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databricks-cli/acceptance/bundle/override/job_cluster/databricks.yml

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Enable environment overrides for job clusters (#658) ## Changes While they are a slice, we can identify a job cluster by its job cluster key. A job definition with multiple job clusters with the same key is always invalid. We can therefore merge definitions with the same key into one. This is compatible with how environment overrides are applied; merging a slice means appending to it. The override will end up in the job cluster slice of the original, which gives us a deterministic way to merge them. Since the alternative is an invalid configuration, this doesn't change behavior. ## Tests New test coverage.
2023-08-14 06:43:45 +00:00
bundle:
name: override_job_cluster
resources:
jobs:
foo:
name: job
job_clusters:
- job_cluster_key: key
new_cluster:
spark_version: 13.3.x-scala2.12
Renamed `environments` to `targets` in bundle configuration (#670) ## Changes Renamed Environments to Targets in bundle.yml. The change is backward-compatible and customers can continue to use `environments` in the time being. ## Tests Added tests which checks that both `environments` and `targets` sections in bundle.yml works correctly
2023-08-17 15:22:32 +00:00
targets:
Enable environment overrides for job clusters (#658) ## Changes While they are a slice, we can identify a job cluster by its job cluster key. A job definition with multiple job clusters with the same key is always invalid. We can therefore merge definitions with the same key into one. This is compatible with how environment overrides are applied; merging a slice means appending to it. The override will end up in the job cluster slice of the original, which gives us a deterministic way to merge them. Since the alternative is an invalid configuration, this doesn't change behavior. ## Tests New test coverage.
2023-08-14 06:43:45 +00:00
development:
resources:
jobs:
foo:
job_clusters:
- job_cluster_key: key
new_cluster:
node_type_id: i3.xlarge
num_workers: 1
staging:
resources:
jobs:
foo:
job_clusters:
- job_cluster_key: key
new_cluster:
node_type_id: i3.2xlarge
num_workers: 4