Azure Databricks — Configuration

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Configuration

Topic	URL
Configure Azure Databricks account-level settings and features	https://learn.microsoft.com/en-us/azure/databricks/admin/account-settings/
Configure disabling of legacy features in new workspaces	https://learn.microsoft.com/en-us/azure/databricks/admin/account-settings/legacy-features
Configure tags to track Azure Databricks usage costs	https://learn.microsoft.com/en-us/azure/databricks/admin/account-settings/usage-detail-tags
Enable and manage verbose audit logs in Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/account-settings/verbose-logs
Configure automatic cluster update maintenance windows	https://learn.microsoft.com/en-us/azure/databricks/admin/clusters/automatic-cluster-update
Author Databricks compute policy JSON definitions	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
Administer SQL warehouse workspace-level settings in Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/sql/
Configure legacy data access for Databricks SQL warehouses	https://learn.microsoft.com/en-us/azure/databricks/admin/sql/data-access-configuration
Use Azure Databricks system tables for operational analytics	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/
Analyze Genie Code usage with assistant events table	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/assistant
Use audit log system table for Databricks account insights	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/audit-logs
Query Azure Databricks billable usage system table	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/billing
Track clean room events using Databricks system table	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/clean-rooms
Use Databricks compute system tables for monitoring	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/compute
Analyze sensitive data via Databricks data classification table	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/data-classification
Use data quality monitoring system table for table health	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/data-quality-monitoring
Monitor Databricks jobs using lakeflow system tables	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/jobs
Monitor Lakeflow job costs and performance using system tables	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/jobs-cost
Analyze data lineage using Databricks lineage system tables	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/lineage
Use Databricks Marketplace system tables for analytics	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/marketplace
Query OpenSharing materialization history system table	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/materialization
Use MLflow system tables in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/mlflow
Track Databricks model serving costs with system tables	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/model-serving-cost
Use Databricks network access events system table for diagnostics	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/network
Use predictive optimization operation history system table	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
Use Azure Databricks query history system table	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/query-history
Monitor DR replication with replication.states table	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/replication
Query Databricks serverless billing usage system table	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/serverless-billing
Track SQL warehouse events with Databricks system table	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/warehouse-events
Monitor SQL warehouses via Databricks warehouses system table	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/warehouses
Use workspaces system table to monitor Databricks workspaces	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/workspaces
Monitor Zerobus Ingest activity with system tables	https://learn.microsoft.com/en-us/azure/databricks/admin/system-tables/zerobus-ingest
Configure serverless usage policies for cost tagging	https://learn.microsoft.com/en-us/azure/databricks/admin/usage/budget-policies
Monitor default storage spending using billable usage table	https://learn.microsoft.com/en-us/azure/databricks/admin/usage/default-storage
Use system.billing.usage to monitor Databricks costs	https://learn.microsoft.com/en-us/azure/databricks/admin/usage/system-tables
Configure workspace base environments for serverless notebooks	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
Configure default deletion vector behavior for 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 Azure Databricks workspace email notifications	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace-settings/email
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 system notification webhooks	https://learn.microsoft.com/en-us/azure/databricks/admin/workspace-settings/notification-destinations
Purge deleted notebooks and logs from Databricks storage	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
Monitor Genie Spaces with audit logs and alerts	https://learn.microsoft.com/en-us/azure/databricks/ai-bi/admin/audit
Configure embedding options for Databricks dashboards and Genie Spaces	https://learn.microsoft.com/en-us/azure/databricks/ai-bi/admin/embed
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 Databricks AI/BI dashboards	https://learn.microsoft.com/en-us/azure/databricks/ai-bi/admin/themes
Set and manage Unity AI Gateway spending budgets	https://learn.microsoft.com/en-us/azure/databricks/ai-gateway/budgets-beta
Configure Unity AI Gateway on Databricks model endpoints	https://learn.microsoft.com/en-us/azure/databricks/ai-gateway/configure-ai-gateway-endpoints
Configure Unity AI Gateway endpoints in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ai-gateway/configure-endpoints-beta
Configure traffic splitting for Unity AI Gateway endpoints	https://learn.microsoft.com/en-us/azure/databricks/ai-gateway/configure-traffic-splitting-beta
Enable Unity AI Gateway inference tables for models	https://learn.microsoft.com/en-us/azure/databricks/ai-gateway/inference-tables
Configure inference tables for Unity AI Gateway	https://learn.microsoft.com/en-us/azure/databricks/ai-gateway/inference-tables-beta
Configure Databricks AI Search usage policies for cost tracking	https://learn.microsoft.com/en-us/azure/databricks/ai-search/budget-policies
Create and configure Databricks AI Search endpoints and indexes	https://learn.microsoft.com/en-us/azure/databricks/ai-search/create-ai-search
Understand legacy Databricks cluster UI 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
Use and configure the legacy Unity Catalog 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
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
Drop Delta table features to resolve compatibility	https://learn.microsoft.com/en-us/azure/databricks/archive/legacy/drop-feature-legacy
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 Delta UniForm for Iceberg compatibility	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
Use legacy Databricks online tables for feature serving	https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/feature-store/online-tables
Configure and interpret Databricks inference tables	https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/inference-tables
Enable optimized LLM serving on Mosaic AI Model Serving	https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/llm-optimized-model-serving
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 legacy WASB driver for Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/storage/wasb-blob
Configure Unity Catalog storage with service principals	https://learn.microsoft.com/en-us/azure/databricks/archive/unity-catalog/service-principals
Configure agent metadata for Databricks metric views	https://learn.microsoft.com/en-us/azure/databricks/business-semantics/agent-metadata
Configure materialization for Azure Databricks metric views	https://learn.microsoft.com/en-us/azure/databricks/business-semantics/metric-views/materialization
Reference YAML syntax for Unity Catalog metric views	https://learn.microsoft.com/en-us/azure/databricks/business-semantics/metric-views/yaml-reference
Create Unity Catalog catalogs in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/catalogs/create-catalog
Run and manage notebooks inside Databricks clean rooms	https://learn.microsoft.com/en-us/azure/databricks/clean-rooms/clean-room-notebook
Create and configure Databricks clean rooms	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
Add and manage comments on Unity Catalog assets	https://learn.microsoft.com/en-us/azure/databricks/comments/
Reference Databricks compute configuration settings and options	https://learn.microsoft.com/en-us/azure/databricks/compute/configure
Use Databricks containers for dedicated compute customization	https://learn.microsoft.com/en-us/azure/databricks/compute/custom-containers
Configure custom Docker containers for Databricks standard compute	https://learn.microsoft.com/en-us/azure/databricks/compute/custom-containers-standard
Migrate to token-based Databricks cluster events pagination	https://learn.microsoft.com/en-us/azure/databricks/compute/events-api-updates
Configure Azure Databricks instance pools in UI	https://learn.microsoft.com/en-us/azure/databricks/compute/pools
Configure environments and dependencies for Databricks serverless	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
Supported serverless write options for Databricks connectors	https://learn.microsoft.com/en-us/azure/databricks/connect/spark-data-sources-serverless-writes
Configure Databricks access to ADLS and Blob Storage	https://learn.microsoft.com/en-us/azure/databricks/connect/storage/azure-storage
Configure Azure Databricks access to Google Cloud Storage	https://learn.microsoft.com/en-us/azure/databricks/connect/storage/gcs
Administer Unity Catalog external locations in Databricks	https://learn.microsoft.com/en-us/azure/databricks/connect/unity-catalog/cloud-storage/manage-external-locations
Configure managed storage locations in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/connect/unity-catalog/cloud-storage/managed-storage
Define custom calculations in Databricks dashboards	https://learn.microsoft.com/en-us/azure/databricks/dashboards/manage/data-modeling/custom-calculations/
Reference functions for Databricks dashboard custom calculations	https://learn.microsoft.com/en-us/azure/databricks/dashboards/manage/data-modeling/custom-calculations/function-reference
Use level of detail expressions in dashboards	https://learn.microsoft.com/en-us/azure/databricks/dashboards/manage/data-modeling/custom-calculations/level-of-detail
Configure dashboard relationships and cross-dataset measures	https://learn.microsoft.com/en-us/azure/databricks/dashboards/manage/data-modeling/dashboard-relationships
Configure local metric views in Databricks dashboards	https://learn.microsoft.com/en-us/azure/databricks/dashboards/manage/data-modeling/local-metric-views
Configure and use dashboard filters in Databricks	https://learn.microsoft.com/en-us/azure/databricks/dashboards/manage/filters/
Configure visualization widgets in AI/BI dashboards	https://learn.microsoft.com/en-us/azure/databricks/dashboards/manage/visualizations/
Configure map visualizations in Azure Databricks dashboards	https://learn.microsoft.com/en-us/azure/databricks/dashboards/manage/visualizations/maps
Configure table and pivot visualizations in Databricks	https://learn.microsoft.com/en-us/azure/databricks/dashboards/manage/visualizations/tables
Create and manage Unity Catalog ABAC policies via UI, SQL, and APIs	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/abac/policies
Create and link Unity Catalog metastores to workspaces	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/create-metastore
Define and manage custom data classifiers in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/data-classification-custom-classifiers
Use supported Databricks Data Classification tags in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/data-classification-tags
Configure anomaly detection for Unity Catalog data quality	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/data-quality-monitoring/anomaly-detection/
Configure alerts for Databricks anomaly detection	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/data-quality-monitoring/anomaly-detection/alerts
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 Hive metastore access in Azure Databricks workspaces	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/disable-hms
Enable existing workspaces for Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/enable-workspaces
Configure external lineage sources in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/external-lineage
Get started configuring Unity Catalog workspaces	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/get-started
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 and configure Unity Catalog metastores	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/manage-metastore
Configure and apply tags to Unity Catalog objects	https://learn.microsoft.com/en-us/azure/databricks/database-objects/tags
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
Configure and manage DBFS mounts in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/dbfs/mounts
Create OpenSharing recipients on Databricks workspaces	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/create-recipient
Create and manage OpenSharing Unity Catalog shares	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/create-share
Grant and revoke access to OpenSharing data shares	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/grant-access
Manage OpenSharing provider objects as a data recipient	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/manage-provider
Manage OpenSharing recipient objects in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/manage-recipients
View and modify existing OpenSharing shares	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/manage-share
Mount shared Genie Spaces in your workspace	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/mount-genie-space
Read Databricks-to-Databricks OpenSharing data and notebooks	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/read-data-databricks
Access OpenSharing data as a Databricks or external recipient	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/recipient
Use SAP BDC semantic metadata in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/sap-bdc/semantic-metadata
Configure SecureConnect for OpenSharing behind firewalls	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/secureconnect-provider
Configure OpenSharing for Azure Databricks providers	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/set-up
Share Genie Spaces externally using OpenSharing	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/share-genie-space
Use built-in operators in Lakeflow Designer	https://learn.microsoft.com/en-us/azure/databricks/designer/built-in-operators
YAML schema reference for Lakeflow Designer user-defined operators	https://learn.microsoft.com/en-us/azure/databricks/designer/operators-yaml-ref
Demo all UI widgets in Lakeflow Designer operators	https://learn.microsoft.com/en-us/azure/databricks/designer/tutorial-all-ui-widgets
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 Databricks bundle configuration examples for common setups	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/examples
Configure bundle variables and job parameters for Databricks jobs	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/job-parameters
Configure job task definitions in Databricks 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 resources in Databricks Declarative Automation Bundles	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 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
Use Databricks CLI bundle commands for automation	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/bundle-commands
Configure Databricks CLI profiles for multiple environments	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/profiles
Configure Databricks account budget policies using CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-budget-policy-commands
Manage Databricks account budgets with CLI commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-budgets-commands
Configure Databricks account log delivery using 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 for Databricks accounts	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-metastores-commands
Configure Databricks network connectivity for serverless compute	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-network-connectivity-commands
Configure Databricks account-level default settings	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
Configure Unity Catalog storage credentials with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-storage-credentials-commands
Manage Databricks account usage dashboards via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-usage-dashboards-commands
Configure workspace network policies using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-workspace-network-configuration-commands
Manage Databricks workspaces with CLI commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-workspaces-commands
Use Databricks CLI aitools commands for AI skills	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/aitools-commands
Create and manage Databricks SQL alerts via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/alerts-commands
Work with legacy Databricks alerts via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/alerts-legacy-commands
Manage Databricks SQL alerts v2 using CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/alerts-v2-commands
Manage Unity Catalog catalogs with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/catalogs-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
Manage Databricks clean room assets with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/clean-room-assets-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
Manage clean room task runs using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/clean-room-task-runs-commands
Enforce Databricks cluster policies with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/cluster-policies-commands
Create and manage Databricks clusters via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/clusters-commands
Enable Databricks CLI shell autocompletion	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/completion-commands
Manage Databricks Marketplace consumer listings via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/consumer-listings-commands
Handle consumer personalization requests via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/consumer-personalization-requests-commands
Interact with Databricks Marketplace providers via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/consumer-providers-commands
Use Databricks CLI experiments command group	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/experiments-commands
Manage Unity Catalog functions with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/functions-commands
Use Databricks CLI postgres command group	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/postgres-commands
Connect with Databricks CLI psql command	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/psql-command
Use Databricks CLI vector-search-endpoints commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/vector-search-endpoints-commands
Use Databricks CLI vector-search-indexes commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/vector-search-indexes-commands
Configure Databricks workspace settings via CLI v2	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/workspace-settings-v2-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 compute size for Azure Databricks apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/compute-size
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
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 in 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 telemetry and OpenTelemetry for Databricks Apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/observability
Configure pre-installed Python libraries for Databricks apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/preinstalled-libraries
Configure SQL warehouse resources for Databricks Apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/sql-warehouse
Configure Databricks Apps runtime environment and variables	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-apps/system-env
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/
Install and configure Databricks Connect for Scala	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/scala/install
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 database objects with Catalog Explorer	https://learn.microsoft.com/en-us/azure/databricks/discover/database-objects
Configure Unity Catalog for external data access	https://learn.microsoft.com/en-us/azure/databricks/external-access/admin
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
Manage workspace files and Git folders in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/files/workspace
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
Use MLflow 2 Agent Evaluation input schema	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-evaluation/evaluation-schema
Migrate legacy Databricks agent schemas to ResponsesAgent	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/agent-legacy-schema
Use system.ai.python_exec code interpreter tool in agents	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/code-interpreter-tools
Replace deprecated Agent Framework feedback model	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/feedback-model
Log and register AI agents with Databricks Model Serving	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/log-agent
Configure non-conversational AI agents with MLflow	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/non-conversational-agents
Migrate from Agent Framework request logs to MLflow Traces	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/request-assessment-logs
Configure custom agents with Databricks Supervisor API	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/supervisor-api-app
Host custom MCP servers as Databricks apps	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/mcp/custom-mcp
Control managed MCP servers with _meta parameters	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/mcp/managed-mcp-meta-param
Configure custom instructions for Genie Code responses	https://learn.microsoft.com/en-us/azure/databricks/genie-code/instructions
Define and manage custom agent skills for Genie Code	https://learn.microsoft.com/en-us/azure/databricks/genie-code/skills
Configure Unity Catalog external locations for data loading	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
Configure Auto Loader file notification mode	https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/auto-loader/file-notification-mode
Configure schema inference and evolution in Auto Loader	https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/auto-loader/schema
Configure Auto Loader ingestion with Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/auto-loader/unity-catalog
Configure COPY INTO for incremental Delta loads	https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/copy-into/
Create custom Lakeflow community connectors for Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/community-build
Create Delta tables via file upload UI	https://learn.microsoft.com/en-us/azure/databricks/ingestion/create-or-modify-table
Query file metadata using the _metadata column	https://learn.microsoft.com/en-us/azure/databricks/ingestion/file-metadata-column
Configure column selection in Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/column-selection
Create Confluence connections for Lakeflow Connect	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/confluence-connection
Use Confluence connector schema and metadata reference	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/confluence-reference
Configure Dynamics 365 connections for Lakeflow Connect	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/d365-connection
Configure full refresh for Lakeflow ingestion pipelines	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/full-refresh
Monitor Lakeflow ingestion gateways with event logs	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/gateway-event-logs
Create and configure GitHub connections in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/github-connection
Apply GitHub connector connection and table reference	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/github-reference
Create and configure Google Ads connection in Catalog Explorer	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-ads-connection
Use Google Ads connector schema and type reference	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-ads-reference
Configure Google Analytics Raw Data connections	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-analytics-connection
Consult GA4 raw data connector configuration reference	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-analytics-reference
Create Google Drive connections in Databricks Catalog	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-drive-connection
Configure Databricks Google Drive connector parameters	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-drive-reference
Configure OAuth 2.0 for Google Drive ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/google-drive-source-setup
Create HubSpot connections in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/hubspot-connection
Create Jira connections in Databricks Catalog Explorer	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/jira-connection
Use Jira Lakeflow connector reference settings	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/jira-reference
Configure Meta Ads connections in Catalog Explorer	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/meta-ads-connection
Reference configuration for Databricks Meta Ads connector	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/meta-ads-reference
Create and configure Monday.com connections in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/monday-com-connection
Set up Monday.com ingestion pipelines in Lakeflow Connect	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/monday-com-pipeline
Reference Monday.com connector tables and schemas	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/monday-com-reference
Configure multi-destination Lakeflow ingestion pipelines	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/multi-destination-pipeline
Configure Amazon RDS and Aurora MySQL for Databricks ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/mysql-aws-rds-config
Configure Azure Database for MySQL for Databricks ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/mysql-azure-config
Create and manage MySQL connections in Databricks Catalog	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/mysql-connection
Configure MySQL on Amazon EC2 for Databricks ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/mysql-ec2-config
Configure GCP Cloud SQL for MySQL for Databricks ingestion	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
Create NetSuite connections for Lakeflow Connect	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/netsuite-connection
Consult NetSuite connector reference for tables and types	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
Create Outlook OAuth connections in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/outlook-connection
Use Outlook connector reference for schema and options	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/outlook-reference
Configure OAuth M2M for Outlook ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/outlook-source-setup
Create and manage Pendo connections in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/pendo-connection
Pendo connector table schemas and supported objects	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/pendo-reference
Configure Pendo source for Databricks authentication	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/pendo-source-setup
Apply and use tags on Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/pipeline-tags
Plan PostgreSQL ingestion workflow for Lakeflow Connect	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/postgresql
Create and manage PostgreSQL connections in Catalog Explorer	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/postgresql-connection
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
Create and configure RabbitMQ connection in Catalog	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/rabbitmq-connection
Configure managed RabbitMQ ingestion pipeline	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/rabbitmq-pipeline
RabbitMQ connector configuration reference	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/rabbitmq-reference
Configure Unity Catalog connection to RabbitMQ	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/rabbitmq-source-setup
Create Salesforce connections for Lakeflow Connect	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/salesforce-connection
Use Salesforce connector reference for objects and types	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/salesforce-reference
Configure SCD type 1 and 2 in Lakeflow	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/scd
Create ServiceNow connections in Catalog Explorer	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/servicenow-connection
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
Configure SharePoint connections for Lakeflow Connect ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sharepoint-connection
Configure managed SharePoint ingestion pipelines	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sharepoint-pipeline
Reference settings for the Lakeflow SharePoint connector	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sharepoint-reference
Configure OAuth M2M authentication for SharePoint	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sharepoint-source-setup-m2m
Configure custom-managed OAuth U2M for SharePoint	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sharepoint-source-setup-u2m
Configure Databricks-managed OAuth U2M for SharePoint	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sharepoint-source-setup-u2m-databricks-managed
Create and configure Slack logs connection in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/slack-access-integration-logs-connection
Create Smartsheet connections for Lakeflow Connect	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/smartsheet-connection
Use Smartsheet connector reference and configuration parameters	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/smartsheet-reference
Configure OAuth 2.0 for Smartsheet ingestion	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/smartsheet-source-setup
Track source-to-destination lineage in Lakeflow	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/source-lineage
Create SQL Server connections in Databricks Catalog	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sql-server-connection
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
Configure SQL Server utility objects script parameters	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sql-server-utility-reference
Configure destination table naming in Lakeflow	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/table-rename
Create TikTok Ads connections in Catalog Explorer	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/tiktok-ads-connection
Reference TikTok Ads connector tables and metrics	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/tiktok-ads-reference
Create Workday HCM connections in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/workday-hcm-connection
Reference for Workday HCM connector options	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/workday-hcm-reference
Create Workday Reports connections in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/workday-reports-connection
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
Create Zendesk Support connections in Catalog Explorer	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/zendesk-support-connection
Use Zendesk Support connector technical reference in Lakeflow	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/zendesk-support-reference
Create and configure Zoho Books connections in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/zoho-books-connection
Reference schemas for Zoho Books connector tables	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/zoho-books-reference
Create and manage Zoom Logs connections in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/zoom-logs-connection
Use Zoom Logs connector reference tables and schemas	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/zoom-logs-reference
Configure Zoom OAuth authentication for Databricks connector	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/zoom-logs-source-setup
Access cloud object metadata via _object_metadata	https://learn.microsoft.com/en-us/azure/databricks/ingestion/object-metadata-column
Configure OpenTelemetry clients for Unity Catalog	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
Configure cluster-scoped init scripts in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/init-scripts/cluster-scoped
Set and use environment variables in Databricks init scripts	https://learn.microsoft.com/en-us/azure/databricks/init-scripts/environment-variables
Configure and manage global init scripts in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/init-scripts/global
Configure Databricks JDBC Driver connections	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc-oss/configure
Use Databricks JDBC Driver connection properties	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc-oss/properties
Configure advanced capabilities for Simba JDBC Driver	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc/capability
Set compute options for Simba Databricks JDBC Driver	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc/compute
Configure connections with Simba Databricks JDBC Driver	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc/configure
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 SQL alert tasks in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/alert
Run backfills for scheduled Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/backfill-jobs
Run Clean Room notebook tasks in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/clean-room-notebook
Configure compute options for Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/compute
Configure and edit Lakeflow Jobs in the UI	https://learn.microsoft.com/en-us/azure/databricks/jobs/configure-job
Configure and edit tasks in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/configure-task
Configure control flow for Lakeflow Job tasks	https://learn.microsoft.com/en-us/azure/databricks/jobs/control-flow
Configure dashboard refresh tasks in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/dashboard
Run dbt Core projects with Lakeflow Job tasks	https://learn.microsoft.com/en-us/azure/databricks/jobs/dbt
Orchestrate dbt platform jobs from Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/dbt-platform
Use disabled tasks and understand their effects in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/disabled-tasks
Use dynamic value references in Databricks Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/dynamic-value-references
Trigger Lakeflow Jobs on new file arrivals	https://learn.microsoft.com/en-us/azure/databricks/jobs/file-arrival-triggers
Use For each tasks to loop in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/for-each
Configure Git-backed tasks for Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/git
Add If/else branching logic to Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/if-else
Configure JAR tasks for Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/jar
Configure job parameters for Azure Databricks Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/job-parameters
Monitor and observe Lakeflow Jobs in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/jobs/monitor
Configure notebook tasks in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/notebook
Configure pipeline tasks in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/pipeline
Configure Power BI tasks in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/powerbi
Configure Python script tasks in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/python-script
Configure Python wheel tasks in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/python-wheel
Configure Run if task dependencies in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/run-if
Configure Run Job tasks and nesting limits in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/run-job
Run Lakeflow Jobs on time-based schedules	https://learn.microsoft.com/en-us/azure/databricks/jobs/scheduled
Configure legacy Spark Submit tasks in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/spark-submit-legacy
Configure SQL tasks for Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/sql
Configure task-level 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 datasets for Foundation Model Fine-tuning	https://learn.microsoft.com/en-us/azure/databricks/large-language-models/foundation-model-training/data-preparation
Configure Foundation Model Fine-tuning runs in UI	https://learn.microsoft.com/en-us/azure/databricks/large-language-models/foundation-model-training/ui
Define and manage flows in Lakeflow Spark SDP	https://learn.microsoft.com/en-us/azure/databricks/ldp/concepts/flows
Configure pipelines in Lakeflow Spark SDP	https://learn.microsoft.com/en-us/azure/databricks/ldp/concepts/pipelines
Configure classic Lakeflow pipeline compute settings	https://learn.microsoft.com/en-us/azure/databricks/ldp/configure-compute
Configure Databricks pipeline settings in the workspace UI	https://learn.microsoft.com/en-us/azure/databricks/ldp/configure-pipeline
Work with standalone Lakeflow pipelines in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/ldp/dbsql/dbsql-for-ldp
Configure standalone materialized views in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/ldp/dbsql/materialized-configure
Schedule refreshes for standalone tables in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/ldp/dbsql/schedule-refreshes
Configure environment versions for Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/environment-versions
Expose pipeline datasets to external Delta and Iceberg clients	https://learn.microsoft.com/en-us/azure/databricks/ldp/external-access
Configure Hive metastore publishing for pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/hive-metastore
Enable default publishing mode for pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/migrate-to-dpm
Lakeflow pipeline event log schema reference	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
Monitor Lakeflow pipelines in the Databricks UI	https://learn.microsoft.com/en-us/azure/databricks/ldp/monitoring-ui
Reassign tables between Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/move-table
Configure and use parameters in Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/parameters
Reference for Lakeflow pipeline properties and settings	https://learn.microsoft.com/en-us/azure/databricks/ldp/properties
Configure serverless Databricks pipelines and performance modes	https://learn.microsoft.com/en-us/azure/databricks/ldp/serverless
Set default catalog and schema for Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/target-schema
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
Configure AI Runtime CLI for Databricks training	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/cli/
Use AI Runtime CLI command options and flags	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/cli/command-reference
Reference YAML configuration for AI Runtime CLI workloads	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/cli/yaml-config
Configure Python environments for Databricks AI Runtime	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/environment
Configure AutoML data preparation for classification in Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/classification-data-prep
Configure AutoML data preparation for forecasting in Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/forecasting-data-prep
Configure AutoML data preparation for regression in Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/regression-data-prep
Configure materialization of declarative features	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/materialized-features
Create and manage Unity Catalog feature tables	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/uc/feature-tables-uc
Create and manage Workspace Feature Store tables	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/workspace-feature-store/feature-tables
Manage MLflow model lifecycle in Unity Catalog	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
Configure legacy Workspace Model Registry lifecycle	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/manage-model-lifecycle/workspace-model-registry
Configure Databricks load tests for custom model endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/configure-load-test
Create and configure Databricks custom model endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/create-manage-serving-endpoints
Persist Databricks custom model telemetry to Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/custom-model-serving-uc-logs
Configure custom model logging and serving on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/custom-models
Configure and manage Azure Databricks model serving endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/manage-serving-endpoints
Export Databricks serving endpoint metrics to Prometheus and Datadog	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
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 splits on Databricks endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/serve-multiple-models-to-serving-endpoint
Configure environment variables for model serving resources	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/store-env-variable-model-serving
Configure and connect Ray clusters on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ray/ray-create
Register as a Databricks Marketplace provider and assign roles	https://learn.microsoft.com/en-us/azure/databricks/marketplace/become-provider
Create and configure Databricks Marketplace listings	https://learn.microsoft.com/en-us/azure/databricks/marketplace/create-listing
Edit and revoke Databricks listings	https://learn.microsoft.com/en-us/azure/databricks/marketplace/manage-listings
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
Configure and manage MLflow experiments on Databricks	https://learn.microsoft.com/en-us/azure/databricks/mlflow/experiments
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
Configure MLflow tracking for Databricks models	https://learn.microsoft.com/en-us/azure/databricks/mlflow/tracking
Configure MLflow tracking server storage locations	https://learn.microsoft.com/en-us/azure/databricks/mlflow/tracking-server-configuration
Backfill historical MLflow traces with scorers	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/backfill-scorers
Reference schema for MLflow evaluation datasets	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/concepts/eval-datasets
Reference for defining MLflow code-based scorers	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/custom-scorer-reference
Manage lifecycle of MLflow production scorers	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/manage-production-scorers
Configure MLflow serverless budget policies for experiments	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/serverless-budget-policy
Configure dev environments to connect to MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/getting-started/connect-environment
Define and manage MLflow labeling schemas	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/human-feedback/concepts/labeling-schemas
Create and run MLflow labeling sessions	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/human-feedback/concepts/labeling-sessions
Label existing MLflow traces with expert feedback	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/human-feedback/expert-feedback/label-existing-traces
Test GenAI apps with MLflow Review App Chat UI	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/human-feedback/expert-feedback/live-app-testing
Use MLflow Prompt Registry prompts in deployments	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/prompt-version-mgmt/prompt-registry/use-prompts-in-deployed-apps
Configure MLflow Tracing for GenAI observability	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/
Migrate MLflow experiment traces to Unity Catalog tables	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/migrate-traces-to-uc
Migrate Unity Catalog traces from schema-linked to table-prefix format	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/migrate-uc-trace-table-prefix
View and configure Databricks MLflow trace UI	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/observe-with-traces/ui-traces
Configure Unity Catalog storage for OpenTelemetry traces	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/trace-unity-catalog
Migrate from legacy ${param} widgets in Databricks	https://learn.microsoft.com/en-us/azure/databricks/notebooks/legacy-widgets
Configure and use Databricks notebook widgets	https://learn.microsoft.com/en-us/azure/databricks/notebooks/widgets
Understand Lakebase PostgreSQL compatibility details	https://learn.microsoft.com/en-us/azure/databricks/oltp/instances/query/postgres-compatibility
Configure Lakebase Postgres connection string formats	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/connection-strings
Define a production Lakebase project bundle configuration	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/dabs-typical-project
Configure and install Postgres extensions in Lakebase	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/extensions
Enable and configure Lakebase Search extensions	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/lakebase-search
Configure lakebase_text BM25 full-text search	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/lakebase-text
Configure lakebase_vector ANN search in Lakebase	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/lakebase-vector
Configure Lakebase with Declarative Automation Bundles	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/manage-with-bundles
Backup and restore Lakebase using pg_dump and pg_restore	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/pg-dump-restore
Provision a production Lakebase project with Terraform	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/terraform-typical-project
Convert Databricks Asset Bundles to Autoscaling	https://learn.microsoft.com/en-us/azure/databricks/oltp/update-to-autoscaling-dabs
Migrate Terraform configs to Lakehouse Autoscaling	https://learn.microsoft.com/en-us/azure/databricks/oltp/update-to-autoscaling-terraform
Configure full-text search indexes on Unity Catalog tables	https://learn.microsoft.com/en-us/azure/databricks/optimizations/full-text-search-indexes
Enable BI compatibility mode for Unity Catalog 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 input options for DataFrameReader sources	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/option
Set multiple input options with DataFrameReader.options	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/options
Define input schemas for DataFrameReader in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/schema
Bucket DataFrame output files with DataFrameWriter.bucketBy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/bucketby
Cluster DataFrame output to optimize queries in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/clusterby
Configure DataFrameWriter save modes for existing data	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/mode
Configure output options for DataFrameWriter	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/option
Set multiple output options with DataFrameWriter.options	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/options
Partition DataFrame output files with DataFrameWriter.partitionBy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/partitionby
Sort bucketed output files with DataFrameWriter.sortBy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/sortby
Create new tables from DataFrames with DataFrameWriterV2.create	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/create
Create or replace tables with DataFrameWriterV2.createOrReplace	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/createorreplace
Overwrite matching rows with DataFrameWriterV2.overwrite	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/overwrite
Overwrite table partitions with DataFrameWriterV2.overwritePartitions	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/overwritepartitions
Replace existing tables with DataFrameWriterV2.replace	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/replace
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 in Databricks	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 configs are modifiable with RuntimeConfig.isModifiable	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/runtimeconfig/ismodifiable
Set Spark runtime configuration properties 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 Databricks runtime configuration	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/conf
Manage separate Spark sessions sharing SparkContext	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/newsession
Profile SparkSession performance and memory usage	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/profile
Access underlying SparkContext from SparkSession	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/sparkcontext
Stop SparkSession and underlying SparkContext cleanly	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/stop
Manage active streaming queries with StreamingQueryManager	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/streams
Check Spark runtime version from SparkSession	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/version-session
Control and inspect PySpark StreamingQuery lifecycle	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery
Use persistent StreamingQuery IDs across restarts	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/id
Check active status of a PySpark StreamingQuery	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/isactive
Access last progress update for StreamingQuery	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/lastprogress
Name and identify StreamingQuery instances uniquely	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/name
Process all available streaming data for testing	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/processallavailable
Inspect recent progress history for StreamingQuery	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/recentprogress
Use runId to distinguish StreamingQuery runs	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/runid
Get current status of a PySpark StreamingQuery	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/status
Stop a running PySpark StreamingQuery safely	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/stop
Listen to PySpark StreamingQuery lifecycle events	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquerylistener
Configure kll_merge_agg_bigint accuracy parameter k	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_merge_agg_bigint
Tune kll_merge_agg_double sketch size and accuracy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_merge_agg_double
Adjust kll_merge_agg_float sketch configuration	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_merge_agg_float
Configure kll_sketch_agg_bigint with k parameter	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_agg_bigint
Configure kll_sketch_agg_double accuracy parameter	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_agg_double
Set kll_sketch_agg_float sketch size and k	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_agg_float
Configure make_timestamp behavior with ANSI and timestampType	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/make_timestamp
Control make_timestamp_ltz behavior with ANSI settings	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/make_timestamp_ltz
Configure make_timestamp_ntz invalid-input handling in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/make_timestamp_ntz
Configure map_concat duplicate-key behavior with mapKeyDedupPolicy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/map_concat
Configure to_binary formats in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/to_binary
Format numeric values with to_char in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/to_char
Configure numeric formats with to_number in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/to_number
Format values as strings with to_varchar in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/to_varchar
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
Sync table and column comments for foreign tables	https://learn.microsoft.com/en-us/azure/databricks/query-federation/foreign-table-comments
Configure external Hive metastore federation with Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/query-federation/hms-federation-external
Configure Hive metastore federation for legacy Databricks workspaces	https://learn.microsoft.com/en-us/azure/databricks/query-federation/hms-federation-internal
Reference serverless environment versions for Databricks	https://learn.microsoft.com/en-us/azure/databricks/release-notes/serverless/environment-version/
Review Azure Databricks serverless GPU v5 environment details	https://learn.microsoft.com/en-us/azure/databricks/release-notes/serverless/environment-version/five-gpu
Reference serverless environment version 4 system configuration	https://learn.microsoft.com/en-us/azure/databricks/release-notes/serverless/environment-version/four
Review environment details for Databricks serverless GPU v4	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
Reference Serverless GPU environment version 3 configuration	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/
Configure Azure Databricks to use on-premises Git servers	https://learn.microsoft.com/en-us/azure/databricks/repos/connect-on-prem-git-server
Configure Databricks Git folders via CLI and REST API	https://learn.microsoft.com/en-us/azure/databricks/repos/enable-disable-repos-with-api
Configure Git provider access tokens for Azure Databricks	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 Git integration for Databricks Git folders	https://learn.microsoft.com/en-us/azure/databricks/repos/repos-setup
Configure Databricks Serverless Private Git with Private Link	https://learn.microsoft.com/en-us/azure/databricks/repos/serverless-private-git
Verify supported browsers for Azure Databricks UI access	https://learn.microsoft.com/en-us/azure/databricks/resources/supported-browsers
Configure just-in-time user provisioning in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/security/auth/jit
Update Azure Databricks workspace VNet configuration	https://learn.microsoft.com/en-us/azure/databricks/security/network/classic/update-workspaces
Configure Azure Databricks inbound Private Link connectivity	https://learn.microsoft.com/en-us/azure/databricks/security/network/front-end/front-end-private-connect
Configure inbound Private Link for Databricks services	https://learn.microsoft.com/en-us/azure/databricks/security/network/front-end/service-direct-privatelink
Configure networking for Azure Databricks serverless compute	https://learn.microsoft.com/en-us/azure/databricks/security/network/serverless-network-security/
Configure network policies for Databricks serverless egress	https://learn.microsoft.com/en-us/azure/databricks/security/network/serverless-network-security/manage-network-policies
Manage Databricks serverless private endpoint rules	https://learn.microsoft.com/en-us/azure/databricks/security/network/serverless-network-security/manage-private-endpoint-rules
Configure Private Link from serverless to VNet resources	https://learn.microsoft.com/en-us/azure/databricks/security/network/serverless-network-security/pl-to-internal-network
Configure serverless Private Link to Azure services	https://learn.microsoft.com/en-us/azure/databricks/security/network/serverless-network-security/serverless-private-link
Use ARM template to enable Databricks workspace storage firewall	https://learn.microsoft.com/en-us/azure/databricks/security/network/storage/firewall-support-arm-template
Use Databricks secrets in Spark configs and env vars	https://learn.microsoft.com/en-us/azure/databricks/security/secrets/secrets-spark-conf-env-var
Query VARIANT semi-structured data in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/semi-structured/variant
Configure Spark properties correctly on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/spark/conf
Configure and connect to Databricks-hosted RStudio Server	https://learn.microsoft.com/en-us/azure/databricks/sparkr/hosted-rstudio-server
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
Clone Delta and Iceberg tables with Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/delta-clone
Create and migrate from Databricks Bloom filter indexes	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/delta-create-bloomfilter-index
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
Query INFORMATION_SCHEMA.COLUMNS in Azure 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
Query CONSTRAINT_TABLE_USAGE in Databricks SQL	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
Query INFORMATION_SCHEMA.METASTORES in Azure Databricks	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
Use INFORMATION_SCHEMA.PROVIDERS in Azure Databricks	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
Configure default collation in Databricks SQL sessions	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/parameters/collation
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
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 limitations for Databricks SQL objects	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-names
Configure Databricks SQL behavior with parameters	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-parameters
Use reserved words and schemas in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-reserved-words
Configure Databricks SQL CACHE TABLE storage behavior	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-cache-cache-table
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
Configure session default collation in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-conf-mgmt-set-collation
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
Use SHOW TABLES DROPPED and recovery period in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-tables-dropped
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 SYNC to upgrade tables to Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-sync
Configure ALTER CATALOG options in Databricks SQL	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
Configure ALTER CONNECTION for Databricks foreign connections	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
Configure ALTER GOVERNED TAG in Databricks Unity Catalog	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 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 with ALTER SCHEMA in Databricks	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
Manage data shares with ALTER SHARE in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-share
Modify streaming tables with ALTER STREAMING TABLE	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-streaming-table
Alter Databricks tables with ALTER TABLE	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-table
Add constraints to Delta tables with 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 DROP CONSTRAINT in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-alter-table-drop-constraint
Manage Delta table columns with ALTER TABLE COLUMN	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
Change view definitions with ALTER VIEW in Databricks	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 in Databricks	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 SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-comment
Create Unity Catalog catalogs with CREATE CATALOG	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-catalog
Create foreign connections with CREATE CONNECTION	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-connection
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 external UDFs with CREATE FUNCTION in Databricks Runtime	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-function
Create account-level governed tags with CREATE GOVERNED TAG	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-governed-tag
Define Databricks SQL external locations via DDL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-location
Configure Databricks SQL materialized views	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-materialized-view
Set refresh policies for Databricks materialized views	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-materialized-view-refresh-policy
Create Unity Catalog stored procedures in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-procedure
Create schemas (databases) in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-schema
Use CREATE SERVER alias for connections	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-server
Create Delta Sharing shares in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-share
Define SQL and Python functions with CREATE FUNCTION	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-sql-function
Create streaming tables for Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-streaming-table
Configure FLOW AUTO CDC for streaming tables	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-streaming-table-auto-cdc
All CREATE TABLE variants in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-table
Define table constraints in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-table-constraint
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
Create managed, external, and temp tables in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-table-using
Create SQL and metric views in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-view
Create Unity Catalog volumes in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-volume
Declare and use session variables in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-declare-variable
Drop catalogs in Databricks Unity Catalog	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 databases (schemas) in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-database
Drop temporary and permanent UDFs in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-function
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 (databases) in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-schema
Drop shares in Databricks Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-share
Drop Databricks tables and underlying data	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
Drop views from the Databricks catalog	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-view
Drop Unity Catalog volumes and manage retention	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-volume
Repair Databricks table partitions and metadata	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-repair-table
Set Databricks table properties and storage options	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
Configure INSERT OVERWRITE DIRECTORY in Databricks SQL	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
Declare and manage session variables in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-variables
Create and customize Databricks SQL alerts	https://learn.microsoft.com/en-us/azure/databricks/sql/user/alerts/create
Manage, share, and govern Databricks SQL alerts	https://learn.microsoft.com/en-us/azure/databricks/sql/user/alerts/manage
Configure query result caching in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/user/queries/query-caching
Configure and use named parameter markers in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/user/queries/query-parameters
Create and manage Databricks SQL query snippets	https://learn.microsoft.com/en-us/azure/databricks/sql/user/queries/query-snippets
Configure scheduled queries in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/user/queries/schedule-query
Use keyboard shortcuts in the Databricks SQL editor	https://learn.microsoft.com/en-us/azure/databricks/sql/user/sql-editor/keyboard-shortcuts
Configure parameter widgets in Databricks SQL editor	https://learn.microsoft.com/en-us/azure/databricks/sql/user/sql-editor/parameter-widgets
Manage schema evolution in Databricks state store	https://learn.microsoft.com/en-us/azure/databricks/stateful-applications/schema-evolution
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
Set up real-time mode for Structured Streaming	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 on-demand state repartitioning for streaming	https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/state-repartitioning
Configure Structured Streaming trigger intervals in Databricks	https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/triggers
Define and manage table constraints on Databricks	https://learn.microsoft.com/en-us/azure/databricks/tables/constraints
Configure Unity Catalog commits for Delta tables	https://learn.microsoft.com/en-us/azure/databricks/tables/features/catalog-commits
Enable and use Delta Lake Checkpoint V2 on Databricks	https://learn.microsoft.com/en-us/azure/databricks/tables/features/checkpoint-v2
Manage Delta Lake columns with column mapping	https://learn.microsoft.com/en-us/azure/databricks/tables/features/column-mapping
Configure and use deletion vectors in Databricks	https://learn.microsoft.com/en-us/azure/databricks/tables/features/deletion-vectors
Drop Delta table features and downgrade protocols	https://learn.microsoft.com/en-us/azure/databricks/tables/features/drop-feature
Configure and use Delta Lake generated columns	https://learn.microsoft.com/en-us/azure/databricks/tables/features/generated-columns
Enable and manage row tracking in Databricks tables	https://learn.microsoft.com/en-us/azure/databricks/tables/features/row-tracking
Use type widening for Delta Lake schema changes	https://learn.microsoft.com/en-us/azure/databricks/tables/features/type-widening
Enable and work with VARIANT data type on Databricks	https://learn.microsoft.com/en-us/azure/databricks/tables/features/variant
Use table history and time travel on Databricks	https://learn.microsoft.com/en-us/azure/databricks/tables/history
Configure auto time-to-live for Unity Catalog managed tables	https://learn.microsoft.com/en-us/azure/databricks/tables/operations/auto-ttl
Configure schema enforcement for Databricks tables	https://learn.microsoft.com/en-us/azure/databricks/tables/schema-enforcement
Reference for Delta and Iceberg table properties on Databricks	https://learn.microsoft.com/en-us/azure/databricks/tables/table-properties
Update and evolve table schemas on Databricks	https://learn.microsoft.com/en-us/azure/databricks/tables/update-schema
Configure and use multi-statement transactions on Databricks	https://learn.microsoft.com/en-us/azure/databricks/transactions/
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
Configure map visualizations in Databricks	https://learn.microsoft.com/en-us/azure/databricks/visualizations/maps
Configure table visualization options in Azure Databricks	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

Command Palette

MicrosoftDocs/azure-databricks — configuration.md

Azure Databricks — Configuration

Configuration