## 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
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
This PR:
1. Move code to load bundle JSON Schema descriptions from the OpenAPI
spec to an internal Go module
2. Remove command line flags from the `bundle schema` command. These
flags were meant for internal processes and at no point were meant for
customer use.
3. Regenerate `bundle_descriptions.json`
4. Add support for `bundle: "deprecated"`. The `environments` field is
tagged as deprecated in this PR and consequently will no longer be a
part of the bundle schema.
## Tests
Tested by regenerating the CLI against its current OpenAPI spec (as
defined in `__openapi_sha`). The `bundle_descriptions.json` in this PR
was generated from the code generator.
Manually checked that the autocompletion / descriptions from the new
bundle schema are correct.
## 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
There were two functions related to loading a bundle configuration file;
one as a package function and one as a member function on the
configuration type. Loading the same configuration object twice doesn't
make sense and therefore we can consolidate to only using the package
function.
The package function would scan for known file names if the specified
path was a directory. This functionality was not in use because the
top-level bundle loader figures out the filename itself as of #580.
## Tests
Pass.
## 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
This PR:
1. Makes the bundle and sync properties optional in the generated
schema.
2. Fixes schema generation that was broken due to a rogue "description"
field in the bundle docs.
## Tests
Tested manually. The generated schema no longer has "bundle" and "sync"
marked as required.
# 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
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
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 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
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
```
## Tests
Tested manually. `"workspace"` is no longer a required field in the
generated JSON schema
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## 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
```
## Changes
Rename all instances of "bricks" to "databricks".
## Tests
* Confirmed the goreleaser build works, uses the correct new binary
name, and produces the right archives.
* Help output is confirmed to be correct.
* Output of `git grep -w bricks` is minimal with a couple changes
remaining for after the repository rename.
## Changes
Allows to override default value for a variable definition from the
environment block in a bundle config. See bundle.yml for example usage
## Tests
Unit tests
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
This PR now allows you to define variables in the bundle config and set
them in three ways
1. command line args
2. process environment variable
3. in the bundle config itself
## Tests
manually, unit, and black box tests
---------
Co-authored-by: Miles Yucht <miles@databricks.com>
## Changes
This PR adds checks during bundle config load and merge to error out if
there are duplicate keys for resource definitions
## Tests
Using unit tests and manually
## Changes
If a configuration file is located in a subdirectory of the bundle root,
files referenced from that configuration file should be relative to its
configuration file's directory instead of the bundle root.
## Tests
* New tests in `bundle/config/mutator/translate_paths_test.go`.
* Existing tests under `bundle/tests` pass and are augmented to assert
on paths.
---------
Co-authored-by: shreyas-goenka <88374338+shreyas-goenka@users.noreply.github.com>
This PR contains a struct to allow you to generate JSON schemas from
Golang types and a struct to allow injecting documentation into the json
schema. This will support autocomplete for DABs
This adds:
* Top level "artifacts" configuration key
* Support for notebooks (does language detection and upload)
* Merge of per-environment artifacts (or artifact overrides) into top level
Load a tree of configuration files anchored at `bundle.yml` into the
`config.Root` struct.
All mutations (from setting defaults to merging files) are observable
through the `mutator.Mutator` interface.
Pieter Noordhuis
Andrew Nester
shreyas-goenka
Lennart Kats (databricks)
Fabian Jakobs