databricks-cli/bundle/config/bundle.go

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package config
type Terraform struct {
ExecPath string `json:"exec_path"`
}
type Bundle struct {
Name string `json:"name"`
// TODO
// Default cluster to run commands on (Python, Scala).
// DefaultCluster string `json:"default_cluster,omitempty"`
// TODO
// Default warehouse to run SQL on.
// DefaultWarehouse string `json:"default_warehouse,omitempty"`
// Environment is set by the mutator that selects the environment.
Environment string `json:"environment,omitempty" bundle:"readonly"`
// Terraform holds configuration related to Terraform.
// For example, where to find the binary, which version to use, etc.
Terraform *Terraform `json:"terraform,omitempty" bundle:"readonly"`
// Lock configures locking behavior on deployment.
Lock Lock `json:"lock" bundle:"readonly"`
// Contains Git information like current commit, current branch and
// origin url. Automatically loaded by reading .git directory if not specified
Git Git `json:"git,omitempty"`
Add development runs (#522) This implements the "development run" functionality that we desire for DABs in the workspace / IDE. ## bundle.yml changes In bundle.yml, there should be a "dev" environment that is marked as `mode: debug`: ``` environments: dev: default: true mode: development # future accepted values might include pull_request, production ``` Setting `mode` to `development` indicates that this environment is used just for running things for development. This results in several changes to deployed assets: * All assets will get '[dev]' in their name and will get a 'dev' tag * All assets will be hidden from the list of assets (future work; e.g. for jobs we would have a special job_type that hides it from the list) * All deployed assets will be ephemeral (future work, we need some form of garbage collection) * Pipelines will be marked as 'development: true' * Jobs can run on development compute through the `--compute` parameter in the CLI * Jobs get their schedule / triggers paused * Jobs get concurrent runs (it's really annoying if your runs get skipped because the last run was still in progress) Other accepted values for `mode` are `default` (which does nothing) and `pull-request` (which is reserved for future use). ## CLI changes To run a single job called "shark_sighting" on existing compute, use the following commands: ``` $ databricks bundle deploy --compute 0617-201942-9yd9g8ix $ databricks bundle run shark_sighting ``` which would deploy and run a job called "[dev] shark_sightings" on the compute provided. Note that `--compute` is not accepted in production environments, so we show an error if `mode: development` is not used. The `run --deploy` command offers a convenient shorthand for the common combination of deploying & running: ``` $ export DATABRICKS_COMPUTE=0617-201942-9yd9g8ix $ bundle run --deploy shark_sightings ``` The `--deploy` addition isn't really essential and I welcome feedback 🤔 I played with the idea of a "debug" or "dev" command but that seemed to only make the option space even broader for users. The above could work well with an IDE or workspace that automatically sets the target compute. One more thing I added is`run --no-wait` can now be used to run something without waiting for it to be completed (useful for IDE-like environments that can display progress themselves). ``` $ bundle run --deploy shark_sightings --no-wait ```
2023-07-12 06:51:54 +00:00
// Determines the mode of the environment.
// For example, 'mode: development' can be used for deployments for
// development purposes.
// Annotated readonly as this should be set at the environment level.
Mode Mode `json:"mode,omitempty" bundle:"readonly"`
// Overrides the compute used for jobs and other supported assets.
ComputeID string `json:"compute_id,omitempty"`
}