databricks-cli/bundle/config/target.go

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package config
import (
"github.com/databricks/cli/bundle/config/resources"
Use dynamic configuration model in bundles (#1098) ## Changes This is a fundamental change to how we load and process bundle configuration. We now depend on the configuration being represented as a `dyn.Value`. This representation is functionally equivalent to Go's `any` (it is variadic) and allows us to capture metadata associated with a value, such as where it was defined (e.g. file, line, and column). It also allows us to represent Go's zero values properly (e.g. empty string, integer equal to 0, or boolean false). Using this representation allows us to let the configuration model deviate from the typed structure we have been relying on so far (`config.Root`). We need to deviate from these types when using variables for fields that are not a string themselves. For example, using `${var.num_workers}` for an integer `workers` field was impossible until now (though not implemented in this change). The loader for a `dyn.Value` includes functionality to capture any and all type mismatches between the user-defined configuration and the expected types. These mismatches can be surfaced as validation errors in future PRs. Given that many mutators expect the typed struct to be the source of truth, this change converts between the dynamic representation and the typed representation on mutator entry and exit. Existing mutators can continue to modify the typed representation and these modifications are reflected in the dynamic representation (see `MarkMutatorEntry` and `MarkMutatorExit` in `bundle/config/root.go`). Required changes included in this change: * The existing interpolation package is removed in favor of `libs/dyn/dynvar`. * Functionality to merge job clusters, job tasks, and pipeline clusters are now all broken out into their own mutators. To be implemented later: * Allow variable references for non-string types. * Surface diagnostics about the configuration provided by the user in the validation output. * Some mutators use a resource's configuration file path to resolve related relative paths. These depend on `bundle/config/paths.Path` being set and populated through `ConfigureConfigFilePath`. Instead, they should interact with the dynamically typed configuration directly. Doing this also unlocks being able to differentiate different base paths used within a job (e.g. a task override with a relative path defined in a directory other than the base job). ## Tests * Existing unit tests pass (some have been modified to accommodate) * Integration tests pass
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"github.com/databricks/cli/bundle/config/variable"
"github.com/databricks/databricks-sdk-go/service/jobs"
)
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 ```
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type Mode string
// Target defines overrides for a single target.
// This structure is recursively merged into the root configuration.
type Target struct {
// Default marks that this target must be used if one isn't specified
// by the user (through target variable or command line argument).
Default bool `json:"default,omitempty"`
// Determines the mode of the target.
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 ```
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// For example, 'mode: development' can be used for deployments for
// development purposes.
Mode Mode `json:"mode,omitempty"`
// Overrides the compute used for jobs and other supported assets.
ComputeID string `json:"compute_id,omitempty"`
Bundle *Bundle `json:"bundle,omitempty"`
Workspace *Workspace `json:"workspace,omitempty"`
Artifacts Artifacts `json:"artifacts,omitempty"`
Resources *Resources `json:"resources,omitempty"`
// Override default values or lookup name for defined variables
// Does not permit defining new variables or redefining existing ones
// in the scope of an target
Use dynamic configuration model in bundles (#1098) ## Changes This is a fundamental change to how we load and process bundle configuration. We now depend on the configuration being represented as a `dyn.Value`. This representation is functionally equivalent to Go's `any` (it is variadic) and allows us to capture metadata associated with a value, such as where it was defined (e.g. file, line, and column). It also allows us to represent Go's zero values properly (e.g. empty string, integer equal to 0, or boolean false). Using this representation allows us to let the configuration model deviate from the typed structure we have been relying on so far (`config.Root`). We need to deviate from these types when using variables for fields that are not a string themselves. For example, using `${var.num_workers}` for an integer `workers` field was impossible until now (though not implemented in this change). The loader for a `dyn.Value` includes functionality to capture any and all type mismatches between the user-defined configuration and the expected types. These mismatches can be surfaced as validation errors in future PRs. Given that many mutators expect the typed struct to be the source of truth, this change converts between the dynamic representation and the typed representation on mutator entry and exit. Existing mutators can continue to modify the typed representation and these modifications are reflected in the dynamic representation (see `MarkMutatorEntry` and `MarkMutatorExit` in `bundle/config/root.go`). Required changes included in this change: * The existing interpolation package is removed in favor of `libs/dyn/dynvar`. * Functionality to merge job clusters, job tasks, and pipeline clusters are now all broken out into their own mutators. To be implemented later: * Allow variable references for non-string types. * Surface diagnostics about the configuration provided by the user in the validation output. * Some mutators use a resource's configuration file path to resolve related relative paths. These depend on `bundle/config/paths.Path` being set and populated through `ConfigureConfigFilePath`. Instead, they should interact with the dynamically typed configuration directly. Doing this also unlocks being able to differentiate different base paths used within a job (e.g. a task override with a relative path defined in a directory other than the base job). ## Tests * Existing unit tests pass (some have been modified to accommodate) * Integration tests pass
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Variables map[string]*variable.Variable `json:"variables,omitempty"`
Add validation for Git settings in bundles (#578) ## Changes This checks whether the Git settings are consistent with the actual Git state of a source directory. (This PR adds to https://github.com/databricks/cli/pull/577.) Previously, we would silently let users configure their Git branch to e.g. `main` and deploy with that metadata even if they were actually on a different branch. With these changes, the following config would result in an error when deployed from any other branch than `main`: ``` bundle: name: example workspace: git: branch: main environments: ... ``` > not on the right Git branch: > expected according to configuration: main > actual: my-feature-branch It's not very useful to set the same branch for all environments, though. For development, it's better to just let the CLI auto-detect the right branch. Therefore, it's now possible to set the branch just for a single environment: ``` bundle: name: example 2 environments: development: default: true production: # production can only be deployed from the 'main' branch git: branch: main ``` Adding to that, the `mode: production` option actually checks that users explicitly set the Git branch as seen above. Setting that branch helps avoid mistakes, where someone accidentally deploys to production from the wrong branch. (I could see us offering an escape hatch for that in the future.) # Testing Manual testing to validate the experience and error messages. Automated unit tests. --------- Co-authored-by: Fabian Jakobs <fabian.jakobs@databricks.com>
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Git Git `json:"git,omitempty"`
RunAs *jobs.JobRunAs `json:"run_as,omitempty"`
Sync *Sync `json:"sync,omitempty"`
Permissions []resources.Permission `json:"permissions,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
const (
// Development mode: deployments done purely for running things in development.
// Any deployed resources will be marked as "dev" and might be hidden or cleaned up.
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 ```
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Development Mode = "development"
// Production mode: deployments done for production purposes.
// Any deployed resources will not be changed but this mode will enable
// various strictness checks to make sure that a deployment is correctly setup
// for production purposes.
Production Mode = "production"
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 ```
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)