## Changes
Added support for complex variables
Now it's possible to add and use complex variables as shown below
```
bundle:
name: complex-variables
resources:
jobs:
my_job:
job_clusters:
- job_cluster_key: key
new_cluster: ${var.cluster}
tasks:
- task_key: test
job_cluster_key: key
variables:
cluster:
description: "A cluster definition"
type: complex
default:
spark_version: "13.2.x-scala2.11"
node_type_id: "Standard_DS3_v2"
num_workers: 2
spark_conf:
spark.speculation: true
spark.databricks.delta.retentionDurationCheck.enabled: false
```
Fixes#1298
- [x] Support for complex variables
- [x] Allow variable overrides (with shortcut) in targets
- [x] Don't allow to provide complex variables via flag or env variable
- [x] Fail validation if complex value is used but not `type: complex`
provided
- [x] Support using variables inside complex variables
## Tests
Added unit tests
---------
Co-authored-by: shreyas-goenka <88374338+shreyas-goenka@users.noreply.github.com>
## Changes
For a future change where the inner rewriting functions need access to
the underlying bundle, this change makes preparations.
All values were passed via the stack before and adding yet another value
would make the code less readable.
## Tests
Unit tests pass.
## Changes
Replace stdin/stdout with files in `PythonMutator`. Files are created in
a temporary directory.
Rename `ApplyPythonMutator` to `PythonMutator`.
Add test for `dyn.Location` behavior during the "load" stage.
## Tests
Unit tests
## Changes
With https://github.com/databricks/cli/pull/1507 and
https://github.com/databricks/cli/pull/1511 we are clarifying the
semantics associated with `dyn.InvalidValue` and `dyn.NilValue`. An
invalid value is the default zero value and is used to signals the
complete absence of the value.
A nil value, on the other hand, is a valid value for a piece of
configuration and signals explicitly setting a key to nil in the
configuration tree. In keeping with that theme, this PR returns
`dyn.InvalidValue` instead of `dyn.NilValue` at error sites. This change
is not expected to have a material change in behaviour and is being done
to set the right convention since we have well-defined semantics
associated with both `NilValue` and `InvalidValue`.
## Tests
Unit tests and integration tests pass. Also manually scanned the changes
and the associated call sites to verify the `NilValue` value itself was
not being relied upon.
## Changes
When a configuration defines:
```yaml
run_as:
```
It first showed up as `run_as -> nil` in the dynamic configuration only
to later be converted to `run_as -> {}` while going through typed
conversion. We were using the presence of a key to initialize an empty
value. This is incorrect and it should have remained a nil value.
This conversion was happening in `convert.FromTyped` where any struct
always returned a map value. Instead, it should only return a map value
in any one of these cases: 1) the struct has elements, 2) the struct was
originally a map in the dynamic configuration, or 3) the struct was
initialized to a non-empty pointer value.
Stacked on top of #1516 and #1518.
## Tests
* Unit tests pass.
* Integration tests pass.
* Manually ran through bundle CRUD with a bundle without resources.
## Changes
This cherry-picks from #1490 to address an issue that came up in #1511.
The function `dyn.SetByPath` requires intermediate values to be present.
If they are not, it returns an error that it cannot index a map. This is
not an issue on main, where the intermediate maps are always created,
even if they are not present in the dynamic configuration tree. As of
#1511, we'll no longer populate empty maps for empty structs if they are
not explicitly set (i.e., a non-nil pointer). This change writes a bool
pointer to avoid this issue altogether.
## Tests
Unit tests pass.
## Changes
Add ApplyPythonMutator, which will fork the Python subprocess and
process pipe bundle configuration through it.
It's enabled through `experimental` section, for example:
```yaml
experimental:
pydabs:
enable: true
venv_path: .venv
```
For now, it's limited to two phases in the mutator pipeline:
- `load`: adds new jobs
- `init`: adds new jobs, or modifies existing ones
It's enforced that no jobs are modified in `load` and not jobs are
deleted in `load/init`, because, otherwise, it will break existing
assumptions.
## Tests
Unit tests
## Changes
Previously, the functions `Get` and `Index` returned `dyn.NilValue` to
indicate that a map key or sequence index wasn't found. This is a valid
value, so we need to differentiate between actual absence and a real
`dyn.NilValue`. We do this with the zero value of a `dyn.Value` (also
captured in the constant `dyn.InvalidValue`).
## Tests
* Unit tests.
* Renamed `Get` and `Index` to find and update all call sites.
## Changes
This PR fixes the behaviour when variables were not overridden with
lookup value from targets if these variables had any default value set
in the default target.
Fixes#1449
## Tests
Added regression test
## Changes
1. Removes `DefaultMutatorsForTarget` which is no longer used anywhere
2. Makes SnapshotPath a private field. It's no longer needed by data
structures outside its package.
FYI, I also tried finding other instances of dead code but I could not
find anything else that was safe to remove. I used
https://go.dev/blog/deadcode to search for them, and the other instances
either implemented an interface, increased test coverage for some of our
other code paths or there was some other reason I could not remove them
(like autogenerated functions or used in tests).
Good sign our codebase is mostly clean (at least superficially).
## Changes
From the [documentation](https://pkg.go.dev/os#IsNotExist) on the
functions in the `os` package:
> This function predates errors.Is. It only supports errors returned by
the os package.
> New code should use errors.Is(err, fs.ErrNotExist).
This issue surfaced while working on using a different `vfs.Path`
implementation that uses errors from the `fs` package. Calls to
`os.IsNotExist` didn't return true for errors that wrap
`fs.ErrNotExist`.
## Tests
n/a
## 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 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
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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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.
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`@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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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
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
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
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
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
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
Andrew Nester
Pieter Noordhuis
Gleb Kanterov
shreyas-goenka
Lennart Kats (databricks)
Aravind Segu
dependabot[bot]