## Changes
Now prepare stage which does cleanup is execute once before every build,
so artifacts built into the same folder are correctly kept
Fixes workaround 2 from this issue #1602
## Tests
Added unit test
## Changes
This PR changes `diag.Diagnostics` to allow including multiple locations
associated with the diagnostic message. The diagnostics that now return
multiple locations with this PR are:
1. Warning for unknown keys in config.
2. Use of experimental.run_as
3. Accidental sync.exludes that exclude all files.
## Tests
Existing unit tests pass. New unit test case to assert on error message
when multiple locations are included.
Example output:
```
➜ bundle-playground-2 ~/cli2/cli/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 resources.yml:10:22
databricks.yml:13:22
Name: fix run_if
Target: default
Workspace:
User: shreyas.goenka@databricks.com
Path: /Users/shreyas.goenka@databricks.com/.bundle/fix run_if/default
Found 1 warning
```
## Changes
By default, construct a read/write instance. If constructed in read-only
mode, the underlying filer is wrapped in a readahead cache.
## Tests
* Filer integration tests pass.
* Manual test that caching is enabled when running on WSFS.
## Changes
DABs deployments should be isolated if `root_path` and workspace host
are different. This PR fixes a bug where local terraform state gets
piggybacked if the same cwd is used to deploy two isolated deployments
for the same bundle target. This can happen if:
1. A user switches to a different identity on the same machine.
2. The workspace host URL the bundle/target points to is changed.
3. A user changes the `root_path` while doing bundle development.
To solve this problem we rely on the lineage field available in the
terraform state, which is a uuid identifying unique terraform
deployments. There's a 1:1 mapping between a terraform deployment and a
bundle deployment.
For more details on how lineage works in terraform, see:
https://developer.hashicorp.com/terraform/language/state/backends#manual-state-pull-push
## Tests
Manually verified that changing the identity no longer results in the
incorrect terraform state being used. Also, new unit tests are added.
## Changes
This PR adds cli to the user agent sent downstream to the databricks
terraform provider when invoked via DABs.
## Tests
Unit tests. Based on the comment here
(10fe02075f/bundle/config/mutator/verify_cli_version_test.go (L113))
we don't need to set the version to make the test assertion work
correctly. This is likely because we use `go test` to run the tests
while the CLI is compiled and the version is set via `goreleaser`.
## Changes
This PR changes the location metadata associated with a `dyn.Value` to a
slice of locations. This will allow us to keep track of location
metadata across merges and overrides.
The convention is to treat the first location in the slice as the
primary location. Also, the semantics are the same as before if there's
only one location associated with a value, that is:
1. For complex values (maps, sequences) the location of the v1 is
primary in Merge(v1, v2)
2. For primitive values the location of v2 is primary in Merge(v1, v2)
## Tests
Modifying existing merge unit tests. Other existing unit tests and
integration tests pass.
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
We need a mechanism to invalidate the locally cached deployment state if
a user uses the same working directory to deploy to multiple distinct
deployments (separate targets, root_paths or even hosts).
This PR just adds the UUID to the deployment state in preparation for
invalidating this cache. The actual invalidation will follow up at a
later date (tracked in internal backlog).
## Tests
Unit test. Manually checked the deployment state is actually being
written.
## Changes
This change allows to specify UC volumes path as an artifact paths so
all artifacts (JARs, wheels) are uploaded to UC Volumes.
Example configuration is here:
```
bundle:
name: jar-bundle
workspace:
host: https://foo.com
artifact_path: /Volumes/main/default/foobar
artifacts:
my_java_code:
path: ./sample-java
build: "javac PrintArgs.java && jar cvfm PrintArgs.jar META-INF/MANIFEST.MF PrintArgs.class"
files:
- source: ./sample-java/PrintArgs.jar
resources:
jobs:
jar_job:
name: "Test Spark Jar Job"
tasks:
- task_key: TestSparkJarTask
new_cluster:
num_workers: 1
spark_version: "14.3.x-scala2.12"
node_type_id: "i3.xlarge"
spark_jar_task:
main_class_name: PrintArgs
libraries:
- jar: ./sample-java/PrintArgs.jar
```
## Tests
Manually + added E2E test for Java jobs
E2E test is temporarily skipped until auth related issues for UC for
tests are resolved
## Changes
Print diagnostics in 'bundle deploy' similar to 'bundle validate'. This
way if a bundle has any errors or warnings, they are going to be easy to
notice.
NB: due to how we render errors, there is one extra trailing new line in
output, preserved in examples below
## Example: No errors or warnings
```
% databricks bundle deploy
Building default...
Deploying resources...
Updating deployment state...
Deployment complete!
```
## Example: Error on load
```
% databricks bundle deploy
Error: Databricks CLI version constraint not satisfied. Required: >= 1337.0.0, current: 0.0.0-dev
```
## Example: Warning on load
```
% databricks bundle deploy
Building default...
Deploying resources...
Updating deployment state...
Deployment complete!
Warning: unknown field: foo
in databricks.yml:6:1
```
## Example: Error + warning on load
```
% databricks bundle deploy
Warning: unknown field: foo
in databricks.yml:6:1
Error: something went wrong
```
## Example: Warning on load + error in init
```
% databricks bundle deploy
Warning: unknown field: foo
in databricks.yml:6:1
Error: Failed to xxx
in yyy.yml
Detailed explanation
in multiple lines
```
## Tests
Tested manually
## Changes
This PR:
1. Moves the if mutator to the bundle package, to live with all-time
greats such as `bundle.Seq` and `bundle.Defer`. Also adds unit tests.
2. `bundle destroy` now returns early if `root_path` does not exist. We
do this by leveraging a `bundle.If` condition.
## Tests
Unit tests and manually.
Here's an example of what it'll look like once the bundle is destroyed.
```
➜ bundle-playground git:(master) ✗ cli bundle destroy
No active deployment found to destroy!
```
I would have added some e2e coverage for this as well, but the
`cobraTestRunner.Run()` method does not seem to return stdout/stderr
logs correctly. We can probably punt looking into it.
## Changes
Previously `SetVariables` mutator mutated typed configuration by using
`v.Set` for variables. This lead to variables `value` field not having
location information.
By using dynamic configuration mutation, we keep the same functionality
but also preserve location information for value when it's set from
default.
Fixes#1568#1538
## Tests
Added unit tests
## Changes
Now local library path in `libraries` section of foreach each tasks are
correctly replaced with remote path for this library when it's uploaded
to Databricks
## Tests
Added unit test
## Changes
At the moment we merge values of complex variables while more expected
behaviour is overriding the value with the target one.
## Tests
Added unit test
## Changes
The FUSE mount of the workspace file system on DBR doesn't include file
extensions for notebooks. When these notebooks are checked into a
repository, they do have an extension. PR #1457 added a filer type that
is aware of this disparity and makes these notebooks show up as if they
do have these extensions.
This change swaps out the native `vfs.Path` with one that uses this
filer when running on DBR.
Follow up: consolidate between interfaces exported by `filer.Filer` and
`vfs.Path`.
## Tests
* Unit tests pass
* (Manually ran a snapshot build on DBR against a bundle with notebooks)
---------
Co-authored-by: Andrew Nester <andrew.nester@databricks.com>
## Changes
Note: this doesn't cover _all_ filesystem interaction.
To intercept calls where read or stat files to determine their type, we
need a layer between our code and the `os` package calls that interact
with the local file system. Interception is necessary to accommodate
differences between a regular local file system and the FUSE-mounted
Workspace File System when running the CLI on DBR.
This change makes use of #1452 in the bundle struct.
It uses #1525 to access the bundle variable in path rewriting.
## Tests
* Unit tests pass.
* Integration tests pass.
## Changes
PyDABs output can omit empty sequences/mappings because we don't track
them as optional. There is no semantic difference between empty and
missing, which makes omitting correct. CLI detects that we falsely
modify input resources by deleting all empty collections.
To handle that, we extend `dyn.Override` to allow visitors to ignore
certain deletes. If we see that an empty sequence or mapping is deleted,
we revert such delete.
## Tests
Unit tests
---------
Co-authored-by: Pieter Noordhuis <pcnoordhuis@gmail.com>
## Changes
Allow PyDABs to report `dyn.Diagnostics` by writing to
`diagnostics.json` supplied as an argument, similar to `input.json` and
`output.json`
Such errors are not yet properly printed in `databricks bundle
validate`, which will be fixed in a follow-up PR.
## Tests
Unit tests
## Changes
Issue #1545 describes how a nil entry in the sync block caused an error.
The fix for this issue is in #1547. This change adds end-to-end test
coverage.
## Tests
New test passes on top of #1547.
## Changes
This combination of changes allows pretty-printing errors happening
during the "load" and "init" phases, including their locations.
Move to render code into a separate module dedicated to rendering
`diag.Diagnostics` in a human-readable format. This will be used for the
`bundle deploy` command.
Preserve the "bundle" value if an error occurs in mutators. Rewrite the
go templates to handle the case when the bundle isn't yet loaded if an
error occurs during loading, that is possible now.
Improve rendering for errors and warnings:
- don't render empty locations
- render "details" for errors if they exist
Add `root.ErrAlreadyPrinted` indicating that the error was already
printed, and the CLI entry point shouldn't print it again.
## Tests
Add tests for output, that are especially handy to detect extra newlines
## Changes
This PR makes two changes:
1. In https://github.com/databricks/cli/pull/1510 we'll be adding
multiple associated location metadata with a dyn.Value. The Go compiler
does not allow comparing structs if they contain slice values
(presumably due to multiple possible definitions for equality). In
anticipation for adding a `[]dyn.Location` type field to `dyn.Value`
this PR removes all direct comparisons of `dyn.Value` and instead relies
on the kind.
2. Retain location metadata for values in convert.FromTyped. The change
diff is exactly the same as https://github.com/databricks/cli/pull/1523.
It's been combined with this PR because they both depend on each other
to prevent test failures (forming a test failure deadlock).
Go patch used:
```
@@
var x expression
@@
-x == dyn.InvalidValue
+x.Kind() == dyn.KindInvalid
@@
var x expression
@@
-x != dyn.InvalidValue
+x.Kind() != dyn.KindInvalid
@@
var x expression
@@
-x == dyn.NilValue
+x.Kind() == dyn.KindNil
@@
var x expression
@@
-x != dyn.NilValue
+x.Kind() != dyn.KindNil
```
## Tests
Unit tests and integration tests pass.
## 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
Using dynamic values allows us to retain references like
`${resources.jobs...}` even when the type of field is not integer, eg:
`run_job_task`, or in general values that do not map to the Go types for
a field.
## Tests
Integration 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
To run bundle deploy from DBR we use an abstraction over the workspace
import / export APIs to create a `filer.Filer` and abstract the file
system. Walking the file tree in such a filer is expensive and requires
multiple API calls. This PR remove the two duplicate file tree walks
that happen by caching the result.
## 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
Currently, there are a number of issues with the non-happy-path flows
for token refresh in the CLI.
If the token refresh fails, the raw error message is presented to the
user, as seen below. This message is very difficult for users to
interpret and doesn't give any clear direction on how to resolve this
issue.
```
Error: token refresh: Post "https://adb-<WSID>.azuredatabricks.net/oidc/v1/token": http 400: {"error":"invalid_request","error_description":"Refresh token is invalid"}
```
When logging in again, I've noticed that the timeout for logging in is
very short, only 45 seconds. If a user is using a password manager and
needs to login to that first, or needs to do MFA, 45 seconds may not be
enough time. to an account-level profile, it is quite frustrating for
users to need to re-enter account ID information when that information
is already stored in the user's `.databrickscfg` file.
This PR tackles these two issues. First, the presentation of error
messages from `databricks auth token` is improved substantially by
converting the `error` into a human-readable message. When the refresh
token is invalid, it will present a command for the user to run to
reauthenticate. If the token fetching failed for some other reason, that
reason will be presented in a nice way, providing front-line debugging
steps and ultimately redirecting users to file a ticket at this repo if
they can't resolve the issue themselves. After this PR, the new error
message is:
```
Error: a new access token could not be retrieved because the refresh token is invalid. To reauthenticate, run `.databricks/databricks auth login --host https://adb-<WSID>.azuredatabricks.net`
```
To improve the login flow, this PR modifies `databricks auth login` to
auto-complete the account ID from the profile when present.
Additionally, it increases the login timeout from 45 seconds to 1 hour
to give the user sufficient time to login as needed.
To test this change, I needed to refactor some components of the CLI
around profile management, the token cache, and the API client used to
fetch OAuth tokens. These are now settable in the context, and a
demonstration of how they can be set and used is found in
`auth_test.go`.
Separately, this also demonstrates a sort-of integration test of the CLI
by executing the Cobra command for `databricks auth token` from tests,
which may be useful for testing other end-to-end functionality in the
CLI. In particular, I believe this is necessary in order to set flag
values (like the `--profile` flag in this case) for use in testing.
## Tests
Unit tests cover the unhappy and happy paths using the mocked API
client, token cache, and profiler.
Manually tested
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
`check_running_resources` now pulls the remote state without modifying
the bundle state, similar to how it was doing before. This avoids a
problem when we fail to compute deployment metadata for a deleted job
(which we shouldn't do in the first place)
`deploy_then_remove_resources_test` now also deploys and deletes a job
(in addition to a pipeline), which catches the error that this PR fixes.
## Tests
Unit and integ tests
## 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
Fixes https://github.com/databricks/cli/issues/559
The CLI generation is now stable and does not produce a diff for the
`bundle_descriptions.json` file.
Before a pointer to the schema was stored in the memo, which would be
mutated later to include the description. This lead to duplicate
documentation for schema components that were used in multiple places.
This PR fixes this issue.
Eg: Before all references of `pause_status` would have the same
description.
## Tests
Added regression test.
## Changes
This PR annotates any pipelines that were deployed using DABs to have
`deployment.kind` set to "BUNDLE", mirroring the annotation for Jobs
(similar PR for jobs FYI: https://github.com/databricks/cli/pull/880).
Breakglass UI is not yet available for pipelines, so this annotation
will just be used for revenue attribution ATM.
Note: The API field has been deployed in all regions including GovCloud.
## Tests
Unit tests and manually.
Manually verified that the kind and metadata_file_path are being set by
DABs, and are returned by a GET API to a pipeline deployed using a DAB.
Example:
```
"deployment": {
"kind":"BUNDLE",
"metadata_file_path":"/Users/shreyas.goenka@databricks.com/.bundle/bundle-playground/default/state/metadata.json"
},
```
`terraform show -json` (`terraform.Show()`) fails if the state file
contains resources with fields that non longer conform to the provider
schemas.
This can happen when you deploy a bundle with one version of the CLI,
then updated the CLI to a version that uses different databricks
terraform provider, and try to run `bundle run` or `bundle summary`.
Those commands don't recreate local terraform state (only `terraform
apply` or `plan` do) and terraform itself fails while parsing it.
[Terraform
docs](https://developer.hashicorp.com/terraform/language/state#format)
point out that it's best to use `terraform show` after successful
`apply` or `plan`.
Here we parse the state ourselves. The state file format is internal to
terraform, but it's more stable than our resource schemas. We only parse
a subset of fields from the state, and only update ID and ModifiedStatus
of bundle resources in the `terraform.Load` mutator.
## Changes
This is a minor improvement to the error about wheel tasks with older
DBR versions, since we get questions about it every now and then. It
also adds a pointer to the docs that were added since the original
messages was committed.
---------
Co-authored-by: Pieter Noordhuis <pcnoordhuis@gmail.com>
## 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
With this change, both job parameters and task parameters can be
specified as positional arguments to bundle run. How the positional
arguments are interpreted depends on the configuration of the job.
### Examples:
For a job that has job parameters configured a user can specify:
```
databricks bundle run my_job -- --param1=value1 --param2=value2
```
And the run is kicked off with job parameters set to:
```json
{
"param1": "value1",
"param2": "value2"
}
```
Similarly, for a job that doesn't use job parameters and only has
`notebook_task` tasks, a user can specify:
```
databricks bundle run my_notebook_job -- --param1=value1 --param2=value2
```
And the run is kicked off with task level `notebook_params` configured
as:
```json
{
"param1": "value1",
"param2": "value2"
}
```
For a job that doesn't doesn't use job parameters and only has either
`spark_python_task` or `python_wheel_task` tasks, a user can specify:
```
databricks bundle run my_python_file_job -- --flag=value other arguments
```
And the run is kicked off with task level `python_params` configured as:
```json
[
"--flag=value",
"other",
"arguments"
]
```
The same is applied to jobs with only `spark_jar_task` or
`spark_submit_task` tasks.
## Tests
Unit tests. Tested the completions manually.
## 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
I spotted a few call sites where the path of a test file was synthesized
multiple times. It is easier to capture the path as a variable and reuse
it.
## Changes
The sync struct initialization would recreate the deleted `file_path`.
This PR moves to not initializing the sync object to delete the
snapshot, thus fixing the lingering `file_path` after `bundle destroy`.
## Tests
Manually, and a integration test to prevent regression.
## Changes
This PR:
1. Uses bash to run the setup.sh script instead of the native busybox sh
shipped with alpine.
2. Verifies the checksums of the installed terraform CLI binaries.
## Tests
Manually. The docker image successfully builds.
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.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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alter it yourself. You can also trigger a rebase manually by commenting
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## Changes
Transform artifact files source patterns in build not upload stage
Resolves the following warning
```
artifact section is not defined for file at /Users/andrew.nester/dabs/wheel/target/myjar.jar. Skipping uploading. In order to use the define 'artifacts' section
```
## Tests
Unit test pass
## Changes
This PR makes changes to support creating a docker image for the CLI
with the `terraform` dependencies built in. This is useful for customers
that operate in a network-restricted environment. Normally DABs makes
API calls to registry.terraform.io to setup the terraform dependencies,
with this setup the CLI/DABs will rely on the provider binaries bundled
in the docker image.
### Specifically this PR makes the following changes:
----------------
Modifies the CLI release workflow to publish the docker images in the
Github Container Registry. URL:
https://github.com/databricks/cli/pkgs/container/cli.
We use docker support in `goreleaser` to build and publish the images.
Using goreleaser ensures the CLI packaged in the docker image is the
same release artifact as the normal releases. For more information see:
1. https://goreleaser.com/cookbooks/multi-platform-docker-images
2. https://goreleaser.com/customization/docker/
Other choices made include:
1. Using `alpine` as the base image. The reason is `alpine` is a small
and lightweight linux distribution (~5MB) and an industry standard.
2. Not using [docker
manifest](https://docs.docker.com/reference/cli/docker/manifest) to
create a multi-arch build. This is because the functionality is still
experimental.
------------------
Make the `DATABRICKS_TF_VERSION` and `DATABRICKS_TF_PROVIDER_VERSION`
environment variables optional for using the terraform file mirror.
While it's not strictly necessary to make the docker image work, it's
the "right" behaviour and reduces complexity. The rationale is:
- These environment variables here are needed so the Databricks CLI does
not accidentally use the file mirror bundled with VSCode if it's
incompatible. This does not require the env vars to be mandatory.
context: https://github.com/databricks/cli/pull/1294
- This makes the `Dockerfile` and `setup.sh` simpler. We don't need an
[entrypoint.sh script to set the version environment
variables](https://medium.com/@leonardo5621_66451/learn-how-to-use-entrypoint-scripts-in-docker-images-fede010f172d).
This also makes using an interactive terminal with `docker run -it ...`
work out of the box.
## Tests
Tested manually.
--------------------
To test the release pipeline I triggered a couple of dummy releases and
verified that the images are built successfully and uploaded to Github.
1. https://github.com/databricks/cli/pkgs/container/cli
3. workflow for release:
https://github.com/databricks/cli/actions/runs/8646106333
--------------------
I tested the docker container itself by setting up
[Charles](https://www.charlesproxy.com/) as an HTTP proxy and verifying
that no HTTP requests are made to `registry.terraform.io`
Before:
FYI, The Charles web proxy is hosted at localhost:8888.
```
shreyas.goenka@THW32HFW6T bundle-playground % rm -r .databricks
shreyas.goenka@THW32HFW6T bundle-playground % HTTP_PROXY="http://localhost:8888" HTTPS_PROXY="http://localhost:8888" cli bundle deploy
Uploading bundle files to /Users/shreyas.goenka@databricks.com/.bundle/bundle-playground/default/files...
Deploying resources...
Updating deployment state...
Deployment complete!
```
<img width="1275" alt="Screenshot 2024-04-11 at 3 21 45 PM"
src="https://github.com/databricks/cli/assets/88374338/15f37324-afbd-47c0-a40e-330ab232656b">
After:
This time bundle deploy is run from inside the docker container. We use
`host.docker.internal` to map to localhost on the host machine, and -v
to mount the host file system as a volume.
```
shreyas.goenka@THW32HFW6T bundle-playground % docker run -v ~/projects/bundle-playground:/bundle -v ~/.databrickscfg:/root/.databrickscfg -it --entrypoint /bin/sh -e HTTP_PROXY="http://host.docker.internal:8888" -e HTTPS_PROXY="http://host.docker.internal:8888" --network host ghcr.io/databricks/cli:latest-arm64
/ # cd /bundle/
/bundle # rm -r .databricks/
/bundle # databricks bundle deploy
Uploading bundle files to /Users/shreyas.goenka@databricks.com/.bundle/bundle-playground/default/files...
Deploying resources...
Updating deployment state...
Deployment complete!
```
<img width="1275" alt="Screenshot 2024-04-11 at 3 22 54 PM"
src="https://github.com/databricks/cli/assets/88374338/2a8f097e-734b-4b3e-8075-c02e98a1b275">
## Changes
In 0.217.0 we started to emit warning on unknown fields in YAML
configuration but wrongly considered YAML anchor blocks as unknown
field.
This PR fixes this by skipping normalising of YAML blocks.
## Tests
Added regression tests
## Changes
`preinit` script needs to be executed before processing configuration
files to allow the script to modify the configuration or add own
configuration files.
## Changes
Variable substitution works as if the variable reference is literally
replaced with its contents.
The following fields should be interpreted in the same way regardless of
where the variable is defined:
```yaml
foo: ${var.some_path}
bar: "./${var.some_path}"
```
Before this change, `foo` would inherit the location information of the
variable definition. After this change, it uses the location information
of the variable reference, making the behavior for `foo` and `bar`
identical.
Fixes#1330.
## Tests
The new test passes only with the fix.
[](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`.
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- Add `bundle debug terraform` command. It prints versions of the
Terraform and the Databricks Terraform provider. In the text mode it
also explains how to setup the CLI in environments with restricted
internet access.
- Use `DATABRICKS_TF_EXEC_PATH` env var to point Databricks CLI to the
Terraform binary. The CLI only uses it if `DATABRICKS_TF_VERSION`
matches the currently used terraform version.
- Use `DATABRICKS_TF_CLI_CONFIG_FILE` env var to point Terraform CLI
config that points to the filesystem mirror for the Databricks provider.
The CLI only uses it if `DATABRICKS_TF_PROVIDER_VERSION` matches the
currently used provider version.
Relevant PR on the VSCode extension side:
https://github.com/databricks/databricks-vscode/pull/1147
Example output of the `databricks bundle debug terraform`:
```
Terraform version: 1.5.5
Terraform URL: https://releases.hashicorp.com/terraform/1.5.5
Databricks Terraform Provider version: 1.38.0
Databricks Terraform Provider URL: https://github.com/databricks/terraform-provider-databricks/releases/tag/v1.38.0
Databricks CLI downloads its Terraform dependencies automatically.
If you run the CLI in an air-gapped environment, you can download the dependencies manually and set these environment variables:
DATABRICKS_TF_VERSION=1.5.5
DATABRICKS_TF_EXEC_PATH=/path/to/terraform/binary
DATABRICKS_TF_PROVIDER_VERSION=1.38.0
DATABRICKS_TF_CLI_CONFIG_FILE=/path/to/terraform/cli/config.tfrc
Here is an example *.tfrc configuration file:
disable_checkpoint = true
provider_installation {
filesystem_mirror {
path = "/path/to/a/folder/with/databricks/terraform/provider"
}
}
The filesystem mirror path should point to the folder with the Databricks Terraform Provider. The folder should have this structure: /registry.terraform.io/databricks/databricks/terraform-provider-databricks_1.38.0_ARCH.zip
For more information about filesystem mirrors, see the Terraform documentation: https://developer.hashicorp.com/terraform/cli/config/config-file#filesystem_mirror
```
---------
Co-authored-by: shreyas-goenka <88374338+shreyas-goenka@users.noreply.github.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 fixes bundle schema being broken because `for_each_task: null`
was set in the generated schema. This is not valid according to the JSON
schema specification and thus the Red Hat YAML VSCode extension was
failing to parse the YAML configuration.
This PR fixes: https://github.com/databricks/cli/issues/1312
## Tests
The fix itself was tested manually. I asserted that the autocompletion
works now. This was mistakenly overlooked the first time around when the
regression was introduced in https://github.com/databricks/cli/pull/1204
because the YAML extension provides best-effort autocomplete suggestions
even if the JSON schema fails to load.
To prevent future regressions we also add a test to assert that the JSON
schema generated itself is a valid JSON schema object. This is done via
using the `ajv-cli` to validate the schema. This package is also used by
the Red Hat YAML extension and thus provides a high fidelity check for
ensuring the JSON schema is valid.
Before, with the old schema:
```
shreyas.goenka@THW32HFW6T cli-versions % ajv validate -s proj/schema-216.json -d ../bundle-playground-3/databricks.yml
schema proj/schema-216.json is invalid
error: schema is invalid: data/properties/resources/properties/jobs/additionalProperties/properties/tasks/items/properties/for_each_task must be object,boolean, data/properties/resources/properties/jobs/additionalProperties/properties/tasks/items must be array, data/properties/resources/properties/jobs/additionalProperties/properties/tasks/items must match a schema in anyOf
```
After, with the new schema:
```
shreyas.goenka@THW32HFW6T cli-versions % ajv validate -s proj/schema-dev.json -d ../bundle-playground-3/databricks.yml
../bundle-playground-3/databricks.yml valid
```
After, autocomplete suggestions:
<img width="600" alt="Screenshot 2024-03-27 at 6 35 57 PM"
src="https://github.com/databricks/cli/assets/88374338/d0a62402-e323-4f36-854d-332b33cbeab8">
## 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
These tests were located in `bundle/tests/bundle` which meant they were
unable to reuse the helper functions defined in the `bundle/tests`
package. There is no need for these tests to live outside the package.
## Tests
Existing tests pass.
## 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
CheckRunningResource does `terraform.Show` which (I believe) expects
valid `bundle.tf.json` which is only written as part of
`terraform.Write` later.
With this PR order is changed.
Fixes#1286
## Tests
Added regression E2E test
## 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
This PR:
1. Adds an integration test for mlops-stacks that checks the
initialization and deployment of the project was successful.
2. Fixes a bug in the initialization of templates from non-tty. We need
to process the input parameters in order since their descriptions can
refer to input parameters that came before in the interactive UX.
## Tests
The integration test passes in CI.
## 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
The databricks terraform provider does not allow changing permission of
the current user. Instead, the current identity is implictly set to be
the owner of all resources on the platform side.
This PR introduces a mutator to filter permissions from the bundle
configuration at deploy time, allowing users to define permissions for
their own identities in their bundle config.
This would allow configurations like, allowing both alice and bob to
collaborate on the same DAB:
```
permissions:
level: CAN_MANAGE
user_name: alice
level: CAN_MANAGE
user_name: bob
```
This PR is a reincarnation of
https://github.com/databricks/cli/pull/1145. The earlier attempt had to
be reverted due to metadata loss converting to and from the dynamic
configuration representation (reverted here:
https://github.com/databricks/cli/pull/1179)
## Tests
Unit test and manually
## 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.
Check if `bundle.tf.json` doesn't exist and create it before executing
`terraform init` (inside `terraform.Load`)
Fixes a problem when during `terraform.Load` it fails with:
```
Error: Failed to load plugin schemas
Error while loading schemas for plugin components: Failed to obtain provider
schema: Could not load the schema for provider
registry.terraform.io/databricks/databricks: failed to instantiate provider
"registry.terraform.io/databricks/databricks" to obtain schema: unavailable
provider "registry.terraform.io/databricks/databricks"..
```
## Changes
Upgrade Terraform provider to 1.37.0
Currently we're using 1.36.2 version which uses Go SDK 0.30 which does
not have U2M enabled for all clouds.
Upgrading to 1.37.0 allows TF provider (and thus DABs) to use U2M
Fixes#1231
## Changes
Currently, when the CLI run a list API call (like list jobs), it uses
the `List*All` methods from the SDK, which list all resources in the
collection. This is very slow for large collections: if you need to list
all jobs from a workspace that has 10,000+ jobs, you'll be waiting for
at least 100 RPCs to complete before seeing any output.
Instead of using List*All() methods, the SDK recently added an iterator
data structure that allows traversing the collection without needing to
completely list it first. New pages are fetched lazily if the next
requested item belongs to the next page. Using the List() methods that
return these iterators, the CLI can proactively print out some of the
response before the complete collection has been fetched.
This involves a pretty major rewrite of the rendering logic in `cmdio`.
The idea there is to define custom rendering logic based on the type of
the provided resource. There are three renderer interfaces:
1. textRenderer: supports printing something in a textual format (i.e.
not JSON, and not templated).
2. jsonRenderer: supports printing something in a pretty-printed JSON
format.
3. templateRenderer: supports printing something using a text template.
There are also three renderer implementations:
1. readerRenderer: supports printing a reader. This only implements the
textRenderer interface.
2. iteratorRenderer: supports printing a `listing.Iterator` from the Go
SDK. This implements jsonRenderer and templateRenderer, buffering 20
resources at a time before writing them to the output.
3. defaultRenderer: supports printing arbitrary resources (the previous
implementation).
Callers will either use `cmdio.Render()` for rendering individual
resources or `io.Reader` or `cmdio.RenderIterator()` for rendering an
iterator. This separate method is needed to safely be able to match on
the type of the iterator, since Go does not allow runtime type matches
on generic types with an existential type parameter.
One other change that needs to happen is to split the templates used for
text representation of list resources into a header template and a row
template. The template is now executed multiple times for List API
calls, but the header should only be printed once. To support this, I
have added `headerTemplate` to `cmdIO`, and I have also changed
`RenderWithTemplate` to include a `headerTemplate` parameter everywhere.
## Tests
- [x] Unit tests for text rendering logic
- [x] Unit test for reflection-based iterator construction.
---------
Co-authored-by: Andrew Nester <andrew.nester@databricks.com>
## 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 builds on #1098 and uses the `dyn.Value` representation of the
bundle configuration to generate the Terraform JSON definition of
resources in the bundle.
The existing code (in `BundleToTerraform`) was not great and in an
effort to slightly improve this, I added a package `tfdyn` that includes
dedicated files for each resource type. Every resource type has its own
conversion type that takes the `dyn.Value` of the bundle-side resource
and converts it into Terraform resources (e.g. a job and optionally its
permissions).
Because we now use a `dyn.Value` as input, we can represent and emit
zero-values that have so far been omitted. For example, setting
`num_workers: 0` in your bundle configuration now propagates all the way
to the Terraform JSON definition.
## Tests
* Unit tests for every converter. I reused the test inputs from
`convert_test.go`.
* Equivalence tests in every existing test case checks that the
resulting JSON is identical.
* I manually compared the TF JSON file generated by the CLI from the
main branch and from this PR on all of our bundles and bundle examples
(internal and external) and found the output doesn't change (with the
exception of the odd zero-value being included by the version in this
PR).
## 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 `${var.num_workers}` for an integer `workers` field was impossible
until now (though not implemented in this change).
The loader for a `dyn.Value` includes functionality to capture any and
all type mismatches between the user-defined configuration and the
expected types. These mismatches can be surfaced as validation errors in
future PRs.
Given that many mutators expect the typed struct to be the source of
truth, this change converts between the dynamic representation and the
typed representation on mutator entry and exit. Existing mutators can
continue to modify the typed representation and these modifications are
reflected in the dynamic representation (see `MarkMutatorEntry` and
`MarkMutatorExit` in `bundle/config/root.go`).
Required changes included in this change:
* The existing interpolation package is removed in favor of
`libs/dyn/dynvar`.
* Functionality to merge job clusters, job tasks, and pipeline clusters
are now all broken out into their own mutators.
To be implemented later:
* Allow variable references for non-string types.
* Surface diagnostics about the configuration provided by the user in
the validation output.
* Some mutators use a resource's configuration file path to resolve
related relative paths. These depend on `bundle/config/paths.Path` being
set and populated through `ConfigureConfigFilePath`. Instead, they
should interact with the dynamically typed configuration directly. Doing
this also unlocks being able to differentiate different base paths used
within a job (e.g. a task override with a relative path defined in a
directory other than the base job).
## Tests
* Existing unit tests pass (some have been modified to accommodate)
* Integration tests pass
## Changes
We plan to use the any-equivalent of a `dyn.Value` such that we can use
variable references for non-string fields (e.g.
`${databricks_job.some_job.id}` where an integer is expected), as well
as properly emit zero values for primitive types (e.g. 0 for integers or
false for booleans).
This change is in preparation for the above.
## Tests
Unit tests.
## Changes
* Update `go.mod` with latest dependencies
* Update `go.mod` to require Go 1.21 to match root `go.mod`
* Regenerate structs for Terraform provider v1.36.2
## Tests
n/a
## 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
The OpenAPI spec used to generate the CLI doesn't match the version used
for the SDK version that the CLI currently depends on. This PR
regenerates the CLI based on the same version of the OpenAPI spec used
by the SDK on v0.30.1.
## Tests
<!-- How is this tested? -->
## Changes
Bundle schema generation does not support recursive API fields. This PR
skips generation for for_each_task until we add proper support for
recursive types in the bundle schema.
## Tests
Manually. This fixes the generation of the CLI and the bundle schema
command works as expected, with the sub-schema for `for_each_task` being
set to null in the output.
```
"for_each_task": null,
```
## Changes
Added `--restart` flag for `bundle run` command
When running with this flag, `bundle run` will cancel all existing runs
before starting a new one
## Tests
Manually
## 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
This reverts commit 4131069a4b.
The integration test for metadata computation failed. The back and forth
to `dyn.Value` erases unexported fields that the code currently still
depends on. We'll have to retry on top of #1098.
## Changes
Group bundle run flags by job and pipeline types
## Tests
```
Run a resource (e.g. a job or a pipeline)
Usage:
databricks bundle run [flags] KEY
Job Flags:
--dbt-commands strings A list of commands to execute for jobs with DBT tasks.
--jar-params strings A list of parameters for jobs with Spark JAR tasks.
--notebook-params stringToString A map from keys to values for jobs with notebook tasks. (default [])
--params stringToString comma separated k=v pairs for job parameters (default [])
--pipeline-params stringToString A map from keys to values for jobs with pipeline tasks. (default [])
--python-named-params stringToString A map from keys to values for jobs with Python wheel tasks. (default [])
--python-params strings A list of parameters for jobs with Python tasks.
--spark-submit-params strings A list of parameters for jobs with Spark submit tasks.
--sql-params stringToString A map from keys to values for jobs with SQL tasks. (default [])
Pipeline Flags:
--full-refresh strings List of tables to reset and recompute.
--full-refresh-all Perform a full graph reset and recompute.
--refresh strings List of tables to update.
--refresh-all Perform a full graph update.
Flags:
-h, --help help for run
--no-wait Don't wait for the run to complete.
Global Flags:
--debug enable debug logging
-o, --output type output type: text or json (default text)
-p, --profile string ~/.databrickscfg profile
-t, --target string bundle target to use (if applicable)
--var strings set values for variables defined in bundle config. Example: --var="foo=bar"
```
## Changes
The databricks terraform provider does not allow changing permission of
the current user. Instead, the current identity is implictly set to be
the owner of all resources on the platform side.
This PR introduces a mutator to filter permissions from the bundle
configuration, allowing users to define permissions for their own
identities in their bundle config.
This would allow configurations like, allowing both alice and bob to
collaborate on the same DAB:
```
permissions:
level: CAN_MANAGE
user_name: alice
level: CAN_MANAGE
user_name: bob
```
## Tests
Unit test and manually
## 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
This PR sets run as permissions after variable interpolation.
Terraform does not allow specifying permissions for current user.
The following configuration would fail becuase we would assign a
permission block for self, bypassing this check here:
4ee926b885/bundle/config/mutator/run_as.go (L47)
```
run_as:
user_name: ${workspace.current_user.userName}
```
## Tests
Manually, setting run_as to ${workspace.current_user.userName} works now
Andrew Nester
shreyas-goenka
Pieter Noordhuis
Gleb Kanterov
dependabot[bot]
Lennart Kats (databricks)
Aravind Segu
Miles Yucht
Ilia Babanov