## 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.
Pieter Noordhuis
Andrew Nester
Ilia Babanov
Miles Yucht
shreyas-goenka
dependabot[bot]
Lennart Kats (databricks)
hectorcast-db
Serge Smertin