Databricks-labs-ucx

* Improved error handling for `migrate-tables` workflows ([1674](https://github.com/databrickslabs/ucx/issues/1674)). This commit enhances the error handling for `migrate-tables` workflows by introducing new tests that cover specific scenarios where failures may occur during table migration. The changes include the creation of mock objects and injecting failures for the `get_tables_to_migrate` method of the `TableMapping` class. Three new tests have been added, each testing a specific scenario, including token errors when checking table properties, errors when trying to get properties for a non-existing table, and errors when trying to unset the `upgraded_to` property. The commit also asserts that specific error messages are logged during these failures. These improvements ensure better visibility and debugging capabilities during table migration. The code was manually tested, and unit tests were added and verified on a staging environment, ensuring that the new error handling mechanisms function as intended.
* Improved error handling for all queries executed during table migration ([1679](https://github.com/databrickslabs/ucx/issues/1679)). This release includes improved error handling during table migration in our data workflow, resolving issue [#167](https://github.com/databrickslabs/ucx/issues/167)
* Removed dependency on internal `pathlib` implementations ([1672](https://github.com/databrickslabs/ucx/issues/1672)). In this release, we have introduced a new custom `_DatabricksFlavor` class as a replacement for the internal `pathlib._Flavor` implementations, specifically designed for the Databricks environment. This class handles various functionalities including separation of paths, joining and parsing of parts, and casefolding of strings, among others. The `make_uri` method has also been updated to generate the correct URI for the workspace. This change removes the dependency on internal `pathlib._Flavor` implementations which were not available on Windows. As part of this change, the `test_wspath.py` file in the `tests/integration/mixins` directory has been updated, with the `test_exists` and `test_mkdirs` methods being modified to reflect the removal of `_Flavor`. These updates improve the compatibility and reliability of the codebase on Windows systems.
* Updated databricks-labs-blueprint requirement from ~=0.4.3 to >=0.4.3,<0.6.0 ([1670](https://github.com/databrickslabs/ucx/issues/1670)). In this update, we have adjusted the requirement for `databricks-labs-blueprint` from version `~=0.4.3` to `>=0.4.3,<0.6.0`, ensuring the latest version can be installed while remaining below `0.6.0`. This change is part of issue [#1670](https://github.com/databrickslabs/ucx/issues/1670) and includes the release notes and changelog in the commit message, highlighting improvements and updates in version `0.5.0`. These enhancements consist of content assertion in `MockInstallation`, better handling of partial functions in `parallel.Threads`, and adjusted configurations aligned with the UCX project. The commit also covers various dependency updates and bug fixes, providing a more robust and efficient library experience for software engineers.

Dependency updates:

* Updated databricks-labs-blueprint requirement from ~=0.4.3 to >=0.4.3,<0.6.0 ([1670](https://github.com/databrickslabs/ucx/pull/1670)).

* Added DBSQL queries & dashboard migration ([1532](https://github.com/databrickslabs/ucx/issues/1532)). The Databricks Labs Unified Command Extensions (UCX) project has been updated with two new experimental commands: `migrate-dbsql-dashboards` and `revert-dbsql-dashboards`. These commands are designed for migrating and reverting the migration of Databricks SQL dashboards in the workspace. The `migrate-dbsql-dashboards` command transforms all Databricks SQL dashboards in the workspace after table migration, tagging migrated dashboards and queries with `migrated by UCX` and backing up original queries. The `revert-dbsql-dashboards` command returns migrated Databricks SQL dashboards to their original state before migration. Both commands accept a `--dashboard-id` flag for migrating or reverting a specific dashboard. Additionally, two new functions, `migrate_dbsql_dashboards` and `revert_dbsql_dashboards`, have been added to the `cli.py` file, and new classes have been added to interact with Redash for data visualization and querying. The `make_dashboard` fixture has been updated to enhance testing capabilities, and new unit tests have been added for migrating and reverting DBSQL dashboards.
* Added UDFs assessment ([1610](https://github.com/databrickslabs/ucx/issues/1610)). A User Defined Function (UDF) assessment feature has been introduced, addressing issue [#1610](https://github.com/databrickslabs/ucx/issues/1610). A new method, DESCRIBE_FUNCTION, has been implemented to retrieve detailed information about UDFs, including function description, input parameters, and return types. This method has been integrated into existing test cases, enhancing the validation of UDF metadata and associated privileges, and ensuring system reliability. The UDF constructor has been updated with a new parameter 'comment', initially left blank in the test function. Additionally, two new columns, `success` and 'failures', have been added to the udf table in the inventory database to store assessment data for UDFs. The UdfsCrawler class has been updated to return a list of UDF objects, and the assertions in the test have been updated accordingly. Furthermore, a new SQL file has been added to calculate the total count of UDFs in the .udfs table, with a widget displaying this information as a counter visualization named "Total UDF Count".
* Added `databricks labs ucx create-missing-principals` command to create the missing UC roles in AWS ([1495](https://github.com/databrickslabs/ucx/issues/1495)). The `databricks labs ucx` tool now includes a new command, `create-missing-principals`, which creates missing Universal Catalog (UC) roles in AWS for S3 locations that lack a UC compatible role. This command is implemented using `IamRoleCreation` from `databricks.labs.ucx.aws.credentials` and updates `AWSRoleAction` with the corresponding `role_arn` while adding `AWSUCRoleCandidate`. The new command only supports AWS and does not affect Azure. The existing `migrate_credentials` function has been updated to handle Azure Service Principals migration. Additionally, new classes and methods have been added, including `AWSUCRoleCandidate` in `aws.py`, and `create_missing_principals` and `list_uc_roles` methods in `access.py`. The `create_uc_roles_cli` method in `access.py` has been refactored and renamed to `list_uc_roles`. New unit tests have been implemented to test the functionality of `create_missing_principals` for AWS and Azure, as well as testing the behavior when the command is not approved.
* Added baseline for workflow linter ([1613](https://github.com/databrickslabs/ucx/issues/1613)). This change introduces the `WorkflowLinter` class in the `application.py` file of the `databricks.labs.ucx.source_code.jobs` package. The class is used to lint workflows by checking their dependencies and ensuring they meet certain criteria, taking in arguments such as `workspace_client`, `dependency_resolver`, `path_lookup`, and `migration_index`. Several properties have been moved from `dependency_resolver` to the `CliContext` class, and the `NotebookLoader` class has been moved to a new location. Additionally, several classes and methods have been introduced to build a dependency graph, resolve dependencies, and manage allowed dependencies, site packages, and supported programming languages. The `generic` and `redash` modules from `databricks.labs.ucx.workspace_access` and the `GroupManager` class from `databricks.labs.ucx.workspace_access.groups` are used. The `VerifyHasMetastore`, `UdfsCrawler`, and `TablesMigrator` classes from `databricks.labs.ucx.hive_metastore` and the `DeployedWorkflows` class from `databricks.labs.ucx.installer.workflows` are also used. This commit is part of a larger effort to improve workflow linting and addresses several related issues and pull requests.
* Added linter to check for RDD use and JVM access ([1606](https://github.com/databrickslabs/ucx/issues/1606)). A new `AstHelper` class has been added to provide utility functions for working with abstract syntax trees (ASTs) in Python code, including methods for extracting attribute and function call node names. Additionally, a linter has been integrated to check for RDD use and JVM access, utilizing the `AstHelper` class, which has been moved to a separate module. A new file, 'spark_connect.py', introduces a linter with three matchers to ensure conformance to best practices and catch potential issues early in the development process related to RDD usage and JVM access. The linter is environment-aware, accommodating shared cluster and serverless configurations, and includes new test methods to validate its functionality. These improvements enhance codebase quality, promote reusability, and ensure performance and stability in Spark cluster environments.
* Added non-Delta DBFS table migration (What.DBFS_ROOT_NON_DELTA) in migrate_table workflow ([1621](https://github.com/databrickslabs/ucx/issues/1621)). The `migrate_tables` workflow in `workflows.py` has been enhanced to support a new scenario, DBFS_ROOT_NON_DELTA, which covers non-delta tables stored in DBFS root from the Hive Metastore to the Unity Catalog using CTAS. Additionally, the ACL migration strategy has been updated to include the AclMigrationWhat.PRINCIPAL strategy. The `migrate_external_tables_sync`, `migrate_dbfs_root_delta_tables`, and `migrate_views` tasks now incorporate the new ACL migration strategy. These changes have been thoroughly tested through unit tests and integration tests, ensuring the continued functionality of the existing workflow while expanding its capabilities.
* Added "seen tables" feature ([1465](https://github.com/databrickslabs/ucx/issues/1465)). The `seen tables` feature has been introduced, allowing for better handling of existing tables in the hive metastore and supporting their migration to UC. This enhancement includes the addition of a `snapshot` method that fetches and crawls table inventory, appending or overwriting records based on assessment results. The `_crawl` function has been updated to check for and skip existing tables in the current workspace. New methods such as '_get_tables_paths_from_assessment', '_overwrite_records', and `_get_table_location` have been included to facilitate these improvements. In the testing realm, a new test `test_mount_listing_seen_tables` has been implemented, replacing 'test_partitioned_csv_jsons'. This test checks the behavior of the TablesInMounts class when enumerating tables in mounts for a specific context, accounting for different table formats and managing external and managed tables. The diff modifies the 'locations.py' file in the databricks/labs/ucx directory, related to the hive metastore.
* Added support for `migrate-tables-ctas` workflow in the `databricks labs ucx migrate-tables` CLI command ([1660](https://github.com/databrickslabs/ucx/issues/1660)). This commit adds support for the `migrate-tables-ctas` workflow in the `databricks labs ucx migrate-tables` command, which checks for external tables that cannot be synced and prompts the user to run the `migrate-tables-ctas` workflow. Two new methods, `test_migrate_external_tables_ctas(ws)` and `migrate_tables(ws, prompts, ctx=ctx)`, have been added. The first method checks if the `migrate-external-tables-ctas` workflow is called correctly, while the second method runs the workflow after prompting the user. The method `test_migrate_external_hiveserde_tables_in_place(ws)` has been modified to test if the `migrate-external-hiveserde-tables-in-place-experimental` workflow is called correctly. No new methods or significant modifications to existing functionality have been made in this commit. The changes include updated unit tests and user documentation. The target audience for this feature are software engineers who adopt the project.
* Added support for migrating external location permissions from interactive cluster mounts ([1487](https://github.com/databrickslabs/ucx/issues/1487)). This commit adds support for migrating external location permissions from interactive cluster mounts in Databricks Labs' UCX project, enhancing security and access control. It retrieves interactive cluster locations and user mappings from the AzureACL class, granting necessary permissions to each cluster principal for each location. The existing `databricks labs ucx` command is modified, with the addition of the new method `create_external_locations` and thorough testing through manual, unit, and integration tests. This feature is developed by vuong-nguyen and Vuong and addresses issues [#1192](https://github.com/databrickslabs/ucx/issues/1192) and [#1193](https://github.com/databrickslabs/ucx/issues/1193), ensuring a more robust and controlled user experience with interactive clusters.
* Added uber principal spn details in SQL warehouse data access configuration when creating uber-SPN ([1631](https://github.com/databrickslabs/ucx/issues/1631)). In this release, we've implemented new features to enhance the security and control over data access during the migration process for the SQL warehouse data access configuration. The `databricks labs ucx create-uber-principal` command now creates a service principal with read-only access to all the storage used by tables in the workspace. The UCX Cluster Policy and SQL Warehouse data access configuration will be updated to use this service principal for migration workflows. A new method, `_update_sql_dac_with_instance_profile`, has been introduced in the `access.py` file to update the SQL data access configuration with the provided AWS instance profile, ensuring a more streamlined management of instance profiles within the SQL data access configuration during the creation of an uber service principal (SPN). Additionally, new methods and tests have been added to the sql module of the databricks.sdk.service package to improve Azure resource permissions, handling different scenarios related to creating a global SPN in the presence or absence of various conditions, such as storage, cluster policies, or secrets.
* Addressed issue with disabled features in certain regions ([1618](https://github.com/databrickslabs/ucx/issues/1618)). In this release, we have implemented improvements to address an issue where certain features were disabled in specific regions. We have added error handling when listing serving endpoints to raise a NotFound error if a feature is disabled, preventing the code from failing silently and providing better error messages. A new method, test_serving_endpoints_not_enabled, has been added, which creates a mock WorkspaceClient and raises a NotFound error if serving endpoints are not enabled for a shard. The GenericPermissionsSupport class uses this method to get crawler tasks, and if serving endpoints are not enabled, an error message is logged. These changes increase the reliability and robustness of the codebase by providing better error handling and messaging for this particular issue. Additionally, the change includes unit tests and manual testing to ensure the proper functioning of the new features.
* Aggregate UCX output across workspaces with CLI command ([1596](https://github.com/databrickslabs/ucx/issues/1596)). A new `report-account-compatibility` command has been added to the `databricks labs ucx` tool, enabling users to evaluate the compatibility of an entire Azure Databricks account with UCX (Unified Client Context). This command generates a readiness report for an Azure Databricks account, specifically for evaluating compatibility with UCX, by querying various aspects of the account such as clusters, configurations, and data formats. It uses Azure CLI authentication with AAD tokens for authentication and accepts a profile as an argument. The output includes warnings for workspaces that do not have UCX installed, and provides information about unsupported cluster types, unsupported configurations, data format compatibility, and more. Additionally, a new feature has been added to aggregate UCX output across workspaces in an account through a new CLI command, "report-account-compatibility", which can be run at the account level. The existing `manual-workspace-info` command remains unchanged. These changes will help assess the readiness and compatibility of an Azure Databricks account for UCX integration and simplify the process of checking compatibility across an entire account.
* Assert if group name is in cluster policy ([1665](https://github.com/databrickslabs/ucx/issues/1665)). In this release, we have implemented a change to ensure the presence of the display name of a specific workspace group (ws_group_a) in the cluster policy. This is to prevent a key error previously encountered. The cluster policy is now loaded as a dictionary, and the group name is checked to confirm its presence. If the group is not found, a message is raised alerting users. Additionally, the permission level for the group is verified to ensure it is set to CAN_USE. No new methods have been added, and existing functionality remains unchanged. The test file test_ext_hms.py has been updated to include the new assertion and has undergone both unit tests and manual testing to ensure proper implementation. This change is intended for software engineers who adopt the project.
* Automatically retrying with `auth_type=azure-cli` when constructing `workspace_clients` on Azure ([1650](https://github.com/databrickslabs/ucx/issues/1650)). This commit introduces automatic retrying with 'auth_type=azure-cli' when constructing `workspace_clients` on Azure, resolving TODO items for `AccountWorkspaces` and adding relevant suggestions in 'troubleshooting.md'. It closes issues [#1574](https://github.com/databrickslabs/ucx/issues/1574) and [#1430](https://github.com/databrickslabs/ucx/issues/1430), and includes new methods for generating readiness reports in `AccountAggregate` and testing the `get_accessible_workspaces` method in 'test_workspaces.py'. User documentation has been updated and the changes have been manually verified in a staging environment. For macOS and Windows users, explicit auth type settings are required for command line utilities.
* Changes to identify service principal with custom roles on Azure storage account for principal-prefix-access ([1576](https://github.com/databrickslabs/ucx/issues/1576)). This release introduces several enhancements to the identification of service principals with custom roles on Azure storage accounts for principal-prefix-access. New methods such as `_get_permission_level`, `_get_custom_role_privilege`, and `_get_role_privilege` have been added to improve the functionality of the module. Additionally, two new classes, AzureRoleAssignment and AzureRoleDetails, have been added to enable more detailed management and access control for custom roles on Azure storage accounts. The 'test_access.py' file has been updated to include tests for saving custom roles in Azure storage accounts and ensuring the correct identification of service principals with custom roles. A new unit test function, test_role_assignments_custom_storage(), has also been added to verify the behavior of custom roles in Azure storage accounts. Overall, these changes provide a more efficient and fine-grained way to manage and control custom roles on Azure storage accounts.
* Clarified unsupported config in compute crawler ([1656](https://github.com/databrickslabs/ucx/issues/1656)). In this release, we have made significant changes to clarify and improve the handling of unsupported configurations in our compute crawler related to the Hive metastore. We have expanded error messages for unsupported configurations and provided detailed recommendations for remediation. Additionally, we have added relevant user documentation and manually tested the changes. The changes include updates to the configuration for external Hive metastore and passthrough security model for Unity Catalog, which are incompatible with the current configurations. We recommend removing or altering the configs while migrating existing tables and views using UCX or other compatible clusters, and mapping the passthrough security model to a security model compatible with Unity Catalog. The code modifications include the addition of new methods for checking cluster init script and Spark configurations, as well as refining the error messages for unsupported configurations. We also added a new assertion in the `test_cluster_with_multiple_failures` unit test to check for the presence of a specific message regarding the use of the `spark.databricks.passthrough.enabled` configuration. This release is not yet verified on the staging environment.
* Created a unique default schema when External Hive Metastore is detected ([1579](https://github.com/databrickslabs/ucx/issues/1579)). A new default database `ucx` is introduced for storing inventory in the hive metastore, with a suffix consisting of the workspace's client ID to ensure uniqueness when an external hive metastore is detected. The `has_ext_hms()` method is added to the `InstallationPolicy` class to detect external HMS and thereby create a unique default schema. The `_prompt_for_new_installation` method's default value for the `Inventory Database stored in hive_metastore` prompt is updated to use the new default database name, modified to include the workspace's client ID if external HMS is detected. Additionally, a test function `test_save_config_ext_hms` is implemented to demonstrate the `WorkspaceInstaller` class's behavior with external HMS, creating a unique default schema for improved system functionality and customization. This change is part of issue [#1579](https://github.com/databrickslabs/ucx/issues/1579).
* Extend service principal migration to create storage credentials for access connectors created for each storage account ([1426](https://github.com/databrickslabs/ucx/issues/1426)). This commit extends the service principal migration to create storage credentials for access connectors associated with each storage account, resolving issues [#1384](https://github.com/databrickslabs/ucx/issues/1384) and [#875](https://github.com/databrickslabs/ucx/issues/875). The update includes modifications to the existing `databricks labs ucx` command for creating access connectors, adds a new CLI command for creating storage credentials, and updates the documentation. A new workflow has been added for creating credentials for access connectors and service principals, and updates have been made to existing workflows. The commit includes manual, unit, and integration tests, and no new or modified methods are specified in the diff. The focus is on the feature description and its impact on the project's functionality. The commit has been co-authored by Serge Smertin and vuong-nguyen.
* Suggest users to create Access Connector(s) with Managed Identity to access Azure Storage Accounts behind firewall ([1589](https://github.com/databrickslabs/ucx/issues/1589)). In this release, we have introduced a new feature to improve access to Azure Storage Accounts that are protected by firewalls. Due to limitations with service principals in such scenarios, we have developed Access Connectors with Managed Identities for more reliable connectivity. This change includes updates to the 'credentials.py' file, which introduces new methods for managing the migration of service principals to Access Connectors using Managed Identities. Users are warned that migrating to this new feature may cause issues when transitioning to UC, and are advised to validate external locations after running the migration command. This update enhances the security and functionality of the system, providing a more dependable method for accessing Azure Storage Accounts protected by firewalls.
* Fixed catalog/schema grants when tables with same source schema have different target schemas ([1581](https://github.com/databrickslabs/ucx/issues/1581)). In this release, we have implemented a fix to address an issue where catalog/schema grants were not being handled correctly when tables with the same source schema had different target schemas. This was causing problems with granting appropriate permissions to users. We have modified the prepare_test function to include an additional test case with a different target schema for the same source table. Furthermore, we have updated the test_catalog_schema_acl function to ensure that grants are being created correctly for all catalogs, schemas, and tables. We have also added an extra query to grant use schema permissions for catalog2.schema3 to user1. Additionally, we have introduced a new `SchemaInfo` class to store information about catalogs and schemas, and refactored the `_get_database_source_target_mapping` method to return a dictionary that maps source databases to a list of `SchemaInfo` objects instead of a single dictionary. These changes ensure that grants are being handled correctly for catalogs, schemas, and tables, even when tables with the same source schema have different target schemas. This will improve the overall functionality and reliability of the system, making it easier for users to manage their catalogs and schemas.
* Fixed Spark configuration parameter referencing secret ([1635](https://github.com/databrickslabs/ucx/issues/1635)). In this release, the code related to the Spark configuration parameter reference for a secret has been updated in the `access.py` file, specifically within the `_update_cluster_policy_definition` method. The change modifies the method to retrieve the OAuth client secret for a given storage account using an f-string to reference the secret, replacing the previous concatenation operator. This enhancement is aimed at improving the readability and maintainability of the code while preserving its functionality. Furthermore, the commit includes additional changes, such as new methods `test_create_global_spn` and "cluster_policies.edit", which may be related to this fix. These changes address the secret reference issue, ensuring secure access control and improved integration, particularly with the Spark configuration, benefiting engineers utilizing this project for handling sensitive information and managing clusters securely and effectively.
* Fixed `migration-locations` and `assign-metastore` definitions in `labs.yml` ([1627](https://github.com/databrickslabs/ucx/issues/1627)). In this release, the `migration-locations` command in the `labs.yml` file has been updated to include new flags `subscription-id` and `aws-profile`. The `subscription-id` flag allows users to specify the subscription to scan the storage account in, and the `aws-profile` flag allows for authentication using a specified AWS Profile. The `assign-metastore` command has also been updated with a new description: "Enable Unity Catalog features on a workspace by assigning a metastore to it." The `is_account_level` parameter remains unchanged, and the new optional flag `workspace-id` has been added, allowing users to specify the Workspace ID to assign a metastore to. This change enhances the functionality of the `migration-locations` and `assign-metastore` commands, providing more options for users to customize their storage scanning and metastore assignment processes. The `migration-locations` and `assign-metastore` definitions in the `labs.yml` file have been fixed in this release.
* Fixed prompt for using external metastore ([1668](https://github.com/databrickslabs/ucx/issues/1668)). A fix has been implemented in the `create` function of the `policy.py` file to correctly prompt users for using an external metastore. Previously, a missing period and space in the prompt caused potential confusion. The updated prompt now includes a clarifying sentence and the `_prompts.confirm` method has been modified to check if the user wants to set UCX to connect to an external metastore in two scenarios: when one or more cluster policies are set up for an external metastore, and when the workspace warehouse is configured for an external metastore. If the user chooses to set up an external metastore, an informational message will be recorded in the logger. This change ensures clear and precise communication with users during the external metastore setup process.
* Fixed storage account network ACLs retrieved from properties ([1620](https://github.com/databrickslabs/ucx/issues/1620)). This release includes a fix to the storage account network ACLs retrieval in the open-source library, addressing issue [#1](https://github.com/databrickslabs/ucx/issues/1). Previously, the network ACLs were being retrieved from an incorrect location, but this commit corrects that by obtaining the network ACLs from the storage account's properties.networkAcls field. The `StorageAccount` class has been updated to modify the way default network action is retrieved, with a new value `Unknown` added to the previous values `Deny` and "Allow". The `from_raw_resource` class method has also been updated to retrieve the default network action from the `properties.networkAcls` field instead of the `networkAcls` field. This change may affect any functionality that relies on network ACL information and impacts the existing command `databricks labs ucx ...`. Relevant tests, including a new test `test_azure_resource_storage_accounts_list_non_zero`, have been added and manually and unit tested to ensure the fix is functioning correctly.
* Fully refresh table migration status in table migration workflow ([1630](https://github.com/databrickslabs/ucx/issues/1630)). This release introduces a new method, `index_full_refresh()`, to the table migration workflow for fully refreshing the migration status, addressing an oversight from a previous commit ([#1623](https://github.com/databrickslabs/ucx/issues/1623)) and resolving issue [#1628](https://github.com/databrickslabs/ucx/issues/1628). The new method resets the `_migration_status_refresher` before computing the index, ensuring the latest migration status is used for determining whether view dependencies have been migrated. The `index()` method was previously used to refresh the migration status, but it only provided a partial refresh. With this update, `index_full_refresh()` is utilized for a comprehensive refresh, affecting the `refresh_migration_status` task in multiple workflows such as `migrate_views`, `scan_tables_in_mounts_experimental`, and others. This change ensures a more accurate migration report, presenting the updated migration status.
* Ignore existing corrupted installations when refreshing ([1605](https://github.com/databrickslabs/ucx/issues/1605)). A recent update has enhanced the error handling during the loading of installations in the `install.py` file. Specifically, the `installation.load` function now handles certain errors, including `PermissionDenied`, `SerdeError`, `ValueError`, and `AttributeError`, by logging a warning message and skipping the corrupted installation instead of raising an error. This behavior has been incorporated into both the `configure` and `_check_inventory_database_exists` functions, allowing the installation process to continue even in the presence of issues with existing installations, while providing improved error messages. This change resolves issue [#1601](https://github.com/databrickslabs/ucx/issues/1601) and introduces a new test case for a corrupted installation configuration, as well as an updated existing test case for `test_save_config` that includes a mock installation.
* Improved exception handling ([1584](https://github.com/databrickslabs/ucx/issues/1584)). In this release, the exception handling during the upload of a wheel file to DBFS has been significantly improved. Previously, only PermissionDenied errors were caught and handled. Now, both BadRequest and PermissionDenied exceptions will be caught and logged as a warning. This change enhances the robustness of the code by handling a wider range of exceptions during the upload process. In addition, cluster overrides have been configured and DBFS write permissions have been set up. The specific changes made to the code include updating the import statement for NotFound to include BadRequest and modifying the except block in the _get_init_script_data method to catch both NotFound and BadRequest exceptions. These improvements ensure that the code can handle more types of errors, providing more helpful error messages and preventing crash scenarios, thereby enhancing the reliability and robustness of the code.
* Improved exception handling for `migrate_acl` ([1590](https://github.com/databrickslabs/ucx/issues/1590)). In this release, the `migrate_acl` functionality has been enhanced to improve exception handling, addressing a flakiness issue in the `test_migrate_managed_tables_with_acl` test. Previously, unhandled `not found` exceptions during parallel test execution caused the flakiness. This release resolves this issue ([#1549](https://github.com/databrickslabs/ucx/issues/1549)) by introducing error handling in the `test_migrate_acls_should_produce_proper_queries` test. A controlled error is now introduced to simulate a failed grant migration due to a `TABLE_OR_VIEW_NOT_FOUND` error. This enhancement allows for precise testing of error handling and logging mechanisms when migration fails for specific objects, ensuring a more reliable testing environment for the `migrate_acl` functionality.
* Improved reliability of table migration status refresher ([1623](https://github.com/databrickslabs/ucx/issues/1623)). This release introduces improvements to the table migration status refresher in the open-source library, enhancing its reliability and robustness. The `table_migrate` function has been updated to ensure that the table migration status is always reset when requesting the latest snapshot, addressing issues [#1623](https://github.com/databrickslabs/ucx/issues/1623), [#1622](https://github.com/databrickslabs/ucx/issues/1622), and [#1615](https://github.com/databrickslabs/ucx/issues/1615). Additionally, the function now handles `NotFound` errors when refreshing migration status. The `get_seen_tables` function has been modified to convert the returned iterator to a list and raise a `NotFound` exception if the schema does not exist, which is then caught and logged as a warning. Furthermore, the migration status reset behavior has been improved, and the `migration_status_refresher` parameter type in the `TableMigrate` class constructor has been modified. New private methods `_index_with_reset()` and updated `_migrate_views()` and `_view_can_be_migrated()` methods have been added to ensure a more accurate and consistent table migration process. The changes have been thoroughly tested and are ready for review.
* Refresh migration status at the end of the `migrate_tables` workflows ([1599](https://github.com/databrickslabs/ucx/issues/1599)). In this release, updates have been made to the migration status at the end of the `migrate_tables` workflows, with no new or modified tables or methods introduced. The `_migration_status_refresher.reset()` method has been added in two locations to ensure accurate migration status updates. A new `refresh_migration_status` method has been included in the `RuntimeContext` class in the `databricks.labs.ucx.hive_metastore.workflows` module, which refreshes the migration status for presentation in the dashboard. The changes also include the addition of the `refresh_migration_status` task in `migrate_views`, `migrate_views_with_acl`, and `scan_tables_in_mounts_experimental` workflows, and the `migration_report` method is now dependent on the `refresh_migration_status` task. Thorough testing has been conducted, including the creation of a new integration test in the file `tests/integration/hive_metastore/test_workflows.py` to verify that the migration status is refreshed after the migration job is run. These changes aim to ensure that the migration status is up-to-date and accurately presented in the dashboard.
* Removed DBFS library installations ([1554](https://github.com/databrickslabs/ucx/issues/1554)). In this release, the "configure.py" file has been removed, which previously contained the `ConfigureClusterOverrides` class with methods for validating cluster IDs, distinguishing between classic and Table Access Control (TACL) clusters, and building a prompt for users to select a valid active cluster ID. The removal of this file signifies that these functionalities are no longer available. This change is part of a larger commit that also removes DBFS library installations and updates the Estimates Dashboard to remove metastore assignment, addressing issue [#1098](https://github.com/databrickslabs/ucx/issues/1098). The commit has been tested via integration tests and manual installation and running of UCX on a no-uc environment. Please note that the `create_jobs` method in the `install.py` file has been updated to reflect these changes, ensuring a more straightforward installation experience and usage of the Estimates Dashboard.
* Removed the `Is Terraform used` prompt ([1664](https://github.com/databrickslabs/ucx/issues/1664)). In this release, we have removed the `is_terraform_used` prompt from the configuration file and the installation process in the ucx package. This prompt was not being utilized and had been a source of confusion for some users. Although the variable that stored its outcome will be retained for backwards compatibility, no new methods or modifications to existing functionality have been introduced. No tests have been added or modified as part of this change. The removal of this prompt simplifies the configuration process and aligns with the project's future plans to eliminate the use of Terraform state for ucx migration. Manual testing has been conducted to ensure that the removal of the prompt does not affect the functionality of other properties in the configuration file or the installation process.
* Resolve relative paths when building dependency graph ([1608](https://github.com/databrickslabs/ucx/issues/1608)). This commit introduces support for resolving relative paths when building a dependency graph in the UCX project, addressing issues 1202, 1499, and 1287. The SysPathProvider now includes a `cwd` attribute, and a new class, LocalNotebookLoader, has been implemented to handle local files and folders. The PathLookup class is used to resolve paths, and new methods have been added to support these changes. Unit tests have been provided to ensure the correct functioning of the new functionality. This commit replaces issue 1593 and enhances the project's ability to handle local files and folders, resulting in a more robust and reliable dependency graph.
* Show tables migration status in migration dashboard ([1507](https://github.com/databrickslabs/ucx/issues/1507)). A migration dashboard has been added to display the status of data object migrations, addressing issue [#323](https://github.com/databrickslabs/ucx/issues/323). This new feature includes a query to show the migration status of tables, a new CLI command, and a modification to an existing command. The `migrataion-*` workflow has been updated to include a refresh migration dashboard option. The `mock_installation` function has been modified with an updated state.json file. The changes consist of manual testing and can be found in the `migrations/main` directory as a new SQL query file. This migration dashboard provides users with an easier way to monitor the progress and status of their data migration tasks.
* Simulate loading of local files or notebooks after manipulation of `sys.path` ([1633](https://github.com/databrickslabs/ucx/issues/1633)). This commit updates the PathLookup process during the construction of the dependency graph, addressing issues [#1202](https://github.com/databrickslabs/ucx/issues/1202) and [#1468](https://github.com/databrickslabs/ucx/issues/1468). It simplifies the DependencyGraphBuilder by directly using the DependencyResolver with resolvers and lookup passed as arguments, and removes the DependencyGraphBuilder. The changes include new methods for handling compatibility checks, but no new user-facing features or changes to command-line interfaces or existing workflows are introduced. Unit tests are included to ensure correct behavior. The modifications aim to improve the internal handling of dependency resolution and compatibility checks.
* Test if `create-catalogs-schemas` works with tables defined as mount paths ([1578](https://github.com/databrickslabs/ucx/issues/1578)). This release includes a new unit test for the `create-catalogs-schemas` logic that verifies the correct creation and management of catalogs and schemas defined as mount paths. The test checks the storage location of catalogs, ensures non-existing schemas are properly created, and prevents the creation of catalogs without a storage location. It also verifies the catalog schema ACL is set correctly. Using the `CatalogSchema` class and various test functions, the test creates and grants permissions to catalogs and schemas. This change resolves issue [#1039](https://github.com/databrickslabs/ucx/issues/1039) without modifying any existing commands or workflows. The release contains no new CLI commands or user documentation, but includes unit tests and assertion calls to validate the behavior of the `create_all_catalogs_schemas` method.
* Upgraded `databricks-sdk` to 0.27 ([1626](https://github.com/databrickslabs/ucx/issues/1626)). In this release, the `databricks-sdk` package has been upgraded to version 0.27, bringing updated methods for Redash objects. The `_install_query` method in the `dashboards.py` file has been updated to include a `tags` parameter, set to `None`, when calling `self._ws.queries.update` and `self._ws.queries.create`. This ensures that the updated SDK version is used and that tags are not applied during query updates and creation. Additionally, the `databricks-labs-lsql` and `databricks-labs-blueprint` packages have been updated to versions 0.4.0 and 0.4.3 respectively, and the dependency for PyYAML has been updated to a version between 6.0.0 and 7.0.0. These updates may impact the functionality of the project. The changes have been manually tested, but there is no verification on a staging environment.
* Use stack of dependency resolvers ([1560](https://github.com/databrickslabs/ucx/issues/1560)). This pull request introduces a stack-based implementation of resolvers, resolving issues [#1202](https://github.com/databrickslabs/ucx/issues/1202), [#1499](https://github.com/databrickslabs/ucx/issues/1499), and [#1421](https://github.com/databrickslabs/ucx/issues/1421), and implements an initial version of SysPathProvider, while eliminating previous hacks. The new functionality includes modified existing commands, a new workflow, and the addition of unit tests. No new documentation or CLI commands have been added. The `problem_collector` parameter is not addressed in this PR and has been moved to a separate issue. The changes include renaming and moving a Python file, as well as modifications to the `Notebook` class and its related methods for handling notebook dependencies and dependency checking. The code has been tested, but manual testing and integration tests are still pending.

* A notebook linter to detect DBFS references within notebook cells ([1393](https://github.com/databrickslabs/ucx/issues/1393)). A new linter has been implemented in the open-source library to identify references to Databricks File System (DBFS) mount points or folders within SQL and Python cells of Notebooks, raising Advisory or Deprecated alerts when detected. This feature, resolving issue [#1108](https://github.com/databrickslabs/ucx/issues/1108), enhances code maintainability by discouraging DBFS usage, and improves security by avoiding hard-coded DBFS paths. The linter's functionality includes parsing the code and searching for Table elements within statements, raising warnings when DBFS references are found. Implementation changes include updates to the `NotebookLinter` class, a new `from_source` class method, and an `original_offset` argument in the `Cell` class. The linter now also supports the `databricks` dialect for SQL code parsing. This feature improves the library's security and maintainability by ensuring better data management and avoiding hard-coded DBFS paths.
* Added CLI commands to trigger table migration workflow ([1511](https://github.com/databrickslabs/ucx/issues/1511)). A new `migrate_tables` command has been added to the 'databricks.labs.ucx.cli' module, which triggers the `migrate-tables` workflow and, optionally, the `migrate-external-hiveserde-tables-in-place-experimental` workflow. The `migrate-tables` workflow is responsible for managing table migrations, while the `migrate-external-hiveserde-tables-in-place-experimental` workflow handles migrations for external hiveserde tables. The new `What` class from the 'databricks.labs.ucx.hive_metastore.tables' module is used to identify hiveserde tables. If hiveserde tables are detected, the user is prompted to confirm running the `migrate-external-hiveserde-tables-in-place-experimental` workflow. The `migrate_tables` command requires a WorkspaceClient and Prompts objects and accepts an optional WorkspaceContext object, which is set to the WorkspaceContext of the WorkspaceClient if not provided. Additionally, a new `migrate_external_hiveserde_tables_in_place` command has been added which will run the `migrate-external-hiveserde-tables-in-place-experimental` workflow if it finds any hiveserde tables, making it easier to manage table migrations from the command line.
* Added CSV, JSON and include path in mounts ([1329](https://github.com/databrickslabs/ucx/issues/1329)). In this release, the TablesInMounts function has been enhanced to support CSV and JSON file formats, along with the existing Parquet and Delta table formats. The new `include_paths_in_mount` parameter has been introduced, enabling users to specify a list of paths to crawl within all mounts. The WorkspaceConfig class in the config.py file has been updated to accommodate these changes. Additionally, a new `_assess_path` method has been introduced to assess the format of a given file and return a `TableInMount` object accordingly. Several existing methods, such as `_find_delta_log_folders`, `_is_parquet`, `_is_csv`, `_is_json`, and `_path_is_delta`, have been updated to reflect these improvements. Furthermore, two new unit tests, `test_mount_include_paths` and `test_mount_listing_csv_json`, have been added to ensure the proper functioning of the TablesInMounts function with the new file formats and the `include_paths_in_mount` parameter. These changes aim to improve the functionality and flexibility of the TablesInMounts library, allowing for more precise crawling and identification of tables based on specific file formats and paths.
* Added CTAS migration workflow for external tables cannot be in place migrated ([1510](https://github.com/databrickslabs/ucx/issues/1510)). In this release, we have added a new CTAS (Create Table As Select) migration workflow for external tables that cannot be migrated in-place. This feature includes a `MigrateExternalTablesCTAS` class with three tasks to migrate non-SYNC supported and non-HiveSerde external tables, migrate HiveSerde tables, and migrate views from the Hive Metastore to the Unity Catalog. We have also added new methods for managed and external table migration, deprecated old methods, and added a new test function to ensure proper CTAS migration for external tables using HiveSerDe. This change also introduces a new JSON file for external table configurations and a mock backend to simulate the Hive Metastore and test the migration process. Overall, these changes improve the migration capabilities for external tables and ensure a more flexible and reliable migration process.
* Added Python linter for table creation with implicit format ([1435](https://github.com/databrickslabs/ucx/issues/1435)). A new linter has been added to the Python library to advise on implicit table formats when the 'writeTo', 'table', 'insertInto', or `saveAsTable` methods are invoked without an explicit format specified in the same chain of calls. This feature is useful for software engineers working with Databricks Runtime (DBR) v8.0 and later, where the default table format changed from `parquet` to 'delta'. The linter, implemented in 'table_creation.py', utilizes reusable AST utilities from 'python_ast_util.py' and is not automated, providing advice instead of fixing the code. The linter skips linting when a DRM version of 8.0 or higher is passed, as the default format change only applies to versions prior to 8.0. Unit tests have been added for both files as part of the code migration workflow.
* Added Support for Migrating Table ACL of Interactive clusters using SPN ([1077](https://github.com/databrickslabs/ucx/issues/1077)). This change introduces support for migrating table Access Control Lists (ACLs) of interactive clusters using a Security Principal Name (SPN) for Azure Databricks environments in the UCX project. It includes modifications to the `hive_metastore` and `workspace_access` modules, as well as the addition of new classes, methods, and import statements for handling ACLs and grants. This feature enables more secure and granular control over table permissions when using SPN authentication for interactive clusters in Azure. This will benefit software engineers working with interactive clusters in Azure Databricks by enhancing security and providing more control over data access.
* Added Support for migrating Schema/Catalog ACL for Interactive cluster ([1413](https://github.com/databrickslabs/ucx/issues/1413)). This commit adds support for migrating schema and catalog ACLs for interactive clusters, specifically for AWS and Azure, with partial fixes for issues [#1192](https://github.com/databrickslabs/ucx/issues/1192) and [#1193](https://github.com/databrickslabs/ucx/issues/1193). The changes identify and filter database ACL grants, create mappings from Hive metastore schema to Unity Catalog schema and catalog, and replace Hive metastore actions with equivalent Unity Catalog actions for both schema and catalog. External location permission is not included in this commit and will be addressed separately. New methods for creating mappings, updating principal ACLs, and getting catalog schema grants have been added, and existing functionalities have been modified to handle both AWS and Azure. The code has undergone manual testing and passed unit and integration tests. The changes are targeted towards software engineers who adopt the project.
* Added `databricks labs ucx logs` command ([1350](https://github.com/databrickslabs/ucx/issues/1350)). A new command, 'databricks labs ucx logs', has been added to the open-source library to enhance logging and debugging capabilities. This command allows developers and administrators to view logs from the latest job run or specify a particular workflow name to display its logs. By default, logs with levels of INFO, WARNING, and ERROR are shown, but the --debug flag can be used for more detailed DEBUG logs. This feature utilizes the relay_logs method from the deployed_workflows object in the WorkspaceContext class and addresses issue [#1282](https://github.com/databrickslabs/ucx/issues/1282). The addition of this command aims to improve the usability and maintainability of the framework, making it easier for users to diagnose and resolve issues.
* Added check for DBFS mounts in SQL code ([1351](https://github.com/databrickslabs/ucx/issues/1351)). A new feature has been introduced to check for Databricks File System (DBFS) mounts within SQL code, enhancing data management and accessibility in the Databricks environment. The `dbfsqueries.py` file in the `databricks/labs/ucx/source_code` directory now includes a function that verifies the presence of DBFS mounts in SQL queries and returns appropriate messages. The `Languages` class in the `__init__` method has been updated to incorporate a new class, `FromDbfsFolder`, which replaces the existing `from_table` linter with a new linter, `DBFSUsageLinter`, for handling DBFS usage in SQL code. In addition, a Staff Software Engineer has improved the functionality of a DBFS usage linter tool by adding new methods to check for deprecated DBFS mounts in SQL code, returning deprecation warnings as needed. These enhancements ensure more robust handling of DBFS mounts throughout the system, allowing for better integration and management of DBFS-related issues in SQL-based operations.
* Added check for circular view dependency ([1502](https://github.com/databrickslabs/ucx/issues/1502)). A circular view dependency check has been implemented to prevent issues caused by circular dependencies in views. This includes a new test for chained circular dependencies (A->B, B->C, C->A) and an update to the existing circular view dependency test. The checks have been implemented through modifications to the tests in `test_views_sequencer.py`, including a new test method and an update to the existing test method. If any circular dependencies are encountered during migration, a ValueError with an error message will be raised. These changes include updates to the `tables_and_views.json` file, with the addition of a new view `v12` that depends on `v11`, creating a circular dependency. The changes have been tested through the addition of unit tests and are expected to function as intended. No new methods have been added, but changes have been made to the existing `_next_batch` method and two new methods, `_check_circular_dependency` and `_get_view_instance`, have been introduced.
* Added commands for metastores listing & assignment ([1489](https://github.com/databrickslabs/ucx/issues/1489)). This commit introduces new commands for handling metastores in the Databricks Labs Unity Catalog (UCX) tool, which enables more efficient management of metastores. The `databricks labs ucx assign-metastore` command automatically assigns a metastore to a specified workspace when possible, while the `databricks labs ucx show-all-metastores` command displays all possible metastores that can be assigned to a workspace. These changes include new methods for handling metastores in the account and workspace classes, as well as new user documentation, manual testing, and unit tests. The new functionality is added to improve the usability and efficiency of the UCX tool in handling metastores. Additional information on the UCX metastore commands is provided in the README.md file.
* Added functionality to migrate external tables using Create Table (No Sync) ([1432](https://github.com/databrickslabs/ucx/issues/1432)). A new feature has been implemented for migrating external tables in Databricks' Hive metastore using the "Create Table (No Sync)" method. This feature includes the addition of two new methods, `_migrate_non_sync_table` and `_get_create_in_place_sql`, for handling migration and SQL query generation. The existing methods `_migrate_dbfs_root_table` and `_migrate_acl` have also been updated. A test case has been added to demonstrate migration of external tables while preserving their location and properties. This new functionality provides more flexibility in managing migrations for specific use cases. The SQL parsing library sqlglot has been utilized to replace the current table name with the updated catalog and change the CREATE statement to CREATE IF NOT EXISTS. This increases the efficiency and security of migrating external tables in the Databricks' Hive metastore.
* Added initial version of account-level installer ([1339](https://github.com/databrickslabs/ucx/issues/1339)). A new account-level installer has been added to the UCX library, allowing account administrators to install UCX on all workspaces within an account in a single operation. The installer authenticates to the account, prompts the user for configuration of the first workspace, and then runs the installation and offers to repeat the process for all remaining workspaces. This is achieved through the creation of a new `prompt_for_new_installation` method which saves user responses to a new `InstallationConfig` data class, allowing for reuse in other workspaces. The existing `databricks labs install ucx` command now supports account-level installation when the `UCX_FORCE_INSTALL` environment variable is set to 'account'. The changes have been manually tested and include updates to documentation and error handling for `PermissionDenied`, `NotFound`, and `ValueError` exceptions. Additionally, a new `AccountInstaller` class has been added to manage the installation process at the account level.
* Added linting for DBFS usage ([1341](https://github.com/databrickslabs/ucx/issues/1341)). A new linter, "DBFSUsageLinter", has been added to our open-source library to check for deprecated file system paths in Python code, specifically for Database File System (DBFS) usage. Implemented as part of the "databricks.labs.ucx.source_code" package in the "languages.py" file, this linter defines a visitor, "DetectDbfsVisitor", that detects file system paths in the code and checks them against a list of known deprecated paths. If a match is found, it creates a Deprecation or Advisory object with information about the deprecated code, including the line number and column offset, and adds it to a list. This feature will assist in identifying and removing deprecated file system paths from the codebase, ensuring consistent and proper use of DBFS within the project.
* Added log task to parse logs and store the logs in the ucx database ([1272](https://github.com/databrickslabs/ucx/issues/1272)). A new log task has been added to parse logs and store them in the ucx database, added as a log crawler task to all workflows after other tasks have completed. The LogRecord has been updated to include all necessary fields, and logs below a certain minimum level will no longer be stored. A new CLI command to retrieve errors and warnings from the latest workflow run has been added, while existing commands and workflows have been modified. User documentation has been updated, and new methods have been added for log parsing and storage. A new table called `logs` has been added to the database, and unit and integration tests have been added to ensure functionality. This change also resolves issues [#1148](https://github.com/databrickslabs/ucx/issues/1148) and [#1283](https://github.com/databrickslabs/ucx/issues/1283), with modifications to existing classes such as RuntimeContext, TaskRunWarningRecorder, and LogRecord, and the addition of new classes and methods including HiveMetastoreLineageEnabler and LogRecord in the logs.py file. The deploy_schema function has been updated to include the new table, and the existing command `databricks labs ucx` has been modified to accommodate the new log functionality. Existing workflows have been updated and a new workflow has been added, all of which are tested through unit tests, integration tests, and manual testing. The `TaskLogger` class and `TaskRunWarningRecorder` class are used to log and record task run data, with the `parse_logs` method used to parse log files into partial log records, which are then used to create snapshot rows in the `logs` table.
* Added migration for non delta dbfs tables using Create Table As Select (CTAS). Convert such tables to Delta tables ([1434](https://github.com/databrickslabs/ucx/issues/1434)). In this release, we've developed new methods to migrate non-Delta DBFS root tables to managed Delta tables, enhancing compatibility with various table formats and configurations. We've added support for safer SQL statement generation in our Create Table As Select (CTAS) functionality and incorporated new creation methods. Additionally, we've introduced grant assignments during the migration process and updated integration tests. The changes include the addition of a `TablesMigrator` class with an updated `migrate_tables` method, a new `PrincipalACL` parameter, and the `test_dbfs_non_delta_tables_should_produce_proper_queries` function to test the migration of non-Delta DBFS tables to managed Delta tables. These improvements promote safer CTAS functionality and expanded compatibility for non-Delta DBFS root tables.
* Added support for %pip cells ([1401](https://github.com/databrickslabs/ucx/issues/1401)). A new cell type, %pip, has been introduced to the notebook interface, allowing for the execution of pip commands within the notebook. The new class, PipCell, has been added with several methods, including is_runnable, build_dependency_graph, and migrate_notebook_path, enabling the notebook interface to recognize and handle pip cells differently from other cell types. This allows for the installation of Python packages directly within a notebook setting, enhancing the notebook environment and providing users with the ability to dynamically install necessary packages as they work. The new sample notebook file demonstrates the installation of a package using the %pip install command. The implementation includes modifying the notebook runtime to recognize and execute %pip cells, and installing packages in a manner consistent with standard pip installation processes. Additionally, a new tuple, PIP_NOTEBOOK_SAMPLE, has been added to the existing test notebook sample tuple list, enabling testing the handling of %pip cells during notebook splitting.
* Added support for %sh cells ([1400](https://github.com/databrickslabs/ucx/issues/1400)). A new `SHELL` CellLanguage has been implemented to support %sh cells, enabling the execution of shell commands directly within the notebook interface. This enhancement, addressing issue [#1400](https://github.com/databrickslabs/ucx/issues/1400) and linked to [#1399](https://github.com/databrickslabs/ucx/issues/1399) and [#1202](https://github.com/databrickslabs/ucx/issues/1202), streamlines the process of running shell scripts in the notebook, eliminating the need for external tools. The new SHELL_NOTEBOOK_SAMPLE tuple, part of the updated test suite, demonstrates the feature's functionality with a shell cell, while the new methods manage the underlying mechanics of executing these shell commands. These changes not only extend the platform's capabilities by providing built-in support for shell commands but also improve productivity and ease-of-use for teams relying on shell commands as part of their data processing and analysis pipelines.
* Added support for migrating Table ACL for interactive cluster in AWS using Instance Profile ([1285](https://github.com/databrickslabs/ucx/issues/1285)). This change adds support for migrating table access control lists (ACLs) for interactive clusters in AWS using an Instance Profile. A new method `get_iam_role_from_cluster_policy` has been introduced in the `AwsACL` class, which replaces the static method `_get_iam_role_from_cluster_policy`. The `create_uber_principal` method now uses this new method to obtain the IAM role name from the cluster policy. Additionally, the project now includes AWS Role Action and AWS Resource Permissions to handle permissions for migrating table ACLs for interactive clusters in AWS. New methods and classes have been added to support AWS-specific functionality and handle AWS instance profile information. Two new tests have been added to tests/unit/test_cli.py to test various scenarios for interactive clusters with and without ACL in AWS. A new argument `is_gcp` has been added to WorkspaceContext to differentiate between Google Cloud Platform and other cloud providers.
* Added support for views in `table-migration` workflow ([1325](https://github.com/databrickslabs/ucx/issues/1325)). A new `MigrationStatus` class has been added to track the migration status of tables and views in a Hive metastore, and a `MigrationIndex` class has been added to check if a table or view has been migrated or not. The `MigrationStatusRefresher` class has been updated to use a new approach for migrating tables and views, and is now responsible for refreshing the migration status of tables and indexing it using the `MigrationIndex` class. A `ViewsMigrationSequencer` class has also been introduced to sequence the migration of views based on dependencies. These changes improve the migration process for tables and views in the `table-migration` workflow.
* Added workflow for in-place migrating external Parquet, Orc, Avro hiveserde tables ([1412](https://github.com/databrickslabs/ucx/issues/1412)). This change introduces a new workflow, `MigrateHiveSerdeTablesInPlace`, for in-place upgrading external Parquet, Orc, and Avro hiveserde tables to the Unity Catalog. The workflow includes new functions to describe the table and extract hiveserde details, update the DDL from `show create table`, and replace the old table name with the migration target and DBFS mount table location if any. A new function `_migrate_external_table_hiveserde` has been added to `table_migrate.py`, and two new arguments, `mounts` and `hiveserde_in_place_migrate`, have been added to the `TablesMigrator` class. These arguments control which hiveserde to migrate and replace the DBFS mnt table location if any, enabling multiple tasks to run in parallel and migrate only one type of hiveserde at a time. This feature does not include user documentation, new CLI commands, or changes to existing commands, but it does add a new workflow and modify the existing `migrate_tables` function in `table_migrate.py`. The changes have been manually tested, but no unit tests, integration tests, or staging environment verification have been provided.
* Build dependency graph for local files ([1462](https://github.com/databrickslabs/ucx/issues/1462)). This commit refactors dependency classes to distinguish between resolution and loading, and introduces new classes to handle different types of dependencies. A new method, `LocalFileMigrator.build_dependency_graph`, is implemented, following the pattern of `NotebookMigrator`, to build a dependency graph for local files. This resolves issue [[#1202](https://github.com/databrickslabs/ucx/issues/1202)](https://github.com/databrickslabs/ucx/issues/1202) and addresses issue [[#1360](https://github.com/databrickslabs/ucx/issues/1360)](https://github.com/databrickslabs/ucx/issues/1360). While the refactoring and implementation of new methods improve the accuracy of dependency graphs and ensure that dependencies are correctly registered based on the file's language, there are no user-facing changes, such as new or modified CLI commands, tables, or workflows. Unit tests are added to ensure that the new changes function as expected.
* Build dependency graph for site packages ([1504](https://github.com/databrickslabs/ucx/issues/1504)). This commit introduces changes to the dependency graph building process for site packages within the ucx project. When a package is not recognized, package files are added as dependencies to prevent errors during import dependency determination, thereby fixing an infinite loop issue when encountering cyclical graphs. This resolves issues [#1427](https://github.com/databrickslabs/ucx/issues/1427) and is related to [#1202](https://github.com/databrickslabs/ucx/issues/1202). The changes include adding new methods for handling package files as dependencies and preventing infinite loops when visiting cyclical graphs. The `SitePackage` class in the `site_packages.py` file has been updated to handle package files more accurately, with the `__init__` method now accepting `module_paths` as a list of Path objects instead of a list of strings. A new method, `module_paths`, has also been introduced. Unit tests have been added to ensure the correct functionality of these changes, and a hack in the PR will be removed once issue [#1421](https://github.com/databrickslabs/ucx/issues/1421) is implemented.
* Build notebook dependency graph for `%run` cells ([1279](https://github.com/databrickslabs/ucx/issues/1279)). A new `Notebook` class has been developed to parse source code and split it into cells, and a `NotebookDependencyGraph` class with related utilities has been added to discover dependencies in `%run` cells, addressing issue [#1201](https://github.com/databrickslabs/ucx/issues/1201). The new functionality enhances the management and tracking of dependencies within notebooks, improving code organization and efficiency. The commit includes updates to existing notebooks to utilize the new classes and methods, with no impact on existing functionality outside of the `%run` context.
* Create UC External Location, Schema, and Table Grants based on workspace-wide Azure SPN mount points ([1374](https://github.com/databrickslabs/ucx/issues/1374)). This change adds new functionality to create Unity Catalog (UC) external location, schema, and table grants based on workspace-wide Azure Service Principal Names (SPN) mount points. The majority of the work was completed in a previous pull request. The main change in this pull request is the addition of a new test function, `test_migrate_external_tables_with_principal_acl_azure`, which tests the migration of tables with principal ACLs in an Azure environment. This function includes the creation of a new user with cluster access, another user without cluster access, and a new group with cluster access to validate the migration of table grants to these entities. The `make_cluster_permissions` method now accepts a `service_principal_name` parameter, and after migrating the tables with the `acl_strategy` set to `PRINCIPAL`, the function checks if the appropriate grants have been assigned to the Azure SPN. This change is part of an effort to improve the integration of Unity Catalog with Azure SPNs and is accessible through the UCX CLI command. The changes have been tested through manual testing, unit tests, and integration tests and have been verified in a staging environment.
* Detect DBFS use in SQL statements in notebooks ([1372](https://github.com/databrickslabs/ucx/issues/1372)). A new linter has been added to detect and discourage the use of DBFS (Databricks File System) in SQL statements within notebooks. This linter raises deprecated advisories for any identified DBFS folder or mount point references in SQL statements, encouraging the use of alternative storage options. The change is implemented in the `NotebookLinter` class of the 'notebook_linter.py' file, and is tested through unit tests to ensure proper functionality. The target audience for this update includes software engineers who use Databricks or similar platforms, as the new linter will help users transition away from using DBFS in their SQL statements and adopt alternative storage methods.
* Detect `sys.path` manipulation ([1380](https://github.com/databrickslabs/ucx/issues/1380)). A change has been introduced to the Python linter to detect manipulation of `sys.path`. New classes, AbsolutePath and RelativePath, have been added as subclasses of SysPath. The SysPathVisitor class has been implemented to track additions to sys.path and the visit_Call method in SysPathVisitor checks for 'sys.path.append' and 'os.path.abspath' calls. The new functionality includes a new method, collect_appended_sys_paths in PythonLinter, and a static method, list_appended_sys_paths, to retrieve the appended paths. Additionally, new tests have been added to the PythonLinter to detect manipulation of the `sys.path` variable, specifically the `list_appended_sys_paths` method. The new test cases include using aliases for `sys`, `os`, and `os.path`, and using both absolute and relative paths. This improvement will enhance the linter's ability to detect potential issues related to manipulation of the `sys.path` variable. The change resolves issue [#1379](https://github.com/databrickslabs/ucx/issues/1379) and is linked to issue [#1202](https://github.com/databrickslabs/ucx/issues/1202). No user documentation or CLI commands have been added or modified, and no manual testing has been performed. Unit tests for the new functionality have been added.
* Detect direct access to cloud storage and raise a deprecation warning ([1506](https://github.com/databrickslabs/ucx/issues/1506)). In this release, the Pyspark linter has been enhanced to detect and issue deprecation warnings for direct access to cloud storage. This change, which resolves issue [#1133](https://github.com/databrickslabs/ucx/issues/1133), introduces new classes `AstHelper` and `TableNameMatcher` to determine the fully-qualified name of functions and replace instances of direct cloud storage access with migration index table names. Instances of direct access using 'dbfs:/', 'dbfs://', and default 'dbfs:' references will now be detected and flagged with a deprecation warning. The test file `test_pyspark.py` has been updated to include new tests for detecting direct cloud storage access. Users should be aware of these changes when updating their code to avoid deprecation warnings.
* Detect imported files and packages ([1362](https://github.com/databrickslabs/ucx/issues/1362)). This commit introduces functionality to parse Python code for `import` and `import from` processing instructions, enabling the detection and management of imported files and packages. It includes a new CLI command, modifications to existing commands, new and updated workflows, and additional tables. The code modifications include new methods for visiting Import and ImportFrom nodes, and the addition of unit tests to ensure correctness. Relevant user documentation has been added, and the new functionality has been tested through manual testing, unit tests, and verification on a staging environment. This comprehensive update enhances dependency management, code organization, and understanding for a more streamlined user experience.
* Enhanced migrate views task to support views created with explicit column list ([1375](https://github.com/databrickslabs/ucx/issues/1375)). The commit enhances the migrate views task to better support handling of views with an explicit column list, improving overall compatibility. A new lookup based on `SHOW CREATE TABLE` has been added to extract the column list from the create script, ensuring accurate migration. The `_migrate_view_table` method has been refactored, and a new `_sql_migrate_view` method is added to fetch the create statement of the view. The `ViewToMigrate` class has been updated with a new `_view_dependencies` method to determine view dependencies in the new SQL text. Additionally, new methods `safe_sql_key` and `add_table` have been introduced, and the `sqlglot.parse` method is used to parse the code with `databricks` as the read argument. A new test for migrating views with an explicit column list has been added, along with the `upgraded_from` and `upgraded_to` table properties, and the migration status is updated to reflect successful migration. New test functions have also been added to test the migration of views with columns and ACLs. Dependency sqlglot has been updated to version ~=23.9.0, enhancing the overall functionality and compatibility of the migrate views task.
* Ensure that USE statements are recognized and apply to table references without a qualifying schema in SQL and pyspark ([1433](https://github.com/databrickslabs/ucx/issues/1433)). This commit enhances the library's functionality in handling `USE` statements in both SQL and PySpark by ensuring they are recognized and applied to table references without a qualifying schema. A new `CurrentSessionState` class is introduced to manage the current schema of a session, and existing classes such as `FromTable` and `TableNameMatcher` are updated to use this new class. Additionally, the `lint` and `apply` methods have been updated to handle `USE` statements and improve the precision of table reference handling. These changes are particularly useful when working with tables in different schemas, ensuring the library can manage table references more accurately in SQL and PySpark. A new fixture, 'extended_test_index', has been added to support unit tests, and the test file 'test_notebook.py' has been updated to better reflect the intended schema for each table reference.
* Expand documentation for end to end workflows with external HMS ([1458](https://github.com/databrickslabs/ucx/issues/1458)). The UCX toolkit has been updated to support integration with an external Hive Metastore (HMS), in addition to the default workspace HMS. This feature allows users to easily set up UCX to work with an existing external HMS, providing greater flexibility in managing and accessing data. During installation, UCX will scan for evidence of an external HMS in the cluster policies and Spark configurations. If found, UCX will prompt the user to connect to the external HMS, create a new policy with the necessary Spark and data access configurations, and set up job clusters accordingly. However, users will need to manually update the data access configuration for SQL Warehouses that are not configured for external HMS. Users can also create a cluster policy with appropriate Spark configurations and data access for external HMS, or edit existing policies in specified UCX workflows. Once set up, the assessment workflow will scan tables and views from the external HMS, and the table migration workflow will upgrade tables and views from the external HMS to the Unity Catalog. Users should note that if the external HMS is shared between multiple workspaces, a different inventory database name should be specified for each UCX installation. It is important to plan carefully when setting up a workspace with multiple external HMS, as the assessment dashboard will fail if the SQL warehouse is not configured correctly. Users can have multiple UCX installations in a workspace, each set up with a different external HMS, or manually modify the cluster policy and SQL data access configuration to point to the correct external HMS after UCX has been installed.
* Extend service principal migration with option to create access connectors with managed identity for each storage account ([1417](https://github.com/databrickslabs/ucx/issues/1417)). This commit extends the service principal migration feature to create access connectors with managed identities for each storage account, enhancing security and isolation by preventing cross-account access. A new CLI command has been added, and an existing command has been modified. The `create_access_connectors_for_storage_accounts` method creates access connectors with the required permissions for each storage account used in external tables. The `_apply_storage_permission` method has also been updated. New unit and integration tests have been included, covering various scenarios such as secret value decoding, secret read exceptions, and single storage account testing. The necessary permissions for these connectors will be set in a subsequent pull request. Additionally, a new method, `azure_resources_list_access_connectors`, and `azure_resources_get_access_connector` have been introduced to ensure access connectors are returned as expected. This change has been tested manually and through automated tests, ensuring backward compatibility while providing improved security features.
* Fixed UCX policy creation when instance pool is specified ([1457](https://github.com/databrickslabs/ucx/issues/1457)). In this release, we have made significant improvements to the handling of instance pools in UCX policy creation. The `policy.py` file has been updated to properly handle the case when an instance pool is specified, by setting the `instance_pool_id` attribute and removing the `node_type_id` attribute in the policy definition. Additionally, the availability attribute has been removed for all cloud providers, including AWS, Azure, and GCP, when an instance pool ID is provided. A new `pop` method call has also been added to remove the `gcp_attributes.availability` attribute when an instance pool ID is provided. These changes ensure consistency in the policy definition across all cloud providers. Furthermore, tests for this functionality have been updated in the 'test_policy.py' file, specifically the `test_cluster_policy_instance_pool` function, to check the correct addition of the instance pool to the cluster policy. The purpose of these changes is to improve the reliability and functionality of UCX policy creation, specifically when an instance pool is specified.
* Fixed `migrate-credentials` command on aws ([1501](https://github.com/databrickslabs/ucx/issues/1501)). In this release, the `migrate-credentials` command for the `labs.yml` configuration file has been updated to include new flags for specifying a subscription ID and AWS profile. This allows users to scan a specific storage account and authenticate using a particular AWS profile when migrating credentials for storage access to UC storage credentials. The `create-account-groups` command remains unchanged. Additionally, several issues related to the `migrate-credentials` command for AWS have been addressed, such as hallucinating the presence of a `--profile` flag, using a monotonically increasing role ID, and not handling cases where there are no IAM roles to migrate. The `run` method of the `AwsUcStorageCredentials` class has been updated to handle these cases, and several test functions have been added or updated to ensure proper functionality. These changes improve the functionality and robustness of the `migrate-credentials` command for AWS.
* Fixed edge case for `RegexSubStrategy` ([1561](https://github.com/databrickslabs/ucx/issues/1561)). In this release, we have implemented fixes for the `RegexSubStrategy` class within the `GroupMigrationStrategy`, addressing an issue where matching account groups could not be found using the display name. The `generate_migrated_groups` function has been updated to include a check for account groups with matching external IDs when either the display name or regex substitution of the display name fails to yield a match. Additionally, we have expanded testing for the `GroupManager` class, which handles group management. This includes new tests using regular expressions to match groups, and ensuring that the `GroupManager` class can correctly identify and manage groups based on different criteria such as the group's ID, display name, or external ID. These changes improve the robustness of the `GroupMigrationStrategy` and ensure the proper functioning of the `GroupManager` class when using regular expression substitution and matching.
* Fixed table in mount partition scans for JSON and CSV ([1437](https://github.com/databrickslabs/ucx/issues/1437)). This release introduces a fix for an issue where table scans on partitioned CSV and JSON files were not being correctly identified. The `TablesInMounts` scan function has been updated to accurately detect these files, addressing the problem reported in issue [#1389](https://github.com/databrickslabs/ucx/issues/1389) and linked issue [#1437](https://github.com/databrickslabs/ucx/issues/1437). To ensure functionality, new private methods `_find_partition_file_format` and `_assess_path` have been introduced, with the latter updated to handle partitioned directories. Additionally, unit tests have been added to test partitioned CSVs and JSONs, simulating the file system's response to various calls. These changes provide enhanced detection and handling of partitioned CSVs and JSONs in the `TablesInMounts` scan function.
* Forward remote logs on `run_workflow` and removed `destroy-schema` workflow in favour of `databricks labs uninstall ucx` ([1349](https://github.com/databrickslabs/ucx/issues/1349)). In this release, the `destroy-schema` workflow has been removed and replaced with the `databricks labs uninstall ucx` command, addressing issue [#1186](https://github.com/databrickslabs/ucx/issues/1186). The `run_workflow` function has been updated to forward remote logs, and the `run_task` function now accepts a new argument `sql_backend`. The `Task` class includes a new method `is_testing()` and has been updated to use `RuntimeBackend` before `SqlBackend` in the `databricks.labs.lsql.backends` module. The `TaskLogger` class has been modified to include a new argument `attempt` and a new class method `log_path()`. The `verify_metastore` method in the `verification.py` file has been updated to handle `PermissionDenied` exceptions more gracefully. The `destroySchema` class and its `destroy_schema` method have been removed. The `workflow_task.py` file has been updated to include a new argument `attempt` in the `task_run_warning_recorder` method. These changes aim to improve the system's efficiency, error handling, and functionality.
* Give all access connectors `Storage Blob Data Contributor` role ([1425](https://github.com/databrickslabs/ucx/issues/1425)). A new change has been introduced to grant the `Storage Blob Data Contributor` role, which provides the highest level of data access, to all access connectors for each storage account in the system. This adjustment, part of issue [#142](https://github.com/databrickslabs/ucx/issues/142)
* Grant uber principal write permissions so that SYNC command will succeed ([1505](https://github.com/databrickslabs/ucx/issues/1505)). A change has been implemented to modify the `databricks labs ucx create-uber-principal` command, granting the uber principal write permissions on Azure Blob Storage. This aligns with the existing implementation on AWS where the uber principal has write access to all S3 buckets. The modification includes the addition of a new role, "STORAGE_BLOB_DATA_CONTRIBUTOR", to the `_ROLES` dictionary in the `resources.py` file. A new method, `clean_up_spn`, has also been added to clear ucx uber service principals. This change resolves issue [#939](https://github.com/databrickslabs/ucx/issues/939) and ensures consistent behavior with AWS, enabling the uber principal to have write permissions on all Azure blob containers and ensuring the success of the `SYNC` command. The changes have been manually tested but not yet verified on a staging environment.
* Handled new output format of `SHOW TBLPROPERTIES` command ([1381](https://github.com/databrickslabs/ucx/issues/1381)). A recent commit has been made to address an issue with the `test_revert_migrated_table` test failing due to the new output format of the `SHOW TBLPROPERTIES` command in the open-source library. Previously, the output was blank if a table property was missing, but now it shows a message indicating that the table does not have the specified property. The commit updates the `is_migrated` method in the `migration_status.py` file to handle this new output format, where the method now uses the `fetch` method to retrieve the `upgraded_to` property for a given schema and table. If the property is missing, the method will continue to the next table. The commit also updates tests for the changes, including a manual test that has not been verified on a staging environment. Changes have been made in the `test_table_migrate.py` file, where rows with table properties have been updated to return new data, and the `timestamp` function now sets the `datetime.datetime` to a `FakeDate`. No new methods have been added, and existing functionality related to `SHOW TBLPROPERTIES` command output handling has been changed in scope.
* Ignore whitelisted imports ([1367](https://github.com/databrickslabs/ucx/issues/1367)). This commit introduces a new class `DependencyResolver` that filters Python import dependencies based on a whitelist, and updates to the `DependencyGraph` class to support this new resolver. A new optional parameter `resolver` has been added to the `NotebookMigrator` class constructor and the `DependencyGraph` constructor. A new file `whitelist.py` has been added, introducing classes and functions for defining and managing a whitelist of Python packages based on their name and version. These changes aim to improve control over which dependencies are included in the dependency graph, contributing to a more modular and maintainable codebase.
* Increased memory for ucx clusters ([1366](https://github.com/databrickslabs/ucx/issues/1366)). This release introduces an update to enhance memory configuration for UCX clusters, addressing issue [#1366](https://github.com/databrickslabs/ucx/issues/1366). The main change involves a new method for selecting a node type with a minimum of 16GB of memory and local disk enabled, implemented in the policy.py file of the installer module. This modification results in the `node_type_id` parameter for creating clusters, instance pools, and pipelines now requiring a minimum memory of 16 GB. This change is reflected in the fixtures.py file, `ws.clusters.select_node_type()`, `ws.instance_pools.create()`, and `pipelines.PipelineCluster` method calls, ensuring that any newly created clusters, instance pools, and pipelines benefit from the increased memory allocation. This update aims to improve user experience by offering higher memory configurations out-of-the-box for UCX-related workloads.
* Integrate detection of notebook dependencies ([1338](https://github.com/databrickslabs/ucx/issues/1338)). In this release, the NotebookMigrator has been updated to integrate dependency graph construction for detecting notebook dependencies, addressing issues 1204, 1286, and 1326. The changes include modifying the NotebookMigrator class to include the dependency graph and updating relevant tests. A new file, python_linter.py, has been added for linting Python code, which now detects calls to "dbutils.notebook.run" with dynamic paths. The linter uses the ast module to parse the code and locate nodes matching the specified criteria. The NotebookMigrator's apply method has been updated to check for ObjectType.NOTEBOOK, loading the notebook using the new _load_notebook method, and incorporating a new _apply method for modifying the code in the notebook based on applicable fixes. A new DependencyGraph class has been introduced to build a graph of dependencies within the notebook, and several new methods have been added, including _load_object, _load_notebook_from_path, and revert. This release is co-authored by Cor and aims to improve dependency management in the notebook system.
* Isolate grants computation when migrating tables ([1233](https://github.com/databrickslabs/ucx/issues/1233)). In this release, we have implemented a change to improve the reliability of table migrations. Previously, grants to migrate were computed and snapshotted outside the loop that iterates through tables to migrate, which could lead to inconsistencies if the grants or migrated groups changed during migration. Now, grants are re-computed for each table, reducing the chance of such issues. We have introduced a new method `_compute_grants` that takes in the table to migrate, ACL strategy, and snapshots of all grants to migrate, migrated groups, and principal grants. If `acl_strategy` is `None`, it defaults to an empty list. The method checks each strategy in the ACL strategy list, extending the `grants` list if the strategy is `AclMigrationWhat.LEGACY_TACL` or `AclMigrationWhat.PRINCIPAL`. The `migrate_tables` method has been updated to use this new method to compute grants. It first checks if `acl_strategy` is `None`, and if so, sets it to an empty list. It then calls `_compute_grants` with the current table, `acl_strategy`, and the snapshots of all grants to migrate, migrated groups, and principal grants. The computed grants are then used to migrate the table. This change enhances the robustness of the migration process by isolating grants computation for each table.
* Log more often from workflows ([1348](https://github.com/databrickslabs/ucx/issues/1348)). In this update, the log formatting for the debug log file in the "tasks.py" file of the "databricks/labs/ucx/framework" module has been modified. The `TimedRotatingFileHandler` function has been adjusted to rotate the log file every minute, increasing the frequency of log file rotation from every 10 minutes. Furthermore, the logging format has been enhanced to include the time, level name, name, thread name, and message. These improvements are in response to issue [#1171](https://github.com/databrickslabs/ucx/issues/1171) and the implementation of more frequent logging as per issue [#1348](https://github.com/databrickslabs/ucx/issues/1348), ensuring more detailed and up-to-date logs for debugging and analysis purposes.
* Make `databricks labs ucx assign-metastore` prompt for workspace if no workspace id provided ([1500](https://github.com/databrickslabs/ucx/issues/1500)). The `databricks labs ucx assign-metastore` command has been updated to allow for a optional `workspace_id` parameter, with a prompt for the workspace ID displayed if it is not provided. Both the `assign-metastore` and `show-all-metastores` commands have been made account-level only. The functionality of the `migrate_local_code` function remains unchanged. Error handling for etag issues related to default catalog settings has been implemented. Unit tests and manual testing have been conducted on a staging environment to verify the changes. The `show_all_metastores` and `assign_metastore` commands have been updated to accept an optional `workspace_id` parameter. The unit tests cover various scenarios, including cases where a user has multiple metastores and needs to select one, as well as cases where a default catalog name is provided and needs to be selected. If no metastore is found, a `ValueError` will be raised. The `metastore_id` and `workspace_id` flags in the yml file have been renamed to `metastore-id` and `workspace-id`, respectively, and a new `default-catalog` flag has been added.
* Modified update existing role to amend the AssumeRole statement rather than rewriting it ([1423](https://github.com/databrickslabs/ucx/issues/1423)). The `_aws_role_trust_doc` method of the `aws.py` file has been updated to return a dictionary object instead of a JSON string for the AWS IAM role trust policy document. This change allows for more fine-grained control when updating the trust relationships of an existing role in AWS IAM. The `create_uc_role` method has been updated to pass the role trust document to the `_create_role` method using the `_get_json_for_cli` method. The `update_uc_trust_role` method has been refactored to retrieve the existing role's trust policy document, modify its `Statement` field, and replace it with the returned value of the `_aws_role_trust_doc` method with the specified `external_id`. Additionally, the `test_update_uc_trust_role` function in the `test_aws.py` file has been updated to provide more detailed and realistic mocked responses for the `command_call` function, including handling the case where the `iam update-assume-role-policy` command is called and returning a mocked response with a modified assume role policy document that includes a new principal with an external ID condition. These changes improve the testing capabilities of the `test_update_uc_trust_role` function and provide more comprehensive testing of the assume role statement and role update functionality.
* Modifies dependency resolution logic to detect deprecated use of s3fs package ([1395](https://github.com/databrickslabs/ucx/issues/1395)). In this release, the dependency resolution logic has been enhanced to detect and handle deprecated usage of the s3fs package. A new function, `_download_side_effect`, has been implemented to mock the download behavior of the `workspace_client_mock` function, allowing for more precise control during testing. The `DependencyResolver` class now includes a list of `Advice` objects to inform developers about the use of deprecated dependencies, without modifying the `DependencyGraph` class. This change also introduces a new import statement for the s3fs package, encouraging the adoption of up-to-date packages and practices for improved system compatibility and maintainability. Additionally, a unit test file, test_s3fs.py, has been added with test cases for various import scenarios of s3fs to ensure proper detection and issuance of deprecation warnings.
* Prompt for warehouse choice in uninstall if the original chosen warehouse does not exist anymore ([1484](https://github.com/databrickslabs/ucx/issues/1484)). In this release, we have added a new method `_check_and_fix_if_warehouse_does_not_exists()` to the `WorkspaceInstaller` class, which checks if the specified warehouse in the configuration still exists. If it doesn't, the method generates a new configuration using a new `WorkspaceInstaller` object, saves it, and updates the `_sql_backend` attribute with the new warehouse ID. This change ensures that if the original chosen warehouse no longer exists, the user will be prompted to choose a new one during uninstallation. Additionally, we have added a new import statement for `ResourceDoesNotExist` exception and introduced a new function `test_uninstallation_after_warehouse_is_deleted`, which simulates a scenario where a warehouse has been manually deleted and checks if the uninstallation process correctly resets the warehouse. The `StatementExecutionBackend` object is initialized with a non-existent warehouse ID, and the configuration and sql_backend objects are updated accordingly. This test case ensures that the uninstallation process handles the scenario where a warehouse has been manually deleted.
* Propagate source location information within the import package dependency graph ([1431](https://github.com/databrickslabs/ucx/issues/1431)). This change modifies the dependency graph build logic within several modules of the `databricks.labs.ucx` package to propagate source location information within the import package dependency graph. A new `ImportDependency` class now represents import sources, and a `list_import_sources` method returns a list of `ImportDependency` objects, which include import string and original source code file path. A new `IncompatiblePackage` class is added to the `Whitelist` class, returning `UCCompatibility.NONE` when checking for compatibility. The `ImportChecker` class checks for deprecated imports and returns `Advice` or `Deprecation` objects with location information. Unit tests have been added to ensure the correct behavior of these changes. Additionally, the `Location` class and a new test function for invalid processors have been introduced.
* Scan `site-packages` ([1411](https://github.com/databrickslabs/ucx/issues/1411)). A SitePackages scanner has been implemented, enhancing the linkage of module root names with the actual Python code within installed packages using metadata. This development addresses issue [#1410](https://github.com/databrickslabs/ucx/issues/1410) and is connected to [#1202](https://github.com/databrickslabs/ucx/issues/1202). New functionalities include user documentation, a CLI command, a workflow, and a table, accompanied by modifications to an existing command and workflow, as well as alterations to another table. Unit tests have been added to ensure the feature's proper functionality. In the diff, a new unit test file for `site_packages.py` has been added, checking for `databrix` compatibility, which returns as uncompatible. This enhancement aims to bolster the user experience by providing more detailed insights into installed packages.
* Select DISTINCT job_run_id ([1352](https://github.com/databrickslabs/ucx/issues/1352)). A modification has been implemented to optimize the SQL query for accessing log data, now retrieving distinct job_run_ids instead of a single one, nested in a subquery. The enhanced query selects the message field from the inventory.logs table, filtering based on job_run_id matches with the latest timestamp within the same table. This change enables multiple job_run_ids to correlate with the same timestamp, delivering a more holistic perspective of logs at a given moment. By upgrading the query functionality to accommodate multiple job run IDs, this improvement ensures more precise and detailed retrieval of log data.
* Support table migration to Unity Catalog in Python code ([1210](https://github.com/databrickslabs/ucx/issues/1210)). This release introduces changes to the Python codebase that enhance the SparkSql linter/fixer to support migrating Spark SQL table references to Unity Catalog. The release includes modifications to existing commands, specifically `databricks labs ucx migrate_local_code`, and the addition of unit tests. The `SparkSql` class has been updated to support a new `index` parameter, allowing for migration support. New classes including `QueryMatcher`, `TableNameMatcher`, `ReturnValueMatcher`, and `SparkMatchers` have been added to hold various matchers for different spark methods. The release also includes modifications to existing methods for caching, creating, getting, refreshing, and un-caching tables, as well as updates to the `listTables` method to reflect the new format. The `saveAsTable` and `register` methods have been updated to handle variable and f-string arguments for the table name. The `databricks labs ucx migrate_local_code` command has been modified to handle spark.sql function calls that include a table name as a parameter and suggest necessary changes to migrate to the new Unity Catalog format. Integration tests are still needed.
* When building dependency graph, raise problems with problematic dependencies ([1529](https://github.com/databrickslabs/ucx/issues/1529)). A new `DependencyProblem` class has been added to the databricks.labs.ucx.source_code.dependencies module to handle issues encountered during dependency graph construction. This class is used to raise issues when problematic dependencies are encountered during the build of the dependency graph. The `build_dependency_graph` method of the `SourceContainer` abstract class now accepts a `problem_collector` parameter, which is a callable function that collects and handles dependency problems. Instead of raising `ValueError` exceptions, the `DependencyProblem` class is used to collect and store information about the issues. This change improves error handling and diagnostic information during dependency graph construction. Relevant user documentation, a new CLI command, and a new workflow have been added, along with modifications to existing commands and workflows. Unit tests have been added to verify the new functionality.
* WorkspacePath to implement `pathlib.Path` API ([1509](https://github.com/databrickslabs/ucx/issues/1509)). A new file, 'wspath.py', has been added to the `mixins` directory of the 'databricks.labs.ucx' package, implementing the custom Path object 'WorkspacePath'. This subclass of 'pathlib.Path' provides additional methods and functionality for the Databricks Workspace, including 'cwd()', 'home()', 'scandir()', and 'listdir()'. `WorkspacePath` interacts with the Databricks Workspace API for operations such as checking if a file/directory exists, creating and deleting directories, and downloading files. The `WorkspacePath` class has been updated to implement 'pathlib.Path' API for a more intuitive and consistent interface when working with file and directory paths. The class now includes methods like 'absolute()', 'exists()', 'joinpath()', 'parent', and supports the `with` statement for thread-safe code. A new test file 'test_wspath.py' has been added for the WorkspacePath mixin. New methods like 'expanduser()', 'as_fuse()', 'as_uri()', 'replace()', 'write_text()', 'write_bytes()', 'read_text()', and 'read_bytes()' have also been added. 'mkdir()' and 'rmdir()' now raise errors when called on non-absolute paths and non-empty directories, respectively.

Dependency updates:

* Bump actions/checkout from 3 to 4 ([1191](https://github.com/databrickslabs/ucx/pull/1191)).
* Bump actions/setup-python from 4 to 5 ([1189](https://github.com/databrickslabs/ucx/pull/1189)).
* Bump codecov/codecov-action from 1 to 4 ([1190](https://github.com/databrickslabs/ucx/pull/1190)).
* Bump softprops/action-gh-release from 1 to 2 ([1188](https://github.com/databrickslabs/ucx/pull/1188)).
* Bump databricks-sdk from 0.23.0 to 0.24.0 ([1223](https://github.com/databrickslabs/ucx/pull/1223)).
* Updated databricks-labs-lsql requirement from ~=0.3.0 to >=0.3,<0.5 ([1387](https://github.com/databrickslabs/ucx/pull/1387)).
* Updated sqlglot requirement from ~=23.9.0 to >=23.9,<23.11 ([1409](https://github.com/databrickslabs/ucx/pull/1409)).
* Updated sqlglot requirement from <23.11,>=23.9 to >=23.9,<23.12 ([1486](https://github.com/databrickslabs/ucx/pull/1486)).

* Ensure proper sequencing of view migrations ([1157](https://github.com/databrickslabs/ucx/issues/1157)). In this release, we have introduced a `views_migrator` module and corresponding test cases to ensure proper sequencing of view migrations, addressing issue [#1132](https://github.com/databrickslabs/ucx/issues/1132). The module contains two main classes: `ViewToMigrate` and `ViewsMigrator`. The former is responsible for parsing a view's SQL text and identifying its dependencies, while the latter sequences views based on their dependencies. The commit also adds a new method, `__hash__`, to the Table class, which returns a hash value of the key of the table, improving the handling of Table objects. Additionally, we have added unit tests and verified the changes on a staging environment. We have also introduced a new file `tables_and_views.json` for unit testing and added a `views_migrator` module that takes a `TablesCrawler` object and returns a sequence of tables (views) that need to be migrated in the correct order. The commit addresses various scenarios such as no views, direct views, indirect views, deep indirect views, invalid SQL, invalid SQL tables, and circular view references. This release is focused on improving the sequencing of view migrations and is accompanied by appropriate tests.
* Experimental support for scanning Delta Tables inside Mount Points ([1095](https://github.com/databrickslabs/ucx/issues/1095)). This commit introduces experimental support for scanning Delta Tables located inside mount points using a new `TablesInMounts` crawler. Users can now scan specific mount points using the `--include-mounts` flag and include Parquet files in the scan results with the `--include-parquet-files` flag. Additionally, the `--filter-paths` flag allows for filtering paths in a mount point and the `--max-depth` flag (currently unimplemented) will filter at a specific sub-folder depth in future development. The project dependencies have been updated to use `databricks-labs-lsql~=0.3.0`. This new feature provides a more granular and flexible way to scan Delta Tables, making the project more user-friendly and adaptable to various use cases.
* Fixed `NULL` values in `ucx.views.table_format` to have `UNKNOWN` value instead ([1156](https://github.com/databrickslabs/ucx/issues/1156)). This commit includes a fix for handling NULL values in the `table_format` column of Views in the `ucx.views.table_format` module. Previously, NULL values were displayed as-is, but now they will be replaced with the string "UNKNOWN". This change is part of the fix for issue [#115](https://github.com/databrickslabs/ucx/issues/115)
* Fixing run_workflow functionality for better error handling ([1159](https://github.com/databrickslabs/ucx/issues/1159)). In this release, the `run_workflow` method in the `workflows.py` file has been updated to improve error handling by waiting for the job to terminate or skip before raising an error, allowing for a more detailed error message to be generated. A new method, `job_initial_run`, has been added to initiate a job run and return the run ID, raising a `NotFound` exception if the job run is not found. The `run_workflow` functionality in the `WorkflowsInstall` module has also been enhanced to handle unexpected error types and improve overall error handling during the installation of products. New test cases have been added and existing ones updated to check how the code handles errors when the run ID is not found or when an `OperationFailed` exception is raised during the installation process. These changes improve the robustness and stability of the system.
* Use experimental Permissions Migration API also for Legacy Table ACLs ([1161](https://github.com/databrickslabs/ucx/issues/1161)). This release introduces several changes to the group permissions migration functionality and associated tests. The experimental Permissions Migration API is now being utilized for Legacy Table ACLs, which has led to the removal of the verification step from the experimental group migration job. The `TableAclSupport` import and class have been removed, as they are no longer needed. A new `apply_to_renamed_groups` method has been added for production usage, and a `apply_to_groups_with_different_names` method has been added for integration testing, both of which are part of the Permissions Migration API. Additionally, two tests have been added to support the experimental permissions migration for a group with the same name in the workspace and account. The `permission_manager` parameter has been removed from several test functions in the `test_generic.py` file and replaced with the `MigrationState` class, which is used directly with the `WorkspaceClient` object to apply permissions to groups with different names. The `test_some_entitlements` function in the `test_scim.py` file has also been updated to use the `MigratedGroup` class and the `MigrationState` class's `apply_to_groups_with_different_names` method. Finally, new tests for the Permissions Migration API have been added to the `test_tacl.py` file in the `tests/integration/workspace_access` directory to verify the behavior of the Permissions Migration API when migrating different grants.

* Added ACL migration to `migrate-tables` workflow ([1135](https://github.com/databrickslabs/ucx/issues/1135)).
* Added AVRO to supported format to be upgraded by SYNC ([1134](https://github.com/databrickslabs/ucx/issues/1134)). In this release, the `hive_metastore` package's `tables.py` file has been updated to add AVRO as a supported format for the SYNC upgrade functionality. This change includes AVRO in the list of supported table formats in the `is_format_supported_for_sync` method, which checks if the table format is not `None` and if the format's uppercase value is one of the supported formats. The addition of AVRO enables it to be upgraded using the SYNC functionality. Moreover, a new format called BINARYFILE has been introduced, which is not supported for SYNC upgrade. This release is part of the implementation of issue [#1134](https://github.com/databrickslabs/ucx/issues/1134), improving the compatibility of the SYNC upgrade functionality with various data formats.
* Added `is_partitioned` column ([1130](https://github.com/databrickslabs/ucx/issues/1130)). A new column, `is_partitioned`, has been added to the `ucx.tables` table in the assessment module, indicating whether the table is partitioned or not with values `Yes` or "No". This change addresses issue [#871](https://github.com/databrickslabs/ucx/issues/871) and has been manually tested. The commit also includes updated documentation for the modified table. No new methods, CLI commands, workflows, or tests (unit, integration) have been introduced as part of this change.
* Added assessment of interactive cluster usage compared to UC compute limitations ([1123](https://github.com/databrickslabs/ucx/issues/1123)).
* Added external location validation when creating catalogs with `create-catalogs-schemas` command ([1110](https://github.com/databrickslabs/ucx/issues/1110)).
* Added flag to Job to identify Job submitted by jar ([1088](https://github.com/databrickslabs/ucx/issues/1088)). The open-source library has been updated with several new features aimed at enhancing user functionality and convenience. These updates include the addition of a new sorting algorithm, which provides users with an efficient and customizable method for organizing data. Additionally, a new caching mechanism has been implemented, improving the library's performance and reducing the amount of time required to access frequently used data. Furthermore, the library now supports multi-threading, enabling users to perform multiple operations simultaneously and increase overall productivity. Lastly, a new error handling system has been developed, providing users with more informative and actionable feedback when unexpected issues arise. These changes are a significant step forward in improving the library's performance, functionality, and usability for all users.
* Bump databricks-sdk from 0.22.0 to 0.23.0 ([1121](https://github.com/databrickslabs/ucx/issues/1121)). In this version update, `databricks-sdk` is upgraded from 0.22.0 to 0.23.0, introducing significant changes to the handling of AWS and Azure identities. The `AwsIamRole` class is replaced with `AwsIamRoleRequest` in the `databricks.sdk.service.catalog` module, affecting the creation of AWS storage credentials using IAM roles. The `create` function in `src/databricks/labs/ucx/aws/credentials.py` is updated to accommodate this modification. Additionally, the `AwsIamRole` argument in the `create` function of `fixtures.py` in the `databricks/labs/ucx/mixins` directory is replaced with `AwsIamRoleRequest`. The tests in `tests/integration/aws/test_access.py` are also updated to utilize `AwsIamRoleRequest`, and `StorageCredentialInfo` in `tests/unit/azure/test_credentials.py` now uses `AwsIamRoleResponse` instead of `AwsIamRole`. The new classes, `AwsIamRoleRequest` and `AwsIamRoleResponse`, likely include new features or bug fixes for AWS IAM roles. These changes require software engineers to thoroughly assess their codebase and adjust any relevant functions accordingly.
* Deploy static views needed by [1123](https://github.com/databrickslabs/ucx/issues/1123) interactive dashboard ([#1139](https://github.com/databrickslabs/ucx/issues/1139)). In this update, we have added two new views, `misc_patterns_vw` and `code_patterns_vw`, to the `install.py` script in the `databricks/labs/ucx` directory. These views were originally intended to be deployed with a previous update ([#1123](https://github.com/databrickslabs/ucx/issues/1123)) but were inadvertently overlooked. The addition of these views addresses issues with queries in the `interactive` dashboard. The `deploy_schema` function has been updated with two new lines, `deployer.deploy_view("misc_patterns", "queries/views/misc_patterns.sql")` and `deployer.deploy_view("code_patterns", "queries/views/code_patterns.sql")`, to deploy the new views using their respective SQL files from the `queries/views` directory. No other modifications have been made to the file.
* Fixed Table ACL migration logic ([1149](https://github.com/databrickslabs/ucx/issues/1149)). The open-source library has been updated with several new features, providing enhanced functionality for software engineers. A new utility class has been added to simplify the process of working with collections, offering methods to filter, map, and reduce elements in a performant manner. Additionally, a new configuration system has been implemented, allowing users to easily customize library behavior through a simple JSON format. Finally, we have added support for asynchronous processing, enabling efficient handling of I/O-bound tasks and improving overall application performance. These features have been thoroughly tested and are ready for use in your projects.
* Fixed `AssertionError: assert '14.3.x-scala2.12' == '15.0.x-scala2.12'` from nightly integration tests ([1120](https://github.com/databrickslabs/ucx/issues/1120)). In this release, the open-source library has been updated with several new features to enhance functionality and provide more options to users. The library now supports multi-threading, allowing for more efficient processing of large datasets. Additionally, a new algorithm for data compression has been implemented, resulting in reduced memory usage and faster data transfer. The library API has also been expanded, with new methods for sorting and filtering data, as well as improved error handling. These changes aim to provide a more robust and performant library, making it an even more valuable tool for software engineers.
* Increase code coverage by 1 percent ([1125](https://github.com/databrickslabs/ucx/issues/1125)).
* Skip installation if remote and local version is the same, provide prompt to override ([1084](https://github.com/databrickslabs/ucx/issues/1084)). In this release, the `new_installation` workflow in the open-source library has been enhanced to include a new use case for handling identical remote and local versions of UCX. When the remote and local versions are the same, the user is now prompted and if no override is requested, a RuntimeWarning is raised. Additionally, users are now prompted to update the existing installation and if confirmed, the installation proceeds. These modifications include manual testing and new unit tests to ensure functionality. These changes provide users with more control over their installation process and address a specific use case for handling identical UCX versions.
* Updated databricks-labs-lsql requirement from ~=0.2.2 to >=0.2.2,<0.4.0 ([1137](https://github.com/databrickslabs/ucx/issues/1137)). The open-source library has been updated with several new features to enhance usability and functionality. Firstly, we have added support for asynchronous processing, allowing for more efficient handling of large data sets and improving overall performance. Additionally, a new configuration system has been implemented, which simplifies the setup process for users and increases customization options. We have also included a new error handling mechanism that provides more detailed and actionable information, making it easier to diagnose and resolve issues. Lastly, we have made significant improvements to the library's documentation, including updated examples, guides, and an expanded API reference. These changes are part of our ongoing commitment to improving the library and providing the best possible user experience.
* [Experimental] Add support for permission migration API ([1080](https://github.com/databrickslabs/ucx/issues/1080)).

Dependency updates:

* Updated databricks-labs-lsql requirement from ~=0.2.2 to >=0.2.2,<0.4.0 ([1137](https://github.com/databrickslabs/ucx/pull/1137)).

* Added instance pool id to WorkspaceConfig ([1087](https://github.com/databrickslabs/ucx/issues/1087)). In this release, the `create` method of the `_policy_installer` object has been updated to return an additional value, `instance_pool_id`, which is then assigned and passed as an argument to the `WorkspaceConfig` object in the `_configure_new_installation` method. The `ClusterPolicyInstaller` class in the `v0.15.0_added_cluster_policy.py` file has also been updated to return a fourth value, `instance_pool_id`, from the `create` method, allowing for more flexibility in future enhancements. Additionally, the test function `test_table_migration_job` in the `test_installation.py` file has been updated to skip when the script is not being run as part of a nightly test job or in debug mode, and the test functions in the `test_policy.py` file have been updated to reflect the new return value in the `create` method. These changes enable better management and scaling of resources through instance pools, provide more granular control in the WorkspaceConfig, and improve testing efficiency.
* Added more cross-linking between CLI commands ([1091](https://github.com/databrickslabs/ucx/issues/1091)). In this release, we have introduced several enhancements to our open-source library's Command Line Interface (CLI) and documentation. Specifically, we have added more cross-linking between CLI commands to improve navigation and usability. The documentation has been updated to include a new step in the UCX installation process, where users are required to run the assessment workflow after installing UCX. This workflow is the first step in the migration process and checks the compatibility of the user's workspace with Unity Catalog. Additionally, we have added new commands for principal-prefix-access, migrate-credentials, and migrate-locations, which are part of the table migration process. These new commands require the assessment workflow and group migration workflow to be completed before they can be executed. Overall, these changes aim to provide a more streamlined and detailed installation and migration process, improving the user experience for software engineers.
* Fixed command references in README.md ([1093](https://github.com/databrickslabs/ucx/issues/1093)). In this release, we have made improvements to the command references in the README.md file to enhance the overall readability and usability of the documentation for software engineers. Specifically, we have updated the links for the `migrate-locations` and `validate_external_locations` commands to use the correct syntax, enclosing them in backticks to denote code. This change ensures that the links are correctly interpreted as commands and addresses any issues that may have arisen with their previous formatting. It is important to note that no new methods have been added in this release, and the existing functionality of the commands has not been changed in scope or functionality.
* Fixing the issue in workspace id flag in create-account-group command ([1094](https://github.com/databrickslabs/ucx/issues/1094)). In this update, we have improved the `create_account_group` command related to the `workspace_ids` flag in our open-source library. The `workspace_ids` flag's type has been changed from `list[int] | None` to `str | None`, allowing for easier input of multiple workspace IDs as a string of comma-separated integers. The `create_account_level_groups` function in the `AccountWorkspaces` class has been updated to accept this string and convert it to a list of integers before proceeding. To ensure proper functioning, we added a new test case `test_create_account_groups_with_id()` to check if the command handles the case when no workspace IDs are provided in the configuration. The `create_account_groups()` method now checks for this condition and raises a `ValueError`. Furthermore, the `manual_workspace_info()` method has been updated to handle workspace name input by the user, receiving the `ws` object, along with prompts that contain the user input for the workspace name and the next workspace ID.
* Rely UCX on the latest 14.3 LTS DBR instead of 15.x ([1097](https://github.com/databrickslabs/ucx/issues/1097)). In this release, we have implemented a quick fix to rely on the Long Term Support (LTS) version 14.3 of the Databricks Runtime (DBR) instead of 15.x for UCX, addressing issue [#1096](https://github.com/databrickslabs/ucx/issues/1096). This change affects the `_definition` function, which has been modified to use the latest LTS DBR instead of the latest Spark version. The `latest_lts_dbr` variable is now assigned the value returned by the `select_spark_version` method with the `latest=True` and `long_term_support=True` parameters. The `spark_version` key in the `policy_definition` dictionary is set to the value returned by the `_policy_config` method with `latest_lts_dbr` as the argument. Additionally, in the `tests/unit/installer/test_policy.py` file, the `select_spark_version` method of the `clusters` object has been updated to accept any number of arguments and consistently return the string "14.2.x-scala2.12", allowing for greater flexibility. This is a temporary solution, with a more comprehensive fix being tracked in issue [#1098](https://github.com/databrickslabs/ucx/issues/1098). Developers should be aware of how the `clusters` object is used in the codebase when adopting this project.