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I'm running a databricks job involving multiple tasks and would like to run the job with different set of task parameters. I can achieve that by edit each task and and change the parameter values. However, it gets very manual when I have a lot of tas...
Dear Team, For now, I found a solution. Disconnect the bundle source on Databricks, edit the parameters that you want to run. After execution, redeploy your code again from repository.
Hi All.. I had created 2 job flows and one for transaction layer and another for datamart layer. I need to specify the job dependency between job1 vs Job2 and need to trigger the job2 after completing job1 without using any other orchestration tool o...
Hey everyone, I'm experiementing with running containerized pyspark jobs in Databricks, and orchestrating them with airflow. I am however, encountering an issue here. When I trigger an airflow DAG, and I look at the logs, I see that airflow is spinni...
Both, I guess? Yes, all jobs share the same config - the question I have is why in the same airflow task log, there are 3 jobs runs. I'm hoping that there's something in the configs and may give me some kind of clue.
I have a big cluster with the auto-scaling(min:1, max: 25) feature enabled. I want to run multiple jobs on that cluster with different values of spark properties( `--executor-cores` and `–executor-memory) but I don't see any option to specify the sam...
Hi @Neelesh databricks Hope everything is going great.Just wanted to check in if you were able to resolve your issue. If yes, would you be happy to mark an answer as best so that other members can find the solution more quickly? If not, please tell ...
I have a Delta table spark101.airlines (sourced from `/databricks-datasets/airlines/`) partitioned by `Year`. My `spark.sql.shuffle.partitions` is set to default 200. I run a simple query:select Origin, count(*)
from spark101.airlines
group by Origi...
