## Changes
Whether or not the CLI is running on DBR can be detected once and stored
in the command's context.
By storing it in the context, it can easily be mocked for testing.
This builds on the simpler approach and conversation in #1744. It
unblocks testing of the DBR-specific paths while not compromising on the
checks we can perform to test if the CLI is running on DBR.
## Tests
* Unit tests for the new `dbr` package
* New unit test for the `ConfigureWSFS` mutator
Known issues:
- [ ] _(non-blocking with a command override)_ `apps.Update` requires 2
`name` params (one from path, one from request body)
- [ ] _(non-blocking)_ `lakeview.Create` does not require positional
argument `display_name` anymore because it's not marked as required in
request body
Bumps
[github.com/databricks/databricks-sdk-go](https://github.com/databricks/databricks-sdk-go)
from 0.49.0 to 0.51.0.
---------
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Andrew Nester <andrew.nester@databricks.com>
## Changes
The file presence check for dashboard files was missing a
`filepath.ToSlash`.
This means it didn't work on Windows unless the dashboard was located at
a path without slashes (i.e. the bundle root).
Closes#1875.
## Tests
* Added a unit test to cover this case (failed before the fix).
* Manually ran a dashboard deployment on Windows.
## Changes
This change adds the `databricks bundle generate dashboard` command.
The command requires one of three flags:
* `--existing-id` to generate configuration for an existing dashboard by
its ID.
* `--existing-path` to generate configuration for an existing dashboard
by its path in the workspace file system.
* `--resource` to generate the `.lvdash.json` dashboard file for a
dashboard that's already defined in the bundle. This option does not
impact the YAML configuration.
A typical workflow could look like this:
1. Use the command with `--existing-id` or `--existing-path` for a
starting point
2. Run `bundle deploy` to deploy a copy of the dashboard
3. Run `bundle open` to open this copy in your browser
4. Navigate to the draft mode and make modifications
5. Run `bundle generate dashboard` with `--resource` to update the local
`.lvdash.json` file with the remote modifications
## Tests
* Unit tests.
* Manual walkthrough as documented in the [Dashboard for NYC Taxi Trip
Analysis
example](https://github.com/databricks/bundle-examples/tree/main/knowledge_base/dashboard_nyc_taxi).
## Changes
This validator checks permissions defined in top-level bundle config and
permissions set in workspace for the folders bundle is deployed to. It
raises the warning if the permissions defined in the workspace are not
defined in bundle.
This validator is executed only during `bundle validate` command.
## Tests
```
Warning: untracked permissions apply to target workspace path
The following permissions apply to the workspace folder at "/Workspace/Users/andrew.nester@databricks.com/.bundle/clusters/default" but are not configured in the bundle:
- level: CAN_MANAGE, user_name: andrew.nester@databricks.com
```
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
Adds a textual output to the `databricks bundle summary` command, which
includes URLs of deployed resources.
Example usage:
```
$ databricks bundle summary
Name: my_pipeline
Target: dev
Workspace:
Host: https://domain.databricks.com
User: user@databricks.com
Path: /Users/user@databricks.com/.bundle/my_pipeline/dev
Resources:
Jobs:
my_project_job:
Name: [dev lennart] my_project_job
URL: https://domain.databricks.com/jobs/206899209187287?o=6051921418418893
Pipelines:
my_project_pipeline:
Name: [dev lennart] my_project_pipeline
URL: https://domain.databricks.com/pipelines/3f849fd5-ba7d-47fa-a34c-c6bf034b4f58?o=6051921418418893
```
Notes:
* The top headers of the output are the same as those from the existing
`bundle validate` command
* URLs are colored light blue in the output
* For resources that haven't been deployed yet, we show `(not deployed)`
in place of the URL
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
Co-authored-by: Pieter Noordhuis <pcnoordhuis@gmail.com>
## Changes
The two functions `GetShortUserName` and `IsServicePrincipal` are
unrelated to auth or the purpose of the auth package. This change moves
them into their own package and updates `IsServicePrincipal` to take an
`*iam.User` argument instead of a string username.
## Tests
Tests pass.
## Changes
This adds diagnostics for collaborative (production) deployment
scenarios, including:
- Bob deploys a bundle that is normally deployed by Alice, but this
fails because Bob can't write to `/Users/Alice/.bundle`.
- Charlie deploys a bundle that is normally deployed by Alice, but this
fails because he can't create a new pipeline where Alice would be the
owner.
- Alice deploys a bundle where she didn't list herself as one of the
CAN_MANAGE users in permissions. That can work, but is probably a
mistake.
## Tests
Unit tests, manual testing.
## Changes
We want to encourage a pattern of specifying only a single resource in a
YAML file when the `.(resource-type).yml` extension is used (for
example, `.job.yml`). This convention could allow us to bijectively map
a resource YAML file to its corresponding resource in the Databricks
workspace.
This PR:
1. Emits a recommendation diagnostic when we detect this convention is
being violated. We can promote this to a warning when we want to
encourage this pattern more strongly.
2. Visualises the recommendation diagnostics in the `bundle validate`
command.
**NOTE:** While this PR also shows the recommendation for `.yaml` files,
we do not encourage users to use this extension. We only support it here
since it's part of the YAML standard and some existing users might
already be using `.yaml`.
## Tests
Unit tests and manually. Here's what an example output looks like:
```
Recommendation: define a single job in a file with the .job.yml extension.
at resources.jobs.bar
resources.jobs.foo
in foo.job.yml:13:7
foo.job.yml:5:7
The following resources are defined or configured in this file:
- bar (job)
- foo (job)
```
---------
Co-authored-by: Lennart Kats (databricks) <lennart.kats@databricks.com>
## Changes
Due to platform changes, all libraries, notebooks and etc. paths used in
Databricks must be started with either /Workspace or /Volumes prefix.
This PR makes sure that all bundle paths are correctly prefixed.
Note: this change is a breaking change if user previously configured and
used `/Workspace/Workspace` folder in their workspace file system or
having `/Workspace/${workspace.root_path}...` pattern configured
anywhere in their bundle config
Fixes: #1751
AI:
- [x] Scan DABs config and error out on
`/Workspace/${workspace.root_path}...` pattern usage
## Tests
Added unit tests
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
Default workspace path for resources with a presence in the workspace
tree.
Note: this path is **not** created automatically (yet). We need this
only for dashboards (so far), so can take care of creation if one or
more dashboards are part of a deployment. This saves an API call for
deployments where this is not necessary.
## Tests
Expanded existing tests.
## Changes
This fixes the user-reported panic in `apply_presets.go`. I'm still
unsure how to reproduce this, since the CLI just reports `ob broken_job
is not defined` when I try to use `bundle deploy` with an empty job.
That said — we may as well be defensive here and I see we have lots of
checks for empty job/cluster/etc. settings scattered throughout our code
base so at least we're somewhat consistent.
## Changes
After introducing the `SyncRootPath` field on the bundle (#1694), the
previous `RootPath` became ambiguous. Does it mean the bundle root path
or the sync root path? This PR renames to field to `BundleRootPath` to
remove the ambiguity.
## Tests
n/a
---------
Co-authored-by: shreyas-goenka <88374338+shreyas-goenka@users.noreply.github.com>
I plan to use this in https://github.com/databricks/cli/pull/1780, to
set the line and column numbers as well for the locations.
gopatch file used:
```
@@
var x expression
var y expression
var z expression
@@
-bundletest.SetLocation(x, y, z)
+bundletest.SetLocation(x, y, []dyn.Location{{File: z}})
```
## Changes
Add JobTaskClusterSpec validate mutator. It catches the case when tasks
don't which cluster to use.
For example, we can get this error with minor modifications to
`default-python` template:
```yaml
tasks:
- task_key: python_file_task
spark_python_task:
python_file: ../src/my_project_10/main.py
```
```
% databricks bundle validate
Error: Missing required cluster or environment settings
at resources.jobs.my_project_10_job.tasks[0]
in resources/my_project_10_job.yml:17:11
Task "print_github_stars" requires a cluster or an environment to run.
Specify one of the following fields: job_cluster_key, environment_key, existing_cluster_id, new_cluster.
```
We implicitly rely on "one of" validation, which does not exist. Many
bundle fields can't co-exist, for instance, specifying:
`JobTask.{existing_cluster_id,job_cluster_key}`, `Library.{whl,pypi}`,
`JobTask.{notebook_task,python_wheel_task}`, etc.
## Tests
Unit tests
---------
Co-authored-by: Pieter Noordhuis <pcnoordhuis@gmail.com>
Ilya Kuznetsov
Pieter Noordhuis
dependabot[bot]
Andrew Nester
Lennart Kats (databricks)
shreyas-goenka
Gleb Kanterov