## Changes
This PR partially reverts the changes in
https://github.com/databricks/cli/pull/1233 and puts the old code under
an "experimental.use_legacy_run_as" configuration. This gives customers
who ran into the breaking change made in the PR a way out.
## Tests
Both manually and via unit tests.
Manually verified that run_as works for pipelines now. And if a user
wants to use the feature they need to be both a Metastore and a
workspace admin.
---------
Error when the deploying user is a workspace admin but not a metastore
admin:
```
Error: terraform apply: exit status 1
Error: cannot update permissions: User is not a metastore admin for Metastore 'deco-uc-prod-aws-us-east-1'.
with databricks_permissions.pipeline_foo,
on bundle.tf.json line 23, in resource.databricks_permissions.pipeline_foo:
23: }
```
--------
Output of bundle validate:
```
➜ bundle-playground git:(master) ✗ cli bundle validate
Warning: You are using the legacy mode of run_as. The support for this mode is experimental and might be removed in a future release of the CLI. In order to run the DLT pipelines in your DAB as the run_as user this mode changes the owners of the pipelines to the run_as identity, which requires the user deploying the bundle to be a workspace admin, and also a Metastore admin if the pipeline target is in UC.
at experimental.use_legacy_run_as
in databricks.yml:13:22
Name: bundle-playground
Target: default
Workspace:
Host: https://dbc-a39a1eb1-ef95.cloud.databricks.com
User: shreyas.goenka@databricks.com
Path: /Users/shreyas.goenka@databricks.com/.bundle/bundle-playground/default
Found 1 warning
```
## Changes
The main changes are:
1. Don't link artifacts to libraries anymore and instead just iterate
over all jobs and tasks when uploading artifacts and update local path
to remote
2. Iterating over `jobs.environments` to check if there are any local
libraries and checking that they exist locally
3. Added tests to check environments are handled correctly
End-to-end test will follow up
## Tests
Added regression test, existing tests (including integration one) pass
## Changes
All these validators will return warnings as part of `bundle validate`
run
Added 2 mutators:
1. To check that if tasks use job_cluster_key it is actually defined
2. To check if there are any files to sync as part of deployment
Also added `bundle.Parallel` to run them in parallel
To make sure mutators under bundle.Parallel do not mutate config,
introduced new `ReadOnlyMutator`, `ReadOnlyBundle` and `ReadOnlyConfig`.
Example
```
databricks bundle validate -p deco-staging
Warning: unknown field: new_cluster
at resources.jobs.my_job
in bundle.yml:24:7
Warning: job_cluster_key high_cpu_workload_job_cluster is not defined
at resources.jobs.my_job.tasks[0].job_cluster_key
in bundle.yml:35:28
Warning: There are no files to sync, please check your your .gitignore and sync.exclude configuration
at sync.exclude
in bundle.yml:18:5
Name: test
Target: default
Workspace:
Host: https://acme.databricks.com
User: andrew.nester@databricks.com
Path: /Users/andrew.nester@databricks.com/.bundle/test/default
Found 3 warnings
```
## Tests
Added unit tests
## Changes
In 0.217.0 we started to emit warning on unknown fields in YAML
configuration but wrongly considered YAML anchor blocks as unknown
field.
This PR fixes this by skipping normalising of YAML blocks.
## Tests
Added regression tests
## Changes
Variable substitution works as if the variable reference is literally
replaced with its contents.
The following fields should be interpreted in the same way regardless of
where the variable is defined:
```yaml
foo: ${var.some_path}
bar: "./${var.some_path}"
```
Before this change, `foo` would inherit the location information of the
variable definition. After this change, it uses the location information
of the variable reference, making the behavior for `foo` and `bar`
identical.
Fixes#1330.
## Tests
The new test passes only with the fix.
## Changes
This PR introduces an allow list for resource types that are allowed
when the run_as for the bundle is not the same as the current deployment
user.
This PR also adds a test to ensure that any new resources added to DABs
will have to add the resource to either the allow list or add an error
to fail when run_as identity is not the same as deployment user.
## Tests
Unit tests
## Changes
Prior to this change, the bundle configuration entry point was loaded
from the function `bundle.Load`. Other configuration files were only
loaded once the caller applied the first set of mutators. This
separation was unnecessary and not ideal in light of gathering
diagnostics while loading _any_ configuration file, not just the ones
from the includes.
This change:
* Updates `bundle.Load` to only verify that the specified path is a
valid bundle root.
* Moves mutators that perform loading to `bundle/config/loader`.
* Adds a "load" phase that takes the place of applying
`DefaultMutators`.
Follow ups:
* Rename `bundle.Load` -> `bundle.Find` (because it no longer performs
loading)
This change depends on #1316 and #1317.
## Tests
Tests pass.
## Changes
The bundle path was previously stored on the `config.Root` type under
the assumption that the first configuration file being loaded would set
it. This is slightly counterintuitive and we know what the path is upon
construction of the bundle. The new location for this property reflects
this.
## Tests
Unit tests pass.
## Changes
This diagnostics type allows us to capture multiple warnings as well as
errors in the return value. This is a preparation for returning
additional warnings from mutators in case we detect non-fatal problems.
* All return statements that previously returned an error now return
`diag.FromErr`
* All return statements that previously returned `fmt.Errorf` now return
`diag.Errorf`
* All `err != nil` checks now use `diags.HasError()` or `diags.Error()`
## Tests
* Existing tests pass.
* I confirmed no call site under `./bundle` or `./cmd/bundle` uses
`errors.Is` on the return value from mutators. This is relevant because
we cannot wrap errors with `%w` when calling `diag.Errorf` (like
`fmt.Errorf`; context in https://github.com/golang/go/issues/47641).
## Changes
These tests were located in `bundle/tests/bundle` which meant they were
unable to reuse the helper functions defined in the `bundle/tests`
package. There is no need for these tests to live outside the package.
## Tests
Existing tests pass.
## Changes
This change addresses the path resolution behavior in resource
definitions. Previously, all paths were resolved relative to where the
resource was first defined, which could lead to confusion and errors
when paths were specified in different directories. The new behavior is
to resolve paths relative to where they are defined, making it more
intuitive.
However, to avoid breaking existing configurations, compatibility with
the old behavior is maintained.
## Tests
* Existing unit tests for path translation pass.
* Additional test to cover both the nominal and the fallback behavior.
## 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
## Changes
The approach to do this was:
1. Iterate over all libraries in all job tasks
2. Find references to local libraries
3. Store pointer to `compute.Library` in the matching artifact file to
signal it should be uploaded
This breaks down when introducing #1098 because we can no longer track
unexported state across mutators. The approach in this PR performs the
path matching twice; once in the matching mutator where we check if each
referenced file has an artifacts section, and once during artifact
upload to rewrite the library path from a local file reference to an
absolute Databricks path.
## Tests
Integration tests pass.
## Changes
Now we can define variables with values which reference different
Databricks resources by name.
When references like this, DABs automatically looks up the resource by
this name and replaces the reference with ID of the resource referenced.
Thus when the variable is used in the configuration it will contain the
correct resolved ID of resource.
The resolvers are code generated and thus DABs support referencing all
resources which has `GetByName`-like methods in Go SDK.
### Example
```
variables:
my_cluster_id:
description: An existing cluster.
lookup:
cluster: "12.2 shared"
resources:
jobs:
my_job:
name: "My Job"
tasks:
- task_key: TestTask
existing_cluster_id: ${var.my_cluster_id}
targets:
dev:
variables:
my_cluster_id:
lookup:
cluster: "dev-cluster"
```
## Tests
Added unit test + manual testing
---------
Co-authored-by: shreyas-goenka <88374338+shreyas-goenka@users.noreply.github.com>
## Changes
If there are no matches when doing Glob call for pipeline library
defined, leave the entry as is.
The next mutators in the chain will detect that file is missing and the
error will be more user friendly.
Before the change
```
Starting resource deployment
Error: terraform apply: exit status 1
Error: cannot create pipeline: libraries must contain at least one element
```
After
```
Error: notebook ./non-existent not found
```
## Tests
Added regression unit tests
## Changes
Some test call sites called directly into the mutator's `Apply` function
instead of `bundle.Apply`. Calling into `bundle.Apply` is preferred
because that's where we can run pre/post logic common across all
mutators.
## Tests
Pass.
## Changes
Now it's possible to define top level `permissions` section in bundle
configuration and permissions defined there will be applied to all
resources defined in the bundle.
Supported top-level permission levels: CAN_MANAGE, CAN_VIEW, CAN_RUN.
Permissions are applied to: Jobs, DLT Pipelines, ML Models, ML
Experiments and Model Service Endpoints
```
bundle:
name: permissions
workspace:
host: ***
permissions:
- level: CAN_VIEW
group_name: test-group
- level: CAN_MANAGE
user_name: user@company.com
- level: CAN_RUN
service_principal_name: 123456-abcdef
```
## Tests
Added corresponding unit tests + ran `bundle validate` and `bundle
deploy` manually
## Changes
We can debate whether or not variable definitions without properties are
valid, but in no case should this panic the CLI.
Fixes#934.
## Tests
Unit.
## Changes
This is a follow-up to #658 and #779 for jobs.
This change applies label normalization the same way the backend does.
## Tests
Unit and config loading tests.
## Changes
Follow up for https://github.com/databricks/cli/pull/658
When a job definition has multiple job tasks using the same key, it's
considered invalid. Instead we should combine those definitions with the
same key into one. This is consistent with environment overrides. This
way, the override ends up in the original job tasks, and we've got a
clear way to put them all together.
## Tests
Added unit tests
## Changes
List available targets when incorrect target passed
## Tests
```
andrew.nester@HFW9Y94129 wheel % databricks bundle validate -t incorrect
Error: incorrect: no such target. Available targets: prod, development
```
# Warning: breaking change
## Changes
Instead of having paths in bundle config files be relative to bundle
root even if the config file is nested, this PR makes such paths
relative to the folder where the config is located.
When bundle is initialised, these paths will be transformed to relative
paths based on bundle root. For example,
we have file structure like this
```
- mybundle
| - bundle.yml
| - subfolder
| -- resource.yml
| -- my.whl
```
Previously, we had to reference `my.whl` in resource.yml like this,
which was confusing because resource.yml is in the same subfolder
```
sync:
include:
- ./subfolder/*.whl
...
tasks:
- task_key: name
libraries:
- whl: ./subfolder/my.whl
...
```
After the change we can reference it like this (which is in line with
the current behaviour for notebooks)
```
sync:
include:
- ./*.whl
...
tasks:
- task_key: name
libraries:
- whl: ./my.whl
...
```
## Tests
Existing `translate_path_tests` successfully passed after refactoring.
Added a couple of uses cases for `Libraries` paths.
Added a bundle config tests with include config and sync section
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
Now if the user reference local Python wheel files and do not specify
"artifacts" section, this file will be automatically uploaded by CLI.
Fixes#693
## Tests
Added unit tests
Ran bundle deploy for this configuration
```
resources:
jobs:
some_other_job:
name: "[${bundle.environment}] My Wheel Job"
tasks:
- task_key: TestTask
existing_cluster_id: ${var.job_existing_cluster}
python_wheel_task:
package_name: "my_test_code"
entry_point: "run"
libraries:
- whl: ./dist/*.whl
```
Result
```
andrew.nester@HFW9Y94129 wheel % databricks bundle deploy
artifacts.whl.AutoDetect: Detecting Python wheel project...
artifacts.whl.AutoDetect: No Python wheel project found at bundle root folder
Starting upload of bundle files
Uploaded bundle files at /Users/andrew.nester@databricks.com/.bundle/wheel-task/default/files!
artifacts.Upload(my_test_code-0.0.1-py3-none-any.whl): Uploading...
artifacts.Upload(my_test_code-0.0.1-py3-none-any.whl): Upload succeeded
```
## Changes
Added run_as section for bundle configuration.
This section allows to define an user name or service principal which
will be applied as an execution identity for jobs and DLT pipelines. In
the case of DLT, identity defined in `run_as` will be assigned
`IS_OWNER` permission on this pipeline.
## Tests
Added unit tests for configuration.
Also ran deploy for the following bundle configuration
```
bundle:
name: "run_as"
run_as:
# service_principal_name: "f7263fcc-56d0-4981-8baf-c2a45296690b"
user_name: "lennart.kats@databricks.com"
resources:
pipelines:
andrew_pipeline:
name: "Andrew Nester pipeline"
libraries:
- notebook:
path: ./test.py
jobs:
job_one:
name: Job One
tasks:
- task_key: "task"
new_cluster:
num_workers: 1
spark_version: 13.2.x-snapshot-scala2.12
node_type_id: i3.xlarge
runtime_engine: PHOTON
notebook_task:
notebook_path: "./test.py"
```
## 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
## Changes
This is not desirable and will be addressed by representing our
configuration in a different structure (e.g. with cty, or with
plain `any`), instead of Go structs.
## Tests
Pass.
## Changes
Originally, these blocks were merged with overrides. This was
(inadvertently) disabled in #94. This change re-enables merging these
blocks with overrides, such that any field set in an environment
override always takes precedence over the field set in the base
definition.
## Tests
New unit test passes.
## 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.
## Changes
This PR:
1. Fixes the computation logic for `ActualBranch`. An error in the
earlier logic caused the validation mutator to be a no-op.
2. Makes the `.git` string a global var. This is useful to configure in
tests.
3. Adds e2e test for the validation mutator.
## Tests
Unit test
## Changes
Some library paths such as for Spark jobs, can reference a lib on remote
path, for example DBFS.
This PR fixes how CLI handles such libraries and do not report them as
missing locally.
## Tests
Added unit tests + ran `databricks bundle deploy` manually
## 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>
## Changes
This adds `mode: production` option. This mode doesn't do any
transformations but verifies that an environment is configured correctly
for production:
```
environments:
prod:
mode: production
# paths should not be scoped to a user (unless a service principal is used)
root_path: /Shared/non_user_path/...
# run_as and permissions should be set at the resource level (or at the top level when that is implemented)
run_as:
user_name: Alice
permissions:
- level: CAN_MANAGE
user_name: Alice
```
Additionally, this extends the existing `mode: development` option,
* now prefixing deployed assets with `[dev your.user]` instead of just
`[dev`]
* validating that development deployments _are_ scoped to a user
## Related
https://github.com/databricks/cli/pull/578/files (in draft)
## Tests
Manual testing to validate the experience, error messages, and
functionality with all resource types. Automated unit tests.
---------
Co-authored-by: Fabian Jakobs <fabian.jakobs@databricks.com>
## Changes
Added support for artifacts building for bundles.
Now it allows to specify `artifacts` block in bundle.yml and define a
resource (at the moment Python wheel) to be build and uploaded during
`bundle deploy`
Built artifact will be automatically attached to corresponding job task
or pipeline where it's used as a library
Follow-ups:
1. If artifact is used in job or pipeline, but not found in the config,
try to infer and build it anyway
2. If build command is not provided for Python wheel artifact, infer it
## Changes
Before this PR we would load all yaml files matching * and \*/\*.yml
files as bundle configurations. This was problematic since this would
also load yaml files that were not meant to be a part of the bundle
## Tests
Manually, now files are no longer included unless manually specified
## Changes
* Add support for using `databricks.yml` as config file. If
`databricks.yml` is not found then falling back to `bundle.yml` for
backwards compatibility.
* Add support for `.yaml` extension.
* Give an error when more than one config file is found
## Tests
* added unit test
* manual testing the different cases
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
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
```
## Changes
Fixed error reporting when included invalid files in include section
Case 1. When the file to include is invalid, throw an error
Case 2. When the file is loaded but the schema is wrong, indicate which
file is failed to load
## Tests
With non-existent notexists.yml
```
databricks bundle deploy
Error: notexists.yml defined in 'include' section does not match any files
```
With malformed notexists.yml
```
databricks bundle deploy
Error: failed to load /Users/andrew.nester/dabs/wheel/notexists.yml: error unmarshaling JSON: json: cannot unmarshal string into Go value of type config.Root
```
Shreyas Goenka
shreyas-goenka
Andrew Nester
Pieter Noordhuis
Arpit Jasapara
Lennart Kats (databricks)
Fabian Jakobs