## 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
Previously local JAR paths were transformed to remote path during
initialisation and thus artifact building logic did not recognise such
libraries as local to be handled and uploaded.
Now it's possible to use spark_jar_tasks with local JAR libraries on
14.1+ DBR clusters
Example configuration
```
bundle:
name: spark-jar
workspace:
host: ***
artifacts:
my_java_code:
path: ./sample-java
build: "javac PrintArgs.java && jar cvfm PrintArgs.jar META-INF/MANIFEST.MF PrintArgs.class"
files:
- source: "/Users/andrew.nester/dabs/wheel/sample-java/PrintArgs.jar"
resources:
jobs:
print_args:
name: "Print Args"
tasks:
- task_key: Print
new_cluster:
num_workers: 0
spark_version: 14.2.x-scala2.12
node_type_id: i3.xlarge
spark_conf:
"spark.databricks.cluster.profile": "singleNode"
"spark.master": "local[*]"
custom_tags:
ResourceClass: "SingleNode"
spark_jar_task:
main_class_name: PrintArgs
libraries:
- jar: ./sample-java/PrintArgs.jar
```
## Tests
Manually running `bundle deploy and bundle run`
## 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
All calls to apply a mutator must go through `bundle.Apply`. This
conflicts with the existing use of the variable `bundle`. This change
un-aliases the variable from the package name by renaming all variables
to `b`.
## Tests
Pass.
## Changes
This PR:
1. Renames `FilesPath` -> `FilePath` and `ArtifactsPath` ->
`ArtifactPath` in the bundle and metadata configuration to make them
consistant with the json tags.
2. Fixes development / production mode error messages to point to
`file_path` and `artifact_path`
## Tests
Existing unit tests. This is a strightforward renaming of the fields.
Partly mitigates #859. It's still not clear to me if there is an actual
use case or if users are trying to use "development" mode jobs for
production, but making this overridable is reasonable.
Beyond this fix I think we could do something in the Jobs schedule UI,
but it would help to better understand the use case (or actual reason of
confusion). I expect we should hint customers to move away from dev mode
rather than unpause.
## 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
Support path rewrites for Dbt and SQL file job taks.
<!-- Summary of your changes that are easy to understand -->
## Tests
* Added unit test
<!-- How is this tested? -->
## Changes
This PR introduces a metadata struct that stores a subset of bundle
configuration that we wish to expose to other Databricks services that
wish to integrate with bundles.
This metadata file is uploaded to a file
`${bundle.workspace.state_path}/metadata.json` in the WSFS destination
of the bundle deployment.
Documentation for emitted metadata fields:
* `version`: Version for the metadata file schema
* `config.bundle.git.branch`: Name of the git branch the bundle was
deployed from.
* `config.bundle.git.origin_url`: URL for git remote "origin"
* `config.bundle.git.bundle_root_path`: Relative path of the bundle root
from the root of the git repository. Is set to "." if they are the same.
* `config.bundle.git.commit`: SHA-1 commit hash of the exact commit this
bundle was deployed from. Note, the deployment might not exactly match
this commit version if there are changes that have not been committed to
git at deploy time,
* `file_path`: Path in workspace where we sync bundle files to.
* `resources.jobs.[job-ref].id`: Id of the job
* `resources.jobs.[job-ref].relative_path`: Relative path of the yaml
config file from the bundle root where this job was defined.
Example metadata object when bundle root and git root are the same:
```json
{
"version": 1,
"config": {
"bundle": {
"lock": {},
"git": {
"branch": "master",
"origin_url": "www.host.com",
"commit": "7af8e5d3f5dceffff9295d42d21606ccf056dce0",
"bundle_root_path": "."
}
},
"workspace": {
"file_path": "/Users/shreyas.goenka@databricks.com/.bundle/pipeline-progress/default/files"
},
"resources": {
"jobs": {
"bar": {
"id": "245921165354846",
"relative_path": "databricks.yml"
}
}
},
"sync": {}
}
}
```
Example metadata when the git root is one level above the bundle repo:
```json
{
"version": 1,
"config": {
"bundle": {
"lock": {},
"git": {
"branch": "dev-branch",
"origin_url": "www.my-repo.com",
"commit": "3db46ef750998952b00a2b3e7991e31787e4b98b",
"bundle_root_path": "pipeline-progress"
}
},
"workspace": {
"file_path": "/Users/shreyas.goenka@databricks.com/.bundle/pipeline-progress/default/files"
},
"resources": {
"jobs": {
"bar": {
"id": "245921165354846",
"relative_path": "databricks.yml"
}
}
},
"sync": {}
}
}
```
This unblocks integration to the jobs break glass UI for bundles.
## Tests
Unit tests and integration tests.
## Changes
Now it's possible to specify glob pattern in pipeline libraries section
and DAB will add all matched files as libraries
```
pipelines:
dummy:
name: " DLT with Python files"
target: "dlt_python_files"
libraries:
- file:
path: ./*.py
```
## Tests
Added unit test
## Changes
The jobs backend propagates job tags to the underlying cloud provider's
resources. As such, they need to match the constraints a cloud provider
places on tag values. The display name can contain anything. With this
change, we modify the tag value to equal the short name as used in the
name prefix.
Additionally, we leverage tag normalization as introduced in #819 to
make sure characters that aren't accepted are removed before using the
value as a tag value.
This is a new stab at #810 and should completely eliminate this class of
problems.
## Tests
Tests pass.
## Changes
Instead of always using notebook wrapper for Python wheel tasks, let's
make this an opt-in option.
Now by default Python wheel tasks will be deployed as is to Databricks
platform.
If notebook wrapper required (DBR < 13.1 or other configuration
differences), users can provide a following experimental setting
```
experimental:
python_wheel_wrapper: true
```
Fixes#783,
https://github.com/databricks/databricks-asset-bundles-dais2023/issues/8
## Tests
Added unit tests.
Integration tests passed for both cases
```
helpers.go:163: [databricks stdout]: Hello from my func
helpers.go:163: [databricks stdout]: Got arguments:
helpers.go:163: [databricks stdout]: ['my_test_code', 'one', 'two']
...
Bundle remote directory is ***/.bundle/ac05d5e8-ed4b-4e34-b3f2-afa73f62b021
Deleted snapshot file at /var/folders/nt/xjv68qzs45319w4k36dhpylc0000gp/T/TestAccPythonWheelTaskDeployAndRunWithWrapper3733431114/001/.databricks/bundle/default/sync-snapshots/cac1e02f3941a97b.json
Successfully deleted files!
--- PASS: TestAccPythonWheelTaskDeployAndRunWithWrapper (214.18s)
PASS
coverage: 93.5% of statements in ./...
ok github.com/databricks/cli/internal/bundle 214.495s coverage: 93.5% of statements in ./...
```
```
helpers.go:163: [databricks stdout]: Hello from my func
helpers.go:163: [databricks stdout]: Got arguments:
helpers.go:163: [databricks stdout]: ['my_test_code', 'one', 'two']
...
Bundle remote directory is ***/.bundle/0ef67aaf-5960-4049-bf1d-dc9e29157421
Deleted snapshot file at /var/folders/nt/xjv68qzs45319w4k36dhpylc0000gp/T/TestAccPythonWheelTaskDeployAndRunWithoutWrapper2340216760/001/.databricks/bundle/default/sync-snapshots/edf0b322cee93b13.json
Successfully deleted files!
--- PASS: TestAccPythonWheelTaskDeployAndRunWithoutWrapper (192.36s)
PASS
coverage: 93.5% of statements in ./...
ok github.com/databricks/cli/internal/bundle 195.130s coverage: 93.5% of statements in ./...
```
## Changes
There are a couple places throughout the code base where interaction
with environment variables takes place. Moreover, more than one of these
would try to read a value from more than one environment variable as
fallback (for backwards compatibility). This change consolidates those
accesses.
The majority of diffs in this change are mechanical (i.e. add an
argument or replace a call).
This change:
* Moves common environment variable lookups for bundles to
`bundles/env`.
* Adds a `libs/env` package that wraps `os.LookupEnv` and `os.Getenv`
and allows for overrides to take place in a `context.Context`. By
scoping overrides to a `context.Context` we can avoid `t.Setenv` in
testing and unlock parallel test execution for integration tests.
* Updates call sites to pass through a `context.Context` where needed.
* For bundles, introduces `DATABRICKS_BUNDLE_ROOT` as new primary
variable instead of `BUNDLE_ROOT`. This was the last environment
variable that did not use the `DATABRICKS_` prefix.
## Tests
Unit tests pass.
## 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
```
## Changes
This follows up on https://github.com/databricks/cli/pull/686. This PR
makes our stubs optional + it adds DLT stubs:
```
$ databricks bundle init
Template to use [default-python]: default-python
Unique name for this project [my_project]: my_project
Include a stub (sample) notebook in 'my_project/src' [yes]: yes
Include a stub (sample) DLT pipeline in 'my_project/src' [yes]: yes
Include a stub (sample) Python package 'my_project/src' [yes]: yes
✨ Successfully initialized template
```
## Tests
Manual testing, matrix tests.
---------
Co-authored-by: Andrew Nester <andrew.nester@databricks.com>
Co-authored-by: PaulCornellDB <paul.cornell@databricks.com>
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
The latest rendition of isServicePrincipal no longer worked for
non-admin users as it used the "principals get" API.
This new version relies on the property that service principals always
have a UUID as their userName. This was tested with the eng-jaws
principal (8b948b2e-d2b5-4b9e-8274-11b596f3b652).
# 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
@pietern this addresses a comment from you on a recently merged PR. It
also updates settings.json based on the settings VS Code adds as soon as
you edit a notebook.
## Changes
***Note: this PR relies on sync.include functionality from here:
https://github.com/databricks/cli/pull/671***
Added transformation mutator for Python wheel task for them to work on
DBR <13.1
Using wheels upload to Workspace file system as cluster libraries is not
supported in DBR < 13.1
In order to make Python wheel work correctly on DBR < 13.1 we do the
following:
1. Build and upload python wheel as usual
2. Transform python wheel task into special notebook task which does the
following
a. Installs all necessary wheels with %pip magic
b. Executes defined entry point with all provided parameters
3. Upload this notebook file to workspace file system
4. Deploy transformed job task
This is also beneficial for executing on existing clusters because this
notebook always reinstall wheels so if there are any changes to the
wheel package, they are correctly picked up
## Tests
bundle.yml
```yaml
bundle:
name: wheel-task
workspace:
host: ****
resources:
jobs:
test_job:
name: "[${bundle.environment}] My Wheel Job"
tasks:
- task_key: TestTask
existing_cluster_id: "***"
python_wheel_task:
package_name: "my_test_code"
entry_point: "run"
parameters: ["first argument","first value","second argument","second value"]
libraries:
- whl: ./dist/*.whl
```
Output
```
andrew.nester@HFW9Y94129 wheel % databricks bundle run test_job
Run URL: ***
2023-08-03 15:58:04 "[default] My Wheel Job" TERMINATED SUCCESS
Output:
=======
Task TestTask:
Hello from my func
Got arguments v1:
['python', 'first argument', 'first value', 'second argument', 'second value']
```
## Changes
This pull request extends the templating support in preparation of a
new, default template (WIP, https://github.com/databricks/cli/pull/686):
* builtin templates that can be initialized using e.g. `databricks
bundle init default-python`
* builtin templates are embedded into the executable using go's `embed`
functionality, making sure they're co-versioned with the CLI
* new helpers to get the workspace name, current user name, etc. help
craft a complete template
* (not enabled yet) when the user types `databricks bundle init` they
can interactively select the `default-python` template
And makes two tangentially related changes:
* IsServicePrincipal now uses the "users" API rather than the
"principals" API, since the latter is too slow for our purposes.
* mode: prod no longer requires the 'target.prod.git' setting. It's hard
to set that from a template. (Pieter is planning an overhaul of warnings
support; this would be one of the first warnings we show.)
The actual `default-python` template is maintained in a separate PR:
https://github.com/databricks/cli/pull/686
## Tests
Unit tests, manual testing
## 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 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
* This PR adds `DATABRICKS_BUNDLE_INCLUDE_PATHS` environment variable,
so that we can specify including bundle config files, which we do not
want to commit. These could potentially be local dev overrides or
overrides by our tools - like the VS Code extension
* We always add these include paths to the "include" field.
## Tests
* [x] Unit tests
## 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
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>
## Changes
Uploading a notebook strips it's file extension. This PR returns an
error if a notebook is specified where a file is expected. For example:
A spark python task in a job or `libraries.file.path` DLT library (where
instead `libraries.notebook.path` should be used
This PR also adds test coverage for the opposite case, when files are
not notebooks where notebooks are expected.
## Tests
Integration tests and manually
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
```
## Changes
Added skipping of translating paths for notebook path in notebook tasks
and python file path in spark python tasks if the git source is not null.
Resolves: #402
## Tests
There is a unit test and also tested with a sample bundle:
```
resources:
jobs:
demo:
git_source:
git_branch: master
git_provider: github
git_url: https://github.com/test/dummy
....
```
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
Added support for `bundle.Seq`, simplified `Mutator.Apply` interface by
removing list of mutators from return values/
## Tests
1. Ran `cli bundle deploy` and interrupted it with Cmd + C mid execution
so lock is not released
2. Ran `cli bundle deploy` top make sure that CLI is not trying to
release lock when it fail to acquire it
```
andrew.nester@HFW9Y94129 multiples-tasks % cli bundle deploy
Starting upload of bundle files
Uploaded bundle files at /Users/andrew.nester@databricks.com/.bundle/simple-task/development/files!
^C
andrew.nester@HFW9Y94129 multiples-tasks % cli bundle deploy
Error: deploy lock acquired by andrew.nester@databricks.com at 2023-05-24 12:10:23.050343 +0200 CEST. Use --force to override
```
## 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
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 config block contains commit, branch and remote_url which will be
automatically loaded if specified in the repo, and can also be specified
by the user
## Tests
Unit and black-box tests
Andrew Nester
Pieter Noordhuis
shreyas-goenka
Lennart Kats (databricks)
Michał Szafrański
Arpit Jasapara
Kartik Gupta
Fabian Jakobs
stikkireddy
Serge Smertin