What's the difference between dagster job launch a...
# ask-ai
s
What's the difference between dagster job launch and dagster job execute? How can I run multiple jobs at once in the same terminal from the cli without waiting for each job to complete?
s
The difference between
dagster job launch
and
dagster job execute
lies in how the job is run: - `dagster job launch`: This command launches a job using the run launcher configured on the Dagster instance. The run launcher is responsible for initiating and managing the lifecycle of a job run. When you use
dagster job launch
, the job is submitted to the run launcher, which can be configured to run the job in different environments, such as on a Kubernetes cluster or a remote machine. This command is typically used when Dagster is running as a service with a persistent Dagster daemon process that can schedule and execute runs. - `dagster job execute`: This command executes a job in-process, meaning that the job runs synchronously within the same process as the CLI command. It is useful for local development and testing because it allows you to run a job directly without the need for a run launcher or a persistent service. The job execution is immediate and blocks the terminal until the job is complete. To run multiple jobs at once in the same terminal without waiting for each job to complete, you would typically use some form of parallel execution provided by your operating system's shell. For example, in Unix-like systems, you can use the
&
operator to run commands in the background:
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shell dagster job launch -f job1.py & dagster job launch -f job2.py & dagster job launch -f job3.py &
Each job will be launched in the background, allowing you to initiate multiple jobs concurrently from the same terminal. You can also use other tools like
xargs
or
parallel
for more sophisticated job management. Remember that when running jobs in parallel, you need to ensure that your Dagster instance is configured to handle concurrent execution, and that your jobs are designed to run concurrently without causing resource contention or other issues.