## 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>
[](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:
- `@dependabot rebase` will rebase this PR
- `@dependabot recreate` will recreate this PR, overwriting any edits
that have been made to it
- `@dependabot merge` will merge this PR after your CI passes on it
- `@dependabot squash and merge` will squash and merge this PR after
your CI passes on it
- `@dependabot cancel merge` will cancel a previously requested merge
and block automerging
- `@dependabot reopen` will reopen this PR if it is closed
- `@dependabot close` will close this PR and stop Dependabot recreating
it. You can achieve the same result by closing it manually
- `@dependabot show <dependency name> ignore conditions` will show all
of the ignore conditions of the specified dependency
- `@dependabot ignore this major version` will close this PR and stop
Dependabot creating any more for this major version (unless you reopen
the PR or upgrade to it yourself)
- `@dependabot ignore this minor version` will close this PR and stop
Dependabot creating any more for this minor version (unless you reopen
the PR or upgrade to it yourself)
- `@dependabot ignore this dependency` will close this PR and stop
Dependabot creating any more for this dependency (unless you reopen the
PR or upgrade to it yourself)
</details>
---------
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>
## 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:
- `@dependabot rebase` will rebase this PR
- `@dependabot recreate` will recreate this PR, overwriting any edits
that have been made to it
- `@dependabot merge` will merge this PR after your CI passes on it
- `@dependabot squash and merge` will squash and merge this PR after
your CI passes on it
- `@dependabot cancel merge` will cancel a previously requested merge
and block automerging
- `@dependabot reopen` will reopen this PR if it is closed
- `@dependabot close` will close this PR and stop Dependabot recreating
it. You can achieve the same result by closing it manually
- `@dependabot show <dependency name> ignore conditions` will show all
of the ignore conditions of the specified dependency
- `@dependabot ignore this major version` will close this PR and stop
Dependabot creating any more for this major version (unless you reopen
the PR or upgrade to it yourself)
- `@dependabot ignore this minor version` will close this PR and stop
Dependabot creating any more for this minor version (unless you reopen
the PR or upgrade to it yourself)
- `@dependabot ignore this dependency` will close this PR and stop
Dependabot creating any more for this dependency (unless you reopen the
PR or upgrade to it yourself)
</details>
---------
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"
```
Pieter Noordhuis
shreyas-goenka
Jim Idle
Kartik Gupta
Andrew Nester
dependabot[bot]
Ilia Babanov
Miles Yucht
Lennart Kats (databricks)