How are parallel and subsequent jobs handled by cluster?

138999
New Contributor

Hello,

Apologize for dumb question but i'm new to Databricks and need clarification on following.

Are parallel and subsequent jobs able to reuse the same compute resources to keep time and cost overhead as low as possible vs. are they spinning a new cluster all the time?

Regards,

Tanja

daniel_sahal
Databricks MVP

@tanja.savic tanja.savic​ 

You can use shared job cluster:

https://docs.databricks.com/workflows/jobs/jobs.html#use-shared-job-clusters

But remember that a shared job cluster is scoped to a single job run, and cannot be used by other jobs or runs of the same job. It means that 1 job = 1 cluster