## Changes
This change adds support for Lakehouse monitoring in bundles.
The associated resource type name is "quality monitor".
## Testing
Unit tests.
---------
Co-authored-by: Pieter Noordhuis <pcnoordhuis@gmail.com>
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
Co-authored-by: Arpit Jasapara <87999496+arpitjasa-db@users.noreply.github.com>
## Changes
Introduce `libs/vfs` for an implementation of `fs.FS` and friends that
_includes_ the absolute path it is anchored to.
This is needed for:
1. Intercepting file operations to inject custom logic (e.g., logging,
access control).
2. Traversing directories to find specific leaf directories (e.g.,
`.git`).
3. Converting virtual paths to OS-native paths.
Options 2 and 3 are not possible with the standard `fs.FS` interface.
They are needed such that we can provide an instance to the sync package
and still detect the containing `.git` directory and convert paths to
native paths.
This change focuses on making the following packages use `vfs.Path`:
* libs/fileset
* libs/git
* libs/sync
All entries returned by `fileset.All` are now slash-separated. This has
2 consequences:
* The sync snapshot now always uses slash-separated paths
* We don't need to call `filepath.FromSlash` as much as we did
## Tests
* All unit tests pass
* All integration tests pass
* Manually confirmed that a deployment made on Windows by a previous
version of the CLI can be deployed by a new version of the CLI while
retaining the validity of the local sync snapshot as well as the remote
deployment state.
## Changes
If only key was defined for a job in YAML config, validate previously
failed with segfault.
This PR validates that jobs are correctly defined and returns an error
if not.
## Tests
Added regression test
## Changes
This is one step toward removing the `path.Paths` struct embedding from
resource types.
Going forward, we'll exclusively use the `dyn.Value` tree for location
information.
## Tests
Existing unit tests that cover path resolution with fallback behavior
pass.
## Changes
This PR ensures every resource implements a custom marshaller /
unmarshaller. This is required because we directly embed Go SDK structs.
which implement custom marshalling overrides. Since the struct is
embedded, the [customer marshalling
overrides](https://pkg.go.dev/encoding/json#example-package-CustomMarshalJSON)
are promoted to the top level. If the embedded struct itself is nil,
then JSON marshal / unmarshal will panic because it tries to call
`MarshalJSON` / `UnmarshalJSON` on a nil object.
Fixing this issue at the Go SDK level does not seem possible. Discussed
with @hectorcast-db.
## Changes
This PR partially reverts the changes in
https://github.com/databricks/cli/pull/1233 and puts the old code under
an "experimental.use_legacy_run_as" configuration. This gives customers
who ran into the breaking change made in the PR a way out.
## Tests
Both manually and via unit tests.
Manually verified that run_as works for pipelines now. And if a user
wants to use the feature they need to be both a Metastore and a
workspace admin.
---------
Error when the deploying user is a workspace admin but not a metastore
admin:
```
Error: terraform apply: exit status 1
Error: cannot update permissions: User is not a metastore admin for Metastore 'deco-uc-prod-aws-us-east-1'.
with databricks_permissions.pipeline_foo,
on bundle.tf.json line 23, in resource.databricks_permissions.pipeline_foo:
23: }
```
--------
Output of bundle validate:
```
➜ bundle-playground git:(master) ✗ cli bundle validate
Warning: You are using the legacy mode of run_as. The support for this mode is experimental and might be removed in a future release of the CLI. In order to run the DLT pipelines in your DAB as the run_as user this mode changes the owners of the pipelines to the run_as identity, which requires the user deploying the bundle to be a workspace admin, and also a Metastore admin if the pipeline target is in UC.
at experimental.use_legacy_run_as
in databricks.yml:13:22
Name: bundle-playground
Target: default
Workspace:
Host: https://dbc-a39a1eb1-ef95.cloud.databricks.com
User: shreyas.goenka@databricks.com
Path: /Users/shreyas.goenka@databricks.com/.bundle/bundle-playground/default
Found 1 warning
```
## 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
This enable queueing for jobs by default, following the behavior from
API 2.2+. Queing is a best practice and will be the default in API 2.2.
Since we're still using API 2.1 which has queueing disabled by default,
this PR enables queuing using a mutator.
Customers can manually turn off queueing for any job by adding the
following to their job spec:
```
queue:
enabled: false
```
## Tests
Unit tests, manual confirmation of property after deployment.
---------
Co-authored-by: Pieter Noordhuis <pcnoordhuis@gmail.com>
## Changes
All these validators will return warnings as part of `bundle validate`
run
Added 2 mutators:
1. To check that if tasks use job_cluster_key it is actually defined
2. To check if there are any files to sync as part of deployment
Also added `bundle.Parallel` to run them in parallel
To make sure mutators under bundle.Parallel do not mutate config,
introduced new `ReadOnlyMutator`, `ReadOnlyBundle` and `ReadOnlyConfig`.
Example
```
databricks bundle validate -p deco-staging
Warning: unknown field: new_cluster
at resources.jobs.my_job
in bundle.yml:24:7
Warning: job_cluster_key high_cpu_workload_job_cluster is not defined
at resources.jobs.my_job.tasks[0].job_cluster_key
in bundle.yml:35:28
Warning: There are no files to sync, please check your your .gitignore and sync.exclude configuration
at sync.exclude
in bundle.yml:18:5
Name: test
Target: default
Workspace:
Host: https://acme.databricks.com
User: andrew.nester@databricks.com
Path: /Users/andrew.nester@databricks.com/.bundle/test/default
Found 3 warnings
```
## Tests
Added unit tests
## Changes
Allows for the syntax below
```
variables:
service_principal_app_id:
description: 'The app id of the service principal for running workflows as.'
lookup:
service_principal: "sp-${bundle.environment}"
```
Fixes#1259
## Tests
Added regression test
## Changes
This changes `databricks bundle deploy` so that it skips the lock
acquisition/release step for a `mode: development` target:
* This saves about 2 seconds (measured over 100 runs on a quiet/busy
workspace).
* This helps avoid the `deploy lock acquired by lennart@company.com at
2024-02-28 15:48:38.40603 +0100 CET. Use --force-lock to override` error
* Risk: this may cause deployment conflicts, but since dev mode
deployments are always scoped to a user, that risk should be minimal
Update after discussion:
* This behavior can now be disabled via a setting.
* Docs PR: https://github.com/databricks/docs/pull/15873
## Measurements
### 100 deployments of the "python_default" project to an empty
workspace
_Before this branch:_
p50 time: 11.479 seconds
p90 time: 11.757 seconds
_After this branch:_
p50 time: 9.386 seconds
p90 time: 9.599 seconds
### 100 deployments of the "python_default" project to a busy (staging)
workspace
_Before this branch:_
* p50 time: 13.335 seconds
* p90 time: 15.295 seconds
_After this branch:_
* p50 time: 11.397 seconds
* p90 time: 11.743 seconds
### Typical duration of deployment steps
* Acquiring Deployment Lock: 1.096 seconds
* Deployment Preparations and Operations: 1.477 seconds
* Uploading Artifacts: 1.26 seconds
* Finalizing Deployment: 9.699 seconds
* Releasing Deployment Lock: 1.198 seconds
---------
Co-authored-by: Pieter Noordhuis <pcnoordhuis@gmail.com>
Co-authored-by: Andrew Nester <andrew.nester.dev@gmail.com>
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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
`preinit` script needs to be executed before processing configuration
files to allow the script to modify the configuration or add own
configuration files.
[](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores)
Dependabot will resolve any conflicts with this PR as long as you don't
alter it yourself. You can also trigger a rebase manually by commenting
`@dependabot rebase`.
[//]: # (dependabot-automerge-start)
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---
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<summary>Dependabot commands and options</summary>
<br />
You can trigger Dependabot actions by commenting on this PR:
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- `@dependabot recreate` will recreate this PR, overwriting any edits
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Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Andrew Nester <andrew.nester@databricks.com>
## Changes
Allow specifying CLI version constraints required to run the bundle
Example of configuration:
#### only allow specific version
```
bundle:
name: my-bundle
databricks_cli_version: "0.210.0"
```
#### allow all patch releases
```
bundle:
name: my-bundle
databricks_cli_version: "0.210.*"
```
#### constrain minimum version
```
bundle:
name: my-bundle
databricks_cli_version: ">= 0.210.0"
```
#### constrain range
```
bundle:
name: my-bundle
databricks_cli_version: ">= 0.210.0, <= 1.0.0"
```
For other examples see:
https://github.com/Masterminds/semver?tab=readme-ov-file#checking-version-constraints
Example error
```
sh-3.2$ databricks bundle validate
Error: Databricks CLI version constraint not satisfied. Required: >= 1.0.0, current: 0.216.0
```
## Tests
Added unit test cover all possible configuration permutations
---------
Co-authored-by: Lennart Kats (databricks) <lennart.kats@databricks.com>
## Changes
We no longer need to store load diagnostics on the `config.Root` type
itself and instead can return them from the `config.Load` call directly.
It is up to the caller of this function to append them to previous
diagnostics, if any.
Background: previous commits moved configuration loading of the entry
point into a mutator, so now all diagnostics naturally flow from
applying mutators.
This PR depends on #1319.
## Tests
Unit and manual validation of the debug statements in the validate
command.
## Changes
This PR introduces an allow list for resource types that are allowed
when the run_as for the bundle is not the same as the current deployment
user.
This PR also adds a test to ensure that any new resources added to DABs
will have to add the resource to either the allow list or add an error
to fail when run_as identity is not the same as deployment user.
## Tests
Unit tests
## Changes
Prior to this change, the bundle configuration entry point was loaded
from the function `bundle.Load`. Other configuration files were only
loaded once the caller applied the first set of mutators. This
separation was unnecessary and not ideal in light of gathering
diagnostics while loading _any_ configuration file, not just the ones
from the includes.
This change:
* Updates `bundle.Load` to only verify that the specified path is a
valid bundle root.
* Moves mutators that perform loading to `bundle/config/loader`.
* Adds a "load" phase that takes the place of applying
`DefaultMutators`.
Follow ups:
* Rename `bundle.Load` -> `bundle.Find` (because it no longer performs
loading)
This change depends on #1316 and #1317.
## Tests
Tests pass.
## Changes
PR #604 added functionality to load a bundle without a `databricks.yml`
if both the `DATABRICKS_BUNDLE_ROOT` and `DATABRICKS_BUNDLE_INCLUDES`
environment variables were set. We never ended up using this in
downstream tools so this can be removed.
## Tests
Unit tests 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
This change addresses the path resolution behavior in resource
definitions. Previously, all paths were resolved relative to where the
resource was first defined, which could lead to confusion and errors
when paths were specified in different directories. The new behavior is
to resolve paths relative to where they are defined, making it more
intuitive.
However, to avoid breaking existing configurations, compatibility with
the old behavior is maintained.
## Tests
* Existing unit tests for path translation pass.
* Additional test to cover both the nominal and the fallback behavior.
## Changes
This PR introduces new structure (and a file) being used locally and
synced remotely to Databricks workspace to track bundle deployment
related metadata.
The state is pulled from remote, updated and pushed back remotely as
part of `bundle deploy` command.
This state can be used for deployment sequencing as it's `Version` field
is monotonically increasing on each deployment.
Currently, it only tracks files being synced as part of the deployment.
This helps fix the issue with files not being removed during deployments
on CI/CD as sync snapshot was never present there.
Fixes#943
## Tests
Added E2E (regression) test for files removal on CI/CD
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
We now keep location metadata associated with every configuration value.
When expanding globs for pipeline libraries, this annotation was erased
because of the conversion to/from the typed structure. This change
modifies the expansion mutator to work with `dyn.Value` and retain the
location of the value that holds the glob pattern.
## Tests
Unit tests pass.
## Changes
This change means the callback supplied to `dyn.Foreach` can introspect
the path of the value it is being called for. It also prepares for
allowing visiting path patterns where the exact path is not known
upfront.
## Tests
Unit tests.
## Changes
This change enables the use of bundle variables for boolean, integer,
and floating point fields.
## Tests
* Unit tests.
* I ran a manual test to confirm parameterizing the number of workers in
a cluster definition works.
## 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
Added `bundle deployment bind` and `unbind` command.
This command allows to bind bundle-defined resources to existing
resources in Databricks workspace so they become DABs-managed.
## Tests
Manually + added E2E test
## Changes
Deploying bundle when there are bundle resources running at the same
time can be disruptive for jobs and pipelines in progress.
With this change during deployment phase (before uploading any
resources) if there is `--fail-if-running` specified DABs will check if
there are any resources running and if so, will fail the deployment
## Tests
Manual + add tests
## 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
Adds the short_name helper function. short_name is useful when templates
do not want to print the full userName (typically email or service
principal application-id) of the current user.
## Tests
Integration test. Also adds integration tests for other helper functions
that interact with the Databricks API.
## Changes
Allow specifying executable in artifact section
```
artifacts:
test:
type: whl
executable: bash
...
```
We also skip bash found on Windows if it's from WSL because it won't be
correctly executed, see the issue above
Fixes#1159
The plan is to use the new command in the Databricks VSCode extension to
render "modified" UI state in the bundle resource tree elements, plus
use resource IDs to generate links for the resources
### New revision
- Renamed `remote-state` to `summary`
- Added "modified statuses" to all resources. Currently we don't set
"updated" status - it's either nothing, or created/deleted
- Added tests for the `TerraformToBundle` command
## Changes
Now it's possible to generate bundle configuration for existing job.
For now it only supports jobs with notebook tasks.
It will download notebooks referenced in the job tasks and generate
bundle YAML config for this job which can be included in larger bundle.
## Tests
Running command manually
Example of generated config
```
resources:
jobs:
job_128737545467921:
name: Notebook job
format: MULTI_TASK
tasks:
- task_key: as_notebook
existing_cluster_id: 0704-xxxxxx-yyyyyyy
notebook_task:
base_parameters:
bundle_root: /Users/andrew.nester@databricks.com/.bundle/job_with_module_imports/development/files
notebook_path: ./entry_notebook.py
source: WORKSPACE
run_if: ALL_SUCCESS
max_concurrent_runs: 1
```
## Tests
Manual (on our last 100 jobs) + added end-to-end test
```
--- PASS: TestAccGenerateFromExistingJobAndDeploy (50.91s)
PASS
coverage: 61.5% of statements in ./...
ok github.com/databricks/cli/internal/bundle 51.209s coverage: 61.5% of
statements in ./...
```
## 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 changes the default and `mode: production` recommendation to
target `/Users` for deployment. Previously, we used `/Shared`, but
because of a lack of POSIX-like permissions in WorkspaceFS this meant
that files inside would be readable and writable by other users in the
workspace.
Detailed change:
* `default-python` no longer uses a path that starts with `/Shared`
* `mode: production` no longer requires a path that starts with
`/Shared`
## Related PRs
Docs: https://github.com/databricks/docs/pull/14585
Examples: https://github.com/databricks/bundle-examples/pull/17
## Tests
* Manual tests
* Template unit tests (with an extra check to avoid /Shared)
## Changes
Instead of handling command chaining ourselves, we execute passed
commands as-is by storing them, in temp file and passing to correct
interpreter (bash or cmd) based on OS.
Fixes#1065
## Tests
Added unit tests
## 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
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
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
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
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
If a bundle configuration specifies a workspace host, and the user
specifies a profile to use, we perform a check to confirm that the
workspace host in the bundle configuration and the workspace host from
the profile are identical. If they are not, we return an error. The
check was introduced in #571.
Previously, the code included an assumption that the client
configuration was already loaded from the environment prior to
performing the check. This was not the case, and as such if the user
intended to use a non-default path to `.databrickscfg`, this path was
not used when performing the check.
The fix does the following:
* Resolve the configuration prior to performing the check.
* Don't treat the configuration file not existing as an error.
* Add unit tests.
Fixes#884.
## Tests
Unit tests and manual confirmation.
## Changes
Previous we (erroneously) kept the reference and merged into the
original tasks and not the copies which we later used to replace
existing tasks. Thus the merging of slices and references was incorrect.
Fixes#864
## Tests
Added a regression test
## 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
This PR adds higher-level wrappers for calling subprocesses. One of the
steps to get https://github.com/databricks/cli/pull/637 in, as
previously discussed.
The reason to add `process.Forwarded()` is to proxy Python's `input()`
calls from a child process seamlessly. Another use-case is plugging in
`less` as a pager for the list results.
## Tests
`make test`
## 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
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
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
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.
## 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
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
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
Aravind Segu
Pieter Noordhuis
Andrew Nester
shreyas-goenka
Lennart Kats (databricks)
dependabot[bot]
Gleb Kanterov
Ilia Babanov
Michał Szafrański
Arpit Jasapara
hectorcast-db
Serge Smertin