable, runable unit of execution. In the diagram above, the application is to be run with a parallelism of two for the source/map and keyBy/Window/apply tasks, and a parallelism of one for the sink -- resulting in a total of 5 subtasks.

    A job is a running instance of an application. Clients submit jobs to the jobmanager, which slices them into subtasks and schedules those subtasks for execution by the taskmanagers.

    Update:

    The community decided to re-align the definitions of task and sub-task to match how these terms are used in the code -- which means that task and sub-task now mean the same thing: exactly one parallel instance of an operator or operator chain. See the Glossary for more details.