Azure Databricks — Integrations & Coding Patterns

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Integrations & Coding Patterns

Topic	URL
Query LLMs and agents via Databricks UIs, SQL, and APIs	https://learn.microsoft.com/en-us/azure/databricks/agents/query-llms
Manage Databricks AI/BI assets via REST APIs	https://learn.microsoft.com/en-us/azure/databricks/ai-bi/admin/use-apis
Integrate coding agents with Unity AI Gateway	https://learn.microsoft.com/en-us/azure/databricks/ai-gateway/coding-agent-integration-beta
Query Unity AI Gateway endpoints via supported APIs	https://learn.microsoft.com/en-us/azure/databricks/ai-gateway/query-endpoints-beta
Use custom Python embedding models with Databricks AI Search	https://learn.microsoft.com/en-us/azure/databricks/ai-search/custom-embedding-model
Register and serve OSS embedding models for AI Search	https://learn.microsoft.com/en-us/azure/databricks/ai-search/embedding-with-oss-models
Use Databricks AI Search Python SDK example notebooks	https://learn.microsoft.com/en-us/azure/databricks/ai-search/example-notebooks
Query Databricks AI Search indexes via SDK, REST, and SQL	https://learn.microsoft.com/en-us/azure/databricks/ai-search/query-ai-search
Integrate Databricks AI Search with OpenAI embeddings	https://learn.microsoft.com/en-us/azure/databricks/ai-search/vector-search-external-embedding-model-example
Use GTE foundation embeddings with Databricks AI Search	https://learn.microsoft.com/en-us/azure/databricks/ai-search/vector-search-foundation-embedding-model-gte-example
Implement Databricks AI Search with the Python SDK	https://learn.microsoft.com/en-us/azure/databricks/ai-search/vector-search-python-sdk-example
Set up legacy ABS-AQS streaming connector for Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/azure/aqs
Read and write data between Databricks and Azure Cosmos DB	https://learn.microsoft.com/en-us/azure/databricks/archive/azure/cosmosdb
Stream data from Databricks to Azure Synapse with Structured Streaming	https://learn.microsoft.com/en-us/azure/databricks/archive/azure/stream-synapse
Configure legacy PolyBase integration between Databricks and Synapse	https://learn.microsoft.com/en-us/azure/databricks/archive/azure/synapse-polybase
Use Azure Databricks connector for Amazon Redshift	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/amazon-redshift
Use Databricks connector for Amazon S3 Select	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/amazon-s3-select
Connect Azure Databricks to Google BigQuery	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/bigquery
Connect Cassandra to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/cassandra
Integrate Couchbase with Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/couchbase
Use Databricks JDBC connector between workspaces	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/databricks
Read and write data to Elasticsearch from Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/elasticsearch
Configure JDBC connections from Azure Databricks to external databases	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/jdbc
Query MariaDB from Azure Databricks using JDBC	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/mariadb
Read and write data to MongoDB Atlas from Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/mongodb
Query MySQL from Azure Databricks using JDBC	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/mysql
Connect Azure Databricks to Neo4j using neo4j-spark-connector	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/neo4j
Query PostgreSQL from Azure Databricks using JDBC	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/postgresql
Integrate Azure Databricks with Snowflake connector	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/snowflake
Use spark-xml library with Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/spark-xml-library
Use the Apache Spark connector for Azure SQL Database and SQL Server in Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/sql-databases-azure
Connect Azure Databricks to SQL Server using JDBC	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/sql-server
Enable SQL Server CDC for Databricks ingestion	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/sql-server-cdc
Enable SQL Server change tracking for Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/sql-server-ct
Set up SQL Server DDL capture for Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/sql-server-ddl-legacy
Use Azure Databricks connector to query Azure Synapse	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/synapse-analytics
Connect Azure Databricks to Azure Synapse dedicated SQL pool	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/synapse-analytics-dedicated-pool
Use legacy Databricks clusters CLI commands	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/cli/clusters-cli
Run and manage Databricks jobs with legacy CLI	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/cli/jobs-cli
Work with Databricks repos via the legacy CLI	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/cli/repos-cli
Manage Databricks job runs with the legacy CLI	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/cli/runs-cli
Manage Databricks workspace objects with legacy CLI	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/cli/workspace-cli
Develop with dbx by Databricks Labs on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/dbx/dbx
Sync local files to Databricks workspaces using dbx	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/dbx/dbx-sync
Develop Databricks code with dbx in Visual Studio Code	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/dbx/ide-how-to
Configure Git folders with the Databricks VS Code extension	https://learn.microsoft.com/en-us/azure/databricks/archive/dev-tools/vscode-repos
Connect Azure Databricks to Excel via ODBC driver	https://learn.microsoft.com/en-us/azure/databricks/archive/integrations/excel
Read Databricks Unity Catalog tables from Iceberg clients	https://learn.microsoft.com/en-us/azure/databricks/archive/legacy/external-access-iceberg
Import external Hive tables stored in cloud storage into Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/legacy/hive-tables
Use Koalas (pandas API on Spark) in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/legacy/koalas
Use ai_generate_text in Databricks SQL for reviews	https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/ai-generate-text-example
Enable Databricks inference tables via REST API	https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/enable-model-serving-inference-tables
Convert Spark Parquet data to Petastorm datasets	https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/petastorm
Run distributed training with Horovod on Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/train-model/horovod
Launch HorovodRunner distributed jobs on Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/train-model/horovod-runner
HorovodRunner CNN training examples on Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/train-model/horovod-runner-examples
Use horovod.spark for distributed deep learning	https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/train-model/horovod-spark
Run Hugging Face NLP inference on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/train-model/model-inference-nlp
Use spark-tensorflow-distributor for distributed TensorFlow	https://learn.microsoft.com/en-us/azure/databricks/archive/machine-learning/train-model/spark-tf-distributor
Track ML runs with MLflow in Java and Scala	https://learn.microsoft.com/en-us/azure/databricks/archive/mlflow/quick-start-java-scala
Track ML experiments with MLflow in R on Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/mlflow/quick-start-r
Export and import ML models with MLeap on Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/model-export/mleap-model-export
Track PySpark training and save models as MLeap	https://learn.microsoft.com/en-us/azure/databricks/archive/model-export/tracking-ex-pyspark
Connect SQL Workbench/J to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/partners/workbenchj
Access Amazon S3 from Azure Databricks using DBFS and APIs	https://learn.microsoft.com/en-us/azure/databricks/archive/storage/amazon-s3
Implement advanced Azure Databricks metric view logic	https://learn.microsoft.com/en-us/azure/databricks/business-semantics/metric-views/advanced-techniques
Define and edit Unity Catalog metric views using UI and SQL	https://learn.microsoft.com/en-us/azure/databricks/business-semantics/metric-views/create-edit
Use LOD expressions in Databricks metric views	https://learn.microsoft.com/en-us/azure/databricks/business-semantics/metric-views/level-of-detail
Run custom JAR workloads in Databricks clean rooms	https://learn.microsoft.com/en-us/azure/databricks/clean-rooms/clean-room-jar-task
Create and consume output tables in Databricks Clean Rooms	https://learn.microsoft.com/en-us/azure/databricks/clean-rooms/output-tables
Set up JDBC Unity Catalog connections in Databricks	https://learn.microsoft.com/en-us/azure/databricks/connect/jdbc-connection
Use Spark Data Source API with external systems	https://learn.microsoft.com/en-us/azure/databricks/connect/spark-data-sources
Connect Azure Databricks Structured Streaming to Kafka	https://learn.microsoft.com/en-us/azure/databricks/connect/streaming/kafka/
Subscribe to Google Pub/Sub with Databricks	https://learn.microsoft.com/en-us/azure/databricks/connect/streaming/pub-sub
Stream data from Apache Pulsar into Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/connect/streaming/pulsar
Use Unity Catalog service credentials to call cloud APIs	https://learn.microsoft.com/en-us/azure/databricks/connect/unity-catalog/cloud-services/use-service-credentials
Connect Unity Catalog to ADLS Gen2 external locations	https://learn.microsoft.com/en-us/azure/databricks/connect/unity-catalog/cloud-storage/external-locations-adls
Create OneLake external locations with Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/connect/unity-catalog/cloud-storage/external-locations-onelake
Connect Unity Catalog to AWS S3 external locations	https://learn.microsoft.com/en-us/azure/databricks/connect/unity-catalog/cloud-storage/s3/s3-external-location-manual
Embed Azure Databricks AI/BI dashboards in apps	https://learn.microsoft.com/en-us/azure/databricks/dashboards/share/embedding/
Use Databricks dashboard REST APIs for management	https://learn.microsoft.com/en-us/azure/databricks/dashboards/tutorials/dashboard-crud-api
Manage AI/BI dashboards via Workspace and Lakeview APIs	https://learn.microsoft.com/en-us/azure/databricks/dashboards/tutorials/workspace-dashboard-api
Create data profiles using Databricks quality_monitors API	https://learn.microsoft.com/en-us/azure/databricks/data-governance/unity-catalog/data-quality-monitoring/data-profiling/create-monitor-api
Read OpenSharing Databricks-to-Open data using bearer tokens	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/read-data-open
Integrate SAP Business Data Cloud with Azure Databricks via OpenSharing	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/sap-bdc/
Create and manage SAP BDC connections for OpenSharing	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/sap-bdc/create-connection
Grant SAP BDC recipients access to Databricks OpenSharing shares	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/sap-bdc/share-to-sap
Use Iceberg REST clients with OpenSharing OIDC federation	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/sharing-over-oidc-iceberg
Access OpenSharing data via M2M OIDC Python clients	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/sharing-over-oidc-m2m
Use MERGE for Delta Lake upserts on Databricks	https://learn.microsoft.com/en-us/azure/databricks/delta/merge
Expose Delta tables as Iceberg to external clients	https://learn.microsoft.com/en-us/azure/databricks/delta/uniform
Build a compound interest UDF operator in Lakeflow Designer	https://learn.microsoft.com/en-us/azure/databricks/designer/tutorial-compound-interest-udf
Create a Gmail email sender operator in Lakeflow Designer	https://learn.microsoft.com/en-us/azure/databricks/designer/tutorial-gmail-email-sender
Implement k-means clustering UDTF operator in Lakeflow Designer	https://learn.microsoft.com/en-us/azure/databricks/designer/tutorial-kmeans-clustering-udtf
Create a SQL UDF operator to send Slack messages	https://learn.microsoft.com/en-us/azure/databricks/designer/tutorial-send-slack-message-sql-udf
Create user-defined operators in Lakeflow Designer	https://learn.microsoft.com/en-us/azure/databricks/designer/user-operators
Use Databricks CLI command groups and options	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/commands
Run Databricks CLI from Azure Cloud Shell	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/databricks-cli-from-azure-cloud-shell
Download Databricks billable usage logs with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-billable-usage-commands
Manage Databricks account resources with CLI account commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-commands
Use Databricks CLI account networks commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-networks-commands
Manage OAuth published apps via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-o-auth-published-apps-commands
Configure published app integrations with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-published-app-integration-commands
Call Databricks REST APIs using CLI api command	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/api-commands
Manage Databricks apps with CLI commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/apps-commands
Use Databricks CLI clean-rooms command group	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/clean-rooms-commands
Create and manage external data connections via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/connections-commands
Manage consumer fulfillments with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/consumer-fulfillments-commands
Manage consumer installations via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/consumer-installations-commands
Use Databricks CLI credentials commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/credentials-commands
Get current user via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/current-user-commands
Manage data classification with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/data-classification-commands
Manage data quality via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/data-quality-commands
Use deprecated data-sources CLI commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/data-sources-commands
Manage Databricks databases with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/database-commands
Assign tags to Unity Catalog entities via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/entity-tag-assignments-commands
Manage Databricks environments using CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/environments-commands
Configure external lineage via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/external-lineage-commands
Manage external locations in Unity Catalog CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/external-locations-commands
Register external metadata with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/external-metadata-commands
Manage feature store via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/feature-engineering-commands
Perform file operations with Databricks fs CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/fs-commands
Use Genie features with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/genie-commands
Configure Git credentials using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/git-credentials-commands
Manage global init scripts via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/global-init-scripts-commands
Manage instance pools with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/instance-pools-commands
Create and manage jobs via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/jobs-commands
Manage Knowledge Assistants with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/knowledge-assistants-commands
Work with Databricks Labs apps via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/labs-commands
Manage Lakeview dashboards using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/lakeview-commands
Use Lakeview embedded dashboards via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/lakeview-embedded-commands
Install and manage libraries with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/libraries-commands
Use Databricks CLI metastores command group	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/metastores-commands
Manage workspace model registry via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/model-registry-commands
Manage model versions in Unity Catalog CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/model-versions-commands
Configure notification destinations via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/notification-destinations-commands
Create and manage online tables via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/online-tables-commands
Manage Lakeflow pipelines via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/pipelines-commands
Use Databricks CLI policy-families commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/policy-families-commands
Manage marketplace exchange filters with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/provider-exchange-filters-commands
Manage Databricks marketplace exchanges via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/provider-exchanges-commands
Manage marketplace provider files using CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/provider-files-commands
Manage Databricks marketplace listings via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/provider-listings-commands
Handle marketplace personalization requests with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/provider-personalization-requests-commands
Manage provider analytics dashboards via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/provider-provider-analytics-dashboards-commands
Manage marketplace providers using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/provider-providers-commands
Manage OpenSharing providers with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/providers-commands
Use deprecated quality-monitor-v2 CLI commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/quality-monitor-v2-commands
Manage quality monitors with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/quality-monitors-commands
Manage Databricks SQL queries via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/queries-commands
Use deprecated queries-legacy CLI commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/queries-legacy-commands
Access query-history using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/query-history-commands
Use Databricks CLI recipient-activation commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/recipient-activation-commands
Configure recipient federation policies via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/recipient-federation-policies-commands
Use Databricks CLI recipients commands for Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/recipients-commands
Manage Unity Catalog registered models via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/registered-models-commands
Manage Databricks repos (Git folders) via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/repos-commands
Manage Unity Catalog resource quotas via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/resource-quotas-commands
Handle Unity Catalog access requests with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/rfa-commands
Use Databricks CLI sandbox command group	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/sandbox-commands
Manage Unity Catalog schemas via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/schemas-commands
Manage Databricks secrets and scopes via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/secrets-commands
Manage service principal secrets via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/service-principal-secrets-proxy-commands
Manage Databricks service principals via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/service-principals-commands
Use service-principals-v2 identities with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/service-principals-v2-commands
Manage model serving endpoints via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/serving-endpoints-commands
Configure workspace settings using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/settings-commands
Manage Unity Catalog shares via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/shares-commands
Set up SSH connections with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/ssh-commands
Manage Unity Catalog storage credentials via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/storage-credentials-commands
Sync local files to Databricks workspace via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/sync-commands
Manage system schemas via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/system-schemas-commands
Manage table constraints using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/table-constraints-commands
Manage Unity Catalog tables via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/tables-commands
Manage governed tag policies via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/tag-policies-commands
Generate temporary path credentials via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/temporary-path-credentials-commands
Generate temporary table credentials via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/temporary-table-credentials-commands
Use Databricks CLI token-management admin commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/token-management-commands
Manage Databricks tokens with CLI commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/tokens-commands
Manage Databricks users via CLI commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/users-commands
Use Databricks CLI users-v2 management commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/users-v2-commands
Retrieve Databricks CLI version information	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/version-command
Manage Unity Catalog volumes via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/volumes-commands
Administer SQL warehouses using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/warehouses-commands
Configure Unity Catalog workspace bindings via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/workspace-bindings-commands
Manage Databricks workspace files with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/workspace-commands
Update Databricks workspace settings with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/workspace-conf-commands
Manage workspace entity tag assignments via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/workspace-entity-tag-assignments-commands
Use Databricks Connect within Databricks notebooks	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/notebooks
Use Databricks Utilities with Databricks Connect for Python	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/python/databricks-utilities
Use Databricks Connect for Python code patterns	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/python/examples
Install and configure Databricks Connect for Python	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/python/install
Develop a Databricks app locally using Databricks Connect	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/python/tutorial-apps
Run PyCharm code on classic Databricks compute	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/python/tutorial-cluster
Run Python code on serverless compute with Databricks Connect	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/python/tutorial-serverless
Use Databricks Utilities via Databricks Connect for Scala	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/scala/databricks-utilities
Use Databricks Connect for Scala code examples	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/scala/examples
Build and deploy Scala JARs to Databricks serverless	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/scala/jar-compile
Run Databricks SQL queries using the SQL CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-sql-cli
Use Databricks dbutils APIs in notebooks	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-utils
Configure JetBrains DataGrip to connect to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/datagrip
Configure DBeaver to work with Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/dbeaver
Run SQL from Go using Databricks SQL Driver	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/go-sql-driver
Run SQL from Node.js using the Databricks SQL Driver	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/nodejs-sql-driver
Use pyodbc to connect Python apps to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/pyodbc
Use the Databricks SQL Connector for Python	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/python-sql-connector
Use the English SDK to generate Spark code	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/sdk-english
Automate Azure Databricks with the Go SDK	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/sdk-go
Automate Azure Databricks with the Java SDK	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/sdk-java
Automate Azure Databricks with the Python SDK	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/sdk-python
Automate Azure Databricks with the R SDK	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/sdk-r
Use the SQL Statement Execution API to run queries	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/sql-execution-tutorial
Integrate SQLAlchemy with Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/sqlalchemy
Use the Databricks SQLTools driver in VS Code	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/sqltools-driver
Automate Unity Catalog deployment with Databricks Terraform	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/terraform/automate-uc
Provision Databricks clusters, notebooks, and jobs with Terraform	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/terraform/cluster-notebook-job
Manage Azure Databricks workspace resources using Terraform	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/terraform/workspace-management
Configure Iceberg REST catalog for Unity tables	https://learn.microsoft.com/en-us/azure/databricks/external-access/iceberg
Use Unity REST API from external Delta clients	https://learn.microsoft.com/en-us/azure/databricks/external-access/unity-rest
Unzip and read compressed files in Databricks	https://learn.microsoft.com/en-us/azure/databricks/files/unzip-files
Parse complex documents with Databricks Document Parsing	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-bricks/document-parsing
Use Azure Databricks Supervisor API for custom agents	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-bricks/supervisor-api
Customize MLflow 2 AI judges for agent evaluation	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-evaluation/advanced-agent-eval
Implement custom evaluation metrics in Databricks agents	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-evaluation/custom-metrics
Use built-in MLflow 2 AI judges and metrics	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-evaluation/llm-judge-reference
Configure AI agent tools and MCP integrations in Databricks	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/agent-tool
Use Unity Catalog tools with Anthropic SDK	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/anthropic-uc-integration
Author and deploy AI agents on Databricks Model Serving	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/author-agent-model-serving
Create Databricks AI agent tools with Unity Catalog functions	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/create-custom-tool
Connect Databricks agents to external APIs and apps	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/external-connection-tools
Integrate LangChain workflows with Databricks Unity Catalog tools	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/langchain-uc-integration
Integrate LlamaIndex workflows with Unity Catalog tools	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/llamaindex-uc-integration
Use Unity Catalog tools in OpenAI workflows	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/openai-uc-integration
Query Databricks agents via APIs and clients	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/query-agent
Integrate Databricks AI agents with Slack via HTTP connections	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/slack-agent
Connect Databricks agents to structured data sources	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/structured-retrieval-tools
Use Unity Catalog tools with third-party agent frameworks	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/unity-catalog-tool-integration
Connect Databricks agents to unstructured data sources	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/unstructured-retrieval-tools
Use Model Context Protocol on Databricks	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/mcp/
Connect external MCP clients to Databricks MCPs	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/mcp/connect-clients
Connect agents and notebooks to custom MCP servers	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/mcp/custom-mcp-usage
Connect Databricks agents to external MCP servers via proxy	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/mcp/external-mcp-usage
Connect Genie Code to GitHub via native or MCP integration	https://learn.microsoft.com/en-us/azure/databricks/genie-code/github-mcp
Integrate Genie Code Agent with MCP servers and connectors	https://learn.microsoft.com/en-us/azure/databricks/genie-code/mcp
Use Genie Code across Azure Databricks development surfaces	https://learn.microsoft.com/en-us/azure/databricks/genie-code/use-genie-code
Integrate Genie Spaces via Conversation and Management APIs	https://learn.microsoft.com/en-us/azure/databricks/genie/conversation-api
Load Unity Catalog tables using COPY INTO from ADLS	https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/copy-into/unity-catalog
Set up incremental ADLS ingestion with Auto Loader	https://learn.microsoft.com/en-us/azure/databricks/ingestion/cloud-object-storage/onboard-data
Convert Parquet and Iceberg tables to Delta Lake	https://learn.microsoft.com/en-us/azure/databricks/ingestion/data-migration/convert-to-delta
Ingest Google Drive files into Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/google-drive
Configure Lakeflow Connect Dynamics 365 connector	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/d365-reference
Build MySQL ingestion pipelines with Lakeflow Connect	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/mysql-pipeline
Build managed Pendo ingestion pipelines with Lakeflow Connect	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/pendo-pipeline
Ingest PostgreSQL data into Databricks with Lakeflow	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/postgresql-pipeline
Configure Lakeflow query-based connector parameters and errors	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/query-based-reference
Use Slack Access and Integration Logs connector in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/slack-access-integration-logs-reference
Create integrated CDC pipelines for SQL Server in Lakeflow	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sql-server-integrated-pipeline
Ingest SQL Server data into Databricks with Lakeflow	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/sql-server-pipeline
Configure TikTok Ads authentication for Lakeflow	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/tiktok-ads-source-setup
Configure Workday HCM authentication for Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/workday-hcm-setup
Configure Zendesk Support OAuth for Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/lakeflow-connect/zendesk-support-source-setup
Ingest OpenTelemetry data via Zerobus OTLP	https://learn.microsoft.com/en-us/azure/databricks/ingestion/opentelemetry/
Query OpenTelemetry traces, logs, and metrics in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/opentelemetry/queries
Ingest SFTP data with Lakeflow Auto Loader	https://learn.microsoft.com/en-us/azure/databricks/ingestion/sftp
Ingest SharePoint files into Delta tables	https://learn.microsoft.com/en-us/azure/databricks/ingestion/sharepoint
Ingest semi-structured data as VARIANT in Databricks	https://learn.microsoft.com/en-us/azure/databricks/ingestion/variant
Use Arrow Flight with Zerobus Ingest	https://learn.microsoft.com/en-us/azure/databricks/ingestion/zerobus-arrow-flight
Ingest data using Zerobus Ingest connector	https://learn.microsoft.com/en-us/azure/databricks/ingestion/zerobus-ingest
Configure OAuth SSO from Tableau Server to Databricks	https://learn.microsoft.com/en-us/azure/databricks/integrations/configure-oauth-tableau
Use Azure Databricks Excel Add-in for Lakehouse data	https://learn.microsoft.com/en-us/azure/databricks/integrations/excel
Import and query Databricks data from Excel	https://learn.microsoft.com/en-us/azure/databricks/integrations/excel-query
Configure and use Azure Databricks Excel Add-in	https://learn.microsoft.com/en-us/azure/databricks/integrations/excel-setup
Write Excel data back to Databricks Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/integrations/excel-write-back
Use Databricks Connector to access data from Google Sheets	https://learn.microsoft.com/en-us/azure/databricks/integrations/google-sheets/
Set up Databricks Connector for Google Sheets	https://learn.microsoft.com/en-us/azure/databricks/integrations/google-sheets/connect
Query Azure Databricks data from Google Sheets connector	https://learn.microsoft.com/en-us/azure/databricks/integrations/google-sheets/query-data
Use the open source Databricks JDBC driver	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc-oss/
Use Databricks JDBC metadata for metric views	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc-oss/metadata
Java API reference for the Databricks JDBC driver	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc-oss/reference
Manage Unity Catalog volume files via Databricks JDBC	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc-oss/volumes
Connect to Azure Databricks with Simba JDBC	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc/
Manage Unity Catalog volume files via JDBC Driver	https://learn.microsoft.com/en-us/azure/databricks/integrations/jdbc/volumes
Connect Lovable no-code apps to Databricks via OAuth	https://learn.microsoft.com/en-us/azure/databricks/integrations/lovable
Add Azure Databricks Genie MCP server to Foundry	https://learn.microsoft.com/en-us/azure/databricks/integrations/microsoft-foundry
Configure Genie plugin integration with Copilot Cowork	https://learn.microsoft.com/en-us/azure/databricks/integrations/msft-cowork
Configure Databricks Genie integration with Microsoft 365 Copilot	https://learn.microsoft.com/en-us/azure/databricks/integrations/msft-m365-copilot
Integrate Azure Databricks with Microsoft Power Platform	https://learn.microsoft.com/en-us/azure/databricks/integrations/msft-power-platform/
Integrate Azure Databricks data with Copilot Studio	https://learn.microsoft.com/en-us/azure/databricks/integrations/msft-power-platform/copilot-studio
Configure Azure Databricks connection in Power Platform	https://learn.microsoft.com/en-us/azure/databricks/integrations/msft-power-platform/setup
Connect Python and R clients to Databricks via ODBC	https://learn.microsoft.com/en-us/azure/databricks/integrations/odbc/connect-databricks-excel-python-r
Manage Unity Catalog volume files via Databricks ODBC	https://learn.microsoft.com/en-us/azure/databricks/integrations/odbc/volumes
Connect Replit-hosted apps to Azure Databricks with OAuth	https://learn.microsoft.com/en-us/azure/databricks/integrations/replit
Integrate Apache Airflow with Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/how-to/use-airflow-with-jobs
Run dbt Core transformations in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/how-to/use-dbt-in-workflows
Package and run Python wheels in Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/how-to/use-python-wheels-in-workflows
Access job and task parameters from Databricks task code	https://learn.microsoft.com/en-us/azure/databricks/jobs/parameter-use
Pass task values between Azure Databricks job tasks	https://learn.microsoft.com/en-us/azure/databricks/jobs/task-values
Analyze customer reviews with Databricks AI Functions	https://learn.microsoft.com/en-us/azure/databricks/large-language-models/ai-functions-example
Call AI models from Databricks using ai_query	https://learn.microsoft.com/en-us/azure/databricks/large-language-models/ai-query
Clone Hive metastore pipelines to Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/ldp/clone-hms-to-uc
Create and use standalone materialized views in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/ldp/dbsql/materialized
Create and manage standalone streaming tables in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/ldp/dbsql/streaming
Use Python notebooks with standalone pipelines on serverless compute	https://learn.microsoft.com/en-us/azure/databricks/ldp/dbsql/using-python
Define Lakeflow datasets with Python functions	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/definition-function
Generate Lakeflow pipelines using dlt-meta metadata	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/dlt-meta
Use Python metaprogramming to generate Lakeflow flows	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-metaprogramming
Use append_flow decorator for streaming tables	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-append-flow
Process CDC feeds with create_auto_cdc_flow	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-apply-changes
Process snapshot CDC with create_auto_cdc_from_snapshot_flow	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-apply-changes-from-snapshot
Apply data quality expectations in Python pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-expectations
Use foreach_batch_sink for custom streaming logic	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-foreach-batch-sink
Define materialized views with Python decorator	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-materialized-view
Create sinks for Kafka, Event Hubs, and Delta	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-sink
Create streaming tables with create_streaming_table	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-streaming-table
Define streaming tables with @table decorator	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-table
Create update flows with @dp.update_flow	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-update-flow
Create temporary views with @temporary_view	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-view
Use AUTO CDC INTO to apply changes in SQL	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-sql-ref-apply-changes-into
Create flows and backfills with SQL CREATE FLOW	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-sql-ref-create-flow
Use CREATE MATERIALIZED VIEW in Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-sql-ref-create-materialized-view
Configure REFRESH POLICY for Lakeflow materialized views	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-sql-ref-create-materialized-view-refresh-policy
Use CREATE STREAMING TABLE in Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-sql-ref-create-streaming-table
Create temporary views in Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-sql-ref-create-temporary-view
Define views with CREATE VIEW in Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-sql-ref-create-view
Develop Lakeflow pipeline code using Python	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/python-dev
Python API reference for Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/python-ref
Develop Lakeflow pipeline code using SQL	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/sql-dev
SQL language reference for Lakeflow pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/sql-ref
Implement custom pipeline monitoring with event hooks	https://learn.microsoft.com/en-us/azure/databricks/ldp/event-hooks
Integrate Azure Event Hubs with Databricks pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/event-hubs
Use ForEachBatch sinks for custom streaming outputs	https://learn.microsoft.com/en-us/azure/databricks/ldp/for-each-batch
Import Python modules from Git or workspace into pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/import-workspace-files
Configure sinks to write pipeline output to external systems	https://learn.microsoft.com/en-us/azure/databricks/ldp/ldp-sinks
Run distributed training examples with AI Runtime CLI	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/cli/examples/
Fine-tune Llama-3.1-8B with FSDP on AI Runtime	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/cli/examples/multinode-llm-sft
Run Ray Train distributed fine-tuning on AI Runtime	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/cli/examples/ray-train-distributed
Map AI Runtime runs to MLflow and Jobs	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/cli/track-runs
Connect notebooks and jobs to Databricks AI Runtime	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/connecting
Use Databricks Serverless GPU Python API for multi-GPU training	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/distributed-training
Use serverless_gpu library with H100 on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-api-h100-starter
Train CNN image classifier on Databricks AI Runtime	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-cnn-mnist
Fine-tune Qwen2-0.5B with LoRA on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-distributed-finetune-qwen2-0.5b
Fine-tune OpenAI gpt-oss-20b with Databricks distributed training	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-distributed-gpt-oss-20b
Train Transformers with PyTorch FSDP on Databricks serverless GPU	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-distributed-pytorch-fsdp
Fine-tune Llama-3.2-3B with Unsloth on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-finetune-llama-unsloth
Distributed fine-tune Llama-3.2-3B with Unsloth on AI Runtime	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-finetune-llama-unsloth-distributed
Fine-tune Qwen2-0.5B with LoRA on Databricks AI Runtime	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-finetune-qwen2-0.5b
Fine-tune GPT-OSS 120B with Databricks distributed training	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-gpt-oss-120b-ddp-fsdp
Fine-tune Llama 3.1 8B with Mosaic LLM Foundry on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-llama3-8b-llmfoundry
Fine-tune Olmo3 7B with Axolotl on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-olmo3-7b-lora-axolotl
Train two-tower recommenders with Lightning on Databricks GPUs	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-recommender-system-lightning
Train RetinaNet object detection on Databricks GPUs	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-retinanet-image-detection-model-training
Fine-tune Llama 3.2 1B with TRL and DeepSpeed on AI Runtime	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-sft-trl-deepspeed-llama-1b
Time series forecasting with GluonTS on Databricks GPU	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-time-series-gluonts-101
Train XGBoost regression on Databricks single GPU	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-xgboost
Train and serve YOLO11n object detection on Databricks AI Runtime	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-yolo11n-detect-coco128
Use Hyperopt with HorovodRunner for distributed tuning on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl-hyperparam-tuning/hyperopt-distributed-ml
Select best model type with Hyperopt and MLflow on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl-hyperparam-tuning/hyperopt-model-selection
Parallelize Hyperopt hyperparameter tuning with MLflow on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl-hyperparam-tuning/hyperopt-spark-mlflow-integration
Integrate Optuna hyperparameter tuning with MLflow on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl-hyperparam-tuning/optuna
Reference for Databricks AutoML Python API methods	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/automl-api-reference
Train classification models with Databricks AutoML Python API	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/classification-train-api
Integrate Databricks AutoML with Feature Store tables	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/feature-store-integration
Train time-series forecasting models with Databricks AutoML API	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/forecasting-train-api
Train regression models with Databricks AutoML Python API	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/regression-train-api
Configure Model Serving with automatic feature lookup	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/automatic-feature-lookup
Use Databricks declarative feature API reference	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/declarative-api-reference
Define features with Databricks declarative APIs	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/declarative-apis
Expose Databricks data via Feature Serving endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/feature-function-serving
Implement on-demand feature computation at inference	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/on-demand-features
Use Databricks features in real-time online workflows	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/online-workflows
Publish Databricks features to third-party online stores	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/publish-features
Use the Databricks Feature Engineering Python client	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/python-api
Serve declarative features via Databricks model endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/serve-declarative-features
Integrate third-party online stores with Feature Store	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/third-party-online-stores
Train models using Databricks feature tables	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/train-models-with-feature-store
Train models with Databricks declarative features	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/train-with-declarative-features
Use Databricks Foundation Model REST APIs	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/foundation-model-apis/api-reference
Load training data with Mosaic Streaming on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/load-data/streaming
Save and load TFRecord data with Spark and TensorFlow on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/load-data/tfrecords-save-load
Copy Databricks model versions to Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/manage-model-lifecycle/migrate-models
Create and call Databricks foundation model endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/create-foundation-model-endpoints
Deploy custom Python code with Databricks Model Serving	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/deploy-custom-python-code
Implement function calling on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/function-calling
Use provider-native LLM APIs on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/provider-native-apis
Use Anthropic Messages API with Databricks model endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/query-anthropic-messages
Query chat and general-purpose models via Databricks endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/query-chat-models
Query embedding models using Databricks Model Serving	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/query-embedding-models
Call Google Gemini API from Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/query-gemini-api
Call OpenAI Responses API from Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/query-openai-responses
Query reasoning models with Databricks Foundation Model API	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/query-reason-models
Query route-optimized Databricks serving endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/query-route-optimization
Call vision foundation models through Databricks APIs	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/query-vision-models
Send scoring requests to Databricks custom model endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/score-custom-model-endpoints
Send requests to Databricks foundation model endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/score-foundation-models
Serve custom LLMs on Databricks with vLLM	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/serve-custom-llms
Implement structured outputs with OpenAI models on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/structured-outputs
Configure web search grounding for models on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/web-search
Featurization for transfer learning with pandas UDFs	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/preprocess-data/transfer-learning-tensorflow
Integrate Ray and Spark in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ray/connect-spark-ray
Integrate MLflow tracking with Ray on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ray/ray-mlflow
Implement distributed image inference on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/reference-solutions/images-etl-inference
Use DeepSpeed distributor for large PyTorch models on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/train-model/distributed-training/deepspeed
Train Spark ML models with pyspark.ml.connect on Databricks Connect	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/train-model/distributed-training/distributed-ml-for-spark-connect
Run distributed PyTorch training with TorchDistributor on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/train-model/distributed-training/spark-pytorch-distributor
Fine-tune Hugging Face models on Databricks GPU	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/train-model/huggingface/fine-tune-model
Prepare datasets for fine-tuning Hugging Face models on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/train-model/huggingface/load-data
Use deprecated sparkdl.xgboost for distributed XGBoost	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/train-model/sparkdl-xgboost
Use TensorBoard for ML debugging on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/train-model/tensorboard
Train XGBoost models on Azure Databricks with Python and Scala	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/train-model/xgboost
Integrate XGBoost with Spark ML pipelines in Scala	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/train-model/xgboost-scala
Use xgboost.spark for distributed XGBoost on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/train-model/xgboost-spark
Log MLflow model dependencies for Databricks deployment	https://learn.microsoft.com/en-us/azure/databricks/mlflow/log-model-dependencies
Integrate Workspace Model Registry webhooks	https://learn.microsoft.com/en-us/azure/databricks/mlflow/model-registry-webhooks
Log, load, and register MLflow models on Databricks	https://learn.microsoft.com/en-us/azure/databricks/mlflow/models
Use mlflow.genai.evaluate() for GenAI testing	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/concepts/eval-harness
API reference for MLflow scorer lifecycle methods	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/concepts/production-quality-monitoring
Simulate conversations to test conversational agents	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/conversation-simulation
Create custom LLM judges with MLflow make_judge	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/custom-judge/
Implement custom MLflow judges with make_judge()	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/custom-judge/create-custom-judge
Developer workflow for MLflow code-based scorers	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/custom-scorer-dev-workflow
Create custom code-based scorers in MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/custom-scorers
Use MLflow GenAI evaluation harness patterns	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/eval-examples
Integrate MLflow Tracing with GenAI apps in local IDEs	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/getting-started/tracing/tracing-ide
Integrate MLflow Tracing in Databricks GenAI notebooks	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/getting-started/tracing/tracing-notebook
Attach feedback and expectations to MLflow traces	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/human-feedback/dev-annotations
Create and manage MLflow Prompt Registry entries	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/prompt-version-mgmt/prompt-registry/create-and-edit-prompts
Apply Prompt Registry operations with examples	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/prompt-version-mgmt/prompt-registry/examples
Track prompt and app versions with MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/prompt-version-mgmt/prompt-registry/track-prompts-app-versions
Choose automatic vs manual MLflow tracing for GenAI apps	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/app-instrumentation/
Enable automatic MLflow Tracing with autolog APIs	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/app-instrumentation/automatic
Instrument Python functions with MLflow trace decorator	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/app-instrumentation/manual-tracing/function-decorator
Use MlflowClient low-level APIs for custom tracing	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/app-instrumentation/manual-tracing/low-level-api
Use mlflow.start_span context managers for fine-grained tracing	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/app-instrumentation/manual-tracing/span-tracing
Instrument Node.js apps with MLflow Tracing SDK	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/app-instrumentation/typescript-sdk
Attach and manage MLflow trace tags and metadata	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/attach-tags/
Integrate MLflow Tracing with GenAI frameworks	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/
Enable MLflow tracing for AG2 multi-agent workflows	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/ag2
Integrate MLflow tracing with Agno agents	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/agno
Enable MLflow tracing for Anthropic models	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/anthropic
Trace AutoGen multi-agent runs with MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/autogen
Trace Amazon Bedrock LLM usage with MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/bedrock
Integrate Claude Code tracing with MLflow on Databricks	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/claude-code
Integrate MLflow tracing with CrewAI multi-agent flows	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/crewai
Trace Databricks Foundation Models via MLflow OpenAI autolog	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/databricks-foundation-models
Trace DeepSeek via OpenAI-compatible MLflow autolog	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/deepseek
Enable MLflow tracing for DSPy workflows	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/dspy
Trace Google Gemini interactions with MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/gemini
Trace Groq SDK usage with MLflow autologging	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/groq
Trace Haystack pipelines and components with MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/haystack
Trace Instructor structured outputs via MLflow LLM integrations	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/instructor
Trace LangChain chains using MLflow autolog	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/langchain
Capture LangGraph executions with MLflow tracing	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/langgraph
Trace LiteLLM gateway calls with MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/litellm
Trace LlamaIndex engines and workflows in MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/llama_index
Trace Mistral AI text generation with MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/mistral
Enable MLflow tracing for Ollama LLM endpoints	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/ollama
Export MLflow traces via OpenTelemetry-compatible formats	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/open-telemetry
Enable MLflow tracing for OpenAI model calls	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/openai
Trace OpenAI Agents SDK multi-agent workflows	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/openai-agent
Autolog PydanticAI agents and tools with MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/pydantic-ai
Trace Semantic Kernel prompts and plugins in MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/semantic-kernel
Trace Smolagents workflows with MLflow autolog	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/smolagents
Trace Strands Agents SDK runs using MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/strands
Trace deprecated OpenAI Swarm agents with MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/swarm
Enable MLflow Tracing autolog for txtai workloads	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/txtai
Use the MLflow MCP server for trace access	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/mlflow-mcp
Access MLflow trace metadata and spans via SDK	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/observe-with-traces/access-trace-data
Query Unity Catalog OpenTelemetry traces with Databricks	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/observe-with-traces/query-dbsql
Search MLflow traces programmatically with Python SDK	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/observe-with-traces/query-via-sdk
Example queries using mlflow.search_traces()	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/observe-with-traces/search-traces-examples
Configure Langfuse to export traces to Databricks MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/third-party/langfuse
Set required OpenTelemetry span attributes for MLflow UI	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/third-party/otel-span-attributes
Create custom MLflow scorers for RAG evaluation	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tutorials/examples/custom-scorers
Optimize chained prompts with MLflow multi-prompt workflows	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tutorials/examples/multi-prompt-optimization
Implement MLflow prompt optimization with GEPA and GPT-OSS	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tutorials/examples/prompt-optimization-quickstart
Connect and query Lakebase from SQL clients	https://learn.microsoft.com/en-us/azure/databricks/oltp/instances/query/connect
Query Lakebase instances from Databricks notebooks	https://learn.microsoft.com/en-us/azure/databricks/oltp/instances/query/notebook
Register Lakebase databases with Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/oltp/instances/register-uc
Use Lakebase Autoscaling APIs, CLI, and SDKs	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/api-usage
Access Lakebase Postgres via the Data API	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/data-api
Integrate Lakebase Postgres with Databricks Apps	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/databricks-apps
Connect external apps to Lakebase via SDK and OAuth	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/external-apps-connect
Call Lakebase REST API for external app access	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/external-apps-manual-api
Connect external monitoring tools to Lakebase	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/external-monitoring-tools
Use framework-specific clients to connect to Lakebase	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/framework-examples
Convert between PySpark and pandas DataFrames with Arrow	https://learn.microsoft.com/en-us/azure/databricks/pandas/pyspark-pandas-conversion
Connect Databricks to ingestion partners via Partner Connect	https://learn.microsoft.com/en-us/azure/databricks/partner-connect/ingestion
Connect Databricks to ML partners via Partner Connect	https://learn.microsoft.com/en-us/azure/databricks/partner-connect/ml
Connect Databricks to data prep partners via Partner Connect	https://learn.microsoft.com/en-us/azure/databricks/partner-connect/prep
Walkthrough: Connect Fivetran to Databricks via Partner Connect	https://learn.microsoft.com/en-us/azure/databricks/partner-connect/walkthrough-fivetran
Access Unity Catalog data from Microsoft Fabric via OneLake	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/fabric-mirror
Publish Unity Catalog to Microsoft Fabric mirrored tables	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/fabric-publish
Connect Databricks SQL warehouses to Hex	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/hex
Connect Looker to Azure Databricks clusters and SQL	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/looker
Connect Looker Studio to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/looker-studio
Connect MicroStrategy Workstation to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/microstrategy
Connect Mode analytics to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/mode
Configure ADBC or ODBC drivers for Power BI	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/power-bi-adbc
Connect Power BI Desktop to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/power-bi-desktop
Integrate Preset BI with Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/preset
Connect Qlik Sense to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/qlik-sense
Connect Sigma BI to Databricks SQL warehouses	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/sigma
Connect Tableau Desktop and Cloud to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/tableau
Connect ThoughtSpot to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/thoughtspot
Connect Anomalo data quality to Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/data-governance/anomalo
Connect erwin Data Modeler to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/data-governance/erwin
Integrate Lightup data quality with Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/data-governance/lightup
Connect Monte Carlo observability to Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/data-governance/monte-carlo
Connect Precisely Data Integrity Suite to Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/data-governance/precisely
Connect Privacera security platform to Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/data-security/privacera
Integrate Azure Databricks with Fivetran for data ingestion	https://learn.microsoft.com/en-us/azure/databricks/partners/ingestion/fivetran
Integrate Hevo Data pipelines with Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/ingestion/hevo
Connect Informatica Cloud Data Integration to Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/ingestion/informatica-cloud-data-integration
Integrate Qlik Replicate with Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/ingestion/qlik
Connect Rivery to Databricks SQL warehouses	https://learn.microsoft.com/en-us/azure/databricks/partners/ingestion/rivery
Integrate RudderStack with Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/ingestion/rudderstack
Connect Snowplow behavioral data to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/ingestion/snowplow
Integrate StreamSets pipelines with Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/ingestion/streamsets
Integrate Azure Databricks clusters with Dataiku	https://learn.microsoft.com/en-us/azure/databricks/partners/ml/dataiku
Set up John Snow Labs on Databricks clusters	https://learn.microsoft.com/en-us/azure/databricks/partners/ml/john-snow-labs
Connect Azure Databricks clusters to Labelbox	https://learn.microsoft.com/en-us/azure/databricks/partners/ml/labelbox
Use SuperAnnotate Python SDK with Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/ml/superannotate
Connect dbt Cloud to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/prep/dbt-cloud
Connect Prophecy low-code platform to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/prep/prophecy
Connect Census reverse ETL to Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/reverse-etl/census
Connect Hightouch reverse ETL to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/reverse-etl/hightouch
Connect AtScale semantic layer to Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/semantic-layer/atscale
Integrate Stardog semantic layer with Databricks	https://learn.microsoft.com/en-us/azure/databricks/partners/semantic-layer/stardog
Implement PySpark custom data sources on Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/datasources
Use PySpark Catalog API on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog
Cache tables with PySpark Catalog.cacheTable	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/cachetable
Clear cached tables with PySpark Catalog.clearCache	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/clearcache
Create tables using PySpark Catalog.createTable	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/createtable
Get current catalog with PySpark Catalog.currentCatalog	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/currentcatalog
Get current database with PySpark Catalog.currentDatabase	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/currentdatabase
Check database existence with PySpark Catalog.databaseExists	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/databaseexists
Drop global temp views with PySpark Catalog.dropGlobalTempView	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/dropglobaltempview
Drop temp views with PySpark Catalog.dropTempView	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/droptempview
Check function existence with PySpark Catalog.functionExists	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/functionexists
Get databases with PySpark Catalog.getDatabase	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/getdatabase
Get functions with PySpark Catalog.getFunction	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/getfunction
Get tables and views with PySpark Catalog.getTable	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/gettable
Check table cache status with PySpark Catalog.isCached	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/iscached
List catalogs with PySpark Catalog.listCatalogs	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/listcatalogs
List table columns with PySpark Catalog.listColumns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/listcolumns
List databases with PySpark Catalog.listDatabases	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/listdatabases
List functions with PySpark Catalog.listFunctions	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/listfunctions
List tables and views with PySpark Catalog.listTables	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/listtables
Recover table partitions with PySpark Catalog.recoverPartitions	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/recoverpartitions
Refresh cached data by path with PySpark Catalog.refreshByPath	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/refreshbypath
Refresh cached tables with PySpark Catalog.refreshTable	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/refreshtable
Set current catalog with PySpark Catalog.setCurrentCatalog	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/setcurrentcatalog
Set current database with PySpark Catalog.setCurrentDatabase	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/setcurrentdatabase
Check table existence with PySpark Catalog.tableExists	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/tableexists
Uncache tables with PySpark Catalog.uncacheTable	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/uncachetable
Use PySpark Column class in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column
Alias PySpark DataFrame columns in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/alias
Sort PySpark columns ascending in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/asc
Sort ascending with nulls first in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/asc_nulls_first
Sort ascending with nulls last in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/asc_nulls_last
Cast PySpark columns using astype in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/astype
Filter PySpark columns between bounds in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/between
Use bitwise AND on PySpark columns in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/bitwiseand
Use bitwise OR on PySpark columns in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/bitwiseor
Use bitwise XOR on PySpark columns in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/bitwisexor
Cast PySpark columns to new data types in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/cast
Check substring containment in PySpark columns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/contains
Sort PySpark columns descending in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/desc
Sort descending with nulls first in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/desc_nulls_first
Sort descending with nulls last in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/desc_nulls_last
Remove struct fields from PySpark columns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/dropfields
Check string suffix in PySpark columns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/endswith
Use null-safe equality on PySpark columns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/eqnullsafe
Access struct fields from PySpark columns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/getfield
Access array or map items from PySpark columns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/getitem
Use case-insensitive LIKE on PySpark columns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/ilike
Check membership of values in PySpark columns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/isin
Detect NaN values in PySpark columns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/isnan
Check non-null values in PySpark columns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/isnotnull
Check null values in PySpark columns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/isnull
Use SQL LIKE pattern matching in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/like
Alias PySpark columns using name in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/name
Specify default values with Column.otherwise	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/otherwise
Apply window specifications to PySpark columns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/over
Use regex RLIKE pattern matching in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/rlike
Check string prefixes in PySpark columns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/startswith
Extract substrings from PySpark columns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/substr
Safely cast PySpark columns with try_cast	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/try_cast
Use conditional expressions with Column.when	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/when
Add or replace struct fields in PySpark columns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/withfield
Use PySpark DataFrame class in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe
Aggregate entire PySpark DataFrames in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/agg
Assign aliases to PySpark DataFrames in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/alias
Compute approximate quantiles on PySpark DataFrames	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/approxquantile
Use DataFrames as table arguments in Databricks TVFs	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/astable
Load Excel files into PySpark DataFrames in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/excel
Specify input data source formats with DataFrameReader	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/format
Read JDBC tables into DataFrames on Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/jdbc
Load JSON and JSON Lines into PySpark DataFrames	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/json
Load data sources into DataFrames with DataFrameReader.load	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/load
Load ORC files into PySpark DataFrames	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/orc
Load Parquet files into PySpark DataFrames	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/parquet
Read Databricks tables as DataFrames with DataFrameReader.table	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/table
Load UTF-8 text files into PySpark DataFrames	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/text
Load XML files into PySpark DataFrames on Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/xml
Write DataFrames to external storage with DataFrameWriter	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter
Write DataFrames as CSV files in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/csv
Write DataFrames as Excel files in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/excel
Specify output data source formats with DataFrameWriter.format	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/format
Insert DataFrame rows into existing tables with insertInto	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/insertinto
Write DataFrames to JDBC tables from Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/jdbc
Write DataFrames as JSON/JSON Lines files	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/json
Write DataFrames as ORC files in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/orc
Write DataFrames as Parquet files in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/parquet
Save DataFrames to configured data sources with DataFrameWriter.save	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/save
Save DataFrames as Databricks tables with saveAsTable	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/saveastable
Write DataFrames as UTF-8 text files	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/text
Write DataFrames as XML files in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/xml
Write DataFrames with the v2 writer API in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2
Append DataFrame rows to tables with DataFrameWriterV2.append	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/append
Cluster data columns for query performance	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/clusterby
Set write options for PySpark data sources	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/option
Configure multiple write options in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/options
Partition output tables with DataFrameWriterV2	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/partitionedby
Add table properties with DataFrameWriterV2	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/tableproperty
Specify output data source provider in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/using
Implement custom PySpark data sources	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource
Define custom data source format name	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource/name
Create DataSourceReader for custom reads	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource/reader
Provide schema for custom data sources	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource/schema
Implement simple streaming reader for data source	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource/simplestreamreader
Create streaming reader for custom data source	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource/streamreader
Create streaming writer for custom sinks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource/streamwriter
Create batch writer for custom data source	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource/writer
Implement Arrow-based data source writer	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcearrowwriter
Write Arrow RecordBatches to custom sink	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcearrowwriter/write
Implement DataSourceReader for custom inputs	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcereader
Partition custom data source reads	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcereader/partitions
Implement filter pushdown in DataSourceReader	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcereader/pushfilters
Read partition data in custom DataSourceReader	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcereader/read
Register custom data sources in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourceregistration
Register Python user-defined data source	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourceregistration/register
Implement Arrow-based streaming data writer	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamarrowwriter
Write Arrow batches to streaming sink	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamarrowwriter/write
Implement streaming reader for custom source	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader
Handle commit offsets in streaming reader	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/commit
Configure default read limits for streaming	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/getdefaultreadlimit
Define initial offset for streaming source	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/initialoffset
Compute latest offset with read limits	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/latestoffset
Partition streaming reads into input splits	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/partitions
Read partition data in streaming reader	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/read
Report latest offset for streaming status	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/reportlatestoffset
Stop streaming reader and release resources	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/stop
Implement streaming data sink writer	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamwriter
Abort streaming microbatch on failures	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamwriter/abort
Commit streaming microbatch with messages	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamwriter/commit
Write streaming data and return commit info	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamwriter/write
Implement batch writer for custom sink	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcewriter
Abort batch write job on task failures	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcewriter/abort
Commit batch write job with messages	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcewriter/commit
Implement custom PySpark DataSourceWriter.write logic	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcewriter/write
Use DataStreamReader to load streaming data	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader
Read CDC changes with DataStreamReader.changes	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/changes
Stream CSV files with DataStreamReader.csv	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/csv
Stream Excel files with DataStreamReader.excel	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/excel
Specify streaming input formats with DataStreamReader	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/format
Stream JSON data with DataStreamReader.json	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/json
Load streaming sources with DataStreamReader.load	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/load
Name streaming sources for checkpoint evolution	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/name
Configure streaming input options with DataStreamReader.option	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/option
Set multiple streaming options with DataStreamReader.options	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/options
Stream ORC files with DataStreamReader.orc	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/orc
Stream Parquet files with DataStreamReader.parquet	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/parquet
Define streaming input schemas with DataStreamReader.schema	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/schema
Create streaming DataFrames from tables	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/table
Stream text files with DataStreamReader.text	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/text
Stream XML files with DataStreamReader.xml	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/xml
Write streaming DataFrames with DataStreamWriter	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter
Cluster streaming output with DataStreamWriter.clusterBy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/clusterby
Process streaming rows with DataStreamWriter.foreach	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/foreach
Use foreachBatch for micro-batch streaming output	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/foreachbatch
Specify streaming sink formats with DataStreamWriter.format	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/format
Configure streaming sink options with DataStreamWriter.option	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/option
Set multiple streaming sink options with DataStreamWriter.options	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/options
Configure streaming output modes with DataStreamWriter.outputMode	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/outputmode
Partition streaming output with DataStreamWriter.partitionBy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/partitionby
Name streaming queries with DataStreamWriter.queryName	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/queryname
Start streaming queries with DataStreamWriter.start	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/start
Write streaming results to tables with table()	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/table
Stream DataFrame output to tables with toTable	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/totable
Work with Geography values in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geography
Create Geography objects from WKB	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geography/fromwkb
Get WKB bytes from Geography objects	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geography/getbytes
Retrieve SRID from Geography values	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geography/getsrid
Work with Geometry values in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geometry
Create Geometry objects from WKB	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geometry/fromwkb
Get WKB bytes from Geometry objects	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geometry/getbytes
Retrieve SRID from Geometry values	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geometry/getsrid
Perform grouped aggregations with GroupedData	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/groupeddata
Use GroupedData.agg for PySpark aggregations in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/groupeddata/agg
Compute grouped averages with GroupedData.avg in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/groupeddata/avg
Count records per group with GroupedData.count	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/groupeddata/count
Find grouped maximums with GroupedData.max in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/groupeddata/max
Compute grouped means with GroupedData.mean in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/groupeddata/mean
Find grouped minimums with GroupedData.min in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/groupeddata/min
Pivot DataFrame columns with GroupedData.pivot in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/groupeddata/pivot
Compute grouped sums with GroupedData.sum in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/groupeddata/sum
Implement custom InputPartition for PySpark data sources	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/inputpartition
Capture DataFrame metrics with Observation in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/observation
Retrieve observed metrics with Observation.get in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/observation/get
Generate plots from DataFrames with PySparkPlotAccessor	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/plotaccessor
Draw stacked area plots with PySparkPlotAccessor.area	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/plotaccessor/area
Create vertical bar charts with PySparkPlotAccessor.bar	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/plotaccessor/bar
Create horizontal bar charts with PySparkPlotAccessor.barh	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/plotaccessor/barh
Build box-and-whisker plots with PySparkPlotAccessor.box	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/plotaccessor/box
Plot histograms of DataFrame columns with PySparkPlotAccessor.hist	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/plotaccessor/hist
Generate KDE plots with PySparkPlotAccessor.kde	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/plotaccessor/kde
Plot DataFrames as line charts with PySparkPlotAccessor.line	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/plotaccessor/line
Create pie charts from DataFrames with PySparkPlotAccessor.pie	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/plotaccessor/pie
Create scatter plots with PySparkPlotAccessor.scatter	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/plotaccessor/scatter
Work with Row objects in Databricks PySpark DataFrames	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/row
Convert Row objects to dictionaries with Row.asDict	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/row/asdict
Implement SimpleDataSourceStreamReader for lightweight streaming in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/simpledatasourcestreamreader
Commit processed offsets with SimpleDataSourceStreamReader.commit	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/simpledatasourcestreamreader/commit
Determine initial offsets with SimpleDataSourceStreamReader.initialOffset	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/simpledatasourcestreamreader/initialoffset
Read streaming batches with SimpleDataSourceStreamReader.read	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/simpledatasourcestreamreader/read
Re-read streaming data ranges with SimpleDataSourceStreamReader.readBetweenOffsets	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/simpledatasourcestreamreader/readbetweenoffsets
Use SparkSession as the entry point for Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession
Access the active SparkSession with SparkSession.active	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/active
Attach local artifacts to Spark sessions with SparkSession.addArtifacts	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/addartifacts
Tag and cancel related Spark operations with SparkSession.addTag	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/addtag
Manage catalogs, databases, and tables with SparkSession.catalog	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/catalog
Clear registered progress handlers with SparkSession.clearProgressHandlers	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/clearprogresshandlers
Create PySpark DataFrames from multiple data sources	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/createdataframe
Register custom data sources in SparkSession	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/datasource
Read data into DataFrames with DataFrameReader	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/read
Read streaming data with DataStreamReader	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/readstream
Execute SQL queries via SparkSession.sql in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/sql
Load Spark SQL tables as DataFrames	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/table
Call table-valued functions via SparkSession.tvf	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/tvf
Register and use UDFs with SparkSession.udf	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/udf
Register and use UDTFs with SparkSession.udtf	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/udtf
Use ai_parse_document PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/ai_parse_document
Create PyArrow-native UDTFs with arrow_udtf	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/arrow_udtf
Use from_utc_timestamp for timezone conversion in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/from_utc_timestamp
Parse XML strings to rows with from_xml in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/from_xml
Access array elements by index with get in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/get
Extract JSON objects with get_json_object in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/get_json_object
Read individual bits with getbit in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/getbit
Compute greatest column value with greatest in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/greatest
Identify aggregated columns with grouping in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/grouping
Compute grouping levels with grouping_id in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/grouping_id
Get H3 cell boundary as GeoJSON in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_boundaryasgeojson
Get H3 cell boundary as WKB in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_boundaryaswkb
Get H3 cell boundary as WKT in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_boundaryaswkt
Get H3 cell center as GeoJSON in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_centerasgeojson
Get H3 cell center as WKB in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_centeraswkb
Get H3 cell center as WKT in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_centeraswkt
Compact H3 cell ID sets with h3_compact in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_compact
Cover geography with H3 cells using h3_coverash3	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_coverash3
Cover geography with H3 strings using h3_coverash3string	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_coverash3string
Compute grid distance between H3 cells with h3_distance	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_distance
Convert H3 IDs to hex strings with h3_h3tostring	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_h3tostring
Generate H3 hexagonal rings with h3_hexring in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_hexring
Check H3 parent-child relationships with h3_ischildof	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_ischildof
Detect H3 pentagon cells with h3_ispentagon	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_ispentagon
Validate H3 cell IDs with h3_isvalid in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_isvalid
Find H3 neighbors within distance k using h3_kring	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_kring
Get H3 neighbors and distances with h3_kringdistances	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_kringdistances
Convert longitude and latitude to H3 IDs with h3_longlatash3	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_longlatash3
Convert longitude and latitude to H3 strings with h3_longlatash3string	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_longlatash3string
Get maximum child H3 cell with h3_maxchild in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_maxchild
Get minimum child H3 cell with h3_minchild in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_minchild
Convert point geometries to H3 IDs with h3_pointash3	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_pointash3
Convert point geometries to H3 strings with h3_pointash3string	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_pointash3string
Fill polygons with H3 IDs using h3_polyfillash3	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_polyfillash3
Fill polygons with H3 strings using h3_polyfillash3string	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_polyfillash3string
Get H3 cell resolution with h3_resolution in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_resolution
Convert H3 strings to big integers with h3_stringtoh3	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_stringtoh3
Tessellate geography into H3 chips with h3_tessellateaswkb	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_tessellateaswkb
Get H3 children at resolution with h3_tochildren in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_tochildren
Get H3 parent at resolution with h3_toparent in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_toparent
Try covering geography with H3 IDs using h3_try_coverash3	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_try_coverash3
Try covering geography with H3 strings using h3_try_coverash3string	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_try_coverash3string
Use st_collect spatial function in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_collect
Parse EWKT geography with st_geogfromewkt	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geogfromewkt
Parse GeoJSON geography with st_geogfromgeojson	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geogfromgeojson
Parse WKT geography with st_geogfromtext	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geogfromtext
Parse WKB geography with st_geogfromwkb	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geogfromwkb
Parse WKT geography with st_geogfromwkt	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geogfromwkt
Use st_m PySpark function for point M coordinate	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_m
Create bounding boxes with st_makeenvelope in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_makeenvelope
Build linestrings from geometries using st_makeline	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_makeline
Construct point geometries with st_makepoint in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_makepoint
Create polygons from linestrings using st_makepolygon	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_makepolygon
Convert geometries to multi types with st_multi	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_multi
Get coordinate dimension with st_ndims in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_ndims
Count points in geometries using st_npoints	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_npoints
Count polygon rings with st_nrings in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_nrings
Get geometry count with st_numgeometries in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_numgeometries
Get interior ring count using st_numinteriorrings	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_numinteriorrings
Count non-empty points with st_numpoints in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_numpoints
Calculate geometry perimeter with st_perimeter in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_perimeter
Create SRID-aware points with st_point in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_point
Generate point from geohash using st_pointfromgeohash	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_pointfromgeohash
Access nth linestring point with st_pointn in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_pointn
Remove nth linestring point using st_removepoint	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_removepoint
Reverse vertex order with st_reverse in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_reverse
Rotate geometries around Z axis with st_rotate	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_rotate
Scale geometries in PySpark using st_scale	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_scale
Set nth linestring point with st_setpoint in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_setpoint
Change geometry SRID using st_setsrid in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_setsrid
Simplify geometries with st_simplify in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_simplify
Retrieve SRID from geospatial values using st_srid	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_srid
Get first linestring point with st_startpoint in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_startpoint
Test geometry adjacency with st_touches in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_touches
Transform geometry CRS with st_transform in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_transform
Translate geometries using st_translate in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_translate
Compute geometry union with st_union in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_union
Aggregate geometry unions with st_union_agg in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_union_agg
Check containment relationships with st_within in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_within
Get X coordinate from point using st_x in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_x
Get maximum X coordinate with st_xmax in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_xmax
Get minimum X coordinate with st_xmin in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_xmin
Get Y coordinate from point using st_y in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_y
Get maximum Y coordinate with st_ymax in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_ymax
Get minimum Y coordinate with st_ymin in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_ymin
Get Z coordinate from point using st_z in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_z
Get maximum Z coordinate with st_zmax in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_zmax
Transform columns into rows with stack in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/stack
Check string prefixes with startswith in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/startswith
Use std aggregate alias in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/std
Use stddev alias for stddev_samp in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/stddev
Compute population standard deviation with stddev_pop	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/stddev_pop
Compute sample standard deviation with stddev_samp	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/stddev_samp
Convert delimited strings to maps with str_to_map	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/str_to_map
Concatenate values with string_agg in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/string_agg
Concatenate distinct values with string_agg_distinct	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/string_agg_distinct
Create struct columns with struct in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/struct
Extract substrings with substr in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/substr
Extract substrings with substring in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/substring
Split strings by delimiter with substring_index	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/substring_index
Aggregate numeric values with sum in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/sum
Aggregate distinct values with sum_distinct in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/sum_distinct
Compute tangent with tan in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/tan
Compute hyperbolic tangent with tanh in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/tanh
Compute Theta Sketch set difference with theta_difference	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/theta_difference
Compute Theta Sketch intersection with theta_intersection	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/theta_intersection
Aggregate Theta Sketch intersections with theta_intersection_agg	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/theta_intersection_agg
Build Theta Sketch aggregates with theta_sketch_agg	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/theta_sketch_agg
Estimate unique counts from Theta Sketch with theta_sketch_estimate	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/theta_sketch_estimate
Merge Theta Sketches with theta_union in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/theta_union
Aggregate Theta Sketch unions with theta_union_agg	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/theta_union_agg
Calculate time differences with time_diff in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/time_diff
Create TIME values from microseconds with time_from_micros	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/time_from_micros
Create TIME values from milliseconds with time_from_millis	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/time_from_millis
Use to_avro with Databricks Schema Registry	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/to_avro
Use to_geometry PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/to_geometry
Use try_ip_as_string PySpark function in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_ip_as_string
Use try_ip_cidr PySpark function in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_ip_cidr
Use try_ip_host PySpark function in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_ip_host
Handle intervals with try_make_interval in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_make_interval
Create timestamps with try_make_timestamp in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_make_timestamp
Create LTZ timestamps with try_make_timestamp_ltz	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_make_timestamp_ltz
Create NTZ timestamps with try_make_timestamp_ntz	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_make_timestamp_ntz
Use try_mod for safe modulo in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_mod
Use try_multiply for overflow-safe multiplication	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_multiply
Parse JSON safely with try_parse_json in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_parse_json
Use try_parse_url for robust URL parsing	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_parse_url
Invoke Java methods safely with try_reflect	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_reflect
Use try_subtract for overflow-safe subtraction	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_subtract
Aggregate with overflow-safe try_sum in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_sum
Convert data safely with try_to_binary in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_to_binary
Convert values to dates with try_to_date	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_to_date
Parse spatial data with try_to_geography in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_to_geography
Convert formatted strings to numbers with try_to_number	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_to_number
Convert columns to TimeType with try_to_time	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_to_time
Parse timestamps safely with try_to_timestamp	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_to_timestamp
Decode URLs safely with try_url_decode in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_url_decode
Validate UTF-8 strings with try_validate_utf8	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_validate_utf8
Extract and cast sub-variants with try_variant_get	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_variant_get
Decompress Zstandard data with try_zstd_decompress	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_zstd_decompress
Use TableValuedFunction.stack in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/tvf-stack
Explode variant arrays/objects with variant_explode	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/tvf-variant_explode
Outer explode of variants with variant_explode_outer	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/tvf-variant_explode_outer
Inspect column data types with typeof in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/typeof
Uppercase strings with ucase in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/ucase
Create user-defined functions (UDFs) in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/udf
Create user-defined table functions (UDTFs) in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/udtf
Decode Base64 strings with unbase64 in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/unbase64
Convert hex strings to bytes with unhex in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/unhex
Generate uniform random values with uniform in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/uniform
Get days since epoch with unix_date in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/unix_date
Get microseconds since epoch with unix_micros	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/unix_micros
Get milliseconds since epoch with unix_millis	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/unix_millis
Get seconds since epoch with unix_seconds	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/unix_seconds
Convert time strings to Unix timestamps with unix_timestamp	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/unix_timestamp
Unwrap UDT columns with unwrap_udt in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/unwrap_udt
Uppercase strings with upper in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/upper
Decode URL-encoded strings with url_decode in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/url_decode
Use url_encode PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/url_encode
Use user PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/user
Generate UUIDs with Databricks PySpark uuid function	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/uuid
Validate UTF-8 strings with Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/validate_utf8
Compute population variance with var_pop in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/var_pop
Compute sample variance with var_samp in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/var_samp
Use variance alias for var_samp in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/variance
Extract sub-variants with variant_get in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/variant_get
Get Spark version with Databricks PySpark version function	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/version
Determine weekday from dates in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/weekday
Get ISO week number with weekofyear in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/weekofyear
Use conditional expressions with when in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/when
Bucket numeric values with width_bucket in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/width_bucket
Create time windows with window function in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/window
Compute event time from window columns in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/window_time
Extract XML values with xpath in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xpath
Evaluate XML XPath to boolean in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xpath_boolean
Get double from XML XPath with xpath_double	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xpath_double
Get float from XML XPath with xpath_float	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xpath_float
Get int from XML XPath with xpath_int	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xpath_int
Get long from XML XPath with xpath_long	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xpath_long
Get numeric double from XML XPath with xpath_number	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xpath_number
Get short from XML XPath with xpath_short	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xpath_short
Extract text from XML with xpath_string in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xpath_string
Hash columns with xxhash64 in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xxhash64
Extract year from dates with year function in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/year
Partition data by years with years transform in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/years
Replace nulls with zero using zeroifnull in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/zeroifnull
Merge arrays element-wise with zip_with in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/zip_with
Compress data with zstd_compress in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/zstd_compress
Decompress Zstandard data with zstd_decompress in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/zstd_decompress
Configure Databricks Lakehouse Federation for BigQuery	https://learn.microsoft.com/en-us/azure/databricks/query-federation/bigquery
Federate another Databricks workspace with Lakehouse	https://learn.microsoft.com/en-us/azure/databricks/query-federation/databricks
Create and use HTTP connections in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/query-federation/http
Configure Lakehouse Federation for MySQL	https://learn.microsoft.com/en-us/azure/databricks/query-federation/mysql
Configure OneLake catalog federation for Databricks	https://learn.microsoft.com/en-us/azure/databricks/query-federation/onelake
Configure Lakehouse Federation for Oracle databases	https://learn.microsoft.com/en-us/azure/databricks/query-federation/oracle
Configure Lakehouse Federation for PostgreSQL	https://learn.microsoft.com/en-us/azure/databricks/query-federation/postgresql
Federate Databricks queries to Amazon Redshift	https://learn.microsoft.com/en-us/azure/databricks/query-federation/redshift
Run remote_query against external databases in Databricks	https://learn.microsoft.com/en-us/azure/databricks/query-federation/remote-queries
Configure Databricks federation to Salesforce Data 360	https://learn.microsoft.com/en-us/azure/databricks/query-federation/salesforce-data-cloud
Use Salesforce Data 360 file sharing connector	https://learn.microsoft.com/en-us/azure/databricks/query-federation/salesforce-data-cloud-file-sharing
Federate Databricks queries to Snowflake using OAuth	https://learn.microsoft.com/en-us/azure/databricks/query-federation/snowflake
Federate Databricks queries to Snowflake with basic auth	https://learn.microsoft.com/en-us/azure/databricks/query-federation/snowflake-basic-auth
Enable Snowflake catalog federation in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/query-federation/snowflake-catalog-federation
Configure Databricks federated queries to Snowflake via Entra ID	https://learn.microsoft.com/en-us/azure/databricks/query-federation/snowflake-entra
Run Databricks federated queries on Snowflake via OAuth	https://learn.microsoft.com/en-us/azure/databricks/query-federation/snowflake-oauth-access-token
Federate Databricks queries to Snowflake with Okta OAuth	https://learn.microsoft.com/en-us/azure/databricks/query-federation/snowflake-okta
Federate Snowflake with Databricks using PEM keys	https://learn.microsoft.com/en-us/azure/databricks/query-federation/snowflake-pem
Configure Databricks Lakehouse Federation for SQL Server	https://learn.microsoft.com/en-us/azure/databricks/query-federation/sql-server
Federate queries to Azure Synapse from Databricks	https://learn.microsoft.com/en-us/azure/databricks/query-federation/sqldw
Configure Lakehouse Federation for Teradata	https://learn.microsoft.com/en-us/azure/databricks/query-federation/teradata
Use Azure Databricks to read and write Avro data	https://learn.microsoft.com/en-us/azure/databricks/query/formats/avro
Load binary file data into Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/query/formats/binary
Read and write CSV files in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/query/formats/csv
Read OpenSharing tables via Spark DataFrames in Databricks	https://learn.microsoft.com/en-us/azure/databricks/query/formats/deltasharing
Read and stream Excel files with Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/query/formats/excel
Ingest image files using Azure Databricks image source	https://learn.microsoft.com/en-us/azure/databricks/query/formats/image
Read and write JSON data in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/query/formats/json
Load MLflow experiment runs with Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/query/formats/mlflow-experiment
Read and write ORC files in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/query/formats/orc
Use Azure Databricks to process Parquet data	https://learn.microsoft.com/en-us/azure/databricks/query/formats/parquet
Read and write text files using Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/query/formats/text
Read and write XML data in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/query/formats/xml
Use MLflow REST APIs on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/reference/mlflow-api
Use Account SCIM v2.1 API for identity management	https://learn.microsoft.com/en-us/azure/databricks/reference/scim-2-1
Query and extract JSON string fields in Azure Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/semi-structured/json
Use Databricks-specific Spark read and write options	https://learn.microsoft.com/en-us/azure/databricks/spark/api-options
Use SparkR, sparklyr, and dplyr DataFrames on Databricks	https://learn.microsoft.com/en-us/azure/databricks/sparkr/dataframes-tables
Connect local RStudio to Azure Databricks compute	https://learn.microsoft.com/en-us/azure/databricks/sparkr/rstudio
Run Shiny applications on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/sparkr/shiny
Use sparklyr with Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/sparkr/sparklyr
Migrate SparkR code to sparklyr on Databricks	https://learn.microsoft.com/en-us/azure/databricks/sparkr/sparkr-migration
Migrate to the latest Databricks SQL REST API version	https://learn.microsoft.com/en-us/azure/databricks/sql/dbsql-api-latest
Use Databricks SQL language constructs and syntax	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/
Close cursors with CLOSE in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/control-flow/close-stmt
Write BEGIN END compound SQL scripts in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/control-flow/compound-stmt
Use agg aggregate function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/agg
Call ai_analyze_sentiment in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_analyze_sentiment
Use ai_classify SQL function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_classify
Use ai_extract SQL function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_extract
Correct text grammar using ai_fix_grammar in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_fix_grammar
Forecast time series with ai_forecast in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_forecast
Generate content using ai_gen in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_gen
Mask sensitive entities with ai_mask in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_mask
Use ai_parse_document in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_parse_document
Prepare documents for RAG using ai_prep_search	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_prep_search
Call model endpoints with ai_query in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_query
Compute semantic similarity with ai_similarity in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_similarity
Summarize text using ai_summarize in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_summarize
Translate text with ai_translate in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_translate
Use approx_top_k aggregate in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/approx_top_k
Accumulate top-K sketches with approx_top_k_accumulate	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/approx_top_k_accumulate
Combine top-K sketches with approx_top_k_combine	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/approx_top_k_combine
Use array_contains in Databricks SQL expressions	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/array_contains
Remove duplicates with array_distinct in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/array_distinct
Insert elements with array_insert in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/array_insert
Remove elements with array_remove in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/array_remove
Create repeated arrays with array_repeat in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/array_repeat
Sort arrays with array_sort in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/array_sort
Use bitmap_and_agg for Databricks SQL bitmaps	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/bitmap_and_agg
Construct bitmap aggregates with bitmap_construct_agg	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/bitmap_construct_agg
Implement CASE expressions in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/case
Compute cube roots with cbrt in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/cbrt
Use cloud_files_state function in Azure Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/cloud_files_state
Aggregate values into arrays with collect_list	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/collect_list
Extract JSON content with Databricks colon operator	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/colonsign
Check substring presence with contains in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/contains
Compute Pearson correlation with corr in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/corr
Calculate cosine values with cos in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/cos
Use hyperbolic cosine via cosh in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/cosh
Compute cotangent with cot in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/cot
Use Databricks SQL event_log table-valued function	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/event_log
Use Databricks SQL flatten function on nested arrays	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/flatten
Cast values to FLOAT with Databricks SQL float	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/float
Round numbers down using Databricks SQL floor	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/floor
Use from_avro to parse Avro in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/from_avro
Use from_csv function in Azure Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/from_csv
Use from_json to parse JSON in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/from_json
Use from_xml to parse XML in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/from_xml
Extract JSON fields with get_json_object in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/get_json_object
Read individual bits using Databricks SQL getbit	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/getbit
Use h3_boundaryasgeojson in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_boundaryasgeojson
Use h3_boundaryaswkb in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_boundaryaswkb
Use h3_boundaryaswkt in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_boundaryaswkt
Get H3 cell center as GeoJSON in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_centerasgeojson
Get H3 cell center as WKB in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_centeraswkb
Get H3 cell center as WKT in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_centeraswkt
Compact H3 cell sets with Databricks h3_compact	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_compact
Cover geography with H3 cells using h3_coverash3	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_coverash3
Cover geography with H3 strings using h3_coverash3string	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_coverash3string
Compute H3 grid distance with h3_distance in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_distance
Convert H3 IDs to hex strings with h3_h3tostring	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_h3tostring
Generate H3 hexagonal rings with h3_hexring in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_hexring
Check H3 parent-child relationships with h3_ischildof	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_ischildof
Detect pentagon H3 cells with h3_ispentagon in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_ispentagon
Validate H3 cell IDs with h3_isvalid in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_isvalid
Get H3 k-ring neighborhoods with h3_kring in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_kring
Convert longitude/latitude to H3 BIGINT with h3_longlatash3	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_longlatash3
Convert longitude/latitude to H3 string with h3_longlatash3string	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_longlatash3string
Get maximum child H3 cell with h3_maxchild in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_maxchild
Get minimum child H3 cell with h3_minchild in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_minchild
Convert geometry point to H3 BIGINT with h3_pointash3	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_pointash3
Convert geometry point to H3 string with h3_pointash3string	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_pointash3string
Polyfill areal geography with H3 BIGINT using h3_polyfillash3	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_polyfillash3
Polyfill areal geography with H3 strings using h3_polyfillash3string	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_polyfillash3string
Get H3 cell resolution with h3_resolution in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_resolution
Convert H3 hex string to BIGINT with h3_stringtoh3	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_stringtoh3
Tessellate geography into H3 WKB cells with h3_tessellateaswkb	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_tessellateaswkb
List child H3 cells at resolution with h3_tochildren	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_tochildren
Get parent H3 cell at resolution with h3_toparent	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_toparent
Safely cover geography with H3 BIGINT using h3_try_coverash3	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_try_coverash3
Safely cover geography with H3 strings using h3_try_coverash3string	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/h3_try_coverash3string
Use Databricks SQL http_request for external HTTP calls	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/http_request
Use ip_as_binary in Azure Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ip_as_binary
Use ip_as_string in Azure Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ip_as_string
Normalize CIDR blocks with ip_cidr in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ip_cidr
Check CIDR containment with ip_cidr_contains in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ip_cidr_contains
Use ip_host SQL function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ip_host
Get network portion of CIDR with ip_network in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ip_network
Use ip_network_first alias for ip_network in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ip_network_first
Get last IP in CIDR with ip_network_last in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ip_network_last
Retrieve CIDR prefix length with ip_prefix_length in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ip_prefix_length
Determine IP version with ip_version in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ip_version
Invoke Java methods from Databricks SQL with java_method	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/java_method
Use kll_merge_agg_bigint for KLL sketches	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_merge_agg_bigint
Use kll_merge_agg_double for KLL sketches	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_merge_agg_double
Use kll_merge_agg_float for KLL sketches	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_merge_agg_float
Use kll_sketch_agg_bigint in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_sketch_agg_bigint
Use kll_sketch_agg_double in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_sketch_agg_double
Use kll_sketch_agg_float in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_sketch_agg_float
Query item count from bigint KLL sketch	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_sketch_get_n_bigint
Query item count from double KLL sketch	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_sketch_get_n_double
Query item count from float KLL sketch	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_sketch_get_n_float
Use kll_sketch_get_rank_double in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_sketch_get_rank_double
Use kll_sketch_get_rank_float in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_sketch_get_rank_float
Merge bigint KLL sketches in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_sketch_merge_bigint
Merge double KLL sketches in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_sketch_merge_double
Merge float KLL sketches in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_sketch_merge_float
Convert bigint KLL sketch to debug string	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_sketch_to_string_bigint
Convert double KLL sketch to debug string	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_sketch_to_string_double
Convert float KLL sketch to debug string	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kll_sketch_to_string_float
Calculate kurtosis with Databricks SQL function	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/kurtosis
Use lag window function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/lag
Pattern matching with like in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/like
Use make_date in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/make_date
Build day-time intervals with make_dt_interval	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/make_dt_interval
Create intervals with deprecated make_interval	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/make_interval
Create year-month intervals with make_ym_interval	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/make_ym_interval
Build map literals with Databricks SQL map	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/map
Merge maps using map_concat in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/map_concat
Create maps from arrays with map_from_arrays	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/map_from_arrays
Build maps from entries using map_from_entries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/map_from_entries
Calculate averages with mean aggregate function	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/mean
Use unary minus operator in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/minussignunary
Compute remainders with mod in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/mod
Negate numeric values with negative function	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/negative
Find next weekday date with next_day function	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/next_day
Use parse_json in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/parse_json
Use parse_timestamp in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/parse_timestamp
Extract URL components with parse_url in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/parse_url
Calculate exact percentiles in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/percentile
Use modulo % operator in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/percentsign
Compute positive modulo with pmod in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/pmod
Use pow function in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/pow
Use power function in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/power
Cast with ?:: operator in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/questiondoublecolonsign
Use radians function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/radians
Raise custom SQL errors in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/raise_error
Generate random numbers with rand in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/rand
Generate random numbers with random in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/random
Use read_files table function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/read_files
Use read_kafka function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/read_kafka
Stream from Amazon Kinesis using read_kinesis TVF	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/read_kinesis
Read Google Pub/Sub streams with read_pubsub in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/read_pubsub
Consume Pulsar streams via read_pulsar in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/read_pulsar
Access streaming state with read_statestore in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/read_statestore
Aggregate arrays with reduce in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/reduce
Use regexp_instr function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/regexp_instr
Compute regression mean with regr_avgx in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/regr_avgx
Compute regression SXX with regr_sxx in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/regr_sxx
Compute regression SXY with regr_sxy in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/regr_sxy
Query remote databases with remote_query in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/remote_query
Use schema_of_csv in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/schema_of_csv
Use schema_of_json in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/schema_of_json
Use schema_of_xml in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/schema_of_xml
Use sql_keywords function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/sql_keywords
Use st_addpoint for Databricks spatial linestrings	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_addpoint
Calculate geometry area with st_area in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_area
Convert geometries to WKB with st_asbinary	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_asbinary
Export geometries as EWKB using st_asewkb	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_asewkb
Return geometries as EWKT with st_asewkt	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_asewkt
Generate GeoJSON from geometries via st_asgeojson	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_asgeojson
Convert geometries to WKT with st_astext	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_astext
Output WKB from geometries using st_aswkb	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_aswkb
Return geometries as WKT with st_aswkt	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_aswkt
Compute azimuth between points with st_azimuth	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_azimuth
Get geometry boundaries using st_boundary	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_boundary
Create geometry buffers with st_buffer in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_buffer
Find geometry centroids using st_centroid	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_centroid
Project closest point on geometry via st_closestpoint	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_closestpoint
Compute concave hulls using st_concavehull	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_concavehull
Test geometry containment with st_contains	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_contains
Generate convex hulls via st_convexhull in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_convexhull
Check geometry coverage using st_covers	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_covers
Compute geometry differences with st_difference	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_difference
Get geometry topological dimension via st_dimension	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_dimension
Determine disjoint geometries with st_disjoint	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_disjoint
Measure 2D distances using st_distance in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_distance
Compute spherical distances with st_distancesphere	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_distancesphere
Calculate geodesic distances via st_distancespheroid	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_distancespheroid
Explode multi-geometries using st_dump in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_dump
Filter geometries within distance using st_dwithin	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_dwithin
Get linestring endpoints with st_endpoint	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_endpoint
Use st_envelope geometry function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_envelope
Aggregate geometry envelopes with st_envelope_agg	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_envelope_agg
Compare geometries with st_equals in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_equals
Estimate projected SRID with st_estimatesrid	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_estimatesrid
Extract polygon exterior ring with st_exteriorring	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_exteriorring
Swap geometry coordinates using st_flipcoordinates	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_flipcoordinates
Force 2D projection with st_force2d in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_force2d
Use st_geogfromewkt in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geogfromewkt
Parse GeoJSON geography with st_geogfromgeojson	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geogfromgeojson
Parse WKT geography with st_geogfromtext	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geogfromtext
Parse WKB geography with st_geogfromwkb	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geogfromwkb
Use st_geogfromwkt to parse WKT geography in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geogfromwkt
Generate geohash strings with st_geohash	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geohash
Access n-th geometry element with st_geometryn	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geometryn
Get geometry type string with st_geometrytype	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geometrytype
Create geometry from EWKB with st_geomfromewkb	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geomfromewkb
Create geometry from EWKT with st_geomfromewkt	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geomfromewkt
Convert geohash to geometry with st_geomfromgeohash	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geomfromgeohash
Create geometry from GeoJSON with st_geomfromgeojson	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geomfromgeojson
Create geometry from WKT with st_geomfromtext	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geomfromtext
Create geometry from WKB with st_geomfromwkb	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geomfromwkb
Create geometry from WKT with st_geomfromwkt	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geomfromwkt
Access polygon interior rings with st_interiorringn	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_interiorringn
Compute geometry intersection with st_intersection	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_intersection
Test geometry intersection with st_intersects	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_intersects
Check for empty geometries with st_isempty	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_isempty
Validate geometries with st_isvalid in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_isvalid
Measure geometry length with st_length	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_length
Access M coordinate with st_m in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_m
Construct envelope geometries with st_makeenvelope	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_makeenvelope
Build linestrings from points with st_makeline	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_makeline
Create point geometries with st_makepoint	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_makepoint
Construct polygons from rings with st_makepolygon	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_makepolygon
Convert to multi-geometry with st_multi	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_multi
Get geometry coordinate dimension with st_ndims	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_ndims
Count points in geometries with st_npoints	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_npoints
Count polygon rings with st_nrings in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_nrings
Count component geometries with st_numgeometries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_numgeometries
Count polygon interior rings with st_numinteriorrings	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_numinteriorrings
Count points in geometries with st_numpoints	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_numpoints
Use st_perimeter in Databricks SQL geospatial queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_perimeter
Create point geometries with st_point in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_point
Convert geohash to point with st_pointfromgeohash	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_pointfromgeohash
Access n-th linestring point using st_pointn	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_pointn
Remove linestring point using st_removepoint in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_removepoint
Reverse geospatial geometries with st_reverse in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_reverse
Rotate geometries around Z axis using st_rotate	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_rotate
Scale geometries in Databricks SQL with st_scale	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_scale
Set linestring point coordinates using st_setpoint	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_setpoint
Assign SRID to geometries with st_setsrid in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_setsrid
Simplify geometries using st_simplify in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_simplify
Retrieve geometry SRID with st_srid in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_srid
Get first linestring point using st_startpoint	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_startpoint
Test geometry boundary contact with st_touches	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_touches
Transform geometry CRS with st_transform in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_transform
Translate geometries with st_translate in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_translate
Compute geometry union with st_union in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_union
Aggregate geometry unions with st_union_agg in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_union_agg
Check geometry containment with st_within in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_within
Get X coordinate of point with st_x in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_x
Retrieve maximum X of geometry using st_xmax	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_xmax
Retrieve minimum X of geometry using st_xmin	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_xmin
Get Y coordinate of point with st_y in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_y
Retrieve maximum Y of geometry using st_ymax	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_ymax
Retrieve minimum Y of geometry using st_ymin	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_ymin
Get Z coordinate of point with st_z in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_z
Retrieve maximum Z of geometry using st_zmax	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_zmax
Retrieve minimum Z of geometry using st_zmin	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_zmin
Use startswith string function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/startswith
Use std aggregate function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/std
Use stddev aggregate function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/stddev
Use stddev_pop aggregate function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/stddev_pop
Use stddev_samp aggregate function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/stddev_samp
Use str_to_map in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/str_to_map
Use string_agg aggregate function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/string_agg
Create structs with struct function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/struct
Apply sum aggregate in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/sum
Use table_changes function for Delta CDF logs	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/table_changes
Use tan trigonometric function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tan
Use tanh hyperbolic function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tanh
Compute theta_difference on Databricks Theta Sketches	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/theta_difference
Use theta_intersection with Databricks Theta Sketches	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/theta_intersection
Aggregate Theta Sketch intersections in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/theta_intersection_agg
Build Theta Sketch aggregates in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/theta_sketch_agg
Estimate unique counts from Theta Sketches	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/theta_sketch_estimate
Union Theta Sketches with Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/theta_union
Aggregate Theta Sketch unions across partitions	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/theta_union_agg
Use time_diff in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/time_diff
Create TIME from microseconds in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/time_from_micros
Create TIME from milliseconds in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/time_from_millis
Create TIME from seconds in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/time_from_seconds
Get microseconds from TIME in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/time_to_micros
Get milliseconds from TIME in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/time_to_millis
Get seconds from TIME in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/time_to_seconds
Truncate TIME values in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/time_trunc
Convert microseconds to timestamp in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/timestamp_micros
Convert milliseconds to timestamp in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/timestamp_millis
Convert seconds to timestamp in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/timestamp_seconds
Cast expressions to TINYINT in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tinyint
Convert values to BINARY with to_binary	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/to_binary
Format values as strings using to_char	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/to_char
Use Databricks SQL to_date for date parsing	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/to_date
Convert spatial data with to_geometry in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/to_geometry
Convert formatted strings to DECIMAL with to_number	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/to_number
Use Databricks SQL to_time function for time casting	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/to_time
Cast expressions to TIMESTAMP with to_timestamp	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/to_timestamp
Get UNIX epoch from timestamps with to_unix_timestamp	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/to_unix_timestamp
Format values as VARCHAR using to_varchar	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/to_varchar
Convert complex types to VARIANT objects in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/to_variant_object
Transform map keys with transform_keys function	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/transform_keys
Compute averages safely with try_avg aggregate	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/try_avg
Safely access array or map elements with try_element_at	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/try_element_at
Use try_ip_as_binary in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/try_ip_as_binary
Use try_ip_as_string in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/try_ip_as_string
Use try_ip_cidr for CIDR handling in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/try_ip_cidr
Parse timestamps safely with try_parse_timestamp	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/try_parse_timestamp
Retrieve Databricks secrets with try_secret function	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/try_secret
Convert formatted strings to DECIMAL with try_to_number	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/try_to_number
Use try_to_timestamp in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/try_to_timestamp
Compute tuple_difference_double in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_difference_double
Compute tuple_difference_integer in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_difference_integer
Aggregate tuple_intersection_agg_double sketches in SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_intersection_agg_double
Aggregate tuple_intersection_agg_integer sketches in SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_intersection_agg_integer
Use tuple_intersection_double on TupleSketches	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_intersection_double
Use tuple_intersection_integer on TupleSketches	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_intersection_integer
Create TupleSketches with tuple_sketch_agg_double	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_sketch_agg_double
Create TupleSketches with tuple_sketch_agg_integer	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_sketch_agg_integer
Estimate unique keys with tuple_sketch_estimate_double	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_sketch_estimate_double
Estimate unique keys with tuple_sketch_estimate_integer	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_sketch_estimate_integer
Summarize TupleSketch doubles with tuple_sketch_summary_double	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_sketch_summary_double
Summarize TupleSketch integers with tuple_sketch_summary_integer	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_sketch_summary_integer
Union multiple TupleSketches with tuple_union_agg_double	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_union_agg_double
Union multiple TupleSketches with tuple_union_agg_integer	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_union_agg_integer
Merge two TupleSketches with tuple_union_double	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_union_double
Merge two TupleSketches with tuple_union_integer	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/tuple_union_integer
Use unix_timestamp in Azure Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/unix_timestamp
Convert strings to uppercase with Databricks upper	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/upper
Decode URL-encoded strings with url_decode	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/url_decode
Encode strings as URLs in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/url_encode
Unnest VARIANT data with variant_explode in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/variant_explode
Outer explode VARIANT data with variant_explode_outer	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/variant_explode_outer
Use variant_get to extract values from VARIANT columns in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/variant_get
Compute element-wise vector averages with vector_avg in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/vector_avg
Calculate vector norms with vector_norm in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/vector_norm
Normalize vectors with vector_normalize in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/vector_normalize
Use vector_search SQL function with AI Search index	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/vector_search
Compute element-wise vector sums with vector_sum in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/vector_sum
Compute week of year with Databricks weekofyear	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/weekofyear
Bucket numeric values with width_bucket in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/width_bucket
Define sliding time windows with Databricks window	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/window
Get window end time with window_time in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/window_time
Query XML with xpath in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/xpath
Evaluate XML XPath to boolean in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/xpath_boolean
Extract INTEGER values from XML with xpath_int	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/xpath_int
Extract BIGINT values from XML with xpath_long	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/xpath_long
Extract SMALLINT values from XML with xpath_short	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/xpath_short
Extract string node contents with xpath_string	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/xpath_string
Compute 64-bit hashes with xxhash64 in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/xxhash64
Replace NULL with zero using zeroifnull in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/zeroifnull
Merge arrays element-wise with zip_with in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/zip_with
Use zstd_compress in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/zstd_compress
Decompress data with zstd_decompress in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/zstd_decompress
Invoke built-in and user-defined functions in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-function-invocation
Implement user-defined aggregate functions in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-functions-udf-aggregate
Integrate Hive UDFs, UDAFs, UDTFs with Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-functions-udf-hive
Create and register scalar UDFs in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-functions-udf-scalar
Use H3 geospatial SQL functions in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-h3-geospatial-functions
Alphabetical reference of H3 functions in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-h3-geospatial-functions-alpha
Example analytics using H3 functions on Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-h3-geospatial-functions-examples
Work with IP address SQL functions in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-ip-functions
Write and use lambda functions in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-lambda-functions
Use IDENTIFIER clause for safe Databricks SQL parameterization	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-names-identifier-clause
Understand NULL semantics in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-null-semantics
Use parameter markers in Azure Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-parameter-marker
Use SQL/PSM scripting constructs in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-scripting
Use ST geospatial SQL functions in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-st-geospatial-functions
Use CALL to invoke Databricks SQL procedures	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-call
Set and manage QUERY_TAGS in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-conf-mgmt-set-query-tags
GET files from volumes using Databricks SQL Connector	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-connector-get
Upload local files to volumes with PUT INTO	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-connector-put-into
Remove volume files using Databricks SQL Connector REMOVE	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-connector-remove
Use DESCRIBE VOLUME in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-describe-volume
Run dynamic SQL with EXECUTE IMMEDIATE in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-execute-immediate
Use LIST to enumerate objects at a URL in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-list
Add archive resources with ADD ARCHIVE in Databricks Runtime	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-resource-mgmt-add-archive
Add file or directory resources with ADD FILE in Databricks Runtime	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-resource-mgmt-add-file
Add JAR resources with ADD JAR in Databricks Runtime	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-resource-mgmt-add-jar
List added archives with LIST ARCHIVE in Databricks Runtime	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-resource-mgmt-list-archive
Use LIST FILE command in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-resource-mgmt-list-file
Use LIST JAR command in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-resource-mgmt-list-jar
List catalogs with SHOW CATALOGS in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-catalogs
Retrieve table column metadata with SHOW COLUMNS	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-columns
List system connections using SHOW CONNECTIONS in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-connections
Use SHOW DATABASES (SCHEMAS) in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-databases
List functions with SHOW FUNCTIONS in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-functions
Use SHOW GOVERNED TAGS in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-governed-tags
List groups with SHOW GROUPS in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-groups
Enumerate table partitions with SHOW PARTITIONS in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-partitions
Discover stored procedures with SHOW PROCEDURES in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-procedures
List Delta Sharing providers with SHOW PROVIDERS	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-providers
List Delta Sharing recipients with SHOW RECIPIENTS	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-recipients
List schemas with SHOW SCHEMAS in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-schemas
Use SHOW SHARES command in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-shares
Use SHOW SHARES IN PROVIDER in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-shares-in-provider
Inspect detailed table metadata with SHOW TABLE EXTENDED	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-table
List tables with SHOW TABLES in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-tables
List users with SHOW USERS in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-users
List views with SHOW VIEWS in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-views
Add comments and hints in Databricks SQL statements	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-comment
Project columns with SELECT clause in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-column-list
Filter grouped results with HAVING in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-having
Join tables using Databricks SQL JOIN	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-join
Use and migrate from LATERAL VIEW in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-lateral-view
Limit query result rows in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-limit
Paginate results with OFFSET in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-offset
Sort query results with ORDER BY in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-orderby
Transform rows with PIVOT in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-pivot
Invoke table-valued functions in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-tvf
Use UNPIVOT to rotate columns in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-unpivot
Filter rows with WHERE in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-where
Use mustache parameters in Databricks legacy SQL editor	https://learn.microsoft.com/en-us/azure/databricks/sql/user/sql-editor/mustache-parameters
Example Databricks transformWithState streaming applications	https://learn.microsoft.com/en-us/azure/databricks/stateful-applications/examples
Use Avro with Kafka streaming in Databricks	https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/avro-dataframe
Structured Streaming integration patterns with external systems	https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/examples
Use foreachBatch for custom streaming sinks	https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/foreach
Write streaming data to Lakebase from Databricks	https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/lakebase
Process protocol buffers with Databricks Structured Streaming	https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/protocol-buffers
Use real-time mode with Kafka and custom sinks	https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/real-time/examples
Use change data feed for Delta and Iceberg tables	https://learn.microsoft.com/en-us/azure/databricks/tables/features/change-data-feed
Create Scala user-defined aggregate functions in Databricks	https://learn.microsoft.com/en-us/azure/databricks/udf/aggregate-scala
Create and use pandas UDFs in Databricks	https://learn.microsoft.com/en-us/azure/databricks/udf/pandas
Implement and register Python UDFs in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/udf/python
Define Python user-defined table functions in Databricks	https://learn.microsoft.com/en-us/azure/databricks/udf/python-udtf
Implement Scala scalar UDFs for Spark SQL	https://learn.microsoft.com/en-us/azure/databricks/udf/scala
Access task context inside Databricks UDFs	https://learn.microsoft.com/en-us/azure/databricks/udf/udf-task-context
Register and use Python UDTFs in Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/udf/udtf-unity-catalog
Store and process unstructured data in Databricks volumes	https://learn.microsoft.com/en-us/azure/databricks/volumes/unstructured-data-tutorial
Create and manage Unity Catalog volumes with SQL	https://learn.microsoft.com/en-us/azure/databricks/volumes/utility-commands
Manage files in Unity Catalog volumes across tools	https://learn.microsoft.com/en-us/azure/databricks/volumes/volume-files

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MicrosoftDocs/azure-databricks — integrations.md

Azure Databricks — Integrations & Coding Patterns

Integrations & Coding Patterns