## 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
added `ConfigFile: cfg.ConfigFile` for `databrickscfg.SaveToProfile` in
`cmd/configure/configure.go` to save the file in a specified path when
the value is not empty
## Tests
`TestConfigFileFromEnvNoInteractive` in
`cmd/configure/configure_test.go` sets a different config file path by
`DATABRICKS_CONFIG_FILE`, after execution, the overwrite config file is
generated, and the default path has no file.
## 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
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
This makes the dbt-sql and default-sql templates public.
These templates were previously not listed and marked "experimental"
since structured streaming tables were still in gated preview and would
result in weird error messages when a workspace wasn't enabled for the
preview.
This PR also incorporates some of the feedback and learnings for these
templates so far.
## 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
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
Currently, the help output of services in preview doesn't show any of
their commands because the commands themselves are hidden as well.
This change updates that behavior to not hide commands in preview if the
service itself is also in preview. This makes the help output of
services in preview actually usable.
## Tests
n/a
## 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
The installer.Upgrade() processing did not install Python dependencies.
This resulted in errors such as:
```
ModuleNotFoundError: No module named 'databricks.labs.blueprint'
```
Any new dependencies are now installed during the upgrade process.
Resolves: databrickslabs/ucx#1276
## Tests
The TestUpgraderWorksForReleases test now checks to see if the upgrade
process resulted in the dependencies being installed.
---------
Signed-off-by: Jim.Idle <jimi@idle.ws>
## Changes
* Currently, we use `auth profiles` command with
`DATABRICKS_CONFIG_FILE` env var set, the file pointed to by the env var
is ONLY used for loading the profile names (ini file sections). It is
not passed to go sdk config object. We also don't use env variable
loader in the go sdk config object, so this env var is ignored by the
config and only default file is read.
* This PR explicitly sets the config file path in the go sdk config
object.
## Tests
* integration tests in vscode
## 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
Fixes to get host from the workspace client rather than only printing
the host when it's configured in the bundle config.
## Tests
Manually. When a profile was specified for auth.
Before:
```
➜ bundle-playground git:(master) ✗ cli bundle validate
Name: bundle-playground
Target: default
Workspace:
Host:
User: shreyas.goenka@databricks.com
Path: /Users/shreyas.goenka@databricks.com/.bundle/bundle-playground/default
```
After:
```
➜ bundle-playground git:(master) ✗ cli bundle validate
Name: bundle-playground
Target: default
Workspace:
Host: https://e2-dogfood.staging.cloud.databricks.com
User: shreyas.goenka@databricks.com
Path: /Users/shreyas.goenka@databricks.com/.bundle/bundle-playground/default
```
## 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
This PR improves the documentation for the `auth login` command,
accounting for the various ways this command can be used in.
---------
Co-authored-by: PaulCornellDB <paul.cornell@databricks.com>
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
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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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Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Andrew Nester <andrew.nester@databricks.com>
## Changes
This PR is a minor UX improvement. By not autofilling the https://
prefix in Databricks Host we allow users to directly copy-paste from
their browser.
UX:
```
➜ cli git:(fix/copy-host) cli auth login
Databricks Profile Name: my-profile
Databricks Host (e.g. https://<databricks-instance>.cloud.databricks.com): https://foobar.cloud.databricks.com
Profile my-profile was successfully saved
```
## Tests
Manually.
This makes the command almost instant, no matter how many profiles cfg
file has. One downside is that we don't set AuthType for profiles that
don't have it defined.
We can technically infer AuthType based on ConfigAttributes tags, but
their names are different from the names of actual auth providers (and
some tags cover multiple providers at the same time).
## Changes
It now shows human-readable warnings and validation status.
## Tests
* Manual tests against many examples.
* Errors still return immediately.
[](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`.
[//]: # (dependabot-automerge-start)
[//]: # (dependabot-automerge-end)
---
<details>
<summary>Dependabot commands and options</summary>
<br />
You can trigger Dependabot actions by commenting on this PR:
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that have been made to it
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</details>
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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
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
The function signature of Cobra's `PreRunE` function has an `error`
return value. We'd like to start returning `diag.Diagnostics` after
loading a bundle, so this is incompatible. This change modifies all
usage of `PreRunE` to load a bundle to inline function calls in the
command's `RunE` function.
## Tests
* Unit tests pass.
* Integration tests pass.
## Changes
Prior to this change, the bundle configuration entry point was loaded
from the function `bundle.Load`. Other configuration files were only
loaded once the caller applied the first set of mutators. This
separation was unnecessary and not ideal in light of gathering
diagnostics while loading _any_ configuration file, not just the ones
from the includes.
This change:
* Updates `bundle.Load` to only verify that the specified path is a
valid bundle root.
* Moves mutators that perform loading to `bundle/config/loader`.
* Adds a "load" phase that takes the place of applying
`DefaultMutators`.
Follow ups:
* Rename `bundle.Load` -> `bundle.Find` (because it no longer performs
loading)
This change depends on #1316 and #1317.
## Tests
Tests pass.
## Changes
The bundle path was previously stored on the `config.Root` type under
the assumption that the first configuration file being loaded would set
it. This is slightly counterintuitive and we know what the path is upon
construction of the bundle. The new location for this property reflects
this.
## Tests
Unit tests pass.
## Changes
This diagnostics type allows us to capture multiple warnings as well as
errors in the return value. This is a preparation for returning
additional warnings from mutators in case we detect non-fatal problems.
* All return statements that previously returned an error now return
`diag.FromErr`
* All return statements that previously returned `fmt.Errorf` now return
`diag.Errorf`
* All `err != nil` checks now use `diags.HasError()` or `diags.Error()`
## Tests
* Existing tests pass.
* I confirmed no call site under `./bundle` or `./cmd/bundle` uses
`errors.Is` on the return value from mutators. This is relevant because
we cannot wrap errors with `%w` when calling `diag.Errorf` (like
`fmt.Errorf`; context in https://github.com/golang/go/issues/47641).
## Changes
This PR introduces new structure (and a file) being used locally and
synced remotely to Databricks workspace to track bundle deployment
related metadata.
The state is pulled from remote, updated and pushed back remotely as
part of `bundle deploy` command.
This state can be used for deployment sequencing as it's `Version` field
is monotonically increasing on each deployment.
Currently, it only tracks files being synced as part of the deployment.
This helps fix the issue with files not being removed during deployments
on CI/CD as sync snapshot was never present there.
Fixes#943
## Tests
Added E2E (regression) test for files removal on CI/CD
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
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
Currently, when the CLI run a list API call (like list jobs), it uses
the `List*All` methods from the SDK, which list all resources in the
collection. This is very slow for large collections: if you need to list
all jobs from a workspace that has 10,000+ jobs, you'll be waiting for
at least 100 RPCs to complete before seeing any output.
Instead of using List*All() methods, the SDK recently added an iterator
data structure that allows traversing the collection without needing to
completely list it first. New pages are fetched lazily if the next
requested item belongs to the next page. Using the List() methods that
return these iterators, the CLI can proactively print out some of the
response before the complete collection has been fetched.
This involves a pretty major rewrite of the rendering logic in `cmdio`.
The idea there is to define custom rendering logic based on the type of
the provided resource. There are three renderer interfaces:
1. textRenderer: supports printing something in a textual format (i.e.
not JSON, and not templated).
2. jsonRenderer: supports printing something in a pretty-printed JSON
format.
3. templateRenderer: supports printing something using a text template.
There are also three renderer implementations:
1. readerRenderer: supports printing a reader. This only implements the
textRenderer interface.
2. iteratorRenderer: supports printing a `listing.Iterator` from the Go
SDK. This implements jsonRenderer and templateRenderer, buffering 20
resources at a time before writing them to the output.
3. defaultRenderer: supports printing arbitrary resources (the previous
implementation).
Callers will either use `cmdio.Render()` for rendering individual
resources or `io.Reader` or `cmdio.RenderIterator()` for rendering an
iterator. This separate method is needed to safely be able to match on
the type of the iterator, since Go does not allow runtime type matches
on generic types with an existential type parameter.
One other change that needs to happen is to split the templates used for
text representation of list resources into a header template and a row
template. The template is now executed multiple times for List API
calls, but the header should only be printed once. To support this, I
have added `headerTemplate` to `cmdIO`, and I have also changed
`RenderWithTemplate` to include a `headerTemplate` parameter everywhere.
## Tests
- [x] Unit tests for text rendering logic
- [x] Unit test for reflection-based iterator construction.
---------
Co-authored-by: Andrew Nester <andrew.nester@databricks.com>
## Changes
```
shreyas.goenka@THW32HFW6T cli % databricks fs -h
Commands to do file system operations on DBFS and UC Volumes.
Usage:
databricks fs [command]
Available Commands:
cat Show file content.
cp Copy files and directories.
ls Lists files.
mkdir Make directories.
rm Remove files and directories.
```
This PR adds support for UC Volumes to the fs commands. The fs commands
for UC volumes work the same as they currently do for DBFS. This is
ensured by running the same test matrix we across both DBFS and UC
Volumes versions of the fs commands.
## Tests
Support for UC volumes is tested by running the same tests as we did
originally for DBFS commands. The tests require a `main` catalog to
exist in the workspace, which does in our test workspaces environments
which have the `TEST_METASTORE_ID` environment variable set.
For the Files API filer, we do the same by running mostly common tests
to ensure the filers for "local", "wsfs", "dbfs" and "files API" are
consistent.
The tests are also made to all run in parallel to reduce the time taken.
To ensure the separation of the tests, each test creates its own UC
schema (for UC volumes tests) or DBFS directories (for DBFS tests).
## 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
The OpenAPI spec used to generate the CLI doesn't match the version used
for the SDK version that the CLI currently depends on. This PR
regenerates the CLI based on the same version of the OpenAPI spec used
by the SDK on v0.30.1.
## Tests
<!-- How is this tested? -->
## Changes
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
If environment variables related to unified authentication are set and a
user runs `auth profiles`, the environment variables will interfere with
the output. This change only takes profile data into account for the
output.
## Tests
Added a unit test.
## Changes
Aids debugging why `auth profiles` may take longer than expected.
## Tests
Confirmed manually that timing information shows up in the log output.
## 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"
```
## Changes
--json flag was removed from this command when MustUseJson / CanUseJson
generator functions were introduced which did not take requests types of
map.
This PR bring the flag back.
Relies on this Go SDK change:
https://github.com/databricks/databricks-sdk-go/pull/786
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
There's a lot of end-user friction for projects that require
account-level commands. This is mainly related to the fact that, as of
January 2024, workspace administrators do not necessarily have access to
call account-level APIs. Ongoing discussions exist on how to implement
this on a platform level best.
A temporary workaround is creating a dummy ~/.databrickscfg profile with
the `account_id` field, though it doesn't remove the end-user friction.
Hence, we don't require an account profile during installation (anymore)
and just prompt it when the context requires it. This also means that we
always prompt for account-level commands unless users specify a
`--profile` flag.
## Tests
- `go run main.go labs install ucx`, don't see an account profile prompt
- `go run main.go labs ucx sync-workspace-info`, to see a profile prompt
and have a valid auth passed
- `go run main.go labs ucx sync-workspace-info --debug --profile
profile-name` to get a concrete profile passed
## 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
Copying a local file in windows to remote directory in DBFS would fail
if the path was specified as a windows style path (compared to a UNIX
style path). This PR fixes that.
Note, UNIX style paths will continue to work because `filepath.Base`
respects both `/` and `\` as file separators. See: `IsPathSeparator` in
https://go.dev/src/os/path_windows.go.
Fixes issue: https://github.com/databricks/cli/issues/1109.
## Tests
Integration test and manually
```
C:\Users\shreyas.goenka>Desktop\cli.exe fs cp .\Desktop\foo.txt dbfs:/Users/shreyas.goenka@databricks.com
.\Desktop\foo.txt -> dbfs:/Users/shreyas.goenka@databricks.com/foo.txt
C:\Users\shreyas.goenka>Desktop\cli.exe fs cat dbfs:/Users/shreyas.goenka@databricks.com/foo.txt
hello, world
````
## Changes
The JSON logger is excellent as a machine-readable logger with lots of
metadata, but the resulting logs are difficult to read:
<img width="1601" alt="Image_from_Databricks"
src="https://github.com/databricks/cli/assets/1850319/76aa852f-756f-4e0a-bc00-3a6e3224296a">
Currently, we only use the friendly log printer when run from a TTY.
This PR removes that restriction, so logs will be pretty-printed by
default, regardless of TTY or not. If a user needs machine-readable
logs, they can still use `--log-format JSON`.
## Tests
Manual test: `databricks current-user me --debug | cat` uses the
pretty-printing logger.
## Changes
Allow account client auth with environment variables when no
.databrickscfg file present
Makes the behaviour to be in line with WorkspaceClient auth.
## Tests
Added regression test
## 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
It wasn't working because it deferred to the regular `slog.TextHandler`
for the `WithAttr` and `WithGroup` functions. Both of these functions
don't mutate the handler but return a new one. When the top-level logger
called one of these, log records in that context used the standard
handler instead of ours.
To implement tracking of attributes and groups, I followed the guide at
https://github.com/golang/example/blob/master/slog-handler-guide/README.md
for writing custom handlers.
## Tests
The new tests demonstrate formatting through `t.Log` and look good.
## Changes
This PR adds documentation for positional arguments in commands that are
generated from the openapi spec.
Note: the changes to `.gitattributes` will be revert / properly fixed in
https://github.com/databricks/cli/pull/1012
## Changes
Only clusters with their source attribute equal to `UI` or `API` should
be presented in the dropdown.
## Tests
Unit test and manual confirmation.
## Changes
The code included the to-be-created profile in the configuration and
that triggered the SDK to try and load it. Instead, we must use the
specified host and token directly.
## Tests
Manually. More integration test coverage tbd.
## Changes
We didn't return the error upon creating a workspace or account client.
If there is an error, it must always propagate up the stack. The result
of this bug was that we were setting a `nil` account or workspace
client, which in turn caused SIGSEGVs.
Fixes#913.
## Tests
Manually confirmed this fixes the linked issue. The CLI now correctly
returns an error when the client cannot be constructed.
The issue was reproducible using a `.databrickscfg` with a single,
incorrectly configured profile.
## 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 breaks out the flags into a separate struct to make it easier to
pass around.
If specified, the flag calls into the `cfgpicker` to prompt for a
cluster to associated with the profile.
## Tests
Existing tests pass; added one for host validation.
---------
Co-authored-by: Miles Yucht <miles@databricks.com>
## Changes
`databricks configure` creates a new .databrickscfg if one doesn't
already exist, but `databricks auth login` fails in this case. Because
`databricks auth login` anyways writes out the config file, we
gracefully handle this error and continue.
## Tests
Unit test.
```
$ ls ~/.databrickscfg*
/Users/miles/.databrickscfg.bak
$ ./cli auth login
Databricks Profile Name: test
Databricks Host: https://<HOST>
Profile test was successfully saved
$ ls ~/.databrickscfg*
/Users/miles/.databrickscfg /Users/miles/.databrickscfg.bak
$ cat ~/.databrickscfg
; The profile defined in the DEFAULT section is to be used as a fallback when no profile is explicitly specified.
[DEFAULT]
[test]
host = https://<HOST>
auth_type = databricks-cli
```
## 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.
Gleb Kanterov
dependabot[bot]
Kai Zhu
shreyas-goenka
Lennart Kats (databricks)
Pieter Noordhuis
Miles Yucht
Jim Idle
Kartik Gupta
Andrew Nester
Ilia Babanov
hectorcast-db
Serge Smertin
Fabian Jakobs