The companion for upgrading to Unity Catalog. After installation, ensure to trigger the assessment workflow,
so that you'll be able to scope the migration and execute the group migration workflow.
<installation_path>/README contains further instructions and explanations of these workflows.
Then you can execute table migration workflow.
More workflows, like notebook code migration is coming in the future releases.
UCX exposes a number of command line utilities accessible via databricks labs ucx.
For questions, troubleshooting or bug fixes, please see our troubleshooting guide or submit an issue. See contributing instructions to help improve this project.
- Databricks Labs UCX
- Installation
- Migration process
- Workflows
- Utility commands
- Metastore related commands
- Table migration commands
- Code migration commands
- Cross-workspace installations
- Star History
- Project Support
- Databricks CLI v0.213 or later. See instructions.
- Python 3.10 or later. See Windows instructions.
- Network access to your Databricks Workspace used for the installation process.
- Network access to the Internet for pypi.org and github.com from machine running the installation.
- Databricks Workspace Administrator privileges for the user, that runs the installation. Running UCX as a Service Principal is not supported.
- Account level Identity Setup. See instructions for AWS, Azure, and GCP.
- Unity Catalog Metastore Created (per region). See instructions for AWS, Azure, and GCP.
- If your Databricks Workspace relies on an external Hive Metastore (such as AWS Glue), make sure to read this guide.
- Databricks Workspace has to have network access to pypi.org to download
databricks-sdkandpyyamlpackages. - A PRO or Serverless SQL Warehouse to render the report for the assessment workflow.
Once you install UCX, you can proceed to the assessment workflow to ensure the compatibility of your workspace with Unity Catalog.
We only support installations and upgrades through Databricks CLI, as UCX requires an installation script run
to make sure all the necessary and correct configurations are in place. Install Databricks CLI on macOS:
Install Databricks CLI on Windows:
Once you install Databricks CLI, authenticate your current machine to a Databricks Workspace:
databricks auth login --host WORKSPACE_HOST
To enable debug logs, simply add --debug flag to any command.
Install UCX via Databricks CLI:
databricks labs install ucx
You'll be prompted to select a configuration profile created by databricks auth login command.
Once you install, proceed to the assessment workflow to ensure the compatibility of your workspace with UCX.
The WorkspaceInstaller class is used to create a new configuration for Unity Catalog migration in a Databricks workspace.
It guides the user through a series of prompts to gather necessary information, such as selecting an inventory database, choosing
a PRO or SERVERLESS SQL warehouse, specifying a log level and number of threads, and setting up an external Hive Metastore if necessary.
Upon the first installation, you're prompted for a workspace local group migration strategy.
Based on user input, the class creates a new cluster policy with the specified configuration. The user can review and confirm the configuration,
which is saved to the workspace and can be opened in a web browser.
The WorkspaceInstallation manages the installation and uninstallation of UCX in a workspace. It handles
the configuration and exception management during the installation process. The installation process creates dashboards, databases, and jobs.
It also includes the creation of a database with given configuration and the deployment of workflows with specific settings. The installation
process can handle exceptions and infer errors from job runs and task runs. The workspace installation uploads wheels, creates cluster policies,
and wheel runners to the workspace. It can also handle the creation of job tasks for a given task, such as job dashboard tasks, job notebook tasks,
and job wheel tasks. The class handles the installation of UCX, including configuring the workspace, installing necessary libraries, and verifying
the installation, making it easier for users to migrate their workspaces to UCX.
After this, UCX will be installed locally and a number of assets will be deployed in the selected workspace.
These assets are available under the installation folder, i.e. /Users/<your user>/.ucx/.
You can also install a specific version by specifying it like @v0.13.2 - databricks labs install ucx@v0.13.2.
Using an environment variable UCX_FORCE_INSTALL you can force the installation of UCX over an existing installation.
The values for the environment variable are 'global' and 'user'.
Global Install: When UCX is installed at '/Applications/ucx' User Install: When UCX is installed at '/Users//.ucx'
If there is an existing global installation of UCX, you can force a user installation of UCX over the existing installation by setting the environment variable UCX_FORCE_INSTALL to 'global'.
At this moment there is no global override over a user installation of UCX. As this requires migration and can break existing installations.
| global | user | expected install location | install_folder | mode |
|---|---|---|---|---|
| no | no | default | /Applications/ucx |
install |
| yes | no | default | /Applications/ucx |
upgrade |
| no | yes | default | /Users/X/.ucx |
upgrade (existing installations must not break) |
| yes | yes | default | /Users/X/.ucx |
upgrade |
| yes | no | USER | /Users/X/.ucx |
install (show prompt) |
| no | yes | GLOBAL | ... | migrate |
UCX_FORCE_INSTALL=user databricks labs install ucx- will force the installation to be for user onlyUCX_FORCE_INSTALL=global databricks labs install ucx- will force the installation to be for root only
Setting the environment variable UCX_FORCE_INSTALL to 'account' will install UCX on all workspaces within a Databricks account.
UCX_FORCE_INSTALL=account databricks labs install ucx
After the first installation, UCX will prompt the user to confirm whether to install UCX on the remaining workspaces with the same answers. If confirmed, the remaining installations will be completed silently.
This installation mode will automatically select the following options:
- Automatically create and enable HMS lineage init script
- Automatically create a new SQL warehouse for UCX assessment
Verify that UCX is installed
databricks labs installed
Name Description Version
ucx Unity Catalog Migration Toolkit (UCX) <version>
Upgrade UCX via Databricks CLI:
databricks labs upgrade ucx
The prompts will be similar to Installation
Uninstall UCX via Databricks CLI:
databricks labs uninstall ucx
Databricks CLI will confirm a few options:
- Whether you want to remove all ucx artefacts from the workspace as well. Defaults to no.
- Whether you want to delete the inventory database in
hive_metastore. Defaults to no.
On the high level, the steps in migration process start with the assessment workflow, followed by group migration, table migration workflow, finalised with the code migration. It can be described as:
flowchart TD
subgraph workspace-admin
assessment --> group-migration
group-migration --> table-migration
table-migration --> code-migration
assessment --> create-table-mapping
create-table-mapping --> table-migration
create-table-mapping --> code-migration
validate-external-locations --> table-migration
table-migration --> revert-migrated-tables
revert-migrated-tables --> table-migration
end
subgraph account-admin
create-account-groups --> group-migration
sync-workspace-info --> create-table-mapping
group-migration --> validate-groups-membership
end
subgraph iam-admin
setup-account-scim --> create-account-groups
assessment --> create-uber-principal
create-uber-principal --> table-migration
assessment --> principal-prefix-access
principal-prefix-access --> migrate-credentials
migrate-credentials --> validate-external-locations
setup-account-scim
end
Part of this application is deployed as Databricks Workflows.
You can view the status of deployed workflows via the workflows command.
Failed workflows can be fixed with the repair-run command.
Every installation creates a README notebook with a detailed description of all deployed workflows and their tasks,
providing quick links to the relevant workflows and dashboards.
The assessment workflow can be triggered using the Databricks UI, or via the command line.
databricks labs ucx ensure-assessment-run
Once you finish the assessment, proceed to the group migration workflow. See the migration process diagram to understand the role of the assessment workflow in the migration process.
The assessment workflow is designed to assess the compatibility of various entities in the current workspace with Unity Catalog.
It identifies incompatible entities and provides information necessary for planning the migration to UC. The tasks in
the assessment workflow can be executed in parallel or sequentially, depending on the dependencies specified in the @task decorators.
The output of each task is stored in Delta tables in the $inventory_database schema, that you specify during installation,
which can be used for further analysis and decision-making through the assessment report.
The assessment workflow can be executed multiple times to ensure that all incompatible entities are identified and accounted
for before starting the migration process.
crawl_tables: This task scans all tables in the Hive Metastore of the current workspace and persists their metadata in a Delta table named$inventory_database.tables. This metadata includes information such as the database name, table name, table type, and table location. This task is used for assessing which tables cannot be easily migrated to Unity Catalog.crawl_grants: This task scans the Delta table named$inventory_database.tablesand issues aSHOW GRANTSstatement for every object to retrieve the permissions assigned to it. The permissions include information such as the principal, action type, and the table it applies to. This task persists the permissions in the Delta table$inventory_database.grants.estimate_table_size_for_migration: This task scans the Delta table named$inventory_database.tablesand locates tables that cannot be synced. These tables will have to be cloned in the migration process. The task assesses the size of these tables and creates the$inventory_database.table_sizetable to list these sizes. The table size is a factor in deciding whether to clone these tables.crawl_mounts: This task scans the workspace to compile a list of all existing mount points and stores this information in the$inventory.mountstable. This is crucial for planning the migration.guess_external_locations: This task determines the shared path prefixes of all the tables that utilize mount points. The goal is to identify the external locations necessary for a successful migration and store this information in the$inventory.external_locationstable.assess_jobs: This task scans through all the jobs and identifies those that are not compatible with UC. The list of all the jobs is stored in the$inventory.jobstable.assess_clusters: This task scans through all the clusters and identifies those that are not compatible with UC. The list of all the clusters is stored in the$inventory.clusterstable.assess_pipelines: This task scans through all the Pipelines and identifies those pipelines that have Azure Service Principals embedded in their configurations. A list of all the pipelines with matching configurations is stored in the$inventory.pipelinestable.assess_azure_service_principals: This task scans through all the clusters configurations, cluster policies, job cluster configurations, Pipeline configurations, and Warehouse configuration and identifies all the Azure Service Principals who have been given access to the Azure storage accounts via spark configurations referred in those entities. The list of all the Azure Service Principals referred in those configurations is saved in the$inventory.azure_service_principalstable.assess_global_init_scripts: This task scans through all the global init scripts and identifies if there is an Azure Service Principal who has been given access to the Azure storage accounts via spark configurations referred in those scripts.
After UCX assessment workflow is executed, the assessment dashboard will be populated with findings and common recommendations. See this guide for more details.
You are required to complete the assessment workflow before starting the group migration workflow. See the migration process diagram to understand the role of the group migration workflow in the migration process.
See the detailed design of this workflow. It helps you to upgrade all Databricks workspace assets: Legacy Table ACLs, Entitlements, AWS instance profiles, Clusters, Cluster policies, Instance Pools, Databricks SQL warehouses, Delta Live Tables, Jobs, MLflow experiments, MLflow registry, SQL Dashboards & Queries, SQL Alerts, Token and Password usage permissions that are set on the workspace level, Secret scopes, Notebooks, Directories, Repos, and Files.
Once done with the group migration, proceed to table migration workflow.
Use validate-groups-membership command for extra confidence.
If you don't have matching account groups, please run create-account-groups command.
The group migration workflow is designed to migrate workspace-local groups to account-level groups in the Unity Catalog (UC) environment. It ensures that all the necessary groups are available in the workspace with the correct permissions, and removes any unnecessary groups and permissions. The tasks in the group migration workflow depend on the output of the assessment workflow and can be executed in sequence to ensure a successful migration. The output of each task is stored in Delta tables in the $inventory_database schema, which can be used for further analysis and decision-making. The group migration workflow can be executed multiple times to ensure that all the groups are migrated successfully and that all the necessary permissions are assigned.
crawl_groups: This task scans all groups for the local group migration scope.rename_workspace_local_groups: This task renames workspace local groups by adding aucx-renamed-prefix. This step is taken to avoid conflicts with account-level groups that may have the same name as workspace-local groups.reflect_account_groups_on_workspace: This task adds matching account groups to this workspace. The matching account level group(s) must preexist(s) for this step to be successful. This step is necessary to ensure that the account-level groups are available in the workspace for assigning permissions.apply_permissions_to_account_groups: This task assigns the full set of permissions of the original group to the account-level one. It covers local workspace-local permissions for all entities, including Legacy Table ACLs, Entitlements, AWS instance profiles, Clusters, Cluster policies, Instance Pools, Databricks SQL warehouses, Delta Live Tables, Jobs, MLflow experiments, MLflow registry, SQL Dashboards & Queries, SQL Alerts, Token and Password usage permissions, Secret Scopes, Notebooks, Directories, Repos, Files. This step is necessary to ensure that the account-level groups have the necessary permissions to manage the entities in the workspace.validate_groups_permissions: This task validates that all the crawled permissions are applied correctly to the destination groups.delete_backup_groups: This task removes all workspace-level backup groups, along with their permissions. This should only be executed after confirming that the workspace-local migration worked successfully for all the groups involved. This step is necessary to clean up the workspace and remove any unnecessary groups and permissions.
Every installation creates a debug notebook, that initializes UCX as a library, so that you can implement missing features and
Every workflow run stores debug logs in the logs folder of the installation.
For tasks shorter than 10 minutes, they appear after task finish, whereas longer-running tasks
flush the logs every 10 minutes.
To enable debug logs of command-line interface,
simply add --debug flag to any command.
The table migration workflow comprises multiple workflows and tasks designed to migrate tables from the Hive Metastore to the Unity Catalog. The subsequent diagram illustrates the workflow's tasks and their dependency CLI commands.
flowchart TB
subgraph CLI
sync-workspace-info[sync-workspace-info] --> create_table_mapping[create-table-mapping]
create_table_mapping[create-table-mapping] --> create_catalogs_schemas[create-catalogs-schemas]
create_uber_principal[create-uber-principal]
principal_prefix_access[principal-prefix-access] --> migrate_credentials[migrate-credentials]
migrate_credentials --> validate-external-locations[validate-external-locations]
validate-external-locations --> migrate_locations[migrate-locations]
migrate_locations --> create_catalogs_schemas
end
create_uber_principal --> workflow
create_table_mapping --> workflow
create_catalogs_schemas --> workflow
subgraph workflow[Table Migration Workflows]
subgraph mt_workflow[workflow: migrate-tables]
dbfs_root_delta_mt_task[migrate_dbfs_root_delta_tables]
external_tables_sync_mt_task[migrate_external_tables_sync]
view_mt_task[roadmap: migrate_views]
dbfs_root_delta_mt_task --> view_mt_task
external_tables_sync_mt_task --> view_mt_task
end
subgraph mt_ctas_wf[roadmap workflow: migrate-tables-ctas]
ctas_mt_task[migrate_tables_ctas] --> view_mt_task_ctas[roadmap: migrate_views]
end
subgraph mt_serde_inplace_wf[roadmap workflow: migrate-external-hiveserde-tables-in-place-experimental]
serde_inplace_mt_task[migrate_external_hiveserde_tables_in_place_experimental] --> view_mt_task_inplace[roadmap: migrate_views]
end
subgraph mt_in_mounts_wf[roadmap workflow: migrate-tables-in-mounts-experimental]
scan_tables_in_mounts_experimental_task[scan_tables_in_mounts_experimental] -->
migrate_tables_in_mounts_experimental[migrate_tables_in_mounts_experimental]
end
end
classDef roadmap stroke:Green,stroke-width:2px,color:Green,stroke-dasharray: 8 3
class view_mt_task roadmap;
class mt_ctas_wf,ctas_mt_task,view_mt_task_ctas roadmap;
class mt_serde_inplace_wf,serde_inplace_mt_task,view_mt_task_inplace roadmap;
class mt_in_mounts_wf,scan_tables_in_mounts_experimental_task,migrate_tables_in_mounts_experimental roadmap;
After a UCX table migration is executed, the migration dashboard will be populated with migration status information. More details can be found in the design of table migration
create-table-mapping- Createmapping.csvwhich will be used by the workflow to identify the targets catalog, schema, table of the HMS table to be migrated. User should review and update the mapping file accordingly before proceeding with the migration workflow.principal-prefix-access- Identify all the storages used in the workspace and corresponding Azure Service Principal or IAM role that are used in the workspace. It outputsazure_storage_account_info.csvoruc_roles_access.csvwhich will be later used bymigrate-credentialscommand to create UC storage credentials. The csv can be edited to control which IAM roles or Azure Service Principals should be used to create UC storage credentials later.migrate-credentials- Create UC storage credentials based on the Azure Service Principal or IAM role (azure_storage_account_info.csvoruc_roles_access.csv) identified byprincipal-prefix-accesscommand.migrate-locations- Create missing external locations in the Unity Catalog.create-catalogs-schemas- Create missing catalogs and schemas in the Unity Catalog. The candidate catalogs and schemas is based onmapping.csvcreate-uber-principal- Create an Uber Principal with access to all storages used in the workspace. This principal will be used by the workflow job cluster to migrate all the tables in the workspace.migrate-tables- Kick off the tables migration workflows.
create-table-mapping and create-uber-principal are required to run the workflow. While other commands are optional, as long as the UC storage credentials, external locations, catalogs and schemas needed for successful migration are created.
To control the scope of the table migration, consider utilizing a combination of editing mapping.csv, employing skip command, and revert-migrated-tables command.
See more details in Table migration commands
There are 3 main table migration workflows, targeting different table types. All table migration workflows are designed to migrate legacy table ACLs if existed, as well as downstream views that depend on the migrated tables.
migrate-tables- Migrate DBFS root Delta tables & external tables using SYNCmigrate_dbfs_root_delta_tables- Migrate Delta tables from the DBFS root using deep clone.migrate_external_tables_sync- Migrate external tables usingSYNCcommand. This does not create copy of the tables.
migrate-external-hiveserde-tables-in-place-experimental- Experimental in-place migration of HiveSerde tables. HiveSerDe tables include ParquetHiveSerDe, OrcSerde, AvroSerDe, LazySimpleSerDe, JsonSerDe, OpenCSVSerde tables.migrate_external_hiveserde_tables_in_place_experimental- Migrate HiveSerde tables in place.
- Following workflows/tasks are on the roadmap and being developed:
- Migrate tables using CTAS
- Experimentally migrate Delta and Parquet data found in dbfs mount but not registered as Hive Metastore table into UC tables.
- You may need to run the workflow multiple times to ensure all the tables are migrated successfully in phases.
- If your Delta tables in DBFS root have a large number of files, consider:
- Setting higher
MinandMax workers for auto-scalewhen being asked during the UCX installation. More cores in the cluster means more concurrency for calling cloud storage API to copy files when deep cloning the Delta tables. - Setting higher
Parallelism for migrating DBFS root Delta tables with deep clone(default 200) when being asked during the UCX installation. This controls the number of Spark tasks/partitions to be created for deep clone.
- Setting higher
- Consider creating an instance pool, and setting its id when prompted during the UCX installation. This instance pool will be specified in the cluster policy used by all UCX workflows job clusters.
- You may also manually edit the job cluster configration per job or per task after the workflows are deployed.
$ databricks labs ucx logs [--workflow WORKFLOW_NAME] [--debug]
This command displays the logs of the last run of the specified workflow. If no workflow is specified, it displays
the logs of the workflow that was run the last. This command is useful for developers and administrators who want to
check the logs of the last run of a workflow and ensure that it was executed as expected. It can also be used for
debugging purposes when a workflow is not behaving as expected. By default, only INFO, WARNING, and ERROR logs
are displayed. To display DEBUG logs, use the --debug flag.
databricks labs ucx ensure-assessment-run
This command ensures that the assessment workflow was run on a workspace.
This command will block until job finishes.
Failed workflows can be fixed with the repair-run command. Workflows and their status can be
listed with the workflows command.
databricks labs ucx repair-run --step WORKFLOW_NAME
This command repairs a failed UCX Workflow. This command is useful for developers and administrators who
want to repair a failed job. It can also be used to debug issues related to job failures. This operation can also be
done via user interface. Workflows and their
status can be listed with the workflows command.
See the migration process diagram to understand the role of each workflow in the migration process.
$ databricks labs ucx workflows
Step State Started
assessment RUNNING 1 hour 2 minutes ago
099-destroy-schema UNKNOWN <never run>
migrate-groups UNKNOWN <never run>
remove-workspace-local-backup-groups UNKNOWN <never run>
validate-groups-permissions UNKNOWN <never run>
This command displays the deployed workflows and their state in the current workspace. It fetches the latest
job status from the workspace and prints it in a table format. This command is useful for developers and administrators
who want to check the status of UCX workflows and ensure that they have been executed as expected. It can also be used
for debugging purposes when a workflow is not behaving as expected. Failed workflows can be fixed with
the repair-run command.
databricks labs ucx open-remote-config
This command opens the remote configuration file in the default web browser. It generates a link to the configuration file
and opens it using the webbrowser.open() method. This command is useful for developers and administrators who want to view or
edit the remote configuration file without having to manually navigate to it in the workspace. It can also be used to quickly
access the configuration file from the command line. Here's the description of configuration properties:
inventory_database: A string representing the name of the inventory database.workspace_group_regex: An optional string representing the regular expression to match workspace group names.workspace_group_replace: An optional string to replace the matched group names with.account_group_regex: An optional string representing the regular expression to match account group names.group_match_by_external_id: A boolean value indicating whether to match groups by their external IDs.include_group_names: An optional list of strings representing the names of groups to include for migration.renamed_group_prefix: An optional string representing the prefix to add to renamed group names.instance_pool_id: An optional string representing the ID of the instance pool.warehouse_id: An optional string representing the ID of the warehouse.connect: An optionalConfigobject representing the configuration for connecting to the warehouse.num_threads: An optional integer representing the number of threads to use for migration.database_to_catalog_mapping: An optional dictionary mapping source database names to target catalog names.default_catalog: An optional string representing the default catalog name.log_level: An optional string representing the log level.workspace_start_path: A string representing the starting path for notebooks and directories crawler in the workspace.instance_profile: An optional string representing the name of the instance profile.spark_conf: An optional dictionary of Spark configuration properties.override_clusters: An optional dictionary mapping job cluster names to existing cluster IDs.policy_id: An optional string representing the ID of the cluster policy.is_terraform_used: A boolean value indicating whether some workspace resources are managed by Terraform.include_databases: An optional list of strings representing the names of databases to include for migration.
$ databricks labs ucx installations
...
13:49:16 INFO [d.labs.ucx] Fetching installations...
13:49:17 INFO [d.l.blueprint.parallel][finding_ucx_installations_5] finding ucx installations 10/88, rps: 22.838/sec
13:49:17 INFO [d.l.blueprint.parallel][finding_ucx_installations_9] finding ucx installations 20/88, rps: 35.002/sec
13:49:17 INFO [d.l.blueprint.parallel][finding_ucx_installations_2] finding ucx installations 30/88, rps: 51.556/sec
13:49:18 INFO [d.l.blueprint.parallel][finding_ucx_installations_9] finding ucx installations 40/88, rps: 56.272/sec
13:49:18 INFO [d.l.blueprint.parallel][finding_ucx_installations_19] finding ucx installations 50/88, rps: 67.382/sec
...
Path Database Warehouse
/Users/serge.smertin@databricks.com/.ucx ucx 675eaf1ff976aa98
This command displays the installations by different users on the same workspace. It fetches all
the installations where the ucx package is installed and prints their details in JSON format. This command is useful
for administrators who want to see which users have installed ucx and where. It can also be used to debug issues
related to multiple installations of ucx on the same workspace.
databricks labs ucx report-account-compatibility --profile labs-azure-account
12:56:09 INFO [databricks.sdk] Using Azure CLI authentication with AAD tokens
12:56:09 INFO [d.l.u.account.aggregate] Generating readiness report
12:56:10 INFO [databricks.sdk] Using Azure CLI authentication with AAD tokens
12:56:10 INFO [databricks.sdk] Using Azure CLI authentication with AAD tokens
12:56:15 INFO [databricks.sdk] Using Azure CLI authentication with AAD tokens
12:56:15 INFO [d.l.u.account.aggregate] Querying Schema ucx
12:56:21 WARN [d.l.u.account.aggregate] Workspace 4045495039142306 does not have UCX installed
12:56:21 INFO [d.l.u.account.aggregate] UC compatibility: 30.303030303030297% (69/99)
12:56:21 INFO [d.l.u.account.aggregate] cluster type not supported : LEGACY_TABLE_ACL: 22 objects
12:56:21 INFO [d.l.u.account.aggregate] cluster type not supported : LEGACY_SINGLE_USER: 24 objects
12:56:21 INFO [d.l.u.account.aggregate] unsupported config: spark.hadoop.javax.jdo.option.ConnectionURL: 10 objects
12:56:21 INFO [d.l.u.account.aggregate] Uses azure service principal credentials config in cluster.: 1 objects
12:56:21 INFO [d.l.u.account.aggregate] No isolation shared clusters not supported in UC: 1 objects
12:56:21 INFO [d.l.u.account.aggregate] Data is in DBFS Root: 23 objects
12:56:21 INFO [d.l.u.account.aggregate] Non-DELTA format: UNKNOWN: 5 objects
These commands are used to assign a Unity Catalog metastore to a workspace. The metastore assignment is a pre-requisite for any further migration steps.
databricks labs ucx show-all-metastores [--workspace-id <workspace-id>]
This command lists all the metastores available to be assigned to a workspace. If no workspace is specified, it lists all the metastores available in the account. This command is useful when there are multiple metastores available within a region and you want to see which ones are available for assignment.
databricks labs ucx assign-metastore --workspace-id <workspace-id> [--metastore-id <metastore-id>]
This command assigns a metastore to a workspace with workspace-id. If there is only a single metastore in the workspace
region, it will be automatically assigned to the workspace. If there are multiple metastores available, you need to specify
the metastore id of the metastore you want to assign to the workspace.
These commands are vital part of table migration workflow process and require the assessment workflow and group migration workflow to be completed. See the migration process diagram to understand the role of the table migration commands in the migration process.
The first step is to run the principal-prefix-access command to identify all
the storage accounts used by tables in the workspace and their permissions on each storage account.
If you don't have any storage credentials and external locations configured, you'll need to run
the migrate-credentials command to migrate the service principals
and migrate-locations command to create the external locations.
If some of the external locations already exist, you should run
the validate-external-locations command.
You'll need to create the uber principal with the access to all storage used to tables in
the workspace, so that you can migrate all the tables. If you already have the principal, you can skip this step.
Ask your Databricks Account admin to run the sync-workspace-info command to sync the
workspace information with the UCX installations. Once the workspace information is synced, you can run the
create-table-mapping command to align your tables with the Unity Catalog,
create catalogs and schemas and start the migration using migrate-tables command. During multiple runs of
the table migration workflow, you can use the revert-migrated-tables command to
revert the tables that were migrated in the previous run. You can also skip the tables that you don't want to migrate
using the skip command.
Once you're done with the table migration, proceed to the code migration.
databricks labs ucx principal-prefix-access [--subscription-id <Azure Subscription ID>] [--aws-profile <AWS CLI profile>]
This command depends on results from the assessment workflow and requires AWS CLI
or Azure CLI to be installed and authenticated for the given machine. This command
identifies all the storage accounts used by tables in the workspace and their permissions on each storage account.
Once you're done running this command, proceed to the migrate-credentials command.
databricks labs ucx principal-prefix-access --aws-profile test-profile
Use to identify all instance profiles in the workspace, and map their access to S3 buckets.
Also captures the IAM roles which has UC arn listed, and map their access to S3 buckets
This requires aws CLI to be installed and configured.
Once done, proceed to the migrate-credentials command.
databricks labs ucx principal-prefix-access --subscription-id test-subscription-id
Use to identify all storage account used by tables, identify the relevant Azure service principals and their permissions
on each storage account. The command is used to identify Azure Service Principals, which have Storage Blob Data Contributor,
Storage Blob Data Reader, Storage Blob Data Owner roles, or custom read/write roles on ADLS Gen2 locations that are being
used in Databricks. This requires Azure CLI to be installed and configured via az login. It outputs azure_storage_account_info.csv
which will be later used by migrate-credentials command to create UC storage credentials.
Once done, proceed to the migrate-credentials command.
databricks labs ucx create-uber-principal [--subscription-id X]
Requires Cloud IAM admin privileges. Once the assessment workflow complete, you should run
this command to creates a service principal with the read-only access to all storage used by tables in this
workspace and configure the UCX Cluster Policy with the details of it. Once migration is complete, this
service principal should be unprovisioned. On Azure, it creates a principal with Storage Blob Data Reader role
assignment on every storage account using Azure Resource Manager APIs.
This command is one of prerequisites for the table migration workflow.
databricks labs ucx migrate-credentials
For Azure, this command prompts to confirm performing the following credential migration steps:
- [RECOMMENDED] For each storage account, create access connectors with managed identities that have the
Storage Blob Data Contributorrole on the respective storage account. An storage credential is created for each access connector. - Migrate Azure Service Principals, which have
Storage Blob Data Contributor,Storage Blob Data Reader,Storage Blob Data Owner, or custom roles on ADLS Gen2 locations that are being used in Databricks, to UC storage credentials. The Azure Service Principals to location mapping are listed in/Users/{user_name}/.ucx/azure_storage_account_info.csvwhich is generated byprincipal-prefix-accesscommand. Please review the file and delete the Service Principals you do not want to be migrated. The command will only migrate the Service Principals that have client secret stored in Databricks Secret.
Warning: Service principals used to access storage accounts behind firewalls might cause connectivity issues. We recommend to use access connectors instead.
Once you're done with this command, run validate-external-locations command after this one.
databricks labs ucx validate-external-locations
Once the assessment workflow finished successfully, storage credentials are configured,
run this command to validate and report the missing Unity Catalog external locations to be created.
This command validates and provides mapping to external tables to external locations, also as Terraform configurations.
Once you're done with this command, proceed to the migrate-locations command.
databricks labs ucx migrate-locations
Once the assessment workflow finished successfully, and storage credentials are configured,
run this command to have Unity Catalog external locations created. The candidate locations to be created are extracted from guess_external_locations
task in the assessment job. You can run validate-external-locations command to check the candidate locations.
Once you're done with this command, proceed to the create-table-mapping command.
databricks labs ucx create-table-mapping
Once the assessment workflow finished successfully
workspace info is synchronized, run this command to create the initial
table mapping for review in CSV format in the Databricks Workspace:
workspace_name,catalog_name,src_schema,dst_schema,src_table,dst_table
labs-azure,labs_azure,default,default,ucx_tybzs,ucx_tybzs
You are supposed to review this mapping and adjust it if necessary. This file is in CSV format, so that you can edit it easier in your favorite spreadsheet application.
Once you're done with this command, create catalogs and schemas. During
multiple runs of the table migration workflow, you can use the revert-migrated-tables command
to revert the tables that were migrated in the previous run. You can also skip the tables that you don't want to migrate
using the skip command.
This command is one of prerequisites for the table migration workflow.
Once you're done with table migration, proceed to the code migration.
databricks labs ucx skip --schema X [--table Y]
Anytime after create-table-mapping command is executed, you can run this command.
This command allows users to skip certain schemas or tables during the table migration process.
The command takes --schema and optionally --table flags to specify the schema and table to skip. If no --table flag
is provided, all tables in the specified HMS database are skipped.
This command is useful to temporarily disable migration of a particular schema or table.
Once you're done with table migration, proceed to the code migration.
databricks labs ucx create-catalogs-schemas
After create-table-mapping command is executed, you can run this command to have the required UC catalogs and schemas created.
This command is supposed to be run before migrating tables to UC using table migration workflow.
databricks labs ucx migrate-tables
Anytime after create-table-mapping command is executed, you can run this command.
This command kicks off the table migration process. It triggers the migrate-tables workflow,
and if there are HiveSerDe tables detected, prompt whether to trigger the migrate-external-hiveserde-tables-in-place-experimental workflow.
databricks labs ucx revert-migrated-tables --schema X --table Y [--delete-managed]
Anytime after create-table-mapping command is executed, you can run this command.
This command removes the upgraded_from property on a migrated table for re-migration in the table migration process.
This command is useful for developers and administrators who want to revert the migration of a table. It can also be used
to debug issues related to table migration.
Go back to the create-table-mapping command after you're done with this command.
databricks labs ucx move --from-catalog A --from-schema B --from-table C --to-catalog D --to-schema E
This command moves a UC table/tables from one schema to another schema after the table migration process. This is useful for developers and administrators who want to adjust their catalog structure after tables upgrade.
Users will be prompted whether tables/view are dropped after moving to new schema. This only applies to MANAGED tables and views.
This command moves different table types differently:
MANAGEDtables are deep-cloned to the new schema.EXTERNALtables are dropped from the original schema, then created in the target schema using the same location. This is due to Unity Catalog not supporting multiple tables with overlapping pathsVIEWare recreated using the same view definition.
This command supports moving multiple tables at once, by specifying * as the table name.
databricks labs ucx alias --from-catalog A --from-schema B --from-table C --to-catalog D --to-schema E
This command aliases a UC table/tables from one schema to another schema in the same or different catalog.
It takes a WorkspaceClient object and from and to parameters as parameters and aliases the tables using
the TableMove class. This command is useful for developers and administrators who want to create an alias for a table.
It can also be used to debug issues related to table aliasing.
See the migration process diagram to understand the role of the code migration commands in the migration process.
After you're done with the table migration, you can proceed to the code migration.
Once you're done with the code migration, you can run the cluster-remap command to remap the
clusters to be UC compatible.
databricks labs ucx migrate-local-code
(Experimental) Once table migration is complete, you can run this command to migrate all python and SQL files in the current working directory. This command is highly experimental and at the moment only supports Python and SQL files and discards code comments and formatting during the automated transformation process.
When installing UCX across multiple workspaces, administrators need to keep UCX configurations in sync.
UCX will prompt you to select an account profile that has been defined in ~/.databrickscfg. If you don't have one,
authenticate your machine with:
databricks auth login --host https://accounts.cloud.databricks.com/(AWS)databricks auth login --host https://accounts.azuredatabricks.net/(Azure)
Ask your Databricks Account admin to run the sync-workspace-info command to sync the
workspace information with the UCX installations. Once the workspace information is synced, you can run the
create-table-mapping command to align your tables with the Unity Catalog.
databricks labs ucx sync-workspace-info
14:07:07 INFO [databricks.sdk] Using Azure CLI authentication with AAD tokens
14:07:07 INFO [d.labs.ucx] Account ID: ...
14:07:10 INFO [d.l.blueprint.parallel][finding_ucx_installations_16] finding ucx installations 10/88, rps: 16.415/sec
14:07:10 INFO [d.l.blueprint.parallel][finding_ucx_installations_0] finding ucx installations 20/88, rps: 32.110/sec
14:07:11 INFO [d.l.blueprint.parallel][finding_ucx_installations_18] finding ucx installations 30/88, rps: 39.786/sec
...
Requires Databricks Account Administrator privileges. This command uploads the workspace config to all workspaces
in the account where ucx is installed. This command is necessary to create an immutable default catalog mapping for
table migration process and is the prerequisite
for create-table-mapping command.
If you cannot get account administrator privileges in reasonable time, you can take the risk and
run manual-workspace-info command to enter Databricks Workspace IDs and Databricks
Workspace names.
$ databricks labs ucx manual-workspace-info
14:20:36 WARN [d.l.ucx.account] You are strongly recommended to run "databricks labs ucx sync-workspace-info" by account admin,
... otherwise there is a significant risk of inconsistencies between different workspaces. This command will overwrite all UCX
... installations on this given workspace. Result may be consistent only within https://adb-987654321.10.azuredatabricks.net
Workspace name for 987654321 (default: workspace-987654321): labs-workspace
Next workspace id (default: stop): 12345
Workspace name for 12345 (default: workspace-12345): other-workspace
Next workspace id (default: stop):
14:21:19 INFO [d.l.blueprint.parallel][finding_ucx_installations_11] finding ucx installations 10/89, rps: 24.577/sec
14:21:19 INFO [d.l.blueprint.parallel][finding_ucx_installations_15] finding ucx installations 20/89, rps: 48.305/sec
...
14:21:20 INFO [d.l.ucx.account] Synchronised workspace id mapping for installations on current workspace
This command is only supposed to be run if the sync-workspace-info command cannot be
run. It prompts the user to enter the required information manually and creates the workspace info. This command is
useful for workspace administrators who are unable to use the sync-workspace-info command, because they are not
Databricks Account Administrators. It can also be used to manually create the workspace info in a new workspace.
$ databricks labs ucx create-account-groups [--workspace-ids 123,456,789]
Requires Databricks Account Administrator privileges. This command creates account-level groups if a workspace local
group is not present in the account. It crawls all workspaces configured in --workspace-ids flag, then creates
account level groups if a WS local group is not present in the account. If --workspace-ids flag is not specified, UCX
will create account groups for all workspaces configured in the account.
The following scenarios are supported, if a group X:
- Exist in workspaces A,B,C, and it has same members in there, it will be created in the account
- Exist in workspaces A,B but not in C, it will be created in the account
- Exist in workspaces A,B,C. It has same members in A,B, but not in C. Then, X and C_X will be created in the account
This command is useful for the setups, that don't have SCIM provisioning in place.
Once you're done with this command, proceed to the group migration workflow.
$ databricks labs ucx validate-groups-membership
...
14:30:36 INFO [d.l.u.workspace_access.groups] Found 483 account groups
14:30:36 INFO [d.l.u.workspace_access.groups] No group listing provided, all matching groups will be migrated
14:30:36 INFO [d.l.u.workspace_access.groups] There are no groups with different membership between account and workspace
Workspace Group Name Members Count Account Group Name Members Count Difference
This command validates the groups to see if the groups at the account level and workspace level have different membership. This command is useful for administrators who want to ensure that the groups have the correct membership. It can also be used to debug issues related to group membership. See group migration and group migration for more details.
Valid group membership is important to ensure users has correct access after legacy table ACL is migrated in table migration workflow
$ databricks labs ucx cluster-remap
21:29:38 INFO [d.labs.ucx] Remapping the Clusters to UC
Cluster Name Cluster Id
Field Eng Shared UC LTS Cluster 0601-182128-dcbte59m
Shared Autoscaling Americas cluster 0329-145545-rugby794
Please provide the cluster id's as comma separated value from the above list (default: <ALL>):
Once you're done with the code migration, you can run this command to remap the clusters to UC enabled.
This command will remap the cluster to uc enabled one. When we run this command it will list all the clusters and its id's and asks to provide the cluster id's as comma separated value which has to be remapped, by default it will take all cluster ids. Once we provide the cluster id's it will update these clusters to UC enabled.Back up of the existing cluster config will be stored in backup folder inside the installed location(backup/clusters/cluster_id.json) as a json file.This will help to revert the cluster remapping.
You can revert the cluster remapping using the revert-cluster-remap command.
$ databricks labs ucx revert-cluster-remap
21:31:29 INFO [d.labs.ucx] Reverting the Remapping of the Clusters from UC
21:31:33 INFO [d.labs.ucx] 0301-055912-4ske39iq
21:31:33 INFO [d.labs.ucx] 0306-121015-v1llqff6
Please provide the cluster id's as comma separated value from the above list (default: <ALL>):
If a customer want's to revert the cluster remap done using the cluster-remap command they can use this command to revert
its configuration from UC to original one.It will iterate through the list of clusters from the back up folder and reverts the
cluster configurations to original one.This will also ask the user to provide the list of clusters that has to be reverted as a prompt.
By default, it will revert all the clusters present in the backup folder
Please note that all projects in the databrickslabs GitHub account are provided for your exploration only, and are not formally supported by Databricks with Service Level Agreements (SLAs). They are provided AS-IS, and we do not make any guarantees of any kind. Please do not submit a support ticket relating to any issues arising from the use of these projects.
Any issues discovered through the use of this project should be filed as GitHub Issues on the Repo. They will be reviewed as time permits, but there are no formal SLAs for support.