## Changes
This PR introduces use of new `isNil` method. It allows to ensure we
filter out all improperly defined resources in `bundle summary` command.
This includes deleted resources or resources with incorrect
configuration such as only defining key of the resource and nothing
else.
Fixes#1919, #1913
## Tests
Added regression unit test case
## Changes
The built-in template contains a reference to `${bundle.environment}`.
This property has been deprecated in favor of `${bundle.target}` a long
time ago (#670), so we should no longer emit it. The environment field
will continue to be usable until we cut a new major version in some far
away future.
## Tests
* Unit tests
* The test `TestInterpolationWithTarget` still covers correct
interpolation of `${bundle.environment}`
## Changes
This PR adds a warning validating that the configuration for a single
node cluster is valid for interactive, job, job-task, and pipeline
clusters.
Note: We skip the validation if a cluster policy is configured because
the policy is likely to configure `spark_conf` / `custom_tags` itself.
Note: Terrform originally only had validation for interactive, job, and
job-task clusters. This PR adding the validation for pipeline clusters
as well is new.
This PR follows the same logic as we used to have in Terraform. The
validation was removed from Terraform because we had no way to demote
the error to a warning:
https://github.com/databricks/terraform-provider-databricks/pull/4222
### Background
Single-node clusters require `spark_conf` and `custom_tags` to be
correctly set in the cluster definition for them to function optimally.
The cluster will be created even if incorrectly configured, but its
performance will not be great.
For example, if both `spark_conf` and `custom_tags` are not set and
`num_workers` is 0, then only the driver process will be launched on the
cluster compute instance thus leading to sub-optimal utilization of
available compute resources and no parallelization across worker
processes when processing a spark query.
### Issue
This PR addresses some issues reported in
https://github.com/databricks/cli/issues/1546
## Tests
Unit tests and manually.
Example output of the warning:
```
➜ bundle-playground git:(master) ✗ cli bundle validate
Warning: Single node cluster is not correctly configured
at resources.pipelines.bar.clusters[0]
in databricks.yml:29:11
num_workers should be 0 only for single-node clusters. To create a
valid single node cluster please ensure that the following properties
are correctly set in the cluster specification:
spark_conf:
spark.databricks.cluster.profile: singleNode
spark.master: local[*]
custom_tags:
ResourceClass: SingleNode
Name: foobar
Target: default
Workspace:
User: shreyas.goenka@databricks.com
Path: /Workspace/Users/shreyas.goenka@databricks.com/.bundle/foobar/default
Found 1 warning
```
## Changes
Users can configure the bundle to not synchronize any files with:
```yaml
sync:
paths: []
```
If it is explicitly configured as an empty list, the validate command
must not warn about not having any files to synchronize. The warning
exists to alert users who are unintentionally not synchronizing any
files (they might have a `.gitignore` pattern that matches everything).
Closes#1663.
## Tests
* New unit test.
## Changes
The full workspace path for a notebook does not contain the notebook's
extension. If a user converts that file path to a relative path (like
`/Workspace/bundle_root/bar/nb` -> `./bar/nb`), they can be confused as
to why the new file path does not work.
The changes in this PR nudge them to add the appropriate file extension
(e.g., `./bar/nb.py` or `./bar/nb.ipynb`).
One common way users can end up in this scenario is by using the view
job as YAML functionality in the Databricks UI.
## Tests
Unit test and manually.
```
(.venv) ➜ bundle-playground git:(master) ✗ cli bundle validate
Error: notebook ./foo not found. Local notebook references are expected
to contain one of the following file extensions: [.py, .r, .scala, .sql, .ipynb]
```
## Changes
While looking into adding variable lookups for notification destinations
([API][API]), I found the codegen approach for different classes of
variable lookups a bit complex. The template had a custom field override
(for service principals), the package had an override for the cluster
lookup, and it didn't produce tests.
The notification destinations API uses a default page size of 20 for
listing. I want to use a larger page size to limit the number of API
calls, so that would imply another customization on the template or a
manual override.
This code being rather mechanical, I used copilot to produce all
instances of the resolvers and their tests (after writing one of them
manually).
[api]: https://docs.databricks.com/api/workspace/notificationdestinations
## Tests
* Unit tests pass
* Manual confirmation that lookups of warehouses still work
## Changes
This change adds a preset for source-linked deployments. It is enabled
by default for targets in `development` mode **if** the Databricks CLI
is running from the `/Workspace` directory on DBR. It does not have an
effect when running the CLI anywhere else.
Key highlights:
1. Files in this mode won't be uploaded to workspace
2. Created resources will use references to source files instead of
their workspace copies
## Tests
1. Apply preset unit test covering conditional logic
2. High-level process target mode unit test for testing integration
between mutators
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
This field was special-cased in #1307 because it's not part of the JSON
payload in the SDK struct.
This approach, while pragmatic, meant it didn't show up in the JSON
schema. While debugging an issue with quality monitors in #1900, I
couldn't figure out why I was getting schema errors on this field, or
how it was passed through to the TF representation. This commit removes
the special case and makes it behave like everything else.
## Tests
* Unit tests pass.
* Confirmed that the updated schema failed validation before this
change.
## 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
As of #1846 we have a generalized package for doing resource lookups and
completion.
This change updates the run command to use this instead of more specific
code under `bundle/run`.
## Tests
* Unit tests pass
* Manually confirmed that completion and prompting works
## 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
This builds on the functionality added in #1731 that produces a URL for
every resource.
Adds `bundle/resources` package to deal with resource lookups and
command completion. The new functionality is similar to the lookup and
command completion functionality located in `bundle/run`. It differs in
that it doesn't gracefully deal with ambiguous references to resources,
now that we explicitly validate this doesn't occur in the bundle
configuration. It still allows resources to be looked up with their
fully qualified key, `<plural type>.<key>`.
## Tests
* Added unit tests for resource lookup and completion
* Manually confirmed that `bundle open` prompts, accepts a key argument,
and opens a browser
## Changes
We don't need to cancel existing runs when the job is continuous and
unpaused. The `/jobs/run-now` command will cancel the existing run and
trigger a new one automatically.
Cancelling the job manually can cause a race condition where both the
manual trigger from the CLI and the continuous trigger from the job
configuration happens at the same time. This PR prevents that from
happening.
## Tests
Unit tests and manually
## Changes
In #1218, the `BundleToTerraform` function was replaced by a version
based on the dynamic configuration tree. Since then, it has only been
used in tests to confirm that the output of the old function was equal
to the output of the new function. We no longer need this and can
exclusively rely on the version based on the dynamic configuration tree.
## Tests
Tests pass.
## Changes
Added a warning when incorrect permissions used for `/Workspace/Shared`
bundle root
## Tests
Added unit test
---------
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 issue reported in #1828 illustrates how using a YAML timestamp-like
value (a date in this case) causes an issue during conversion to and
from the typed configuration tree.
We use the `AsAny()` function on the `dyn.Value` when normalizing for
the `any` type. We only use the `any` type for variable values, because
they can assume every type. The `AsAny()` function returns a `time.Time`
for the time value during conversion **to** the typed configuration
tree. Upon conversion **from** the typed configuration tree back into
the dynamic configuration tree, we cannot distinguish a `time.Time`
struct from any other struct.
To address this, we use the underlying string value of the time value
when we normalize for the `any` type.
Fixes#1828.
## Tests
Existing unit tests pass
## Changes
Added JSON input validation for CLI commands. Now when invalid JSON
passed as a payload to CLI commands, CLI performs input normalisation
and detects if there are any mismatches such as incorrect types, unknown
fields and etc.
This diagnostic information is printed in standard error output and does
not block command execution, so the change is backward compatible.
Fixes#1769#1764#1625#1560
## Tests
Added unit tests
```
andrew.nester@HFW9Y94129 ~ % databricks jobs create --json '{"seeti}'
Error: error decoding JSON at (inline):1:2: unexpected EOF
andrew.nester@HFW9Y94129 ~ % databricks jobs create --json '{"seeti": true}'
Warning: unknown field: seeti
in (inline):1:9
Error: Job settings must be specified.
```
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.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 do not need the user to specify these fields in their bundle
configuration, so we remove them from the JSON schema.
## Tests
Manually and end to end tests. The JSON schema has also been regenerated
after these changes.
## 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
Currently API limits on exporting files from workspaces are set at 10
MBs while uploading to is 500 MBs. We want to prevent users running into
deadlock when they won't be able to pull state file anymore so we
prevent from uploading large state files (over 10 MBs) to Databricks
workspace.
## 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>
Andrew Nester
dependabot[bot]
Denis Bilenko
Pieter Noordhuis
shreyas-goenka
Ilya Kuznetsov
Lennart Kats (databricks)