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
Fixes an issue when `compute_id` is defined in the bundle config,
correctly replaced in `validate` command but not used in `deploy`
command
## Tests
Manually
## Changes
This adds a `default-sql` template!
In this latest revision, I've hidden the new template from the list so
we can merge it, iterate over it, and properly release the template at
the right time.
- [x] WorkspaceFS support for .sql files is in prod
- [x] SQL extension is preconfigured based on extension settings (if
possible)
- [ ] Streaming tables support is either ungated or the template
provides instructions about signup
- _Mitigation for now: this template is hidden from the list of
templates._
- [x] Support non-UC workspaces
## Tests
- [x] Unit tests
- [x] Manual testing
- [x] More manual testing
- [x] Reviewer testing
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
Co-authored-by: PaulCornellDB <paul.cornell@databricks.com>
## Changes
This adds a new dbt-sql template. This work requires the new WorkspaceFS
support for dbt tasks.
In this latest revision, I've hidden the new template from the list so
we can merge it, iterate over it, and propertly release the template at
the right time.
Blockers:
- [x] WorkspaceFS support for dbt projects is in prod
- [x] Move dbt files into a subdirectory
- [ ] Wait until the next (>1.7.4) release of the dbt plugin which will
have major improvements!
- _Rather than wait, this template is hidden from the list of
templates._
- [x] SQL extension is preconfigured based on extension settings (if
possible)
- MV / streaming tables:
- [x] Add to template
- [x] Fix https://github.com/databricks/dbt-databricks/issues/535 (to be
released with in 1.7.4)
- [x] Merge https://github.com/databricks/dbt-databricks/pull/338 (to be
released with in 1.7.4)
- [ ] Fix "too many 503 errors" issue
(https://github.com/databricks/dbt-databricks/issues/570, internal
tracker: ES-1009215, ES-1014138)
- [x] Support ANSI mode in the template
- [ ] Streaming tables support is either ungated or the template
provides instructions about signup
- _Mitigation for now: this template is hidden from the list of
templates._
- [x] Support non-workspace-admin deployment
- [x] Make sure `data_security_mode: SINGLE_USER` works on non-UC
workspaces (it's required to be explicitly specified on UC workspaces
with single-node clusters)
- [x] Support non-UC workspaces
## Tests
- [x] Unit tests
- [x] Manual testing
- [x] More manual testing
- [ ] Reviewer manual testing
- _I'd like to do a small bug bash post-merging._
- [x] Unit tests
## 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
These fields (key and values) needs to be double quoted in order for
yaml loader to read, parse and unmarshal it into Go struct correctly
because these fields are `map[string]string` type.
## Tests
Added regression unit and E2E tests
## 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
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
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"
```
The plan is to use the new command in the Databricks VSCode extension to
render "modified" UI state in the bundle resource tree elements, plus
use resource IDs to generate links for the resources
### New revision
- Renamed `remote-state` to `summary`
- Added "modified statuses" to all resources. Currently we don't set
"updated" status - it's either nothing, or created/deleted
- Added tests for the `TerraformToBundle` command
## Changes
Now it's possible to generate bundle configuration for existing job.
For now it only supports jobs with notebook tasks.
It will download notebooks referenced in the job tasks and generate
bundle YAML config for this job which can be included in larger bundle.
## Tests
Running command manually
Example of generated config
```
resources:
jobs:
job_128737545467921:
name: Notebook job
format: MULTI_TASK
tasks:
- task_key: as_notebook
existing_cluster_id: 0704-xxxxxx-yyyyyyy
notebook_task:
base_parameters:
bundle_root: /Users/andrew.nester@databricks.com/.bundle/job_with_module_imports/development/files
notebook_path: ./entry_notebook.py
source: WORKSPACE
run_if: ALL_SUCCESS
max_concurrent_runs: 1
```
## Tests
Manual (on our last 100 jobs) + added end-to-end test
```
--- PASS: TestAccGenerateFromExistingJobAndDeploy (50.91s)
PASS
coverage: 61.5% of statements in ./...
ok github.com/databricks/cli/internal/bundle 51.209s coverage: 61.5% of
statements in ./...
```
## Changes
This tweaks the help output shown when using `databricks help`:
* make`jobs` appears under `Workflows` (as done in baseline OpenAPI).
* move `bundle` and `sync` under a new group called `Developer Tools`
(similar to what we have in docs)
* minor wording changes
## Changes
This PR:
1. Move code to load bundle JSON Schema descriptions from the OpenAPI
spec to an internal Go module
2. Remove command line flags from the `bundle schema` command. These
flags were meant for internal processes and at no point were meant for
customer use.
3. Regenerate `bundle_descriptions.json`
4. Add support for `bundle: "deprecated"`. The `environments` field is
tagged as deprecated in this PR and consequently will no longer be a
part of the bundle schema.
## Tests
Tested by regenerating the CLI against its current OpenAPI spec (as
defined in `__openapi_sha`). The `bundle_descriptions.json` in this PR
was generated from the code generator.
Manually checked that the autocompletion / descriptions from the new
bundle schema are correct.
## Changes
This makes mlops-stacks more discoverable and makes the UX of
initialising the mlops-stack template better.
## Tests
Manually
Dropdown UI:
```
shreyas.goenka@THW32HFW6T projects % cli bundle init
Template to use:
▸ default-python
mlops-stacks
```
Help message:
```
shreyas.goenka@THW32HFW6T bricks % cli bundle init -h
Initialize using a bundle template.
TEMPLATE_PATH optionally specifies which template to use. It can be one of the following:
- default-python: The default Python template
- mlops-stacks: The Databricks MLOps Stacks template. More information can be found at: https://github.com/databricks/mlops-stacks
```
## Changes
This PR makes changes required to automatically update the bundle docs
during the CLI release process. We rely on `post_generate` scripts that
are executed after code generation with CWD as the CLI repo root.
The new `output-file` flag is introduced because stdout redirect does
not work here and would otherwise require changes to our release
automation CLI (deco CLI)
## Tests
Manually. Regenerated the CLI and the descriptions were indeed generated
for the CLI from the provided openapi spec.
## 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
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.
Improve the output of help, prompts, and so on for `databricks bundle
init` and the default template.
Among other things, this PR adds support for a new `welcome_message`
property that lets a template print a custom message on success:
```
$ databricks bundle init
Template to use [default-python]:
Unique name for this project [my_project]: lennart_project
Include a stub (sample) notebook in 'lennart_project/src': yes
Include a stub (sample) Delta Live Tables pipeline in 'lennart_project/src': yes
Include a stub (sample) Python package in 'lennart_project/src': yes
✨ Your new project has been created in the 'lennart_project' directory!
Please refer to the README.md of your project for further instructions on getting started.
Or read the documentation on Databricks Asset Bundles at https://docs.databricks.com/dev-tools/bundles/index.html.
```
---------
Co-authored-by: shreyas-goenka <88374338+shreyas-goenka@users.noreply.github.com>
## Changes
<!-- Summary of your changes that are easy to understand -->
Rename `mlops-stack` `bundle init` redirect to `mlops-stacks`.
## Tests
<!-- How is this tested? -->
N/A
## 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
## Changes
This PR fixes a bug where the temp directory created to download the
template would not be cleaned up.
## Tests
Tested manually. The exact process is described in a comment below.
## Changes
There are a couple places throughout the code base where interaction
with environment variables takes place. Moreover, more than one of these
would try to read a value from more than one environment variable as
fallback (for backwards compatibility). This change consolidates those
accesses.
The majority of diffs in this change are mechanical (i.e. add an
argument or replace a call).
This change:
* Moves common environment variable lookups for bundles to
`bundles/env`.
* Adds a `libs/env` package that wraps `os.LookupEnv` and `os.Getenv`
and allows for overrides to take place in a `context.Context`. By
scoping overrides to a `context.Context` we can avoid `t.Setenv` in
testing and unlock parallel test execution for integration tests.
* Updates call sites to pass through a `context.Context` where needed.
* For bundles, introduces `DATABRICKS_BUNDLE_ROOT` as new primary
variable instead of `BUNDLE_ROOT`. This was the last environment
variable that did not use the `DATABRICKS_` prefix.
## Tests
Unit tests pass.
~(this should be changed to target `main`)~
This reveals the template from
https://github.com/databricks/cli/pull/686 in CLI prompts for once #686
and #708 are merged.
---------
Co-authored-by: Andrew Nester <andrew.nester@databricks.com>
Co-authored-by: PaulCornellDB <paul.cornell@databricks.com>
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
This adds a built-in "default-python" template to the CLI. This is based
on the new default-template support of
https://github.com/databricks/cli/pull/685.
The goal here is to offer an experience where customers can simply type
`databricks bundle init` to get a default template:
```
$ databricks bundle init
Template to use [default-python]: default-python
Unique name for this project [my_project]: my_project
✨ Successfully initialized template
```
The present template:
- [x] Works well with VS Code
- [x] Works well with the workspace
- [x] Works well with DB Connect
- [x] Uses minimal stubs rather than boiler-plate-heavy examples
I'll have a followup with tests + DLT support.
---------
Co-authored-by: Andrew Nester <andrew.nester@databricks.com>
Co-authored-by: PaulCornellDB <paul.cornell@databricks.com>
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
This pull request extends the templating support in preparation of a
new, default template (WIP, https://github.com/databricks/cli/pull/686):
* builtin templates that can be initialized using e.g. `databricks
bundle init default-python`
* builtin templates are embedded into the executable using go's `embed`
functionality, making sure they're co-versioned with the CLI
* new helpers to get the workspace name, current user name, etc. help
craft a complete template
* (not enabled yet) when the user types `databricks bundle init` they
can interactively select the `default-python` template
And makes two tangentially related changes:
* IsServicePrincipal now uses the "users" API rather than the
"principals" API, since the latter is too slow for our purposes.
* mode: prod no longer requires the 'target.prod.git' setting. It's hard
to set that from a template. (Pieter is planning an overhaul of warnings
support; this would be one of the first warnings we show.)
The actual `default-python` template is maintained in a separate PR:
https://github.com/databricks/cli/pull/686
## Tests
Unit tests, manual testing
## Changes
This flag allows users to initialize a template from a subdirectory in
the repo root. Also enables multi template repositories.
## Tests
Manually
## Changes
This PR:
1. Renames the project-dir flag to output-dir
2. Makes the project dir flag optional. When unspecified we default to
the current working directory.
## Tests
Manually
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
Renamed Environments to Targets in bundle.yml.
The change is backward-compatible and customers can continue to use
`environments` in the time being.
## Tests
Added tests which checks that both `environments` and `targets` sections
in bundle.yml works correctly
## Changes
This PR adds two features:
1. The bundle init command
2. Support for prompting for input values
In order to do this, this PR also introduces a new `config` struct which
handles reading config files, prompting users and all validation steps
before we materialize the template
With this PR users can start authoring custom templates, based on go
text templates, for their projects / orgs.
## Tests
Unit tests, both existing and new
## Changes
This checks whether the Git settings are consistent with the actual Git
state of a source directory.
(This PR adds to https://github.com/databricks/cli/pull/577.)
Previously, we would silently let users configure their Git branch to
e.g. `main` and deploy with that metadata even if they were actually on
a different branch.
With these changes, the following config would result in an error when
deployed from any other branch than `main`:
```
bundle:
name: example
workspace:
git:
branch: main
environments:
...
```
> not on the right Git branch:
> expected according to configuration: main
> actual: my-feature-branch
It's not very useful to set the same branch for all environments,
though. For development, it's better to just let the CLI auto-detect the
right branch. Therefore, it's now possible to set the branch just for a
single environment:
```
bundle:
name: example 2
environments:
development:
default: true
production:
# production can only be deployed from the 'main' branch
git:
branch: main
```
Adding to that, the `mode: production` option actually checks that users
explicitly set the Git branch as seen above. Setting that branch helps
avoid mistakes, where someone accidentally deploys to production from
the wrong branch. (I could see us offering an escape hatch for that in
the future.)
# Testing
Manual testing to validate the experience and error messages. Automated
unit tests.
---------
Co-authored-by: Fabian Jakobs <fabian.jakobs@databricks.com>
## Changes
This removes the remaining dependency on global state and unblocks work
to parallelize integration tests. As is, we can already uncomment an
integration test that had to be skipped because of other tests tainting
global state. This is no longer an issue.
Also see #595 and #606.
## Tests
* Unit and integration tests pass.
* Manually confirmed the help output is the same.
## Changes
This change is another step towards a CLI without globals. Also see #595.
The flags for the root command are now encapsulated in struct types.
## Tests
Unit tests pass.
This implements the "development run" functionality that we desire for DABs in the workspace / IDE.
## bundle.yml changes
In bundle.yml, there should be a "dev" environment that is marked as
`mode: debug`:
```
environments:
dev:
default: true
mode: development # future accepted values might include pull_request, production
```
Setting `mode` to `development` indicates that this environment is used
just for running things for development. This results in several changes
to deployed assets:
* All assets will get '[dev]' in their name and will get a 'dev' tag
* All assets will be hidden from the list of assets (future work; e.g.
for jobs we would have a special job_type that hides it from the list)
* All deployed assets will be ephemeral (future work, we need some form
of garbage collection)
* Pipelines will be marked as 'development: true'
* Jobs can run on development compute through the `--compute` parameter
in the CLI
* Jobs get their schedule / triggers paused
* Jobs get concurrent runs (it's really annoying if your runs get
skipped because the last run was still in progress)
Other accepted values for `mode` are `default` (which does nothing) and
`pull-request` (which is reserved for future use).
## CLI changes
To run a single job called "shark_sighting" on existing compute, use the
following commands:
```
$ databricks bundle deploy --compute 0617-201942-9yd9g8ix
$ databricks bundle run shark_sighting
```
which would deploy and run a job called "[dev] shark_sightings" on the
compute provided. Note that `--compute` is not accepted in production
environments, so we show an error if `mode: development` is not used.
The `run --deploy` command offers a convenient shorthand for the common
combination of deploying & running:
```
$ export DATABRICKS_COMPUTE=0617-201942-9yd9g8ix
$ bundle run --deploy shark_sightings
```
The `--deploy` addition isn't really essential and I welcome feedback 🤔
I played with the idea of a "debug" or "dev" command but that seemed to
only make the option space even broader for users. The above could work
well with an IDE or workspace that automatically sets the target
compute.
One more thing I added is`run --no-wait` can now be used to run
something without waiting for it to be completed (useful for IDE-like
environments that can display progress themselves).
```
$ bundle run --deploy shark_sightings --no-wait
```
## Changes
`--force` flag did not exist for `bundle destroy`. This PR adds that in.
## Tests
manually tested. Now adding the `--force` flag hijacks the deploy lock
on the target directory.
Andrew Nester
Pieter Noordhuis
Ilia Babanov
Lennart Kats (databricks)
shreyas-goenka
Arpit Jasapara