cancel
Showing results forย 
Search instead forย 
Did you mean:ย 
Get Started Discussions
Start your journey with Databricks by joining discussions on getting started guides, tutorials, and introductory topics. Connect with beginners and experts alike to kickstart your Databricks experience.
cancel
Showing results forย 
Search instead forย 
Did you mean:ย 

DLT Job Clusters: Continuous vs Triggered Cluster Start Times

ChristianRRL
Valued Contributor

Hi there,

I'm curious if anyone is able to definitively help me answer how DLT Job Clusters operate/run.

For example, the following is my baseline understanding of DLT Job Clusters. If I run a Triggered DLT Pipeline (e.g. daily) the job cluster takes more or less 5 minutes to spin up until it can start running through the operations. If I have it in Development mode the job cluster stays alive for a bit longer for testing/development, but if it's in Production mode the cluster starts and is killed immediately.

I'm curious about the for a "Semi-Continuous" (e.g. running every minute) or a Continuous Job Cluster, what happens to these DLT Job Clusters? Are they "Always On" in either/both of these cases? For the one that runs every minute, does it spin up an entire job cluster every time (which takes usually about 5 minutes)??

1 ACCEPTED SOLUTION

Accepted Solutions

melbourne
Contributor

Ideally one would expect clusters used for DLT pipeline to terminate after the pipeline execution has finished. However, while running in `development` environment, you'll notice it doesn't terminate on its own, whereas in `production` it terminates immediately after the pipeline has finished.

This is to do with `clusterShutdown.delay` value. In development the default value is 2 hours and in production it is 0 seconds. You can set this value in cluster settings on the UI under configuration tab:

 

"pipelines.clusterShutdown.delay": "0s"

 


This setting will shut down the cluster automatically.

Until databricks comes up with a serverless compute for DLT pipelines, I believe run the pipeline at every 15 minutes interval to save real cost, else just keep running it in continuous mode. 

View solution in original post

3 REPLIES 3

melbourne
Contributor

Ideally one would expect clusters used for DLT pipeline to terminate after the pipeline execution has finished. However, while running in `development` environment, you'll notice it doesn't terminate on its own, whereas in `production` it terminates immediately after the pipeline has finished.

This is to do with `clusterShutdown.delay` value. In development the default value is 2 hours and in production it is 0 seconds. You can set this value in cluster settings on the UI under configuration tab:

 

"pipelines.clusterShutdown.delay": "0s"

 


This setting will shut down the cluster automatically.

Until databricks comes up with a serverless compute for DLT pipelines, I believe run the pipeline at every 15 minutes interval to save real cost, else just keep running it in continuous mode. 

Hi @melbourne, intuitively I think what you're saying makes sense. I guess I have a general follow-up question. If what you're saying is right, then I agree 100% that anything more frequent than 15 minutes wouldn't really save on costs and should be set in continuous mode... but if that's the case, why even offer anything more frequent than 15 minutes? Why would anyone run a DLT job in Triggered mode every 5 minutes or less? It seems odd to me, and I feel like I'm missing something.

@Retired_mod FYI. I'd be curious to get your thoughts on this as well!

Well itโ€™s maybe for future and will be beneficial for serverless clusters 

Connect with Databricks Users in Your Area

Join a Regional User Group to connect with local Databricks users. Events will be happening in your city, and you wonโ€™t want to miss the chance to attend and share knowledge.

If there isnโ€™t a group near you, start one and help create a community that brings people together.

Request a New Group