configuration.md

Azure Databricks — Configuration

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Configuration

Topic	URL
Configure Azure Databricks account-level settings	https://learn.microsoft.com/en-us/azure/databricks/admin/account-settings/
Interpret Azure Databricks diagnostic audit logs	https://learn.microsoft.com/en-us/azure/databricks/admin/account-settings/audit-logs
Configure and monitor Azure Databricks account budgets	https://learn.microsoft.com/en-us/azure/databricks/admin/account-settings/budgets
Enable and configure custom URL for Databricks account	https://learn.microsoft.com/en-us/azure/databricks/admin/account-settings/custom-url
Configure disabling legacy features in new Databricks workspaces	https://learn.microsoft.com/en-us/azure/databricks/admin/account-settings/legacy-features
Enable and configure verbose audit logs in Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/account-settings/verbose-logs
Configure and enforce Personal Compute policy in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/clusters/personal-compute
Define Azure Databricks compute policy attributes	https://learn.microsoft.com/en-us/azure/databricks/admin/clusters/policy-definition
Enable and manage the Azure Databricks web terminal	https://learn.microsoft.com/en-us/azure/databricks/admin/clusters/web-terminal
Configure SQL warehouse admin settings and access controls	https://learn.microsoft.com/en-us/azure/databricks/admin/sql/
Set up and manage serverless SQL warehouses	https://learn.microsoft.com/en-us/azure/databricks/admin/sql/serverless
Use Azure Databricks system tables for monitoring	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/
Monitor Genie Code usage with assistant events system table	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/assistant
Use the Databricks audit log system table schema	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/audit-logs
Query billable usage system table in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/billing
Track clean room activity with events system table	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/clean-rooms
Reference Databricks compute system tables for monitoring	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/compute
Use data classification system table for sensitive data detection	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/data-classification
Use data quality monitoring results system table in Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/data-quality-monitoring
Use Databricks jobs system tables for monitoring	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/jobs
Use Databricks system tables to monitor job costs	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/jobs-cost
Use Databricks lineage system tables for data tracking	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/lineage
Analyze Databricks Marketplace data with system tables	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/marketplace
Use Delta Sharing materialization history system table	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/materialization
Query MLflow experiment metadata via Databricks system tables	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/mlflow
Analyze Databricks model serving costs with system tables	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/model-serving-cost
Analyze network access denials with Databricks system tables	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/network
Use predictive optimization system table in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/predictive-optimization
Use Databricks pricing system table for SKU price history	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/pricing
Query Azure Databricks query history system table	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/query-history
Analyze Databricks serverless compute costs via system tables	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/serverless-billing
Use warehouse events system table for SQL warehouse monitoring	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/warehouse-events
Analyze SQL warehouses via Databricks warehouses system table	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/warehouses
Monitor Azure Databricks workspaces with system table reference	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/workspaces
Monitor Zerobus Ingest activity using Databricks system tables	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/zerobus-ingest
Configure Databricks serverless usage policies for tagging	https://learn.microsoft.com/en-us/azure/databricks/admin/usage/budget-policies
Use Databricks billable usage system table for costs	https://learn.microsoft.com/en-us/azure/databricks/admin/usage/system-tables
Configure automatic identity sync from Entra ID to Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/users-groups/automatic-identity-management
Configure SCIM-based user and group provisioning to Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/users-groups/scim/
Manage legacy workspace-local groups in Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/users-groups/workspace-local-groups
Configure workspace appearance settings in Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace-settings/appearance
Configure serverless workspace base environments in Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace-settings/base-environment
Manage DBFS visual file browser access in Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace-settings/dbfs-browser
Set default access mode for Databricks jobs compute	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace-settings/default-access-mode
Configure default Python package repositories in Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace-settings/default-python-packages
Auto-enable deletion vectors for new Delta tables	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace-settings/deletion-vectors
Disable the upload data UI in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace-settings/disable-upload-data-ui
Configure email notification settings for Databricks workspaces	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace-settings/email
Manage Azure Databricks preview feature settings	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace-settings/manage-previews
Configure storage location for Databricks notebook results	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace-settings/notebook-results
Manage user access to Databricks notebook features	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace-settings/notebooks
Configure Azure Databricks notification destinations via webhooks	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace-settings/notification-destinations
Purge Azure Databricks workspace storage securely	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace-settings/storage
Change Azure Databricks workspace storage redundancy settings	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace/workspace-storage-redundancy
Configure Slack notifications for AI/BI dashboard subscriptions	https://learn.microsoft.com/en-us/azure/databricks/ai-bi/admin/slack-subscriptions
Configure Microsoft Teams notifications for AI/BI dashboards	https://learn.microsoft.com/en-us/azure/databricks/ai-bi/admin/teams-subscriptions
Configure workspace themes for AI/BI dashboards	https://learn.microsoft.com/en-us/azure/databricks/ai-bi/admin/themes
Configure AI Gateway endpoints in the beta experience	https://learn.microsoft.com/en-us/azure/databricks/ai-gateway/configure-endpoints-beta
Understand Databricks cluster UI changes and access modes	https://learn.microsoft.com/en-us/azure/databricks/archive/compute/cluster-ui-preview
Configure legacy Azure Databricks cluster settings	https://learn.microsoft.com/en-us/azure/databricks/archive/compute/configure
Install and configure legacy Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/cli/
Use legacy Databricks Cluster Policies CLI commands	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/cli/cluster-policies-cli
Use legacy Databricks DBFS CLI commands	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/cli/dbfs-cli
Use legacy Lakeflow Spark Declarative Pipelines CLI	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/cli/dlt-cli
Manage Databricks groups with legacy CLI	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/cli/groups-cli
Manage Databricks instance pools with legacy CLI	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/cli/instance-pools-cli
Manage Databricks libraries with legacy CLI	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/cli/libraries-cli
Manage Unity Catalog with legacy Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/cli/unity-catalog-cli
Use legacy dbutils.library utilities in Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/dbutils-library
Select workspace directories for the Databricks VS Code extension	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/workspace-dir
Configure external Apache Hive metastores for Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/external-metastores/external-hive-metastore
Configure legacy cluster-named init scripts in Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/init-scripts/legacy-cluster-named
Configure legacy global init scripts in Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/init-scripts/legacy-global
Configure legacy Spark Submit tasks in Databricks jobs	https://learn.microsoft.com/en-us/azure/databricks/archive/jobs/spark-submit
Manage notebook-scoped libraries with legacy %conda in Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/legacy/conda
Create and manage DBFS tables using the legacy Data tab	https://learn.microsoft.com/en-us/azure/databricks/archive/legacy/data-tab
Browse and search DBFS files using the Databricks file browser	https://learn.microsoft.com/en-us/azure/databricks/archive/legacy/file-browser
Use DBFS FileStore for browser-accessible files in Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/legacy/filestore
Configure legacy UniForm IcebergCompatV1 for Delta tables	https://learn.microsoft.com/en-us/azure/databricks/archive/legacy/uniform
Use and manage legacy workspace libraries in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/legacy/workspace-libraries
Configure ai_generate_text() with Azure OpenAI in SQL	https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/ai-onboard
Share Databricks feature store tables across workspaces	https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/feature-store/multiple-workspaces
Enable optimized LLM serving on Mosaic AI Model Serving	https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/llm-optimized-model-serving
Use bamboolib for no-code data wrangling in notebooks	https://learn.microsoft.com/en-us/azure/databricks/archive/notebooks/bamboolib
Use and migrate from DATASKIPPING INDEX on Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/spark-3.x-migration/dataskipping-index
Handle dates and timestamps in Databricks Runtime 7+	https://learn.microsoft.com/en-us/azure/databricks/archive/spark-3.x-migration/dates-timestamps
Configure legacy Delta Lake storage credentials	https://learn.microsoft.com/en-us/azure/databricks/archive/storage/delta-storage-credentials
Configure agent (semantic) metadata for Databricks metric views	https://learn.microsoft.com/en-us/azure/databricks/business-semantics/agent-metadata
Create and edit Unity Catalog metric views	https://learn.microsoft.com/en-us/azure/databricks/business-semantics/metric-views/create-edit
Reference YAML configuration for Databricks metric views	https://learn.microsoft.com/en-us/azure/databricks/business-semantics/metric-views/yaml-reference
Use Catalog Explorer Entity Relationship Diagram in Databricks	https://learn.microsoft.com/en-us/azure/databricks/catalog-explorer/entity-relationship-diagram
Create Unity Catalog catalogs in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/catalogs/create-catalog
Manage Unity Catalog catalogs in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/catalogs/manage-catalog
Run notebooks securely in clean rooms	https://learn.microsoft.com/en-us/azure/databricks/clean-rooms/clean-room-notebook
Create Azure Databricks clean rooms for secure collaboration	https://learn.microsoft.com/en-us/azure/databricks/clean-rooms/create-clean-room
Manage and monitor Azure Databricks clean rooms	https://learn.microsoft.com/en-us/azure/databricks/clean-rooms/manage-clean-room
Create and use Clean Rooms output tables	https://learn.microsoft.com/en-us/azure/databricks/clean-rooms/output-tables
Add and manage comments on Unity Catalog assets	https://learn.microsoft.com/en-us/azure/databricks/comments/
Use AI-generated comments for Unity Catalog objects	https://learn.microsoft.com/en-us/azure/databricks/comments/ai-comments
Use Databricks compute configuration settings effectively	https://learn.microsoft.com/en-us/azure/databricks/compute/configure
Configure custom Docker containers for Databricks compute	https://learn.microsoft.com/en-us/azure/databricks/compute/custom-containers
Reference compatible instance groups for flexible nodes	https://learn.microsoft.com/en-us/azure/databricks/compute/flexible-node-type-instances
Configure Databricks instance pools in the UI	https://learn.microsoft.com/en-us/azure/databricks/compute/pools
Configure environments and policies for Databricks serverless notebooks	https://learn.microsoft.com/en-us/azure/databricks/compute/serverless/dependencies
Configure and manage Databricks SQL warehouses	https://learn.microsoft.com/en-us/azure/databricks/compute/sql-warehouse/create
Monitor Databricks SQL warehouses in the UI	https://learn.microsoft.com/en-us/azure/databricks/compute/sql-warehouse/monitor/
Configure Kafka connector options in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/connect/streaming/kafka/options
Configure Unity Catalog external locations for cloud storage	https://learn.microsoft.com/en-us/azure/databricks/connect/unity-catalog/cloud-storage/external-locations
Connect DBFS root as a Unity Catalog external location	https://learn.microsoft.com/en-us/azure/databricks/connect/unity-catalog/cloud-storage/external-locations-dbfs-root
Configure Unity Catalog managed storage locations	https://learn.microsoft.com/en-us/azure/databricks/connect/unity-catalog/cloud-storage/managed-storage
Reference functions for Databricks dashboard custom calculations	https://learn.microsoft.com/en-us/azure/databricks/dashboards/manage/data-modeling/custom-calculations/function-reference
Configure global settings for Databricks dashboards	https://learn.microsoft.com/en-us/azure/databricks/dashboards/manage/settings
Configure map visualizations in Databricks AI/BI dashboards	https://learn.microsoft.com/en-us/azure/databricks/dashboards/manage/visualizations/maps
Query Databricks audit logs to monitor dashboard usage	https://learn.microsoft.com/en-us/azure/databricks/dashboards/monitor-usage
Apply certified and deprecated tags in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/certify-deprecate-data
Create and link Unity Catalog metastores in Databricks	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/create-metastore
Use supported Databricks data classification tags	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/data-classification-tags
View and analyze data lineage with Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/data-lineage
Create and configure data profiles in Databricks UI	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/data-quality-monitoring/data-profiling/create-monitor-ui
Define and use custom metrics in Databricks data profiling	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/data-quality-monitoring/data-profiling/custom-metrics
Query Databricks data quality monitoring expenses	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/data-quality-monitoring/data-profiling/expense
Configure Databricks SQL alerts for profile metrics	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/data-quality-monitoring/data-profiling/monitor-alerts
Understand Databricks data profiling metric tables	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/data-quality-monitoring/data-profiling/monitor-output
Disable direct Hive metastore access in Databricks workspaces	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/disable-hms
Configure Azure Databricks workspaces for Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/enable-workspaces
Ingest external data lineage into Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/external-lineage
Configure legacy Hive metastore alongside Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/hive-metastore
Update Databricks jobs after upgrading to Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/jobs-update
Manage Unity Catalog metastore lifecycle and behavior	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/manage-metastore
Upgrade Hive metastore tables and views to Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/migrate
Use UCX utilities to automate Unity Catalog workspace upgrade	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/ucx
Understand Databricks DBFS behavior and deprecation	https://learn.microsoft.com/en-us/azure/databricks/dbfs/
Disable DBFS root and mounts in existing workspaces	https://learn.microsoft.com/en-us/azure/databricks/dbfs/disable-dbfs-root-mounts
Create and manage Delta Sharing recipients in Databricks	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/create-recipient
Create and manage Unity Catalog Delta Sharing shares	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/create-share
Access Delta Sharing data as a recipient in Databricks	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/recipient
Configure SAP BDC connector for Delta Sharing	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/sap-bdc/create-connection
Configure Delta Sharing for Azure Databricks providers	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/set-up
Configure Databricks-to-Databricks Delta Sharing for providers	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/share-data-databricks
Configure open Delta Sharing for external data recipients	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/share-data-open
Configure catalog commits for Unity Catalog Delta tables	https://learn.microsoft.com/en-us/azure/databricks/delta/catalog-commits
Enable and use Delta Lake Checkpoint V2 in Databricks	https://learn.microsoft.com/en-us/azure/databricks/delta/checkpoint-v2
Clone Delta, Parquet, and Iceberg tables on Databricks	https://learn.microsoft.com/en-us/azure/databricks/delta/clone
Use shallow clone with Unity Catalog tables	https://learn.microsoft.com/en-us/azure/databricks/delta/clone-unity-catalog
Manage Delta Lake columns with column mapping on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/delta/column-mapping
Configure and use Delta Lake change data feed on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/delta/delta-change-data-feed
Drop Delta table features and downgrade protocol versions	https://learn.microsoft.com/en-us/azure/databricks/delta/drop-feature
Drop and replace Delta and Unity Catalog tables	https://learn.microsoft.com/en-us/azure/databricks/delta/drop-table
Define and use Delta Lake generated columns on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/delta/generated-columns
Work with Delta table history and time travel on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/delta/history
Enable and use row tracking for Delta and Iceberg tables	https://learn.microsoft.com/en-us/azure/databricks/delta/row-tracking
Inspect Azure Databricks Delta table metadata with DESCRIBE DETAIL	https://learn.microsoft.com/en-us/azure/databricks/delta/table-details
Reference table properties for Delta and Iceberg on Databricks	https://learn.microsoft.com/en-us/azure/databricks/delta/table-properties
Configure Delta Lake type widening in Databricks	https://learn.microsoft.com/en-us/azure/databricks/delta/type-widening
Configure Delta tables for Iceberg client reads (UniForm) on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/delta/uniform
Store semi-structured data with VARIANT type	https://learn.microsoft.com/en-us/azure/databricks/delta/variant
Configure Databricks authentication profiles in .databrickscfg	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/auth/config-profiles
Reference for Databricks unified authentication environment variables	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/auth/env-vars
Use private artifacts and repositories in Databricks bundles	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/artifact-private
Configure deployment modes for Declarative Automation Bundles	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/deployment-modes
Use example Databricks bundle configurations for common scenarios	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/examples
Define job tasks in Declarative Automation Bundles	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/job-task-types
Declare library dependencies in bundle configuration	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/library-dependencies
Generate bundle config from existing Databricks resources	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/migrate-resources
Override bundle settings with target-specific configuration	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/overrides
Configure bundles to build and deploy Python wheels	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/python-wheel
Define and modify Databricks bundle resources using Python	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/python/
Reference for databricks.yml bundle configuration keys	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/reference
Configure Azure Databricks Declarative Automation Bundles resources	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/resources
Configure bundles to build and deploy Scala JARs	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/scala-jar
Understand Databricks bundle configuration file syntax	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/settings
Share configuration and files across Databricks bundles	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/sharing
Author custom bundle templates for Docker-based Python jobs	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/template-tutorial
Use Declarative Automation Bundles project templates	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/templates
Use substitutions and variables in bundle configs	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/variables
Manage the full lifecycle of Databricks bundles	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/work-tasks
Collaborate on Databricks bundles directly in the workspace UI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/workspace
Author and edit bundle configurations in the Databricks workspace	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/workspace-author
Create and deploy bundles from the Databricks workspace	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/workspace-tutorial
Use Azure Databricks CLI command groups and options	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/commands
Install and configure the Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/install
Use configuration profiles with the Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/profiles
Configure Databricks account credential settings via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-credentials-commands
Configure Databricks account log delivery via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-log-delivery-commands
Assign Unity Catalog metastores to workspaces via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-metastore-assignments-commands
Manage Unity Catalog metastores at account level	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-metastores-commands
Configure Databricks workspace network connectivity via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-network-connectivity-commands
Manage Databricks customer-managed VPC networks via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-networks-commands
Configure Databricks account-level settings via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-settings-commands
Manage Databricks workspace storage configurations via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-storage-commands
Manage Unity Catalog storage credentials via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-storage-credentials-commands
Manage Databricks VPC endpoint configurations via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-vpc-endpoints-commands
Configure Databricks workspace network policies via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-workspace-network-configuration-commands
Manage Databricks workspaces at account level via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-workspaces-commands
Use deprecated Databricks legacy alerts CLI commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/alerts-legacy-commands
Manage clean room asset revisions via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/clean-room-asset-revisions-commands
Configure clean room auto-approval rules via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/clean-room-auto-approval-rules-commands
Configure Databricks CLI shell autocompletion	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/completion-commands
Manage Unity Catalog data quality via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/data-quality-commands
Query Databricks SQL data sources using CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/data-sources-commands
Administer Databricks database instances with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/database-commands
Assign and manage Unity Catalog entity tags via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/entity-tag-assignments-commands
Define external lineage relationships via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/external-lineage-commands
Configure Unity Catalog external locations with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/external-locations-commands
Register external metadata in Unity Catalog via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/external-metadata-commands
Configure global init scripts with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/global-init-scripts-commands
View cluster policy compliance using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/policy-compliance-for-clusters-commands
Check job policy compliance with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/policy-compliance-for-jobs-commands
Configure Databricks workspace settings via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/settings-commands
Configure Databricks Apps with app.yaml runtime settings	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/app-runtime
Configure app-to-app resources for Databricks Apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/apps-resource
Configure Databricks Apps templates, auth, and routing	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/configuration
Configure Python and Node.js dependencies for Databricks apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/dependencies
Configure iframe embedding for Databricks apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/embed
Configure environment variables for Databricks apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/environment-variables
Add Unity Catalog UDF resources to Databricks Apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/functions
Integrate Genie spaces as resources in Databricks Apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/genie
Use HTTP headers forwarded to Databricks apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/http-headers
Configure Lakebase database resources for Databricks Apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/lakebase
Add and configure Lakeflow Jobs as Databricks app resources	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/lakeflow
Configure MLflow experiment resources for Databricks Apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/mlflow
Add model serving endpoint resources to Databricks Apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/model-serving
Configure OpenTelemetry-based telemetry for Databricks Apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/observability
Configure Databricks app resources and secret management	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/resources
Configure SQL warehouse resources for Databricks Apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/sql-warehouse
Understand environment and dependencies for Databricks apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/system-env
Configure vector search index resources in Databricks Apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/vector-search
Configure compute connections for Databricks Connect	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/cluster-config
Configure and use Databricks Connect for Python	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/python/
Use Databricks Utilities (dbutils) in notebooks	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-utils
Terraform configuration to deploy Azure Databricks workspaces	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/terraform/azure-workspace
Configure Databricks projects in VS Code extension	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/vscode-ext/configure
Configure settings for the Databricks VS Code extension	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/vscode-ext/settings
Explore Unity Catalog volumes and storage paths	https://learn.microsoft.com/en-us/azure/databricks/discover/files
Enable Compatibility Mode for external table reads	https://learn.microsoft.com/en-us/azure/databricks/external-access/compatibility-mode
Configure Iceberg REST catalog access to Databricks tables	https://learn.microsoft.com/en-us/azure/databricks/external-access/iceberg
Use Databricks file utilities and APIs	https://learn.microsoft.com/en-us/azure/databricks/files/
Understand Databricks default working directory behavior	https://learn.microsoft.com/en-us/azure/databricks/files/cwd-dbr-14
Use Unity Catalog volumes for file storage	https://learn.microsoft.com/en-us/azure/databricks/files/volumes
Store and reference init scripts in Databricks workspace files	https://learn.microsoft.com/en-us/azure/databricks/files/workspace-init-scripts
Programmatically manage Databricks workspace files	https://learn.microsoft.com/en-us/azure/databricks/files/workspace-interact
Import Python and R modules from Databricks workspace files	https://learn.microsoft.com/en-us/azure/databricks/files/workspace-modules
Identify where Databricks writes operational data	https://learn.microsoft.com/en-us/azure/databricks/files/write-data
Define custom metrics in MLflow 2 Agent Evaluation	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-evaluation/custom-metrics
Use MLflow 2 Agent Evaluation input schema	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-evaluation/evaluation-schema
Configure and use built-in MLflow 2 AI judges	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-evaluation/llm-judge-reference
Migrate from legacy Databricks agent input/output schemas	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/agent-legacy-schema
Replace deprecated Databricks agent feedback model	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/feedback-model
Log and register Databricks Model Serving AI agents	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/log-agent
Migrate from deprecated Databricks agent inference tables	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/request-assessment-logs
Host custom MCP servers as Databricks apps	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/mcp/custom-mcp
Configure external MCP servers with Databricks proxies	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/mcp/external-mcp
Configure _meta parameters for Databricks managed MCP servers	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/mcp/managed-mcp-meta-param
Configure Databricks external endpoints for OpenAI	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/tutorials/external-models-tutorial
Create and configure custom Genie Code agent skills	https://learn.microsoft.com/en-us/azure/databricks/genie-code/skills
Configure and use Apache Iceberg v3 features in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/iceberg/iceberg-v3
Load data via Unity Catalog external locations in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/add-data-external-locations
Configure Auto Loader directory listing mode for ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/auto-loader/directory-listing-mode
Use managed file events with Auto Loader	https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/auto-loader/file-events-explained
Configure Databricks Auto Loader in file notification mode	https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/auto-loader/file-notification-mode
Configure Auto Loader cloudFiles options in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/auto-loader/options
Configure schema inference and evolution in Auto Loader	https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/auto-loader/schema
Enable automatic type widening in Auto Loader	https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/auto-loader/type-widening
Configure COPY INTO with Unity Catalog volumes	https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/copy-into/unity-catalog
Configure incremental ingestion from ADLS with Auto Loader	https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/onboard-data
Create or modify Delta tables via file upload UI	https://learn.microsoft.com/en-us/azure/databricks/ingestion/create-or-modify-table
Configure column selection for Lakeflow Connect ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/column-selection
Use Confluence connector reference for schemas and metadata	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/confluence-reference
Use Dynamics 365 connector configuration reference	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/d365-reference
Configure Dynamics 365 and storage for Databricks ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/d365-source-setup
Monitor Lakeflow ingestion gateways with event logs	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/gateway-event-logs
Use Google Ads connector table schemas and data types	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-ads-reference
Configure OAuth 2.0 for Google Ads Databricks ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-ads-source-setup
Consult GA4 raw data connector configuration reference	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-analytics-reference
Use HubSpot connector reference for tables and updates	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/hubspot-reference
Use Jira Lakeflow connector reference settings	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/jira-reference
Reference Meta Ads connector objects and mappings	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/meta-ads-reference
Configure Meta Ads as Lakeflow data source	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/meta-ads-source-setup
Configure multi-destination Lakeflow Connect ingestion pipelines	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/multi-destination-pipeline
Configure Amazon RDS and Aurora MySQL for CDC	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/mysql-aws-rds-config
Configure Azure Database for MySQL for CDC	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/mysql-azure-config
Configure MySQL on EC2 for Databricks ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/mysql-ec2-config
Configure Cloud SQL for MySQL for Lakeflow	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/mysql-gcp-config
Use MySQL connector reference for types and DDL handling	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/mysql-reference
Configure MySQL for Lakeflow CDC ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/mysql-source-setup
Prepare MySQL with utility objects for Lakeflow	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/mysql-utility-script
Use NetSuite connector tables and type mappings	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/netsuite-reference
Configure NetSuite token-based auth for ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/netsuite-source-setup
Configure tags on Lakeflow managed ingestion pipelines	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/pipeline-tags
Reference PostgreSQL connector types and unsupported objects	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/postgresql-reference
Configure PostgreSQL source for Lakeflow Connect ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/postgresql-source-setup
Configure query-based connectors in Lakeflow Connect	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/query-based-reference
Configure row filtering for Lakeflow Connect ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/row-filtering
Reference Salesforce connector objects and type mappings	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/salesforce-reference
Configure SCD type 1 and 2 history tracking in Lakeflow Connect	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/scd
Use ServiceNow connector data type mappings	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/servicenow-reference
Configure ServiceNow instance for Databricks ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/servicenow-source-setup
Use Microsoft SharePoint connector reference settings	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sharepoint-reference
Review SharePoint ingestion authentication options	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sharepoint-source-setup-overview
Use SQL Server connector reference for types and objects	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sql-server-reference
Prepare SQL Server source for Databricks ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sql-server-source-setup
Run SQL Server utility script for Lakeflow ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sql-server-utility
Reference SQL Server utility objects script for Lakeflow	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sql-server-utility-reference
Set custom destination table names in Lakeflow Connect	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/table-rename
Reference TikTok Ads tables, dimensions, metrics	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/tiktok-ads-reference
Use Workday HCM connector reference in Lakeflow	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/workday-hcm-reference
Configure Workday Reports connector authentication and setup	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/workday-reports
Use Workday Reports connector reference mappings	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/workday-reports-reference
Set up Workday reports for Lakeflow ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/workday-reports-source-setup
Use Zendesk Support connector technical reference in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/zendesk-support-reference
Configure OTLP clients for Unity Catalog ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/opentelemetry/configure
OpenTelemetry table schemas for Zerobus Ingest	https://learn.microsoft.com/en-us/azure/databricks/ingestion/opentelemetry/table-reference
Ingest data as VARIANT type using Auto Loader and COPY INTO	https://learn.microsoft.com/en-us/azure/databricks/ingestion/variant
Configure cluster-scoped init scripts in Databricks	https://learn.microsoft.com/en-us/azure/databricks/init-scripts/cluster-scoped
Configure environment variables in Databricks init scripts	https://learn.microsoft.com/en-us/azure/databricks/init-scripts/environment-variables
Configure global init scripts across Databricks workspace	https://learn.microsoft.com/en-us/azure/databricks/init-scripts/global
Configure scheduled data refreshes in Google Sheets connector	https://learn.microsoft.com/en-us/azure/databricks/integrations/google-sheets/schedule-refresh
Configure Databricks JDBC driver connections (v3+)	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc-oss/configure
Configure Databricks JDBC driver connection properties	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc-oss/properties
Configure legacy Simba-based Databricks JDBC driver	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc/
Configure capability settings for legacy Databricks JDBC driver	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc/capability
Set compute options for the legacy Databricks JDBC driver	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc/compute
Configure connections using the legacy Databricks JDBC driver	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc/configure
Create Azure Databricks connections in Microsoft Power Platform	https://learn.microsoft.com/en-us/azure/databricks/integrations/msft-power-platform-setup
Configure advanced capability settings for Databricks ODBC driver	https://learn.microsoft.com/en-us/azure/databricks/integrations/odbc/capability
Configure Databricks compute settings for the ODBC driver	https://learn.microsoft.com/en-us/azure/databricks/integrations/odbc/compute
Create and configure ODBC DSNs for Databricks	https://learn.microsoft.com/en-us/azure/databricks/integrations/odbc/dsn
Build DSN-less ODBC connection strings for Databricks	https://learn.microsoft.com/en-us/azure/databricks/integrations/odbc/dsn-less
Configure and run backfill jobs in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/backfill-jobs
Configure Clean Room notebook tasks in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/clean-room-notebook
Configure and edit Azure Databricks Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/configure-job
Configure task dependencies and control flow in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/control-flow
Configure dashboard tasks to refresh Databricks dashboards	https://learn.microsoft.com/en-us/azure/databricks/jobs/dashboard
Configure dbt tasks in Azure Databricks jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/dbt
Use dynamic value references in Databricks jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/dynamic-value-references
Configure file arrival triggers for Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/file-arrival-triggers
Configure For each looping tasks in Databricks jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/for-each
Configure Git-backed source for Lakeflow Jobs tasks	https://learn.microsoft.com/en-us/azure/databricks/jobs/git
Add If/else branching logic in Databricks jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/if-else
Configure JAR tasks for Azure Databricks jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/jar
Create Databricks-compatible JARs for Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/jar-create
Configure and use job parameters in Databricks	https://learn.microsoft.com/en-us/azure/databricks/jobs/job-parameters
Monitor and inspect Lakeflow Jobs runs in Databricks	https://learn.microsoft.com/en-us/azure/databricks/jobs/monitor
Configure notebook tasks in Azure Databricks jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/notebook
Configure job and task notifications in Databricks	https://learn.microsoft.com/en-us/azure/databricks/jobs/notifications
Parameterize Azure Databricks jobs and tasks	https://learn.microsoft.com/en-us/azure/databricks/jobs/parameters
Configure pipeline tasks to run Lakeflow Spark Declarative Pipelines	https://learn.microsoft.com/en-us/azure/databricks/jobs/pipeline
Configure Python script tasks in Azure Databricks jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/python-script
Configure Python wheel tasks in Azure Databricks jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/python-wheel
Configure Run Job tasks for Databricks workflows	https://learn.microsoft.com/en-us/azure/databricks/jobs/run-job
Configure time-based schedules for Azure Databricks jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/scheduled
Configure SQL tasks and warehouses for Databricks jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/sql
Configure and use task parameters in Azure Databricks jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/task-parameters
Trigger Lakeflow Jobs on source table updates	https://learn.microsoft.com/en-us/azure/databricks/jobs/trigger-table-update
Configure schedules and triggers for Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/triggers
Configure Foundation Model Fine-tuning runs via API	https://learn.microsoft.com/en-us/azure/databricks/large-language-models/foundation-model-training/create-fine-tune-run
Prepare training data for Foundation Model Fine-tuning	https://learn.microsoft.com/en-us/azure/databricks/large-language-models/foundation-model-training/data-preparation
Configure and run Databricks foundation model fine-tuning	https://learn.microsoft.com/en-us/azure/databricks/large-language-models/foundation-model-training/fine-tune-run-tutorial
Set up Foundation Model Fine-tuning runs in UI	https://learn.microsoft.com/en-us/azure/databricks/large-language-models/foundation-model-training/ui
Implement AUTO CDC and AUTO CDC FROM SNAPSHOT in Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/cdc
Configure classic compute resources for pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/configure-compute
Configure Lakeflow pipelines with Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/ldp/configure-pipeline
Configure Databricks SQL materialized view options and access	https://learn.microsoft.com/en-us/azure/databricks/ldp/dbsql/materialized-configure
Monitor and manage materialized view refresh data	https://learn.microsoft.com/en-us/azure/databricks/ldp/dbsql/materialized-monitor
Generate Lakeflow pipelines from metadata with dlt-meta	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/dlt-meta
Configure pipeline event hooks for custom monitoring	https://learn.microsoft.com/en-us/azure/databricks/ldp/event-hooks
Configure pipeline expectations for data quality	https://learn.microsoft.com/en-us/azure/databricks/ldp/expectations
Example configurations of flows in Lakeflow Spark Declarative Pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/flow-examples
Configure and use flows in Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/flows
Configure JSON schema inference and evolution with from_json	https://learn.microsoft.com/en-us/azure/databricks/ldp/from-json-schema-evolution
Configure pipelines with legacy Hive metastore	https://learn.microsoft.com/en-us/azure/databricks/ldp/hive-metastore
Configure and use Lakeflow sink API with flows	https://learn.microsoft.com/en-us/azure/databricks/ldp/ldp-sinks
Understand and migrate from legacy LIVE schema	https://learn.microsoft.com/en-us/azure/databricks/ldp/live-schema
Load data into Lakeflow pipelines from supported sources	https://learn.microsoft.com/en-us/azure/databricks/ldp/load
Migrate Databricks pipelines to the default publishing mode	https://learn.microsoft.com/en-us/azure/databricks/ldp/migrate-to-dpm
Use Lakeflow pipeline event log schema for auditing	https://learn.microsoft.com/en-us/azure/databricks/ldp/monitor-event-log-schema
Query and use the Lakeflow pipeline event log	https://learn.microsoft.com/en-us/azure/databricks/ldp/monitor-event-logs
Use Lakeflow Pipelines Editor for ETL development	https://learn.microsoft.com/en-us/azure/databricks/ldp/multi-file-editor
Parameterize Lakeflow Spark Declarative Pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/parameters
Choose and configure triggered vs continuous pipeline modes	https://learn.microsoft.com/en-us/azure/databricks/ldp/pipeline-mode
Configure Lakeflow pipeline JSON and table properties	https://learn.microsoft.com/en-us/azure/databricks/ldp/properties
Configure serverless Lakeflow Spark pipelines in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ldp/serverless
Configure custom sinks in Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/sinks
Configure source-controlled Lakeflow pipelines with Git	https://learn.microsoft.com/en-us/azure/databricks/ldp/source-controlled
Set default catalog and schema for Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/target-schema
Declare and manage data transformations in pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/transform
Configure Unity Catalog usage in Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/unity-catalog
Use ALTER SQL statements with pipeline datasets	https://learn.microsoft.com/en-us/azure/databricks/ldp/using-alter-sql
Manage compute-scoped libraries on Databricks clusters	https://learn.microsoft.com/en-us/azure/databricks/libraries/cluster-libraries
Configure notebook-scoped Python libraries in Databricks	https://learn.microsoft.com/en-us/azure/databricks/libraries/notebooks-python-libraries
Configure notebook-scoped R libraries in Databricks	https://learn.microsoft.com/en-us/azure/databricks/libraries/notebooks-r-libraries
Install Databricks libraries from cloud object storage	https://learn.microsoft.com/en-us/azure/databricks/libraries/object-storage-libraries
Install Databricks libraries from Unity Catalog volumes	https://learn.microsoft.com/en-us/azure/databricks/libraries/volume-libraries
Install libraries from workspace files in Databricks	https://learn.microsoft.com/en-us/azure/databricks/libraries/workspace-files-libraries
Connect notebooks and jobs to Databricks AI Runtime	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/connecting
Configure Python environments for Databricks AI Runtime	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/environment
Configure AutoML classification data preparation settings	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/classification-data-prep
Configure AutoML forecasting data preparation settings	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/forecasting-data-prep
Configure AutoML regression data preparation settings	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/regression-data-prep
Configure Databricks Runtime for Machine Learning compute	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/databricks-runtime-ml
Configure Model Serving with automatic feature lookup	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/automatic-feature-lookup
Configure and use Databricks Feature Serving endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/feature-function-serving
Configure Databricks Feature Engineering Python client	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/python-api
Create and manage feature tables in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/uc/feature-tables-uc
Manage Workspace Feature Store feature tables	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/workspace-feature-store/feature-tables
Prepare data for distributed ML training on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/load-data/ddl-data
Manage MLflow models in Unity Catalog lifecycle	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/manage-model-lifecycle/
Share Databricks models across multiple workspaces	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/manage-model-lifecycle/multiple-workspaces
Manage MLflow models in legacy Workspace Model Registry	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/manage-model-lifecycle/workspace-model-registry
Create and configure custom model serving endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/create-manage-serving-endpoints
Configure telemetry persistence for Databricks custom model serving	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/custom-model-serving-uc-logs
Configure custom models and compute for Databricks serving	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/custom-models
Enable inference tables on Databricks endpoints via API	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/enable-model-serving-inference-tables
Use inference tables to monitor and debug Databricks endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/inference-tables
Configure and manage Azure Databricks model serving endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/manage-serving-endpoints
Configure Databricks serving endpoint health metrics export	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/metrics-export-serving-endpoint
Package custom artifacts for Databricks Model Serving	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/model-serving-custom-artifacts
Monitor Databricks model quality and endpoint health	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/monitor-diagnose-endpoints
Use custom and private Python libraries in Model Serving	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/private-libraries-model-serving
Enable route optimization on Databricks serving endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/route-optimization
Configure multiple models and traffic splitting on Databricks endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/serve-multiple-models-to-serving-endpoint
Configure and create Ray clusters on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ray/ray-create
Start Ray clusters using Databricks Spark jobs	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ray/start-ray
Configure Databricks Marketplace listings and shares	https://learn.microsoft.com/en-us/azure/databricks/marketplace/create-listing
Access Databricks Marketplace data in UC workspaces	https://learn.microsoft.com/en-us/azure/databricks/marketplace/get-started-consumer
Edit and revoke Databricks listings	https://learn.microsoft.com/en-us/azure/databricks/marketplace/manage-listings
Manage received Databricks Marketplace data products	https://learn.microsoft.com/en-us/azure/databricks/marketplace/manage-requests-consumer
Configure private exchanges in Databricks Marketplace	https://learn.microsoft.com/en-us/azure/databricks/marketplace/private-exchange
Build dashboards from MLflow system table metadata	https://learn.microsoft.com/en-us/azure/databricks/mlflow/build-dashboards
Configure Databricks Autologging with MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow/databricks-autologging
Log MLflow model dependencies as reproducible artifacts	https://learn.microsoft.com/en-us/azure/databricks/mlflow/log-model-dependencies
Use MLflow Logged Models to track model lifecycle	https://learn.microsoft.com/en-us/azure/databricks/mlflow/logged-model
Use MLflow 3 Model Registry metrics and parameters	https://learn.microsoft.com/en-us/azure/databricks/mlflow/model-registry-3
Log, load, and register MLflow models for deployment	https://learn.microsoft.com/en-us/azure/databricks/mlflow/models
Configure MLflow tracking server storage locations	https://learn.microsoft.com/en-us/azure/databricks/mlflow/tracking-server-configuration
Use MLflow evaluation dataset schema and APIs	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/concepts/eval-datasets
Configure and use MLflow Safety judge for content	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/concepts/judges/is_safe
Configure MLflow scorer lifecycle for production monitoring	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/concepts/production-quality-monitoring
Configure dev environments to connect to MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/getting-started/connect-environment
Configure and understand MLflow prompt caching behavior	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/prompt-version-mgmt/prompt-registry/cache-prompts
Create and manage prompts in MLflow Prompt Registry	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/prompt-version-mgmt/prompt-registry/create-and-edit-prompts
Configure MLflow to track prompt and app versions together	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/prompt-version-mgmt/prompt-registry/track-prompts-app-versions
Configure deployed apps to load prompts via registry aliases	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/prompt-version-mgmt/prompt-registry/use-prompts-in-deployed-apps
Configure production trace linking to MLflow app versions	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/prompt-version-mgmt/version-tracking/link-production-traces-to-app-versions
Track external GenAI app versions with MLflow LoggedModel	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/prompt-version-mgmt/version-tracking/track-application-versions-with-mlflow
Configure MLflow LoggedModel for GenAI version tracking	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/prompt-version-mgmt/version-tracking/version-concepts
Access and view MLflow traces in Databricks UI	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/observe-with-traces/ui-traces
Configure Langfuse to export traces to MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/third-party/langfuse
Set OpenTelemetry span attributes for Databricks MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/third-party/otel-span-attributes
Configure MLflow trace storage in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/trace-unity-catalog
Use and migrate legacy ${param} notebook widgets	https://learn.microsoft.com/en-us/azure/databricks/notebooks/legacy-widgets
Configure Databricks notebook file formats and commits	https://learn.microsoft.com/en-us/azure/databricks/notebooks/notebook-format
Apply and manage Databricks notebook tags	https://learn.microsoft.com/en-us/azure/databricks/notebooks/notebook-tags
Configure and use Databricks notebook widgets	https://learn.microsoft.com/en-us/azure/databricks/notebooks/widgets
Configure high availability for Lakebase instances	https://learn.microsoft.com/en-us/azure/databricks/oltp/instances/create/high-availability
Configure Lakebase Postgres connection string formats	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/connection-strings
Configure and install Postgres extensions in Lakebase	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/extensions
Create and manage Lakebase branches	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/manage-branches
Enable and configure Lakebase high availability	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/manage-high-availability
Create and configure Lakebase Postgres projects	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/manage-projects
Manage Lakebase with Declarative Automation Bundles	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/manage-with-bundles
Use Lakebase metrics dashboard for monitoring	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/metrics
Use point-in-time branches in Lakebase	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/point-in-time-branching
Register Lakebase Postgres databases in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/register-uc
Configure Lakebase scale-to-zero idle suspension behavior	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/scale-to-zero
Create and restore Lakebase database snapshots	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/snapshots
Configure automatic updates for Lakebase computes	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/updates
Use pandas API on Spark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pandas/pandas-on-spark
Enable BI compatibility mode for Databricks metric views	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/bi-metric-view
Create and use Power BI connections in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/power-bi-uc-connect
Set up Azure Databricks integration with Matillion Data Productivity Cloud	https://learn.microsoft.com/en-us/azure/databricks/partners/prep/matillion
Configure DataFrame persistence and storage levels	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/persist
Configure single streaming input option with DataStreamReader.option	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/option
Configure multiple streaming input options with DataStreamReader.options	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/options
Define streaming input schemas with DataStreamReader.schema	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/schema
Configure clustered output files with DataStreamWriter.clusterBy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/clusterby
Configure single streaming output option with DataStreamWriter.option	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/option
Configure multiple streaming output options with DataStreamWriter.options	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/options
Control streaming sink semantics with DataStreamWriter.outputMode	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/outputmode
Partition streaming output by columns with DataStreamWriter.partitionBy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/partitionby
Name streaming queries with DataStreamWriter.queryName	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/queryname
Configure streaming triggers with DataStreamWriter.trigger	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/trigger
Manage Spark runtime settings with RuntimeConfig	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/runtimeconfig
Read Spark configuration values with RuntimeConfig.get	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/runtimeconfig/get
List all Spark configuration properties with RuntimeConfig.getAll	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/runtimeconfig/getall
Check if Spark config keys are modifiable with isModifiable	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/runtimeconfig/ismodifiable
Set Spark runtime configuration with RuntimeConfig.set	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/runtimeconfig/set
Unset Spark configuration keys with RuntimeConfig.unset	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/runtimeconfig/unset
Use SparkSession.conf for runtime configuration	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/conf
Check Spark runtime version via SparkSession.version	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/version-session
Access recent streaming progress via recentProgress	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/recentprogress
Partition data into hourly buckets in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/hours
Manage Lakehouse Federation connections in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/query-federation/connections
Manage and query foreign catalogs in Databricks	https://learn.microsoft.com/en-us/azure/databricks/query-federation/foreign-catalogs
Configure external Hive metastore federation in Databricks	https://learn.microsoft.com/en-us/azure/databricks/query-federation/hms-federation-external
Enable Hive metastore federation for legacy Databricks workspaces	https://learn.microsoft.com/en-us/azure/databricks/query-federation/hms-federation-internal
Configure OneLake catalog federation with Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/query-federation/onelake
Enable Snowflake catalog federation in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/query-federation/snowflake-catalog-federation
Configure Databricks Lakehouse Federation for Teradata	https://learn.microsoft.com/en-us/azure/databricks/query-federation/teradata
Read Excel files with Databricks built-in format	https://learn.microsoft.com/en-us/azure/databricks/query/formats/excel
Configure Databricks image data source for Spark	https://learn.microsoft.com/en-us/azure/databricks/query/formats/image
Choose appropriate Databricks serverless environment versions	https://learn.microsoft.com/en-us/azure/databricks/release-notes/serverless/environment-version/
Reference serverless environment version 5 system details	https://learn.microsoft.com/en-us/azure/databricks/release-notes/serverless/environment-version/five
Reference serverless environment version 4 system details	https://learn.microsoft.com/en-us/azure/databricks/release-notes/serverless/environment-version/four
Use serverless GPU environment version 4 for AI workloads	https://learn.microsoft.com/en-us/azure/databricks/release-notes/serverless/environment-version/four-gpu
Reference serverless environment version 1 system details	https://learn.microsoft.com/en-us/azure/databricks/release-notes/serverless/environment-version/one
Reference serverless environment version 3 system details	https://learn.microsoft.com/en-us/azure/databricks/release-notes/serverless/environment-version/three
Understand deprecated serverless GPU environment version 3	https://learn.microsoft.com/en-us/azure/databricks/release-notes/serverless/environment-version/three-gpu
Reference serverless environment version 2 system details	https://learn.microsoft.com/en-us/azure/databricks/release-notes/serverless/environment-version/two
Use Azure Databricks Git folders for version control	https://learn.microsoft.com/en-us/azure/databricks/repos/
Enable or disable Databricks Git folders via API	https://learn.microsoft.com/en-us/azure/databricks/repos/enable-disable-repos-with-api
Configure Git credentials for Azure Databricks Git folders	https://learn.microsoft.com/en-us/azure/databricks/repos/get-access-tokens-from-git-provider
Understand Databricks Git folders concepts and providers	https://learn.microsoft.com/en-us/azure/databricks/repos/git-folders-concepts
Create and manage Azure Databricks Git folders	https://learn.microsoft.com/en-us/azure/databricks/repos/git-operations-with-repos
Configure Git server proxy for private Git with Databricks	https://learn.microsoft.com/en-us/azure/databricks/repos/git-proxy
Configure IPs and domains for Azure Databricks networking	https://learn.microsoft.com/en-us/azure/databricks/resources/ip-domain-region
Verify supported browsers for Azure Databricks UI access	https://learn.microsoft.com/en-us/azure/databricks/resources/supported-browsers
Create schemas in Unity Catalog and Hive metastore	https://learn.microsoft.com/en-us/azure/databricks/schemas/create-schema
Configure Databricks connectivity to on-premises networks	https://learn.microsoft.com/en-us/azure/databricks/security/network/classic/on-prem-network
Configure user-defined routes for Databricks VNets	https://learn.microsoft.com/en-us/azure/databricks/security/network/classic/udr
Update Azure Databricks workspace VNet settings	https://learn.microsoft.com/en-us/azure/databricks/security/network/classic/update-workspaces
Deploy Azure Databricks with VNet injection	https://learn.microsoft.com/en-us/azure/databricks/security/network/classic/vnet-inject
Configure inbound Private Link for Databricks services	https://learn.microsoft.com/en-us/azure/databricks/security/network/front-end/service-direct-privatelink
Manage Databricks serverless private endpoint rules	https://learn.microsoft.com/en-us/azure/databricks/security/network/serverless-network-security/manage-private-endpoint-rules
Set up Private Link from serverless to VNets	https://learn.microsoft.com/en-us/azure/databricks/security/network/serverless-network-security/pl-to-internal-network
Configure Private Link from Databricks serverless compute	https://learn.microsoft.com/en-us/azure/databricks/security/network/serverless-network-security/serverless-private-link
Use ARM template to enable Databricks storage firewall	https://learn.microsoft.com/en-us/azure/databricks/security/network/storage/firewall-support-arm-template
Set and manage Spark configuration properties on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/spark/conf
Manage R dependencies with renv on Databricks	https://learn.microsoft.com/en-us/azure/databricks/sparkr/renv
Use BOOLEAN data type in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/data-types/boolean-type
Define STRUCT types and fields in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/data-types/struct-type
Use REORG TABLE to optimize Delta layout	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/delta-reorg-table
Use (deprecated) ai_generate_text for LLM text in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_generate_text
Attach explicit collations with Databricks SQL collate	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/collate
Inspect string collation settings in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/collation
List supported collations in Azure Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/collations
Use count_min_sketch with Databricks SQL aggregates	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/count_min_sketch
Inspect catalog provider share usage in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/catalog_provider_share_usage
List catalog tags using INFORMATION_SCHEMA in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/catalog_tags
Describe Unity Catalog catalogs via INFORMATION_SCHEMA	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/catalogs
Query COLUMN_MASKS metadata in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/column_masks
Retrieve column tagging metadata with COLUMN_TAGS	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/column_tags
Use INFORMATION_SCHEMA.COLUMNS in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/columns
Describe foreign connections with INFORMATION_SCHEMA.CONNECTIONS	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/connections
List constraint column usage in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/constraint_column_usage
Inspect table usage in constraints via INFORMATION_SCHEMA	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/constraint_table_usage
Describe external locations via INFORMATION_SCHEMA in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/external_locations
Get information schema catalog name in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/information_schema_catalog_name
List key column usage for constraints in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/key_column_usage
Describe current metastore with INFORMATION_SCHEMA.METASTORES	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/metastores
Query routine parameters via INFORMATION_SCHEMA.PARAMETERS	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/parameters
Describe Delta Sharing providers with INFORMATION_SCHEMA.PROVIDERS	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/providers
Describe Delta Sharing recipients via INFORMATION_SCHEMA	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/recipients
View referential constraints with INFORMATION_SCHEMA in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/referential_constraints
List table-valued function result columns via ROUTINE_COLUMNS	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/routine_columns
Describe functions and routines via INFORMATION_SCHEMA.ROUTINES	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/routines
Inspect schema share usage via INFORMATION_SCHEMA.SCHEMA_SHARE_USAGE	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/schema_share_usage
Retrieve schema tagging metadata with SCHEMA_TAGS	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/schema_tags
Describe schemas via INFORMATION_SCHEMA.SCHEMATA in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/schemata
Describe Delta shares via INFORMATION_SCHEMA.SHARES	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/shares
Describe storage credentials via INFORMATION_SCHEMA.STORAGE_CREDENTIALS	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/storage_credentials
Query TABLE_CONSTRAINTS metadata in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/table_constraints
Inspect TABLE_PRIVILEGES metadata in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/table_privileges
Use TABLE_SHARE_USAGE metadata in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/table_share_usage
Access TABLE_TAGS metadata for Databricks tables	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/table_tags
Query TABLES metadata via INFORMATION_SCHEMA in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/tables
Retrieve VIEWS metadata from Databricks INFORMATION_SCHEMA	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/views
Inspect VOLUME_PRIVILEGES metadata in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/volume_privileges
Use VOLUME_TAGS metadata for Databricks volumes	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/volume_tags
Query VOLUMES metadata via INFORMATION_SCHEMA in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/information-schema/volumes
Configure ANSI_MODE behavior in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/parameters/ansi_mode
Set LEGACY_TIME_PARSER_POLICY for Databricks SQL datetime handling	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/parameters/legacy_time_parser_policy
Tune MAX_FILE_PARTITION_BYTES for Databricks SQL file reads	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/parameters/max_partition_bytes
Configure READ_ONLY_EXTERNAL_METASTORE in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/parameters/read_only_external_metastore
Set TIMEZONE for Databricks SQL sessions and warehouses	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/parameters/timezone
Use USE_CACHED_RESULT to control query result caching in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/parameters/use_cached_result
Configure ANSI compliance options in Databricks Runtime	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-ansi-compliance
Apply SQL data type resolution rules in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-datatype-rules
Use Apache Hive compatibility features in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-hive-compatibility
Use JSON path expressions in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-json-path-expression
Name resolution rules in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-name-resolution
Naming rules and limits for Databricks SQL objects	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-names
Configure and use parameter markers in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-parameter-marker
Understand Databricks SQL configuration parameter hierarchy	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-parameters
Define and manage table partitions in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-partition
Use reserved words and schemas in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-reserved-words
Reset Databricks SQL session parameters with RESET	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-conf-mgmt-reset
Manage Databricks SQL session parameters with SET	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-conf-mgmt-set
Set session time zone with SET TIME ZONE in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-conf-mgmt-set-timezone
Describe governed tags in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-describe-governed-tag
Set CURRENT_RECIPIENT for Delta Sharing with SET RECIPIENT	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-set-recipient
Use SET variable for Databricks SQL temporary variables	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-set-variable
List Unity Catalog external locations with SHOW EXTERNAL LOCATIONS	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-locations
Inspect table properties with SHOW TBLPROPERTIES in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-tblproperties
List Unity Catalog volumes with SHOW VOLUMES	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-volumes
Use ALTER CATALOG to configure Databricks Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-catalog
Use DROP CONNECTION to convert foreign catalogs	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-catalog-drop-connection
Manage Unity Catalog connections with ALTER CONNECTION	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-connection
ALTER CREDENTIAL names in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-credential
Use ALTER DATABASE (alias for ALTER SCHEMA) in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-database
Modify governed tags with ALTER GOVERNED TAG in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-governed-tag
ALTER EXTERNAL LOCATION properties in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-location
Use ALTER MATERIALIZED VIEW in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-materialized-view
ALTER PROVIDER name and ownership in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-provider
ALTER RECIPIENT name and ownership in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-recipient
Configure schemas using ALTER SCHEMA in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-schema
Set managed locations for foreign schemas in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-schema-set-managed-location
ALTER STREAMING TABLE metadata in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-streaming-table
Alter table schema and properties in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-table
Add table constraints with ALTER TABLE ADD CONSTRAINT	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-table-add-constraint
Drop table constraints with ALTER TABLE DROP CONSTRAINT	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-table-drop-constraint
Alter table columns and fields in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-table-manage-column
Manage table partitions with ALTER TABLE in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-table-manage-partition
ALTER VIEW definitions and properties in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-view
Convert foreign views to managed views with SET MANAGED	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-view-set-managed
ALTER VOLUME name and owner in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-volume
Define liquid clustering with CLUSTER BY on Delta tables	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-cluster-by
Set object comments with COMMENT ON in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-comment
Use CREATE DATABASE (alias for CREATE SCHEMA) in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-database
Create governed tags with Databricks CREATE GOVERNED TAG	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-governed-tag
Configure external locations with CREATE EXTERNAL LOCATION	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-location
Configure REFRESH POLICY for materialized views	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-materialized-view-refresh-policy
Create Delta Sharing recipients in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-recipient
Use CREATE SERVER alias for connections	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-server
Create Unity Catalog shares in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-share
All CREATE TABLE variants in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-table
Create Hive-format tables in Databricks Runtime	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-table-hiveformat
Create tables LIKE existing tables in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-table-like
Drop Unity Catalog catalogs in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-catalog
Drop connections in Databricks Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-connection
Drop credentials in Databricks Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-credential
Drop databases (schemas) in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-database
Use DROP GOVERNED TAG in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-governed-tag
Drop external locations in Databricks Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-location
Drop stored procedures in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-procedure
Drop Delta Sharing providers in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-provider
Drop Delta Sharing recipients in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-recipient
Drop schemas in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-schema
Drop Unity Catalog shares in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-share
Drop tables and metadata in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-table
Drop session variables in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-variable
Set table properties and options in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-tblproperties
Truncate tables and partitions in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-truncate-table
Switch Unity Catalog context with USE CATALOG in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-use-catalog
Set current schema with USE SCHEMA in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-use-schema
Change current database with USE DATABASE (USE SCHEMA) in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-usedb
Write query results to directories with INSERT OVERWRITE	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-dml-insert-overwrite-directory
Use INSERT OVERWRITE DIRECTORY with HiveSerDe	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-dml-insert-overwrite-directory-hive
Load data into Hive SerDe tables with LOAD DATA	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-dml-load
Repartition and sort results with CLUSTER BY	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-clusterby
Control data partitioning with DISTRIBUTE BY	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-distributeby
Filter window function results with QUALIFY	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-qualify
Sample tables with TABLESAMPLE in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-sampling
Sort within partitions using SORT BY in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-sortby
Reference tables and derived results in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-table-reference
Declare and manage session variables in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-variables
Use Unity Catalog volumes for governed file storage	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-volumes
Configure query tags for Databricks SQL workloads	https://learn.microsoft.com/en-us/azure/databricks/sql/user/queries/query-tags
Customize SQL auto-formatting in Databricks editor	https://learn.microsoft.com/en-us/azure/databricks/sql/user/sql-editor/custom-format
Use mustache parameter syntax in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/user/sql-editor/mustache-parameters
Configure parameter widgets in Databricks SQL editor	https://learn.microsoft.com/en-us/azure/databricks/sql/user/sql-editor/parameter-widgets
Configure and use default storage in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/storage/default-storage
Configure Structured Streaming batch size with admission controls	https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/batch-size
Configure Structured Streaming checkpoints on Databricks	https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/checkpoints
Read and query Structured Streaming state data on Databricks	https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/read-state
Set up and configure real-time mode in Databricks	https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/real-time/setup
Configure RocksDB state store for Databricks Structured Streaming	https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/rocksdb-state-store
Configure Structured Streaming trigger intervals on Databricks	https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/triggers
Define constraints on Databricks Delta tables	https://learn.microsoft.com/en-us/azure/databricks/tables/constraints
Convert foreign tables to Unity Catalog managed tables	https://learn.microsoft.com/en-us/azure/databricks/tables/convert-foreign-managed
Configure partition discovery for Unity Catalog external tables	https://learn.microsoft.com/en-us/azure/databricks/tables/external-partition-discovery
Query and register Unity Catalog foreign tables	https://learn.microsoft.com/en-us/azure/databricks/tables/foreign
Create and manage Unity Catalog managed tables	https://learn.microsoft.com/en-us/azure/databricks/tables/managed
Understand schema enforcement on Databricks tables	https://learn.microsoft.com/en-us/azure/databricks/tables/schema-enforcement
Use multi-statement transactions on Unity Catalog tables	https://learn.microsoft.com/en-us/azure/databricks/transactions/
Implement batch Python UDFs in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/udf/python-batch-udf
Configure Python user-defined table functions on Databricks	https://learn.microsoft.com/en-us/azure/databricks/udf/python-udtf
Register Python UDTFs in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/udf/udtf-unity-catalog
Configure SQL and Python UDFs in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/udf/unity-catalog
Configure and create Mosaic AI Vector Search endpoints and indexes	https://learn.microsoft.com/en-us/azure/databricks/vector-search/create-vector-search
Create and manage Unity Catalog views in Databricks	https://learn.microsoft.com/en-us/azure/databricks/views/create-views
Configure box chart options in Databricks	https://learn.microsoft.com/en-us/azure/databricks/visualizations/boxplot
Configure chart visualization options in Databricks	https://learn.microsoft.com/en-us/azure/databricks/visualizations/charts
Configure cohort visualizations in Databricks	https://learn.microsoft.com/en-us/azure/databricks/visualizations/cohorts
Format numeric values in Databricks visualizations	https://learn.microsoft.com/en-us/azure/databricks/visualizations/format-numeric-types
Configure heatmap chart options in Databricks	https://learn.microsoft.com/en-us/azure/databricks/visualizations/heatmap
Configure histogram visualization options in Databricks	https://learn.microsoft.com/en-us/azure/databricks/visualizations/histogram
Use and migrate Databricks legacy visualizations	https://learn.microsoft.com/en-us/azure/databricks/visualizations/legacy-visualizations
Configure map visualizations in Databricks	https://learn.microsoft.com/en-us/azure/databricks/visualizations/maps
Customize Databricks table visualization options	https://learn.microsoft.com/en-us/azure/databricks/visualizations/tables
Apply path rules and access controls in volumes	https://learn.microsoft.com/en-us/azure/databricks/volumes/paths
Create and manage Unity Catalog volumes in Databricks	https://learn.microsoft.com/en-us/azure/databricks/volumes/utility-commands