## Changes
This PR adds support for UC volumes to DABs.
### Can I use a UC volume managed by DABs in `artifact_path`?
Yes, but we require the volume to exist before being referenced in
`artifact_path`. Otherwise you'll see an error that the volume does not
exist. For this case, this PR also adds a warning if we detect that the
UC volume is defined in the DAB itself, which informs the user to deploy
the UC volume in a separate deployment first before using it in
`artifact_path`.
We cannot create the UC volume and then upload the artifacts to it in
the same `bundle deploy` because `bundle deploy` always uploads the
artifacts to `artifact_path` before materializing any resources defined
in the bundle. Supporting this in a single deployment requires us to
migrate away from our dependency on the Databricks Terraform provider to
manage the CRUD lifecycle of DABs resources.
### Why do we not support `preset.name_prefix` for UC volumes?
UC volumes will not have a `dev_shreyas_goenka` prefix added in `mode:
development`. Configuring `presets.name_prefix` will be a no-op for UC
volumes. We have decided not to support prefixing for UC resources. This
is because:
1. UC provides its own namespace hierarchy that is independent of DABs.
2. Users can always manually use `${workspace.current_user.short_name}`
to configure the prefixes manually.
Customers often manually set up a UC hierarchy for dev and prod,
including a schema or catalog per developer. Thus, it's often
unnecessary for us to add prefixing in `mode: development` by default
for UC resources.
In retrospect, supporting prefixing for UC schemas and registered models
was a mistake and will be removed in a future release of DABs.
## Tests
Unit, integration test, and manually.
### Manual Testing cases:
1. UC volume does not exist:
```
➜ bundle-playground git:(master) ✗ cli bundle deploy
Error: failed to fetch metadata for the UC volume /Volumes/main/caps/my_volume that is configured in the artifact_path: Not Found
```
2. UC Volume does not exist, but is defined in the DAB
```
➜ bundle-playground git:(master) ✗ cli bundle deploy
Error: failed to fetch metadata for the UC volume /Volumes/main/caps/managed_by_dab that is configured in the artifact_path: Not Found
Warning: You might be using a UC volume in your artifact_path that is managed by this bundle but which has not been deployed yet. Please deploy the UC volume in a separate bundle deploy before using it in the artifact_path.
at resources.volumes.bar
in databricks.yml:24:7
```
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## 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>
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
Library glob expansion happens during deployment. Before that, all
entries that refer to local paths in resource definitions are made
relative to the _sync root_. Before #1694, they were made relative to
the _bundle root_. This PR didn't update the library glob expansion code
to use the sync root path.
If you were using the sync paths setting with library globs, the CLI
would fail to expand the globs because the code was using the wrong path
to anchor those globs.
This change fixes the issue.
## Tests
Manually confirmed that this fixes the issue reported in #1755.
## Changes
Some call sites hold on to the `dyn.Path` provided to them by the
callback. It must therefore never be mutated after the callback returns,
or these mutations leak out into unknown scope.
This change means it is no longer possible for this failure mode to
happen.
## Tests
Unit test.
## Changes
Fixes issue introduced here https://github.com/databricks/cli/pull/1699
where PyPi packages were treated as local library.
The reason is that `libraryPath` returns an empty string as a path for
PyPi packages and then `IsLibraryLocal` treated empty string as local
path.
Both of these functions are fixed in this PR.
## Tests
Added regression test
## Changes
While experimenting with DAB I discovered that requirements libraries
are being ignored.
One thing worth mentioning is that `bundle validate` runs successfully,
but `bundle deploy` fails. This PR only covers the second part.
## Tests
<!-- How is this tested? -->
Added a unit test
## Changes
Previously for all the libraries referenced in configuration DABs made
sure that there is corresponding artifact section.
But this is not really necessary and flexible, because local libraries
might be built outside of dabs context.
It also created difficult to follow logic in code where we back
referenced libraries to artifacts which was difficult to fllow
This PR does 3 things:
1. Allows all local libraries referenced in DABs config to be uploaded
to remote
2. Simplifies upload and glob references expand logic by doing this in
single place
3. Speed things up by uploading library only once and doing this in
parallel
## Tests
Added unit + integration tests + made sure that change is backward
compatible (no changes in existing tests)
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## 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
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
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 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
Workspace library will be detected by trampoline in 2 cases:
- User defined to use local wheel file
- User defined to use remote wheel file from Workspace file system
In both of these cases we should correctly apply Python trampoline
## Tests
Added a regression test (also covered by Python e2e 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
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