## Changes
It makes the behaviour consistent with or without `python_wheel_wrapper`
on when job is run with `--python-params` flag.
In `python_wheel_wrapper` mode it converts dynamic `python_params` in a
dynamic specially named `notebook_param` and the wrapper reads them with
`dbutils` and pass to `sys.argv`
Fixes#1000
## Tests
Added an integration test.
Integration tests pass.
## Changes
If there are no matches when doing Glob call for pipeline library
defined, leave the entry as is.
The next mutators in the chain will detect that file is missing and the
error will be more user friendly.
Before the change
```
Starting resource deployment
Error: terraform apply: exit status 1
Error: cannot create pipeline: libraries must contain at least one element
```
After
```
Error: notebook ./non-existent not found
```
## Tests
Added regression unit tests
## Changes
Removed hash from the upload path since it's not useful anyway.
The main reason for that change was to make it work on all-purpose
clusters. But in order to make it work, wheel version needs to be
increased anyway. So having only hash in path is useless.
Note: using --build-number (build tag) flag does not help with
re-installing libraries on all-purpose clusters. The reason is that
`pip` ignoring build tag when upgrading the library and only look at
wheel version.
Build tag is only used for sorting the versions and the one with higher
build tag takes priority when installed. It only works if no library is
installed.
See
a15dd75d98/src/pip/_internal/index/package_finder.py (L522-L556)https://github.com/pypa/pip/issues/4781
Thus, the only way to reinstall the library on all-purpose cluster is to
increase wheel version manually or use automatic version generation,
f.e.
```
setup(
version=datetime.datetime.utcnow().strftime("%Y%m%d.%H%M%S"),
...
)
```
## Tests
Integration tests passed.
## Changes
A bug in the code that pulls the remote state could cause the local
state to be empty instead of a copy of the remote state. This happened
only if the local state was present and stale when compared to the
remote version.
We correctly checked for the state serial to see if the local state had
to be replaced but didn't seek back on the remote state before writing
it out. Because the staleness check would read the remote state in full,
copying from the same reader would immediately yield an EOF.
## Tests
* Unit tests for state pull and push mutators that rely on a mocked
filer.
* An integration test that deploys the same bundle from multiple paths,
triggering the staleness logic.
Both failed prior to the fix and now pass.
## Changes
It appears that `USERPROFILE` env variable indicates where Azure CLI
stores configuration data (aka `.azure` folder).
https://learn.microsoft.com/en-us/cli/azure/azure-cli-configuration#cli-configuration-file
Passing it to terraform executable allows it to correctly authenticate
using Azure CLI.
Fixes#983
## Tests
Ran deployment on Window VM before and after the fix.
## Changes
Previously local JAR paths were transformed to remote path during
initialisation and thus artifact building logic did not recognise such
libraries as local to be handled and uploaded.
Now it's possible to use spark_jar_tasks with local JAR libraries on
14.1+ DBR clusters
Example configuration
```
bundle:
name: spark-jar
workspace:
host: ***
artifacts:
my_java_code:
path: ./sample-java
build: "javac PrintArgs.java && jar cvfm PrintArgs.jar META-INF/MANIFEST.MF PrintArgs.class"
files:
- source: "/Users/andrew.nester/dabs/wheel/sample-java/PrintArgs.jar"
resources:
jobs:
print_args:
name: "Print Args"
tasks:
- task_key: Print
new_cluster:
num_workers: 0
spark_version: 14.2.x-scala2.12
node_type_id: i3.xlarge
spark_conf:
"spark.databricks.cluster.profile": "singleNode"
"spark.master": "local[*]"
custom_tags:
ResourceClass: "SingleNode"
spark_jar_task:
main_class_name: PrintArgs
libraries:
- jar: ./sample-java/PrintArgs.jar
```
## Tests
Manually running `bundle deploy and bundle run`
## Changes
Some test call sites called directly into the mutator's `Apply` function
instead of `bundle.Apply`. Calling into `bundle.Apply` is preferred
because that's where we can run pre/post logic common across all
mutators.
## Tests
Pass.
## Changes
All calls to apply a mutator must go through `bundle.Apply`. This
conflicts with the existing use of the variable `bundle`. This change
un-aliases the variable from the package name by renaming all variables
to `b`.
## Tests
Pass.
## Changes
This PR:
1. Renames `FilesPath` -> `FilePath` and `ArtifactsPath` ->
`ArtifactPath` in the bundle and metadata configuration to make them
consistant with the json tags.
2. Fixes development / production mode error messages to point to
`file_path` and `artifact_path`
## Tests
Existing unit tests. This is a strightforward renaming of the fields.
## Changes
The Jobs service expects these fields to always be present in the
metadata in their validation logic, which is reasonable. This PR removes
the omit empty tags so these fields are always uploaded to the workspace
`metadata.json` file.
Partly mitigates #859. It's still not clear to me if there is an actual
use case or if users are trying to use "development" mode jobs for
production, but making this overridable is reasonable.
Beyond this fix I think we could do something in the Jobs schedule UI,
but it would help to better understand the use case (or actual reason of
confusion). I expect we should hint customers to move away from dev mode
rather than unpause.
## Changes
Now it's possible to define top level `permissions` section in bundle
configuration and permissions defined there will be applied to all
resources defined in the bundle.
Supported top-level permission levels: CAN_MANAGE, CAN_VIEW, CAN_RUN.
Permissions are applied to: Jobs, DLT Pipelines, ML Models, ML
Experiments and Model Service Endpoints
```
bundle:
name: permissions
workspace:
host: ***
permissions:
- level: CAN_VIEW
group_name: test-group
- level: CAN_MANAGE
user_name: user@company.com
- level: CAN_RUN
service_principal_name: 123456-abcdef
```
## Tests
Added corresponding unit tests + ran `bundle validate` and `bundle
deploy` manually
## Changes
We can debate whether or not variable definitions without properties are
valid, but in no case should this panic the CLI.
Fixes#934.
## Tests
Unit.
## Changes
Support path rewrites for Dbt and SQL file job taks.
<!-- Summary of your changes that are easy to understand -->
## Tests
* Added unit test
<!-- How is this tested? -->
## Changes
This PR fixes metadata computation for empty bundle. Before we would
error because the `terraform.Load()` mutator errors on a empty / no
state file.
## Tests
Failing integration tests now pass.
## Changes
This PR introduces a metadata struct that stores a subset of bundle
configuration that we wish to expose to other Databricks services that
wish to integrate with bundles.
This metadata file is uploaded to a file
`${bundle.workspace.state_path}/metadata.json` in the WSFS destination
of the bundle deployment.
Documentation for emitted metadata fields:
* `version`: Version for the metadata file schema
* `config.bundle.git.branch`: Name of the git branch the bundle was
deployed from.
* `config.bundle.git.origin_url`: URL for git remote "origin"
* `config.bundle.git.bundle_root_path`: Relative path of the bundle root
from the root of the git repository. Is set to "." if they are the same.
* `config.bundle.git.commit`: SHA-1 commit hash of the exact commit this
bundle was deployed from. Note, the deployment might not exactly match
this commit version if there are changes that have not been committed to
git at deploy time,
* `file_path`: Path in workspace where we sync bundle files to.
* `resources.jobs.[job-ref].id`: Id of the job
* `resources.jobs.[job-ref].relative_path`: Relative path of the yaml
config file from the bundle root where this job was defined.
Example metadata object when bundle root and git root are the same:
```json
{
"version": 1,
"config": {
"bundle": {
"lock": {},
"git": {
"branch": "master",
"origin_url": "www.host.com",
"commit": "7af8e5d3f5dceffff9295d42d21606ccf056dce0",
"bundle_root_path": "."
}
},
"workspace": {
"file_path": "/Users/shreyas.goenka@databricks.com/.bundle/pipeline-progress/default/files"
},
"resources": {
"jobs": {
"bar": {
"id": "245921165354846",
"relative_path": "databricks.yml"
}
}
},
"sync": {}
}
}
```
Example metadata when the git root is one level above the bundle repo:
```json
{
"version": 1,
"config": {
"bundle": {
"lock": {},
"git": {
"branch": "dev-branch",
"origin_url": "www.my-repo.com",
"commit": "3db46ef750998952b00a2b3e7991e31787e4b98b",
"bundle_root_path": "pipeline-progress"
}
},
"workspace": {
"file_path": "/Users/shreyas.goenka@databricks.com/.bundle/pipeline-progress/default/files"
},
"resources": {
"jobs": {
"bar": {
"id": "245921165354846",
"relative_path": "databricks.yml"
}
}
},
"sync": {}
}
}
```
This unblocks integration to the jobs break glass UI for bundles.
## Tests
Unit tests and integration tests.
This PR:
1. Regenerates go structs using provider version 1.29
2. Adds QOL autogenerated diff labels for github
3. Adds a small SOP for doing the tf provider bump for go structs
## Changes
Upload terraform state even if apply fails
Fixes#893
## Tests
Manually running `databricks bundle deploy` with incorrect permissions
in bundle config and observe that it gets uploaded correctly
## Changes
There were two functions related to loading a bundle configuration file;
one as a package function and one as a member function on the
configuration type. Loading the same configuration object twice doesn't
make sense and therefore we can consolidate to only using the package
function.
The package function would scan for known file names if the specified
path was a directory. This functionality was not in use because the
top-level bundle loader figures out the filename itself as of #580.
## Tests
Pass.
## Changes
If a bundle configuration specifies a workspace host, and the user
specifies a profile to use, we perform a check to confirm that the
workspace host in the bundle configuration and the workspace host from
the profile are identical. If they are not, we return an error. The
check was introduced in #571.
Previously, the code included an assumption that the client
configuration was already loaded from the environment prior to
performing the check. This was not the case, and as such if the user
intended to use a non-default path to `.databrickscfg`, this path was
not used when performing the check.
The fix does the following:
* Resolve the configuration prior to performing the check.
* Don't treat the configuration file not existing as an error.
* Add unit tests.
Fixes#884.
## Tests
Unit tests and manual confirmation.
## Changes
Previously we only supported uploading Python wheels smaller than 10mb
due to using Workspace.Import API and `content ` field
https://docs.databricks.com/api/workspace/workspace/import
By switching to use `WorkspaceFilesClient` we overcome the limit because
it uses POST body for the API instead.
## Tests
`TestAccUploadArtifactFileToCorrectRemotePath` integration test passes
```
=== RUN TestAccUploadArtifactFileToCorrectRemotePath
artifacts_test.go:28: gcp
2023/10/17 15:24:04 INFO Using Google Credentials sdk=true
helpers.go:356: Creating /Users/.../integration-test-wsfs-ekggbkcfdkid
artifacts.Upload(test.whl): Uploading...
2023/10/17 15:24:06 INFO Using Google Credentials mutator=artifacts.Upload(test) sdk=true
artifacts.Upload(test.whl): Upload succeeded
helpers.go:362: Removing /Users/.../integration-test-wsfs-ekggbkcfdkid
--- PASS: TestAccUploadArtifactFileToCorrectRemotePath (5.66s)
PASS
coverage: 14.9% of statements in ./...
ok github.com/databricks/cli/internal 6.109s coverage: 14.9% of statements in ./...
```
## Changes
Previous we (erroneously) kept the reference and merged into the
original tasks and not the copies which we later used to replace
existing tasks. Thus the merging of slices and references was incorrect.
Fixes#864
## Tests
Added a regression test
## Changes
Now it's possible to specify glob pattern in pipeline libraries section
and DAB will add all matched files as libraries
```
pipelines:
dummy:
name: " DLT with Python files"
target: "dlt_python_files"
libraries:
- file:
path: ./*.py
```
## Tests
Added unit test
This PR adds a few utilities related to Python interpreter detection:
- `python.DetectInterpreters` to detect all Python versions available in
`$PATH` by executing every matched binary name with `--version` flag.
- `python.DetectVirtualEnvPath` to detect if there's any child virtual
environment in `src` directory
- `python.DetectExecutable` to detect if there's python3 installed
either by `which python3` command or by calling
`python.DetectInterpreters().AtLeast("v3.8")`
To be merged after https://github.com/databricks/cli/pull/804, as one of
the steps to get https://github.com/databricks/cli/pull/637 in, as
previously discussed.
## Changes
The jobs backend propagates job tags to the underlying cloud provider's
resources. As such, they need to match the constraints a cloud provider
places on tag values. The display name can contain anything. With this
change, we modify the tag value to equal the short name as used in the
name prefix.
Additionally, we leverage tag normalization as introduced in #819 to
make sure characters that aren't accepted are removed before using the
value as a tag value.
This is a new stab at #810 and should completely eliminate this class of
problems.
## Tests
Tests pass.
## Changes
This PR adds higher-level wrappers for calling subprocesses. One of the
steps to get https://github.com/databricks/cli/pull/637 in, as
previously discussed.
The reason to add `process.Forwarded()` is to proxy Python's `input()`
calls from a child process seamlessly. Another use-case is plugging in
`less` as a pager for the list results.
## Tests
`make test`
## Changes
Instead of always using notebook wrapper for Python wheel tasks, let's
make this an opt-in option.
Now by default Python wheel tasks will be deployed as is to Databricks
platform.
If notebook wrapper required (DBR < 13.1 or other configuration
differences), users can provide a following experimental setting
```
experimental:
python_wheel_wrapper: true
```
Fixes#783,
https://github.com/databricks/databricks-asset-bundles-dais2023/issues/8
## Tests
Added unit tests.
Integration tests passed for both cases
```
helpers.go:163: [databricks stdout]: Hello from my func
helpers.go:163: [databricks stdout]: Got arguments:
helpers.go:163: [databricks stdout]: ['my_test_code', 'one', 'two']
...
Bundle remote directory is ***/.bundle/ac05d5e8-ed4b-4e34-b3f2-afa73f62b021
Deleted snapshot file at /var/folders/nt/xjv68qzs45319w4k36dhpylc0000gp/T/TestAccPythonWheelTaskDeployAndRunWithWrapper3733431114/001/.databricks/bundle/default/sync-snapshots/cac1e02f3941a97b.json
Successfully deleted files!
--- PASS: TestAccPythonWheelTaskDeployAndRunWithWrapper (214.18s)
PASS
coverage: 93.5% of statements in ./...
ok github.com/databricks/cli/internal/bundle 214.495s coverage: 93.5% of statements in ./...
```
```
helpers.go:163: [databricks stdout]: Hello from my func
helpers.go:163: [databricks stdout]: Got arguments:
helpers.go:163: [databricks stdout]: ['my_test_code', 'one', 'two']
...
Bundle remote directory is ***/.bundle/0ef67aaf-5960-4049-bf1d-dc9e29157421
Deleted snapshot file at /var/folders/nt/xjv68qzs45319w4k36dhpylc0000gp/T/TestAccPythonWheelTaskDeployAndRunWithoutWrapper2340216760/001/.databricks/bundle/default/sync-snapshots/edf0b322cee93b13.json
Successfully deleted files!
--- PASS: TestAccPythonWheelTaskDeployAndRunWithoutWrapper (192.36s)
PASS
coverage: 93.5% of statements in ./...
ok github.com/databricks/cli/internal/bundle 195.130s coverage: 93.5% of statements in ./...
```
## Changes
This is a follow-up to #658 and #779 for jobs.
This change applies label normalization the same way the backend does.
## Tests
Unit and config loading tests.
## Changes
It's not uncommon for job runs to take more than 2 hours. On the client
side, we should not stop waiting for a job to complete if it is
intentionally running for a long time. If a job isn't supposed to run
this long, the user can specify a run timeout in the job specification
itself.
## Tests
n/a
## Changes
Follow up for https://github.com/databricks/cli/pull/658
When a job definition has multiple job tasks using the same key, it's
considered invalid. Instead we should combine those definitions with the
same key into one. This is consistent with environment overrides. This
way, the override ends up in the original job tasks, and we've got a
clear way to put them all together.
## Tests
Added unit tests
## Changes
This PR sets "resource" to nil in the terraform representation if no
resources are defined in the bundle configuration. This solves two
problems:
1. Makes bundle deploy work without any resources specified.
2. Previously if a `resources` block was removed after a deployment,
that would fail with an error. Now the resources would get destroyed as
expected.
Also removes `TerraformHasNoResources` which is no longer needed.
## Tests
New e2e tests.
## Changes
Display an interactive prompt with a list of resources to run if one
isn't specified and the command is run interactively.
## Tests
Manually confirmed:
* The new prompt works
* Shell completion still works
* Specifying a key argument still works
Andrew Nester
shreyas-goenka
Pieter Noordhuis
Lennart Kats (databricks)
Michał Szafrański
Arpit Jasapara
hectorcast-db
Serge Smertin