## Changes
Library glob expansion happens during deployment. Before that, all
entries that refer to local paths in resource definitions are made
relative to the _sync root_. Before #1694, they were made relative to
the _bundle root_. This PR didn't update the library glob expansion code
to use the sync root path.
If you were using the sync paths setting with library globs, the CLI
would fail to expand the globs because the code was using the wrong path
to anchor those globs.
This change fixes the issue.
## Tests
Manually confirmed that this fixes the issue reported in #1755.
## Changes
We added a custom resolver for the cluster to add filtering for the
cluster source when we list all clusters.
Without the filtering listing could take a very long time (5-10 mins)
which leads to lookup timeouts.
## Tests
Existing unit tests passing
## Changes
Some call sites hold on to the `dyn.Path` provided to them by the
callback. It must therefore never be mutated after the callback returns,
or these mutations leak out into unknown scope.
This change means it is no longer possible for this failure mode to
happen.
## Tests
Unit test.
## Changes
Fixes an `Error: no value assigned to required variable <variable>.`
when the main complex variable definition is defined in one file but
target override is defined in separate file which is included in the
main one.
## Tests
Added regression test
## Changes
DLT pipeline recreations are destructive. They can lead to lost history
of previous updates, outage of the tables temporarily and are
potentially computationally expensive. Thus we make a breaking change
where a prompt is shown to the user if there configuration changes will
lead to a DLT recreation.
Users can skip the prompt by specifying the `--auto-approve` flag.
This PR also fixes an issue with our test runner where logs from the
cmdio.Logger would not get propagated to the reader returned by our
cobra test runner.
## Tests
Manually, and new unit and integration tests.
```
➜ bundle-playground-3 cli bundle deploy
Uploading bundle files to /Users/63ec021d-b0c6-49c0-93a0-5123953a1cb2/.bundle/test/development/files...
The following DLT pipelines will be recreated. Underlying tables will be unavailable for a transient period until the newly recreated pipelines are run once successfully. History of previous pipeline update runs will be lost because of recreation:
recreate pipeline foo
Would you like to proceed? [y/n]: n
Deployment cancelled!
```
## Changes
We were not using the readers and writers set in the test fixtures in
the progress logger. This PR fixes that. It also modifies
`TestAccAbortBind`, which was implicitly relying on the bug.
I encountered this bug while working on
https://github.com/databricks/cli/pull/1672.
## Tests
Manually.
From non-tty:
```
Error: failed to bind the resource, err: This bind operation requires user confirmation, but the current console does not support prompting. Please specify --auto-approve if you would like to skip prompts and proceed.
```
From tty, bind works as expected.
```
Confirm import changes? Changes will be remotely applied only after running 'bundle deploy'. [y/n]: y
Updating deployment state...
Successfully bound databricks_pipeline with an id '9d2dedbb-f522-4503-96ba-4bc4d5bfa77d'. Run 'bundle deploy' to deploy changes to your workspace
```
## Changes
Explain the error when the `databricks-pydabs` package is not installed
or the Python environment isn't correctly activated.
Example output:
```
Error: python mutator process failed: ".venv/bin/python3 -m databricks.bundles.build --phase load --input .../input.json --output .../output.json --diagnostics .../diagnostics.json: exit status 1", use --debug to enable logging
.../.venv/bin/python3: Error while finding module specification for 'databricks.bundles.build' (ModuleNotFoundError: No module named 'databricks')
Explanation: 'databricks-pydabs' library is not installed in the Python environment.
If using Python wheels, ensure that 'databricks-pydabs' is included in the dependencies,
and that the wheel is installed in the Python environment:
$ .venv/bin/pip install -e .
If using a virtual environment, ensure it is specified as the venv_path property in databricks.yml,
or activate the environment before running CLI commands:
experimental:
pydabs:
venv_path: .venv
```
## Tests
Unit tests
## Changes
Preserve diagnostics if there are any errors or warnings when
PythonMutator normalizes output. If anything goes wrong during
conversion, diagnostics contain the relevant location and path.
## Tests
Unit tests
## Changes
This ensures that the CLI and Terraform can both use an Azure CLI
session configured under a non-standard path. This is the default
behavior on Azure DevOps when using the AzureCLI@2 task.
Fixes#1722.
## Tests
Unit test.
## Changes
Consider serverless clusters as compatible for Python wheel tasks.
Fixes a `Python wheel tasks require compute with DBR 13.3+ to include
local libraries` warning shown for serverless clusters
## Changes
* Provide a more helpful error when using an artifact_path based on
/Volumes
* Allow the use of short_names in /Volumes paths
## Example cases
Example of a valid /Volumes artifact_path:
* `artifact_path:
/Volumes/catalog/schema/${workspace.current_user.short_name}/libs`
Example of an invalid /Volumes path (when using `mode: development`):
* `artifact_path: /Volumes/catalog/schema/libs`
* Resulting error: `artifact_path should contain the current username or
${workspace.current_user.short_name} to ensure uniqueness when using
'mode: development'`
## Changes
Fixes issue introduced here https://github.com/databricks/cli/pull/1699
where PyPi packages were treated as local library.
The reason is that `libraryPath` returns an empty string as a path for
PyPi packages and then `IsLibraryLocal` treated empty string as local
path.
Both of these functions are fixed in this PR.
## Tests
Added regression test
## Changes
This changes makes sure we ignore CLI version check on development
builds of the CLI.
Before:
```
$ cat databricks.yml | grep cli_version
databricks_cli_version: ">= 0.223.1"
$ cli bundle deploy
Error: Databricks CLI version constraint not satisfied. Required: >= 0.223.1, current: 0.0.0-dev+06b169284737
```
after
```
...
$ cli bundle deploy
...
Warning: Ignoring Databricks CLI version constraint for development build. Required: >= 0.223.1, current: 0.0.0-dev+d52d6f08fcd5
```
## Tests
<!-- How is this tested? -->
## Changes
This field allows a user to configure paths to synchronize to the
workspace.
Allowed values are relative paths to files and directories anchored at
the directory where the field is set. If one or more values traverse up
the directory tree (to an ancestor of the bundle root directory), the
CLI will dynamically determine the root path to use to ensure that the
file tree structure remains intact.
For example, given a `databricks.yml` in `my_bundle` that includes:
```yaml
sync:
paths:
- ../common
- .
```
Then upon synchronization, the workspace will look like:
```
.
├── common
│ └── lib.py
└── my_bundle
├── databricks.yml
└── notebook.py
```
If not set behavior remains identical.
## Tests
* Newly added unit tests for the mutators and under `bundle/tests`.
* Manually confirmed a bundle without this configuration works the same.
* Manually confirmed a bundle with this configuration works.
## Changes
In https://github.com/databricks/cli/pull/1490 we regressed and started
using the development mode prefix for UC schemas regardless of the mode
of the bundle target.
This PR fixes the regression and adds a regression test
## Tests
Failing integration tests pass now.
## Changes
While experimenting with DAB I discovered that requirements libraries
are being ignored.
One thing worth mentioning is that `bundle validate` runs successfully,
but `bundle deploy` fails. This PR only covers the second part.
## Tests
<!-- How is this tested? -->
Added a unit test
## Changes
Make `pydabs/venv_path` optional. When not specified, CLI detects the
Python interpreter using `python.DetectExecutable`, the same way as for
`artifacts`. `python.DetectExecutable` works correctly if a virtual
environment is activated or `python3` is available on PATH through other
means.
Extract the venv detection code from PyDABs into `libs/python/detect`.
This code will be used when we implement the `python/venv_path` section
in `databricks.yml`.
## Tests
Unit tests and manually
---------
Co-authored-by: Pieter Noordhuis <pcnoordhuis@gmail.com>
## Changes
These tests inadvertently re-ran mutators, the first time through
`loadTarget` and the second time by running `phases.Initialize()`
themselves. Some of the mutators that are executed in
`phases.Initialize()` are also run as part of `loadTarget`. This is
overdue a refactor to make it unambiguous what runs when. Until then,
this removes the duplicated execution.
## Tests
Unit tests pass.
## Changes
This PR addressed post-merge feedback from
https://github.com/databricks/cli/pull/1673.
## Tests
Unit tests, and manually.
```
Error: experiment undefined-experiment is not defined
at resources.experiments.undefined-experiment
in databricks.yml:11:26
Error: job undefined-job is not defined
at resources.jobs.undefined-job
in databricks.yml:6:19
Error: pipeline undefined-pipeline is not defined
at resources.pipelines.undefined-pipeline
in databricks.yml:14:24
Name: undefined-job
Target: default
Found 3 errors
```
## Changes
This adds configurable transformations based on the transformations
currently seen in `mode: development`.
Example databricks.yml showcasing how some transformations:
```
bundle:
name: my_bundle
targets:
dev:
presets:
prefix: "myprefix_" # prefix all resource names with myprefix_
pipelines_development: true # set development to true by default for pipelines
trigger_pause_status: PAUSED # set pause_status to PAUSED by default for all triggers and schedules
jobs_max_concurrent_runs: 10 # set max_concurrent runs to 10 by default for all jobs
tags:
dev: true
```
## Tests
* Existing process_target_mode tests that were adapted to use this new
code
* Unit tests specific for the new mutator
* Unit tests for config loading and merging
* Manual e2e testing
## Changes
Before this change, the fileset library would take a single root path
and list all files in it. To support an allowlist of paths to list (much
like a Git `pathspec` without patterns; see [pathspec](pathspec)), this
change introduces an optional argument to `fileset.New` where the caller
can specify paths to list. If not specified, this argument defaults to
list `.` (i.e. list all files in the root).
The motivation for this change is that we wish to expose this pattern in
bundles. Users should be able to specify which paths to synchronize
instead of always only synchronizing the bundle root directory.
[pathspec]:
https://git-scm.com/docs/gitglossary#Documentation/gitglossary.txt-aiddefpathspecapathspec
## Tests
New and existing unit tests.
## Changes
This PR removes the dependency to the `databricks-sdk-go/openapi`
package by copying the struct and functions that are needed in a new
`schema/spec.go` file.
The reason to remove this dependency is that it is being deprecated.
Copying the code in the `cli` repo seems reasonable given that it only
uses a couple of very small structs.
## Tests
Verified that CLI code can be properly generated after this change.
## Changes
Previously for all the libraries referenced in configuration DABs made
sure that there is corresponding artifact section.
But this is not really necessary and flexible, because local libraries
might be built outside of dabs context.
It also created difficult to follow logic in code where we back
referenced libraries to artifacts which was difficult to fllow
This PR does 3 things:
1. Allows all local libraries referenced in DABs config to be uploaded
to remote
2. Simplifies upload and glob references expand logic by doing this in
single place
3. Speed things up by uploading library only once and doing this in
parallel
## Tests
Added unit + integration tests + made sure that change is backward
compatible (no changes in existing tests)
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
Since locations are already tracked in the dynamic value tree, we no
longer need to track it at the resource/artifact level. This PR:
1. Removes use of `paths.Paths`. Uses dyn.Location instead.
2. Refactors the validation of resources not being empty valued to be
generic across all resource types.
## Tests
Existing unit tests.
## Changes
This didn't work as expected because the generic build mutator called
into the type-specific build mutator in the middle of the function. This
invalidated the `config.Artifact` pointer that was being mutated later
on, effectively hiding these mutations from its caller.
To fix this, I turned glob expansion into its own mutator. It now works
as expected, _and_ produces better errors if the glob patterns are
invalid or do not match files.
## Tests
Unit tests.
Manual verification:
```
% databricks bundle deploy
Building sbt_example...
Error: target/scala-2.12/sbt-e[xam22ple*.jar: syntax error in pattern
at artifacts.sbt_example.files[1].source
in databricks.yml:15:17
```
## Changes
This change enables overriding the default value of job parameters in
target overrides.
This is the same approach we already take for job clusters and job
tasks.
Closes#1620.
## Tests
Mutator unit tests and lightweight end-to-end tests.
## Changes
In https://github.com/databricks/cli/pull/1618 we introduced prepare
step in which Python wheel folder was cleaned. Now it was cleaned
everytime instead of only when there is a build command how it is used
to work.
This PR fixes it by only cleaning up dist folder when there is a build
command for wheels.
Fixes#1638
## Tests
Added regression test
# Changes
With https://github.com/databricks/cli/pull/1413 we started to compute
and partially print the plan if it contained deletion of UC schemas.
This PR uses the precomputed plan to avoid double planning when actually
doing the terraform plan.
This fixes a performance regression introduced in
https://github.com/databricks/cli/pull/1413.
# Tests
Tested manually.
1. Verified bundle deployment still works and deploys resources.
2. Verified that the precomputed plan is indeed being used by attaching
a debugger and removing the plan file right before the terraform apply
process is spawned and asserting that terraform apply fails because the
plan is not found.
## Changes
This PR adds support for UC Schemas to DABs. This allows users to define
schemas for tables and other assets their pipelines/workflows create as
part of the DAB, thus managing the life-cycle in the DAB.
The first version has a couple of intentional limitations:
1. The owner of the schema will be the deployment user. Changing the
owner of the schema is not allowed (yet). `run_as` will not be
restricted for DABs containing UC schemas. Let's limit the scope of
run_as to the compute identity used instead of ownership of data assets
like UC schemas.
2. API fields that are present in the update API but not the create API.
For example: enabling predictive optimization is not supported in the
create schema API and thus is not available in DABs at the moment.
## Tests
Manually and integration test. Manually verified the following work:
1. Development mode adds a "dev_" prefix.
2. Modified status is correctly computed in the `bundle summary`
command.
3. Grants work as expected, for assigning privileges.
4. Variable interpolation works for the schema ID.
## Changes
This PR:
1. Uses dynamic walking (via the `dyn.MapByPattern` func) to validate no
two resources have the same resource key. The allows us to remove this
validation at merge time.
2. Modifies `dyn.Mapping` to always return a sorted slice of pairs. This
makes traversal functions like `dyn.Walk` or `dyn.MapByPattern`
deterministic.
## Tests
Unit tests. Also manually.
## Changes
Some diagnostics can have multiple paths associated with them. For
instance, ensuring that unique resource keys are used across all
resources. This PR extends `diag.Diagnostic` to accept multiple paths.
This PR is symmetrical to
https://github.com/databricks/cli/pull/1610/files
## Tests
Unit tests
## Changes
Right now we ask users for two confirmations when destroying a bundle.
One to destroy the resources and one to delete the files. This PR
consolidates the two prompts into one.
## Tests
Manually
Destroying a bundle with no resources:
```
➜ bundle-playground git:(master) ✗ cli bundle destroy
All files and directories at the following location will be deleted: /Users/shreyas.goenka@databricks.com/.bundle/bundle-playground/default
Would you like to proceed? [y/n]: y
No resources to destroy
Updating deployment state...
Deleting files...
Destroy complete!
```
Destroying a bundle with no remote state:
```
➜ bundle-playground git:(master) ✗ cli bundle destroy
No active deployment found to destroy!
```
When a user cancells a deployment:
```
➜ bundle-playground git:(master) ✗ cli bundle destroy
The following resources will be deleted:
delete job job_1
delete job job_2
delete pipeline foo
All files and directories at the following location will be deleted: /Users/shreyas.goenka@databricks.com/.bundle/bundle-playground/default
Would you like to proceed? [y/n]: n
Destroy cancelled!
```
When a user destroys resources:
```
➜ bundle-playground git:(master) ✗ cli bundle destroy
The following resources will be deleted:
delete job job_1
delete job job_2
delete pipeline foo
All files and directories at the following location will be deleted: /Users/shreyas.goenka@databricks.com/.bundle/bundle-playground/default
Would you like to proceed? [y/n]: y
Updating deployment state...
Deleting files...
Destroy complete!
```
## 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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## 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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---------
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>
- 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
Shreyas Goenka
Pieter Noordhuis
Andrew Nester
shreyas-goenka
Gleb Kanterov
Lennart Kats (databricks)
dependabot[bot]
Witold Czaplewski
Renaud Hartert
Alex Moschos
Aravind Segu
Miles Yucht
Ilia Babanov