integrations.md

Azure Databricks — Integrations & Coding Patterns

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Integrations & Coding Patterns

Topic	URL
Query Databricks billable usage for storage cost tracking	https://learn.microsoft.com/en-us/azure/databricks/admin/usage/default-storage
Manage AI/BI assets using Databricks REST APIs	https://learn.microsoft.com/en-us/azure/databricks/ai-bi/admin/use-apis
Use legacy ABS-AQS streaming connector in 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 connector for Databricks	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 the Databricks JDBC connector to query another workspace	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
Read and write data between Azure Databricks and Snowflake	https://learn.microsoft.com/en-us/azure/databricks/archive/connectors/snowflake
Read and write XML data in Databricks using spark-xml	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
Configure Azure Databricks connector for 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 Microsoft Excel to Azure Databricks using ODBC	https://learn.microsoft.com/en-us/azure/databricks/archive/integrations/excel
Drop legacy Delta Lake table features in Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/legacy/drop-feature-legacy
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
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
Integrate Infoworks DataFoundry with Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/partners/infoworks
Connect Spotfire Analyst to Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/partners/spotfire
Use Syncsort (Precisely) with Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/partners/syncsort
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
Connect Azure Databricks to ADLS and Blob using ABFS	https://learn.microsoft.com/en-us/azure/databricks/archive/storage/azure-storage
Configure legacy cloud object storage access for Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/archive/storage/connect-storage-index
Connect Azure Databricks to Google Cloud Storage	https://learn.microsoft.com/en-us/azure/databricks/archive/storage/gcs
Connect Azure Databricks to Azure Data Lake Storage with OAuth	https://learn.microsoft.com/en-us/azure/databricks/archive/storage/tutorial-azure-storage
Configure legacy WASB connector for Azure Blob Storage	https://learn.microsoft.com/en-us/azure/databricks/archive/storage/wasb-blob
Implement advanced metric view calculations in Databricks	https://learn.microsoft.com/en-us/azure/databricks/business-semantics/metric-views/advanced-techniques
Use LOD expressions in Databricks metric views	https://learn.microsoft.com/en-us/azure/databricks/business-semantics/metric-views/level-of-detail
Configure Azure Databricks connections to external data	https://learn.microsoft.com/en-us/azure/databricks/connect/
Configure JDBC Unity Catalog connections to external databases	https://learn.microsoft.com/en-us/azure/databricks/connect/jdbc-connection
Connect Azure Databricks streaming to Apache Kafka	https://learn.microsoft.com/en-us/azure/databricks/connect/streaming/kafka/
Integrate Google Pub/Sub with Azure Databricks streaming	https://learn.microsoft.com/en-us/azure/databricks/connect/streaming/pub-sub
Configure Apache Pulsar streaming source on 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
Embed Azure Databricks dashboards in external apps	https://learn.microsoft.com/en-us/azure/databricks/dashboards/share/embedding/
Implement basic iframe embedding for Databricks dashboards	https://learn.microsoft.com/en-us/azure/databricks/dashboards/share/embedding/basic
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 Databricks-to-Databricks Delta Sharing data	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/read-data-databricks
Consume Delta Sharing open shares with bearer tokens	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/read-data-open
Integrate SAP BDC with Azure Databricks via Delta Sharing	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/sap-bdc/
Configure Delta Sharing access for SAP BDC recipients	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/sap-bdc/share-to-sap
Use Python M2M OIDC federation to access Delta Sharing	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/sharing-over-oidc-m2m
Use U2M OIDC federation clients with Delta Sharing	https://learn.microsoft.com/en-us/azure/databricks/delta-sharing/sharing-over-oidc-u2m
Use MERGE to upsert into Delta tables on Databricks	https://learn.microsoft.com/en-us/azure/databricks/delta/merge
Use Databricks CLI bundle commands for deployments	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/bundle-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 via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-billable-usage-commands
Manage Databricks account resources via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/account-commands
Use Databricks CLI alerts command group	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/alerts-commands
Call Databricks REST APIs with CLI api command	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/api-commands
Manage Databricks Apps using CLI commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/apps-commands
Manage Unity Catalog artifact allowlists via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/artifact-allowlists-commands
Configure Databricks CLI authentication with auth commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/auth-commands
Manage Unity Catalog catalogs with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/catalogs-commands
Manage clean room assets via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/clean-room-assets-commands
Control clean room task runs with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/clean-room-task-runs-commands
Administer clean rooms using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/clean-rooms-commands
Manage cluster policies with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/cluster-policies-commands
Create and manage Databricks clusters via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/clusters-commands
Manage external data connections with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/connections-commands
Manage consumer fulfillments in Databricks Marketplace via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/consumer-fulfillments-commands
Control consumer installations for Marketplace via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/consumer-installations-commands
Manage consumer listings in Databricks Marketplace via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/consumer-listings-commands
Handle consumer personalization requests via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/consumer-personalization-requests-commands
Use Databricks CLI consumer-providers Marketplace commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/consumer-providers-commands
Retrieve current user information via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/current-user-commands
Manage MLflow experiments using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/experiments-commands
Manage Databricks feature store via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/feature-engineering-commands
Use Databricks CLI fs commands for DBFS and volumes	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/fs-commands
Manage Unity Catalog user-defined functions via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/functions-commands
Use Databricks CLI genie commands for Genie spaces	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/genie-commands
Configure Git credentials for Databricks via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/git-credentials-commands
Manage Databricks instance pools using CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/instance-pools-commands
Create and manage Databricks jobs via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/jobs-commands
Use Databricks CLI labs commands for experimental apps	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/labs-commands
Manage Lakeview dashboards with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/lakeview-commands
Manage Databricks libraries via CLI commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/libraries-commands
Administer Unity Catalog metastores using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/metastores-commands
Use CLI model-registry commands for workspace models	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/model-registry-commands
Manage Unity Catalog model versions with 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 using CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/online-tables-commands
Control Databricks pipelines with CLI commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/pipelines-commands
Manage Lakebase Postgres resources with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/postgres-commands
Manage marketplace exchange filters with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/provider-exchange-filters-commands
Administer Databricks marketplace exchanges via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/provider-exchanges-commands
Manage Databricks marketplace files using CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/provider-files-commands
Use Databricks CLI provider-listings marketplace commands	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 Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/provider-provider-analytics-dashboards-commands
Administer Databricks marketplace providers using CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/provider-providers-commands
Manage Delta Sharing providers with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/providers-commands
Connect to Databricks Postgres instances with psql CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/psql-command
Configure Databricks quality monitors via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/quality-monitors-commands
Create and manage Databricks SQL queries with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/queries-commands
Use deprecated queries-legacy commands in CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/queries-legacy-commands
Access Databricks SQL query history using CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/query-history-commands
Retrieve Delta Sharing recipient activation via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/recipient-activation-commands
Manage Unity Catalog share recipients with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/recipients-commands
Administer Unity Catalog registered models via CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/registered-models-commands
Manage Databricks Git repos (folders) using CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/repos-commands
Manage Unity Catalog schemas with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/schemas-commands
Manage Databricks model serving endpoints with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/serving-endpoints-commands
Manage Unity Catalog shares using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/shares-commands
Use Databricks CLI ssh commands for remote development	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/ssh-commands
Use Databricks CLI storage-credentials commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/storage-credentials-commands
Sync local files with Databricks CLI sync command	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/sync-commands
Manage system schemas with Databricks CLI commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/system-schemas-commands
Manage table constraints via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/table-constraints-commands
Manage Unity Catalog tables with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/tables-commands
Administer governed tag policies with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/tag-policies-commands
Generate temporary path credentials with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/temporary-path-credentials-commands
Generate temporary table credentials with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/temporary-table-credentials-commands
Administer token management using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/token-management-commands
Create and revoke tokens with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/tokens-commands
Manage Databricks users with CLI users commands	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/users-commands
Manage vector search endpoints via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/vector-search-endpoints-commands
Manage vector search indexes with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/vector-search-indexes-commands
Check Databricks CLI version with version command	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/version-command
Manage Unity Catalog volumes using Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/volumes-commands
Manage SQL warehouses with Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/warehouses-commands
Configure Unity Catalog workspace bindings with CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/workspace-bindings-commands
Manage workspace files and folders via Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/cli/reference/workspace-commands
Update advanced workspace settings via Databricks 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
Implement user-defined functions with Databricks Connect Python	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/python/udf
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
Install Databricks Connect client for Scala	https://learn.microsoft.com/en-us/azure/databricks/dev-tools/databricks-connect/scala/install
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
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
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 documents using Databricks Document Parsing	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-bricks/document-parsing
Create information extraction agents with Databricks	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-bricks/key-info-extraction
Orchestrate Databricks multi-agent systems with Supervisor	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-bricks/multi-agent-supervisor
Implement Databricks AI agent tools with MCP and Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/agent-tool
Integrate Anthropic SDK with Databricks Unity Catalog tools	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/anthropic-uc-integration
Use the Databricks Python code interpreter tool in AI agents	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/code-interpreter-tools
Create custom 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 services and APIs	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/external-connection-tools
Integrate LangChain workflows with Unity Catalog tools	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/langchain-uc-integration
Integrate LlamaIndex workflows with Databricks Unity Catalog tools	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/llamaindex-uc-integration
Integrate OpenAI workflows with Databricks Unity Catalog tools	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/openai-uc-integration
Query Databricks agents via REST and SDK 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 AI agents to structured data sources	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/structured-retrieval-tools
Integrate Databricks AI agents with Microsoft Teams via OAuth OBO	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/teams-agent
Use Unity Catalog tools with third-party gen AI frameworks	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/unity-catalog-tool-integration
Connect Databricks AI agents to unstructured data with Vector Search	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/agent-framework/unstructured-retrieval-tools
Use Databricks managed MCP servers to connect agents to data	https://learn.microsoft.com/en-us/azure/databricks/generative-ai/mcp/managed-mcp
Connect Genie Code to external MCP servers	https://learn.microsoft.com/en-us/azure/databricks/genie-code/mcp
Integrate Genie natural language querying via API	https://learn.microsoft.com/en-us/azure/databricks/genie/conversation-api
Incrementally clone Parquet and Iceberg to Delta Lake	https://learn.microsoft.com/en-us/azure/databricks/ingestion/data-migration/clone-parquet
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
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 data from SFTP using Lakeflow Connect	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 data with 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 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 Databricks data from Google Sheets with SQL	https://learn.microsoft.com/en-us/azure/databricks/integrations/google-sheets/query-data
Use GraphFrames with Scala on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/integrations/graphframes/user-guide-scala
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
Manage Unity Catalog volume files via legacy 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 Databricks Genie MCP server to Microsoft Foundry	https://learn.microsoft.com/en-us/azure/databricks/integrations/microsoft-foundry
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
Automate Databricks job management with CLI, SDK, and REST	https://learn.microsoft.com/en-us/azure/databricks/jobs/automate
Orchestrate dbt platform jobs with Azure Databricks dbt platform tasks	https://learn.microsoft.com/en-us/azure/databricks/jobs/dbt-platform
Orchestrate Lakeflow Jobs with Apache Airflow integration	https://learn.microsoft.com/en-us/azure/databricks/jobs/how-to/use-airflow-with-jobs
Integrate dbt Core transformations with Lakeflow Jobs	https://learn.microsoft.com/en-us/azure/databricks/jobs/how-to/use-dbt-in-workflows
Configure Python wheel tasks in Lakeflow Jobs workflows	https://learn.microsoft.com/en-us/azure/databricks/jobs/how-to/use-python-wheels-in-workflows
Access Databricks job parameters from task code	https://learn.microsoft.com/en-us/azure/databricks/jobs/parameter-use
Configure Power BI tasks to orchestrate semantic models from Databricks	https://learn.microsoft.com/en-us/azure/databricks/jobs/powerbi
Pass task values between Databricks job tasks	https://learn.microsoft.com/en-us/azure/databricks/jobs/task-values
Use Azure Databricks AI Functions from SQL and Python	https://learn.microsoft.com/en-us/azure/databricks/large-language-models/ai-functions
Call ai_query to access AI models in Databricks	https://learn.microsoft.com/en-us/azure/databricks/large-language-models/ai-query
Use LangChain integrations with Databricks LLMs	https://learn.microsoft.com/en-us/azure/databricks/large-language-models/langchain
Clone Hive metastore pipelines to Unity Catalog via REST	https://learn.microsoft.com/en-us/azure/databricks/ldp/clone-hms-to-uc
Replicate external RDBMS tables with AUTO CDC	https://learn.microsoft.com/en-us/azure/databricks/ldp/database-replication
Create and manage Databricks SQL materialized views	https://learn.microsoft.com/en-us/azure/databricks/ldp/dbsql/materialized
Define Lakeflow pipeline datasets with Python decorators	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/definition-function
Use append_flow decorator for pipeline append-only flows	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-append-flow
Use create_auto_cdc_flow for pipeline CDC processing	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-apply-changes
Use create_auto_cdc_from_snapshot_flow for snapshot CDC	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-apply-changes-from-snapshot
Apply data quality expectations in Lakeflow Python pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-expectations
Define materialized views in pipelines with Python	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-materialized-view
Use create_sink in Lakeflow pipelines for Kafka and Delta	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-sink
Create streaming tables in Lakeflow pipelines with Python	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-streaming-table
Define streaming tables in pipelines with @table decorator	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-table
Create temporary views in pipelines with Python decorators	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-python-ref-view
Use AUTO CDC INTO in Lakeflow pipeline SQL	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-sql-ref-apply-changes-into
Create pipeline flows with CREATE FLOW SQL	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-sql-ref-create-flow
Create materialized views in pipelines with SQL	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-sql-ref-create-materialized-view
Configure REFRESH POLICY for pipeline materialized views	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-sql-ref-create-materialized-view-refresh-policy
Create streaming tables in pipelines with SQL	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-sql-ref-create-streaming-table
Create temporary views in pipelines with SQL	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-sql-ref-create-temporary-view
Use CREATE VIEW in Lakeflow pipelines SQL	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/ldp-sql-ref-create-view
Develop Lakeflow pipeline logic with Python APIs	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/python-dev
Reference for Lakeflow Python pipeline APIs	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 Spark pipelines	https://learn.microsoft.com/en-us/azure/databricks/ldp/developer/sql-ref
Use Azure Event Hubs as a Lakeflow data source	https://learn.microsoft.com/en-us/azure/databricks/ldp/event-hubs
Use ForEachBatch sink in Lakeflow streaming pipelines	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
Develop and debug Databricks pipelines using legacy notebooks	https://learn.microsoft.com/en-us/azure/databricks/ldp/notebook-devex
Run Lakeflow pipelines from Jobs, Airflow, or Data Factory	https://learn.microsoft.com/en-us/azure/databricks/ldp/workflows
Use Serverless GPU Python API for multi-GPU training	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/distributed-training
Get started with H100 serverless GPU using serverless_gpu API	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
Distributed fine-tuning of gpt-oss-20b on Databricks	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	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-distributed-pytorch-fsdp
Distributed Unsloth finetuning of Llama-3.2-3B on Databricks	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
Distributed GPT-OSS 120B finetuning with DDP/FSDP on Databricks	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	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 serverless GPU	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-olmo3-7b-lora-axolotl
Distributed two-tower recommender training with Lightning on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-recommender-system-lightning
Train RetinaNet object detection model on Databricks	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 LoRA and DeepSpeed	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 model on Databricks GPU	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/ai-runtime/examples/tutorials/sgc-xgboost
Use Hyperopt with distributed training on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl-hyperparam-tuning/hyperopt-distributed-ml
Use Hyperopt and MLflow for model selection on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl-hyperparam-tuning/hyperopt-model-selection
Parallelize Hyperopt tuning with Spark and MLflow	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl-hyperparam-tuning/hyperopt-spark-mlflow-integration
Scale Optuna hyperparameter tuning with MLflow on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl-hyperparam-tuning/optuna
Use the Databricks AutoML Python API for runs	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/automl-api-reference
Use AutoML Python API for classification on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/classification-train-api
Integrate Databricks Feature Store with AutoML experiments	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/feature-store-integration
Use AutoML Python API for forecasting on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/forecasting-train-api
Use AutoML Python API for regression on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/automl/regression-train-api
Implement on-demand feature computation with UDFs	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/on-demand-features
Publish Databricks feature tables to third-party online stores	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/publish-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 and run batch inference with Databricks feature tables	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/feature-store/train-models-with-feature-store
Use Databricks Foundation Model REST APIs	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/foundation-model-apis/api-reference
Use Mosaic Streaming to load Spark data into PyTorch	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/load-data/streaming
Save and load TFRecord data with Spark on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/load-data/tfrecords-save-load
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 logic 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
Call provider-native OpenAI, Anthropic, and Gemini APIs on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/provider-native-apis
Query Databricks Anthropic models with Messages API	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/query-anthropic-messages
Write and send chat model queries on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/query-chat-models
Query embedding models via Databricks endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/query-embedding-models
Integrate Google Gemini API with Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/query-gemini-api
Use OpenAI Responses API with Databricks endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/query-openai-responses
Query reasoning models using 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
Query vision foundation models via Databricks endpoints	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 query requests to Databricks foundation models	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/score-foundation-models
Use structured outputs with Databricks LLM endpoints	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/structured-outputs
Use web search grounding with Databricks models	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/model-serving/web-search
Featurize data for transfer learning with pandas UDFs on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/preprocess-data/transfer-learning-tensorflow
Combine Spark and Ray in one Databricks environment	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
Run NLP workloads with Spark NLP on Databricks	https://learn.microsoft.com/en-us/azure/databricks/machine-learning/reference-solutions/natural-language-processing
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 using pyspark.ml.connect with 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
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	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
Use Databricks Workspace Model Registry webhooks	https://learn.microsoft.com/en-us/azure/databricks/mlflow/model-registry-webhooks
Examples of custom code-based scorers for GenAI	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/code-based-scorer-examples
Use relevance judges for RAG context evaluation	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/concepts/judges/is_context_relevant
Simulate conversations to test conversational agents	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/conversation-simulation
Tutorial: Build a custom judge for GenAI agents	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/custom-judge/create-custom-judge
Evaluate multi-turn conversations with MLflow judges	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/eval-monitor/evaluate-conversations
Test GenAI apps with MLflow Review App Chat UI	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/human-feedback/expert-feedback/live-app-testing
Use MLflow Prompt Registry operations with code examples	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/prompt-version-mgmt/prompt-registry/examples
Add contextual metadata to MLflow traces	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/add-context-to-traces
Tutorial: Track users and environments in MLflow traces	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/add-context-to-traces-tutorial
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 low-level MlflowClient APIs for advanced 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/
Log and analyze GenAI user feedback with MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/collect-user-feedback/
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
Trace Anthropic LLM calls with MLflow autologging	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/anthropic
Enable MLflow tracing for AutoGen multi-agent systems	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
Trace Claude Code conversations with MLflow	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 model calls using MLflow OpenAI integration	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/deepseek
Enable MLflow tracing for DSPy modular AI systems	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 with MLflow autologging	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
Enable MLflow tracing for LangChain applications	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/langchain
Trace LangGraph agent workflows using MLflow LangChain autolog	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
Integrate MLflow tracing with LlamaIndex GenAI apps	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
Automatically trace OpenAI calls with MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/openai
Trace OpenAI Agents SDK with MLflow autologging	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 workflows using MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/semantic-kernel
Trace Smolagents runs with MLflow autologging	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/smolagents
Enable MLflow tracing for Strands Agents SDK	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/strands
Use MLflow tracing with deprecated OpenAI Swarm	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/swarm
Trace txtai embeddings and LLM workflows with MLflow	https://learn.microsoft.com/en-us/azure/databricks/mlflow3/genai/tracing/integrations/txtai
Use MLflow MCP server to manage traces	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 MLflow GenAI traces programmatically via 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
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
Use Genie Code agent for Databricks data science	https://learn.microsoft.com/en-us/azure/databricks/notebooks/ds-agent
Use Databricks notebook features for code development	https://learn.microsoft.com/en-us/azure/databricks/notebooks/notebooks-code
Share and modularize code across Databricks notebooks	https://learn.microsoft.com/en-us/azure/databricks/notebooks/share-code
Connect to and query Lakebase database instances	https://learn.microsoft.com/en-us/azure/databricks/oltp/instances/query/
Query Lakebase instances from Databricks notebooks	https://learn.microsoft.com/en-us/azure/databricks/oltp/instances/query/notebook
Connect external SQL clients to Lakebase instances	https://learn.microsoft.com/en-us/azure/databricks/oltp/instances/query/psql
Register Lakebase instances with Unity Catalog	https://learn.microsoft.com/en-us/azure/databricks/oltp/instances/register-uc
Integrate Lakebase with Unity Catalog and synced data	https://learn.microsoft.com/en-us/azure/databricks/oltp/instances/sync-data/
Use Lakebase Autoscaling APIs, CLI, and SDKs	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/api-usage
Manage Lakebase with the Databricks CLI	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/cli
Connect to Lakebase using DBeaver	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/connect-dbeaver
Connect and monitor Lakebase with pgAdmin	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/connect-pgadmin
Monitor Lakebase Postgres performance with PgHero	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/connect-pghero
Connect to Lakebase Postgres using psql	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/connect-psql
Use Lakebase Data API for RESTful Postgres access	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	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/external-apps-connect
Connect external apps to Lakebase via REST API	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/external-apps-manual-api
Integrate external monitoring tools with Lakebase Postgres	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/external-monitoring-tools
Back Databricks Online Feature Stores with Lakebase	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/feature-store
Use frameworks to connect to Lakebase	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/framework-examples
Backup and restore Lakebase with pg_dump/pg_restore	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/pg-dump-restore
Use Postgres clients with Lakebase databases	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/postgres-clients
Query Lakebase from Lakehouse SQL editor	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/query-sql-editor
Store AI agent state in Lakebase Postgres	https://learn.microsoft.com/en-us/azure/databricks/oltp/projects/state-management
Apply pandas function APIs to PySpark DataFrames	https://learn.microsoft.com/en-us/azure/databricks/pandas/pandas-function-apis
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
Read Unity Catalog data from Microsoft Fabric	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/fabric
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 vs ODBC drivers for Power BI with Databricks	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
Publish Azure Databricks datasets to Power BI service	https://learn.microsoft.com/en-us/azure/databricks/partners/bi/power-bi-service
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
Integrate Tableau Desktop/Cloud with 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
Set up Fivetran integration with Azure Databricks	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 ML 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 Catalog.clearCache	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/clearcache
Create tables using Catalog.createTable in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/createtable
Get current catalog with Catalog.currentCatalog	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/currentcatalog
Get current database with Catalog.currentDatabase	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/currentdatabase
Check database existence with Catalog.databaseExists	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/databaseexists
Drop global temp views with Catalog.dropGlobalTempView	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/dropglobaltempview
Drop local temp views with Catalog.dropTempView	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/droptempview
Check function existence with Catalog.functionExists	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/functionexists
Retrieve databases with Catalog.getDatabase in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/getdatabase
Retrieve functions with Catalog.getFunction in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/getfunction
Retrieve tables and views with Catalog.getTable	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/gettable
Check table cache status with Catalog.isCached	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/iscached
List catalogs in session with Catalog.listCatalogs	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/listcatalogs
List table columns with Catalog.listColumns	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/listcolumns
List databases with Catalog.listDatabases in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/listdatabases
List registered functions with Catalog.listFunctions	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/listfunctions
List tables and views with Catalog.listTables	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/listtables
Recover table partitions with Catalog.recoverPartitions	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/recoverpartitions
Refresh cached data by path with Catalog.refreshByPath	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/refreshbypath
Refresh cached tables with Catalog.refreshTable	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/refreshtable
Use Catalog.setCurrentCatalog in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/setcurrentcatalog
Use Catalog.setCurrentDatabase in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/setcurrentdatabase
Check table existence with Catalog.tableExists in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/tableexists
Remove cached tables with Catalog.uncacheTable in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/catalog/uncachetable
Work with the Column class in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column
Assign aliases to columns with Column.alias in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/alias
Sort columns ascending with Column.asc in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/asc
Sort ascending with nulls first using Column.asc_nulls_first	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/asc_nulls_first
Sort ascending with nulls last using Column.asc_nulls_last	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/asc_nulls_last
Cast column types with Column.astype in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/astype
Filter values within ranges using Column.between in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/between
Compute bitwise AND with Column.bitwiseAND in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/bitwiseand
Compute bitwise OR with Column.bitwiseOR in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/bitwiseor
Compute bitwise XOR with Column.bitwiseXOR in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/bitwisexor
Change column data types with Column.cast in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/cast
Check substring presence with Column.contains in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/contains
Sort columns descending with Column.desc in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/desc
Sort descending with nulls first using Column.desc_nulls_first	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/desc_nulls_first
Sort descending with nulls last using Column.desc_nulls_last	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/desc_nulls_last
Remove struct fields with Column.dropFields in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/dropfields
Check string suffixes with Column.endswith in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/endswith
Perform null-safe equality with Column.eqNullSafe in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/eqnullsafe
Access struct fields with Column.getField in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/getfield
Access array or map elements with Column.getItem in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/getitem
Use case-insensitive pattern matching with Column.ilike in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/ilike
Test membership in value lists with Column.isin in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/isin
Detect NaN values with Column.isNaN in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/isnan
Filter non-null values with Column.isNotNull in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/isnotnull
Filter null values with Column.isNull in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/isnull
Use SQL LIKE pattern matching with Column.like in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/like
Rename columns using Column.name alias in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/name
Provide default values with Column.otherwise in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/otherwise
Apply window specifications with Column.over in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/over
Use regex pattern matching with Column.rlike in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/rlike
Check string prefixes with Column.startswith in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/startswith
Extract substrings with Column.substr in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/substr
Safely cast column types with Column.try_cast in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/try_cast
Implement conditional logic with Column.when in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/when
Add or replace struct fields with Column.withField in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/column/withfield
Use the DataFrame class in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe
Use DataFrame.agg for aggregations in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/agg
Apply aliases to DataFrames with alias() in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/alias
Compute approximate quantiles with DataFrame.approxQuantile	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/approxquantile
Convert DataFrames to table arguments with asTable	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/astable
Cache DataFrames with default storage level in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/cache
Checkpoint DataFrames and manage logical plans in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/checkpoint
Repartition DataFrames with coalesce(numPartitions)	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/coalesce
Collect all DataFrame rows into driver with collect()	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/collect
Select columns by regex with DataFrame.colRegex	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/colregex
Access DataFrame column names via columns property	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/columns
Compute column correlation with DataFrame.corr	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/corr
Count DataFrame rows with count() in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/count
Calculate sample covariance with DataFrame.cov	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/cov
Create global temporary views from DataFrames	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/createglobaltempview
Create or replace global temp views with DataFrames	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/createorreplaceglobaltempview
Create or replace local temp views from DataFrames	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/createorreplacetempview
Create local temporary views with createTempView	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/createtempview
Perform cartesian products with DataFrame.crossJoin	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/crossjoin
Build contingency tables with DataFrame.crosstab	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/crosstab
Create aggregation cubes with DataFrame.cube	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/cube
Compute basic column statistics with DataFrame.describe	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/describe
Return distinct DataFrame rows with distinct()	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/distinct
Drop DataFrame columns with drop() in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/drop
Remove duplicate rows with DataFrame.dropDuplicates	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/dropduplicates
Drop duplicates within watermark in streaming DataFrames	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/dropduplicateswithinwatermark
Drop null or NaN rows with DataFrame.dropna	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/dropna
Inspect DataFrame column names and types via dtypes	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/dtypes
Subtract DataFrames with duplicates using exceptAll	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/exceptall
Inspect query execution details with DataFrame.executionInfo	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/executioninfo
Build EXISTS subqueries with DataFrame.exists	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/exists
Print logical and physical plans with DataFrame.explain	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/explain
Fill null values in DataFrames with fillna()	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/fillna
Filter DataFrame rows with filter() conditions	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/filter
Retrieve the first row of a DataFrame with first()	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/first
Apply functions to each DataFrame row with foreach()	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/foreach
Process DataFrame partitions with foreachPartition()	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/foreachpartition
Find frequent items in columns with DataFrame.freqItems	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/freqitems
Group DataFrames for aggregation with groupBy()	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/groupby
Create multi-dimensional aggregations with groupingSets()	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/groupingsets
Return first n rows of a DataFrame with head()	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/head
Use DataFrame.hint for query optimization in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/hint
Retrieve composing files with DataFrame.inputFiles	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/inputfiles
Compute DataFrame intersections with intersect	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/intersect
Preserve duplicates using DataFrame.intersectAll	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/intersectall
Check for empty DataFrames with isEmpty	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/isempty
Detect local collect capability with isLocal	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/islocal
Work with streaming DataFrames using isStreaming	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/isstreaming
Join DataFrames with DataFrame.join in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/join
Perform lateral joins with DataFrame.lateralJoin	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/lateraljoin
Limit DataFrame result rows with limit	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/limit
Use localCheckpoint for DataFrame logical plan truncation	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/localcheckpoint
Apply Arrow-based batch transforms with mapInArrow	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/mapinarrow
Apply pandas batch transforms with mapInPandas	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/mapinpandas
Unpivot wide DataFrames using melt/unpivot	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/melt
Merge source changes into target tables with mergeInto	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/mergeinto
Access logical metadata columns with metadataColumn	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/metadatacolumn
Handle missing values via DataFrame.na functions	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/na
Define and capture DataFrame metrics with observe	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/observe
Skip initial rows using DataFrame.offset	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/offset
Sort DataFrames using orderBy/sort aliases	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/orderby
Convert PySpark DataFrames to pandas-on-Spark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/pandas_api
Create visualizations with DataFrame.plot accessor	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/plot
Inspect DataFrame schemas with printSchema	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/printschema
Randomly split DataFrames with randomSplit	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/randomsplit
Access underlying RDDs via DataFrame.rdd	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/rdd
Hash partition DataFrames with repartition	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/repartition
Partition DataFrames by column identifier with repartitionById	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/repartitionbyid
Range partition DataFrames with repartitionByRange	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/repartitionbyrange
Replace values in DataFrames with replace	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/replace
Create multi-dimensional aggregations with rollup	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/rollup
Compare DataFrame logical plans with sameSemantics	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/samesemantics
Sample subsets of DataFrames with sample	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/sample
Perform stratified sampling with sampleBy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/sampleby
Use scalar subqueries via DataFrame.scalar	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/scalar
Inspect DataFrame schema via schema property	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/schema
Project columns and expressions with select	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/select
Project SQL expressions with selectExpr	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/selectexpr
Generate logical plan hashes with semanticHash	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/semantichash
Display DataFrame rows in console with show	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/show
Use DataFrame.sort in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/sort
Use sortWithinPartitions for partitioned sorting	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/sortwithinpartitions
Access DataFrame.sparkSession in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/sparksession
Use DataFrame.stat for statistics in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/stat
Check DataFrame.storageLevel in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/storagelevel
Use DataFrame.subtract to diff DataFrames	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/subtract
Compute DataFrame.summary statistics in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/summary
Use DataFrame.tail to get last rows	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/tail
Use DataFrame.take to get first rows	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/take
Reconcile DataFrame schema with to() in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/to
Convert DataFrame to PyArrow Table in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/toarrow
Rename DataFrame columns with toDF in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/todf
Convert DataFrame to JSON RDD in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/tojson
Iterate over all DataFrame rows with toLocalIterator	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/tolocaliterator
Convert Spark DataFrame to pandas in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/topandas
Chain custom DataFrame.transform operations	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/transform
Transpose a DataFrame in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/transpose
Union two DataFrames with union in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/union
Union DataFrames by column name with unionByName	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/unionbyname
Unpersist a DataFrame in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/unpersist
Unpivot wide DataFrames to long format in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/unpivot
Filter DataFrames using where alias in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/where
Add or replace columns with withColumn in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/withcolumn
Rename a DataFrame column with withColumnRenamed	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/withcolumnrenamed
Add multiple columns with withColumns in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/withcolumns
Rename multiple columns with withColumnsRenamed	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/withcolumnsrenamed
Update column metadata with withMetadata in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/withmetadata
Define event-time watermarks with withWatermark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/withwatermark
Write non-streaming DataFrames to storage in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/write
Write streaming DataFrames with writeStream in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/writestream
Configure v2 data source writes with writeTo	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframe/writeto
Handle nulls with DataFrameNaFunctions in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframenafunctions
Drop null or NaN rows with DataFrameNaFunctions.drop	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframenafunctions/drop
Fill null values with DataFrameNaFunctions.fill	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframenafunctions/fill
Replace values with DataFrameNaFunctions.replace	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframenafunctions/replace
Load data with DataFrameReader in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader
Read CSV files with DataFrameReader.csv in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/csv
Read Excel files using DataFrameReader.excel in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/excel
Specify input data source format with DataFrameReader.format	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/format
Read database tables via JDBC with DataFrameReader.jdbc	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/jdbc
Read JSON and JSON Lines with DataFrameReader.json	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/json
Load data from sources with DataFrameReader.load	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/load
Set single input option with DataFrameReader.option	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/option
Set multiple input options with DataFrameReader.options	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/options
Read ORC files with DataFrameReader.orc in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/orc
Read Parquet files with DataFrameReader.parquet	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/parquet
Define input schema with DataFrameReader.schema	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/schema
Load tables as DataFrames with DataFrameReader.table	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/table
Read text files with DataFrameReader.text in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/text
Read XML files with DataFrameReader.xml in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframereader/xml
Use DataFrameStatFunctions for statistics in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframestatfunctions
Compute approximate quantiles with approxQuantile	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframestatfunctions/approxquantile
Calculate column correlation with DataFrameStatFunctions.corr	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframestatfunctions/corr
Compute sample covariance with DataFrameStatFunctions.cov	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframestatfunctions/cov
Generate crosstab frequency tables with DataFrameStatFunctions.crosstab	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframestatfunctions/crosstab
Use freqItems for frequent value detection in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframestatfunctions/freqitems
Stratified sampling with sampleBy in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframestatfunctions/sampleby
Write DataFrames with DataFrameWriter in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter
Bucket output data with DataFrameWriter.bucketBy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/bucketby
Cluster data for performance with DataFrameWriter.clusterBy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/clusterby
Write CSV files with DataFrameWriter.csv in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/csv
Write Excel files with DataFrameWriter.excel in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/excel
Specify output data source with DataFrameWriter.format	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/format
Insert DataFrame rows into tables with DataFrameWriter.insertInto	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/insertinto
Write DataFrames to databases via DataFrameWriter.jdbc	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/jdbc
Write JSON output with DataFrameWriter.json in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/json
Control overwrite behavior with DataFrameWriter.mode	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/mode
Set single output option with DataFrameWriter.option	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/option
Set multiple output options with DataFrameWriter.options	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/options
Write ORC files with DataFrameWriter.orc in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/orc
Write Parquet output with DataFrameWriter.parquet	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/parquet
Partition output data with DataFrameWriter.partitionBy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/partitionby
Save DataFrames to data sources with DataFrameWriter.save	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/save
Save DataFrames as tables with DataFrameWriter.saveAsTable	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/saveastable
Sort bucketed output with DataFrameWriter.sortBy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/sortby
Write text files with DataFrameWriter.text in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/text
Write XML files with DataFrameWriter.xml in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriter/xml
Write tables using DataFrameWriterV2 in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2
Append data to tables with DataFrameWriterV2.append	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/append
Cluster data using DataFrameWriterV2.clusterBy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/clusterby
Create new tables with DataFrameWriterV2.create	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/create
Use DataFrameWriterV2.createOrReplace in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/createorreplace
Set write options with DataFrameWriterV2.option	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/option
Configure multiple write options with options()	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/options
Use DataFrameWriterV2.overwrite for conditional updates	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/overwrite
Use overwritePartitions with DataFrameWriterV2	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/overwritepartitions
Partition tables with DataFrameWriterV2.partitionedBy	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/partitionedby
Replace tables using DataFrameWriterV2.replace	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/replace
Add table properties via tableProperty()	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/tableproperty
Specify data source providers with using()	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/dataframewriterv2/using
Implement custom PySpark DataSource in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource
Define custom data source name() identifier	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource/name
Provide a DataSource.reader implementation	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource/reader
Infer custom data source schema() in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource/schema
Implement simpleStreamReader for custom sources	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource/simplestreamreader
Implement streamReader for streaming data sources	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource/streamreader
Implement streamWriter for streaming sinks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource/streamwriter
Provide DataSource.writer for custom sinks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasource/writer
Use DataSourceArrowWriter for Arrow-based sinks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcearrowwriter
Implement write() in DataSourceArrowWriter	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
Define partitions() in DataSourceReader for parallelism	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcereader/partitions
Implement pushFilters() for filter pushdown	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcereader/pushfilters
Implement read() in DataSourceReader partitions	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcereader/read
Register custom DataSource with DataSourceRegistration	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourceregistration
Use register() to expose custom data sources	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourceregistration/register
Use DataSourceStreamArrowWriter for streaming sinks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamarrowwriter
Implement write() in DataSourceStreamArrowWriter	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamarrowwriter/write
Implement DataSourceStreamReader for streaming inputs	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader
Handle commit() in DataSourceStreamReader offsets	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/commit
Use getDefaultReadLimit in streaming sources	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/getdefaultreadlimit
Define initialOffset() for streaming data sources	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/initialoffset
Implement latestOffset() with read limits	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/latestoffset
Define partitions() for DataSourceStreamReader	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/partitions
Implement read() in DataSourceStreamReader	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/read
Report latest offsets with reportLatestOffset()	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/reportlatestoffset
Stop streaming sources with stop() in DataSourceStreamReader	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamreader/stop
Implement DataSourceStreamWriter for streaming sinks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamwriter
Handle abort() in DataSourceStreamWriter failures	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamwriter/abort
Commit microbatches with DataSourceStreamWriter.commit	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamwriter/commit
Implement custom streaming sinks with DataSourceStreamWriter.write	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcestreamwriter/write
Implement custom batch data sources with DataSourceWriter	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcewriter
Handle failed batch writes with DataSourceWriter.abort	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcewriter/abort
Commit successful batch writes with DataSourceWriter.commit	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcewriter/commit
Write partition data in custom sources with DataSourceWriter.write	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datasourcewriter/write
Load streaming DataFrames with DataStreamReader	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader
Read table change data capture with DataStreamReader.changes	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/changes
Stream CSV data into DataFrames with DataStreamReader.csv	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/csv
Stream Excel files into DataFrames with DataStreamReader.excel	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/excel
Specify streaming input formats with DataStreamReader.format	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 generic streaming sources with DataStreamReader.load	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/load
Name streaming sources for checkpoint evolution with DataStreamReader.name	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/name
Stream ORC data into DataFrames with DataStreamReader.orc	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/orc
Stream Parquet data into DataFrames with DataStreamReader.parquet	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/parquet
Create streaming DataFrames from tables with DataStreamReader.table	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/table
Stream text files into DataFrames with DataStreamReader.text	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamreader/text
Stream XML data into DataFrames 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
Process streaming rows with custom foreach writers	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/foreach
Process micro-batches with DataStreamWriter.foreachBatch	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/foreachbatch
Select streaming output data source with DataStreamWriter.format	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/format
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 DataStreamWriter.table	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/table
Stream DataFrame output into tables with DataStreamWriter.toTable	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/datastreamwriter/totable
Work with geography values using the Geography class	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geography
Create Geography objects from WKB with Geography.fromWKB	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geography/fromwkb
Export Geography values to WKB with Geography.getBytes	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geography/getbytes
Retrieve SRID from Geography objects with Geography.getSrid	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geography/getsrid
Work with geometry values using the Geometry class	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geometry
Use Geometry.fromWKB in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geometry/fromwkb
Return Geometry WKB bytes with getBytes	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geometry/getbytes
Retrieve Geometry SRID using getSrid in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/geometry/getsrid
Work with GroupedData aggregations in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/groupeddata
Compute custom aggregates with GroupedData.agg	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/groupeddata/agg
Calculate group averages with GroupedData.avg	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
Get maximum values per group with GroupedData.max	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/groupeddata/max
Use GroupedData.mean alias for averages	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/groupeddata/mean
Get minimum values per group with GroupedData.min	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/groupeddata/min
Pivot DataFrame columns with GroupedData.pivot	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/groupeddata/pivot
Sum numeric columns per group with GroupedData.sum	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 using Observation.get	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/observation/get
Generate plots from PySpark 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 DataFrame histograms 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 DataFrame lines 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
Visualize correlations with PySparkPlotAccessor.scatter	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/plotaccessor/scatter
Use the Row class for PySpark DataFrames	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/row
Convert Row objects to dictionaries with asDict	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/row/asdict
Implement SimpleDataSourceStreamReader for lightweight streaming	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 streaming offsets with SimpleDataSourceStreamReader.initialOffset	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/simpledatasourcestreamreader/initialoffset
Read streaming data and next offset with SimpleDataSourceStreamReader.read	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/simpledatasourcestreamreader/read
Re-read batches deterministically 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
Use SparkSession.addArtifacts in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/addartifacts
Tag operations with SparkSession.addTag in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/addtag
Access Spark catalog via SparkSession.catalog	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/catalog
Clear Spark progress handlers with clearProgressHandlers	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/clearprogresshandlers
Manage Spark operation tags with clearTags	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/cleartags
Create DataFrames with SparkSession.createDataFrame	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/createdataframe
Register data sources via SparkSession.dataSource	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/datasource
Retrieve current Spark session with getActiveSession	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/getactivesession
Inspect current Spark operation tags with getTags	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/gettags
Interrupt all operations in a Spark session	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/interruptall
Cancel specific Spark operations with interruptOperation	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/interruptoperation
Cancel tagged Spark operations with interruptTag	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/interrupttag
Create isolated Spark sessions with newSession	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/newsession
Profile Spark performance via SparkSession.profile	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/profile
Generate numeric ranges with SparkSession.range	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/range
Read data as DataFrames with SparkSession.read	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/read
Read streaming data with SparkSession.readStream	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/readstream
Register Spark progress handlers with registerProgressHandler	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/registerprogresshandler
Remove Spark progress handlers with removeProgressHandler	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/removeprogresshandler
Remove Spark operation tags with removeTag	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/removetag
Access underlying SparkContext via SparkSession.sparkContext	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/sparkcontext
Run SQL queries with SparkSession.sql in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/sql
Stop Spark applications with SparkSession.stop	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/stop
Manage streaming queries via SparkSession.streams	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/streams
Load tables as DataFrames with SparkSession.table	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 UDFs with SparkSession.udf in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/udf
Register UDTFs with SparkSession.udtf in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/sparksession/udtf
Control streaming queries with StreamingQuery in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery
Inspect streaming failures with StreamingQuery.exception	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/exception
Explain streaming query plans with StreamingQuery.explain	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/explain
Check streaming query activity with isActive	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/isactive
Get last progress update via lastProgress	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/lastprogress
Process all available streaming data with processAllAvailable	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/processallavailable
Use StreamingQuery.runId in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/runid
Access StreamingQuery.status in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/status
Stop a StreamingQuery in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquery/stop
Implement StreamingQueryListener for Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquerylistener
Handle onQueryIdle events in StreamingQueryListener	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquerylistener/onqueryidle
Use onQueryProgress for streaming status updates	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquerylistener/onqueryprogress
React to onQueryStarted events in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquerylistener/onquerystarted
Handle onQueryTerminated events in StreamingQueryListener	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquerylistener/onqueryterminated
Manage streaming queries with StreamingQueryManager	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquerymanager
List active streaming queries in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquerymanager/active
Register StreamingQueryListener with StreamingQueryManager	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquerymanager/addlistener
Use awaitAnyTermination on StreamingQueryManager	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquerymanager/awaitanytermination
Get streaming query by ID in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquerymanager/get
Remove StreamingQueryListener from StreamingQueryManager	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquerymanager/removelistener
Reset terminated streaming queries in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/streamingquerymanager/resetterminated
Work with UserDefinedFunction in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/udf
Mark PySpark UserDefinedFunction as nondeterministic	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/udf/asnondeterministic
Register UDFs with UDFRegistration in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/udfregistration
Register Python functions as SQL UDFs in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/udfregistration/register
Register Java UDFs as SQL functions in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/udfregistration/registerjavafunction
Register Java UDAFs as SQL functions in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/udfregistration/registerjavaudaf
Use UserDefinedTableFunction in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/udtf
Mark UserDefinedTableFunction as deterministic	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/udtf/asdeterministic
Use UDTFRegistration for table functions in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/udtfregistration
Register Python UDTFs as SQL table functions	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/udtfregistration/register
Work with VariantVal type in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/variantval
Parse JSON into VariantVal in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/variantval/parsejson
Convert VariantVal to JSON with time zone control	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/variantval/tojson
Convert VariantVal to native Python structures	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/variantval/topython
Define window specifications with Window in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/window
Specify ordering for Window in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/window/orderby
Specify partitioning for Window in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/window/partitionby
Define rangeBetween frames for Window in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/window/rangebetween
Define rowsBetween frames for Window in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/window/rowsbetween
Use WindowSpec to configure windowing in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/windowspec
Set ordering columns on WindowSpec in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/windowspec/orderby
Set partitioning columns on WindowSpec in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/windowspec/partitionby
Configure rangeBetween on WindowSpec in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/windowspec/rangebetween
Configure rowsBetween on WindowSpec in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/windowspec/rowsbetween
Use WriterCommitMessage in Databricks data sources	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/classes/writercommitmessage
Use abs numeric function in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/abs
Use acos inverse cosine in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/acos
Use acosh inverse hyperbolic cosine in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/acosh
Manipulate dates with add_months in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/add_months
Aggregate array elements with aggregate in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/aggregate
Parse documents with ai_parse_document in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/ai_parse_document
Use any_value aggregate function in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/any_value
Estimate distinct counts with approx_count_distinct	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/approx_count_distinct
Compute approximate percentiles with approx_percentile	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/approx_percentile
Create array columns with array function in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/array
Aggregate values into arrays with array_agg	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/array_agg
Remove nulls from arrays with array_compact	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/array_compact
Test array membership with array_contains in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/array_contains
Remove duplicates from arrays with array_distinct	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/array_distinct
Compute array differences with array_except in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/array_except
Insert elements into arrays with array_insert in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/array_insert
Compute array intersections with array_intersect	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/array_intersect
Join array elements into strings with array_join	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/array_join
Find maximum element in arrays with array_max	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/array_max
Find minimum element in arrays with array_min	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/array_min
Use explode_outer PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/explode_outer
Use expm1 PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/expm1
Use expr column expression function in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/expr
Extract date and interval parts with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/extract
Compute factorial with PySpark in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/factorial
Filter array elements with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/filter
Use find_in_set string search in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/find_in_set
Use first aggregate function with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/first
Use first_value window function in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/first_value
Flatten nested arrays with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/flatten
Use floor numeric function with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/floor
Validate array predicates with forall in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/forall
Format numbers as strings with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/format_number
Use format_string printf-style formatting in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/format_string
Use from_avro in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/from_avro
Parse CSV strings to rows with from_csv in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/from_csv
Parse JSON strings to complex types with from_json in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/from_json
Convert Unix epoch seconds to timestamps with from_unixtime in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/from_unixtime
Convert UTC timestamps to time zones with from_utc_timestamp in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/from_utc_timestamp
Parse XML strings to rows with from_xml in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/from_xml
Access array elements by index with get in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/get
Extract JSON objects with get_json_object in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/get_json_object
Read individual bits with getbit in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/getbit
Compute greatest value across columns with Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/greatest
Use grouping aggregate indicator in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/grouping
Compute grouping_id for rollups in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/grouping_id
Use h3_hexring PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_hexring
Use h3_ischildof PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_ischildof
Use h3_ispentagon PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_ispentagon
Use h3_isvalid PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_isvalid
Use h3_kring PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_kring
Use h3_kringdistances PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_kringdistances
Use h3_longlatash3 PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_longlatash3
Use h3_longlatash3string PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_longlatash3string
Use h3_maxchild PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_maxchild
Use h3_minchild PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_minchild
Use h3_pointash3 PySpark function with WKT, GeoJSON, WKB	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_pointash3
Use h3_pointash3string PySpark function with geography inputs	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_pointash3string
Use h3_polyfillash3 PySpark function for areal geographies	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_polyfillash3
Use h3_polyfillash3string PySpark function for polygons	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_polyfillash3string
Use h3_resolution PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_resolution
Use h3_stringtoh3 PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_stringtoh3
Use h3_tessellateaswkb PySpark function for geography chips	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_tessellateaswkb
Use h3_tochildren PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_tochildren
Use h3_toparent PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_toparent
Use h3_try_coverash3 PySpark function for minimal coverage	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_try_coverash3
Use h3_try_coverash3string PySpark function with error handling	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_try_coverash3string
Use h3_try_distance PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_try_distance
Use h3_try_polyfillash3 PySpark function with safe parsing	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_try_polyfillash3
Use h3_try_polyfillash3string PySpark function safely	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_try_polyfillash3string
Use h3_try_tessellateaswkb PySpark function with null on invalid	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_try_tessellateaswkb
Use h3_try_validate PySpark function for H3 cells	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_try_validate
Use h3_uncompact PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_uncompact
Use h3_validate PySpark function with error on invalid	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/h3_validate
Use hash column function in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/hash
Convert values to hex in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/hex
Compute numeric histograms in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/histogram_numeric
Create HllSketch aggregates in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/hll_sketch_agg
Estimate cardinality from HllSketch in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/hll_sketch_estimate
Union Datasketches HllSketch binaries in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/hll_union
Aggregate union of HllSketches in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/hll_union_agg
Extract hour from timestamp in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/hour
Use hypot numeric function in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/hypot
Use ifnull for null handling in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/ifnull
Perform case-insensitive LIKE (ilike) in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/ilike
Capitalize words with initcap in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/initcap
Explode array of structs with inline in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/inline
Use inline_outer PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/inline_outer
Use input_file_block_length in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/input_file_block_length
Use input_file_block_start in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/input_file_block_start
Get current task file name with input_file_name	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/input_file_name
Locate substring position with instr in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/instr
Validate UTF-8 strings with is_valid_utf8 in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/is_valid_utf8
Check variant nulls with is_variant_null in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/is_variant_null
Detect NaN values with isnan in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/isnan
Test non-null columns with isnotnull in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/isnotnull
Test null columns with isnull in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/isnull
Invoke JVM methods via java_method in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/java_method
Count JSON array elements with json_array_length in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/json_array_length
Extract JSON object keys with json_object_keys in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/json_object_keys
Create rows from JSON fields with json_tuple in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/json_tuple
Get item count from KLL bigint sketch in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_get_n_bigint
Get item count from KLL double sketch in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_get_n_double
Get item count from KLL float sketch in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_get_n_float
Extract quantiles from KLL bigint sketch in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_get_quantile_bigint
Extract quantiles from KLL double sketch in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_get_quantile_double
Extract quantiles from KLL float sketch in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_get_quantile_float
Get rank from KLL bigint sketch in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_get_rank_bigint
Get rank from KLL double sketch in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_get_rank_double
Get rank from KLL float sketch in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_get_rank_float
Merge KLL bigint sketch buffers in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_merge_bigint
Merge KLL double sketch buffers in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_merge_double
Merge KLL float sketch buffers in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_merge_float
Summarize KLL bigint sketch with kll_sketch_to_string_bigint	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_to_string_bigint
Summarize KLL double sketch with kll_sketch_to_string_double	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_to_string_double
Summarize KLL float sketch with kll_sketch_to_string_float	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kll_sketch_to_string_float
Compute kurtosis over groups in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/kurtosis
Use lag window function in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/lag
Get last value in group with last in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/last
Use PySpark mask function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/mask
Use PySpark max aggregation in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/max
Use PySpark max_by window function in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/max_by
Compute MD5 digests with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/md5
Use PySpark mean aggregation in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/mean
Use PySpark median aggregation in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/median
Use PySpark min aggregation in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/min
Use PySpark min_by window function in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/min_by
Extract minutes from timestamps with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/minute
Use PySpark mode aggregation in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/mode
Generate monotonically increasing IDs in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/monotonically_increasing_id
Extract month from dates with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/month
Get abbreviated month names with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/monthname
Partition data by months with Databricks PySpark months transform	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/months
Compute months_between dates with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/months_between
Create named structs with PySpark in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/named_struct
Handle NaN values with nanvl in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/nanvl
Use negate numeric function in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/negate
Use negative numeric function in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/negative
Find next weekday dates with PySpark next_day in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/next_day
Get current timestamp with PySpark now in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/now
Use nth_value window function in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/nth_value
Use ntile window function in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/ntile
Use nullif conditional function in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/nullif
Convert zero to null with nullifzero in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/nullifzero
Use nvl to replace nulls in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/nvl
Use nvl2 for conditional null handling in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/nvl2
Calculate string byte length with octet_length in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/octet_length
Overlay substrings in strings with PySpark overlay in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/overlay
Define and use pandas_udf functions in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/pandas_udf
Parse JSON strings to VariantType with Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/parse_json
Extract URL components with parse_url in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/parse_url
Partition data by hash buckets with Databricks PySpark partitioning.bucket	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/partitioning_bucket
Partition timestamp and date data into days with Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/partitioning_days
Partition timestamp data into hours with Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/partitioning_hours
Partition timestamp and date data into months with Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/partitioning_months
Partition timestamp and date data into years with Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/partitioning_years
Use percent_rank window function in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/percent_rank
Compute exact percentiles with percentile in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/percentile
Compute approximate percentiles with percentile_approx in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/percentile_approx
Use randstr PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/randstr
Use repeat PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/repeat
Use replace PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/replace
Reverse strings and arrays with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/reverse
Extract rightmost characters with PySpark right in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/right
Round to nearest integer with PySpark rint in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/rint
Use rlike regex matching in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/rlike
Round numeric values with PySpark round in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/round
Generate row numbers with PySpark window functions in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/row_number
Right-pad strings with PySpark rpad in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/rpad
Infer schema from CSV strings with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/schema_of_csv
Infer schema from JSON strings with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/schema_of_json
Get SQL schema of variant values in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/schema_of_variant
Aggregate and merge variant schemas with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/schema_of_variant_agg
Infer schema from XML strings with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/schema_of_xml
Compute secant values with PySpark sec in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/sec
Extract seconds from timestamps with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/second
Split text into sentences and words with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/sentences
Generate numeric sequences with PySpark sequence in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/sequence
Create session windows on event streams with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/session_window
Shift bits left with PySpark shiftleft in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/shiftleft
Signed right bit shift with PySpark shiftright in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/shiftright
Unsigned right bit shift with PySpark shiftrightunsigned in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/shiftrightunsigned
Compute sign of values with PySpark sign in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/sign
Compute signum of values with PySpark signum in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/signum
Compute sine values with PySpark sin in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/sin
Compute hyperbolic sine with PySpark sinh in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/sinh
Get size of arrays and maps with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/size
Calculate skewness over groups with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/skewness
Slice array columns with PySpark slice in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/slice
Evaluate boolean aggregates with PySpark some in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/some
Sort array elements with PySpark sort_array in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/sort_array
Generate SoundEx encodings with PySpark soundex in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/soundex
Access Spark partition IDs with PySpark in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/spark_partition_id
Split strings by pattern with PySpark split in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/split
Use split_part PySpark function in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/split_part
Use st_addpoint in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_addpoint
Calculate geometry area with st_area in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_area
Convert geometry to WKB with st_asbinary	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_asbinary
Return EWKB geometry with st_asewkb in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_asewkb
Return EWKT geometry with st_asewkt in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_asewkt
Export geometry as GeoJSON with st_asgeojson	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_asgeojson
Convert geometry to WKT with st_astext in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_astext
Convert geometry to WKB with st_aswkb in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_aswkb
Convert geometry to WKT with st_aswkt in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_aswkt
Compute azimuth between points with st_azimuth	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_azimuth
Get geometry boundary with st_boundary in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_boundary
Create geometry buffers with st_buffer in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_buffer
Compute geometry centroid with st_centroid in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_centroid
Find closest point on geometry with st_closestpoint	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_closestpoint
Generate concave hulls with st_concavehull in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_concavehull
Test geometry containment with st_contains in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_contains
Generate convex hulls with st_convexhull in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_convexhull
Check geometry coverage with st_covers in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_covers
Compute geometry difference with st_difference in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_difference
Get geometry dimension with st_dimension in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_dimension
Test geometry disjointness with st_disjoint in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_disjoint
Measure Cartesian distance with st_distance in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_distance
Measure spherical distance with st_distancesphere in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_distancesphere
Measure geodesic distance with st_distancespheroid in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_distancespheroid
Explode geometry collections with st_dump in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_dump
Filter by distance with st_dwithin in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_dwithin
Get linestring endpoint with st_endpoint in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_endpoint
Compute geometry envelope with st_envelope in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_envelope
Aggregate geometry envelopes with st_envelope_agg in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_envelope_agg
Test geometry equality with st_equals in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_equals
Estimate projected SRID with st_estimatesrid in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_estimatesrid
Get polygon exterior ring with st_exteriorring in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_exteriorring
Swap geometry coordinates with st_flipcoordinates in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_flipcoordinates
Force 2D projection with st_force2d in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_force2d
Use st_geogfromewkt in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geogfromewkt
Use st_geogfromgeojson in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geogfromgeojson
Use st_geogfromtext in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geogfromtext
Use st_geogfromwkb in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geogfromwkb
Use st_geogfromwkt in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geogfromwkt
Compute geohash with st_geohash in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geohash
Access multi-geometry elements with st_geometryn	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geometryn
Get geometry type with st_geometrytype in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geometrytype
Use st_geomfromewkb in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geomfromewkb
Use st_geomfromewkt and SRID handling in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geomfromewkt
Convert geohash to polygon with st_geomfromgeohash	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geomfromgeohash
Use st_geomfromgeojson in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geomfromgeojson
Use st_geomfromtext in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geomfromtext
Use st_geomfromwkb in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geomfromwkb
Use st_geomfromwkt in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_geomfromwkt
Get polygon interior rings with st_interiorringn	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_interiorringn
Compute geometry intersections with st_intersection	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_intersection
Test geometry overlap with st_intersects in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_intersects
Check empty geospatial values with st_isempty	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_isempty
Validate geometries with st_isvalid in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_isvalid
Measure geospatial length with st_length in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_length
Access M coordinate with st_m in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_m
Build linestrings from points with st_makeline	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_makeline
Construct polygons from rings with st_makepolygon	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_makepolygon
Convert to multi-geometry with st_multi in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_multi
Get coordinate dimensions with st_ndims in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_ndims
Count points with st_npoints in Azure Databricks	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
Count geometries in collections with st_numgeometries	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_numgeometries
Count interior rings with st_numinteriorrings	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_numinteriorrings
Use st_numpoints alias for st_npoints in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_numpoints
Measure perimeter with st_perimeter in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_perimeter
Create point geometries with st_point in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_point
Get geohash center point with st_pointfromgeohash	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_pointfromgeohash
Access linestring vertices with st_pointn in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_pointn
Remove linestring points with st_removepoint	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_removepoint
Reverse vertex order with st_reverse in Azure Databricks	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 with st_scale in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_scale
Set linestring vertices with st_setpoint in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_setpoint
Use st_setsrid geospatial function 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
Get geometry SRID using st_srid in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_srid
Extract linestring start point with st_startpoint	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_startpoint
Test geometry adjacency using 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 with st_translate in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_translate
Compute geometry union using 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 spatial containment with st_within in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_within
Get point X coordinate using st_x in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_x
Find maximum X of geometry with st_xmax	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_xmax
Find minimum X of geometry with st_xmin	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_xmin
Get point Y coordinate using st_y in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_y
Find maximum Y of geometry with st_ymax	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_ymax
Find minimum Y of geometry with st_ymin	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_ymin
Get point Z coordinate using st_z in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_z
Find maximum Z of geometry with st_zmax	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_zmax
Find minimum Z of geometry with st_zmin	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/st_zmin
Transform columns to rows with stack in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/stack
Evaluate prefixes with startswith in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/startswith
Compute standard deviation using std in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/std
Use stddev alias for stddev_samp in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/stddev
Calculate population standard deviation in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/stddev_pop
Calculate sample standard deviation in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/stddev_samp
Convert strings to maps with str_to_map in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/str_to_map
Aggregate strings with string_agg in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/string_agg
Aggregate distinct strings 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	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
Use substring function with 1-based indexing in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/substring
Split by delimiter using substring_index in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/substring_index
Sum column values with sum in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/sum
Sum distinct values with sum_distinct in Databricks	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 Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/tanh
Compute Theta Sketch set difference in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/theta_difference
Compute Theta Sketch intersection in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/theta_intersection
Aggregate Theta Sketch intersections in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/theta_intersection_agg
Use theta_sketch_agg in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/theta_sketch_agg
Estimate unique counts from Theta Sketches in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/theta_sketch_estimate
Use theta_union with Databricks PySpark sketches	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/theta_union
Use theta_union_agg for Theta Sketch unions in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/theta_union_agg
Compute 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 in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/time_from_micros
Create TIME values from milliseconds in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/time_from_millis
Use to_avro in PySpark on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/to_avro
Convert values to Geography in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/to_geography
Convert values to Geometry in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/to_geometry
Apply trim string function in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/trim
Create timestamps with try_make_timestamp in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_make_timestamp
Use try_make_timestamp_ltz for local-timezone timestamps	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_make_timestamp_ltz
Use try_make_timestamp_ntz for local date-time values	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_make_timestamp_ntz
Use try_mod for safe modulo in Databricks 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 PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_parse_json
Use try_parse_url for error-tolerant URL parsing	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_parse_url
Use try_reflect for safe Java method invocation	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
Use try_sum for overflow-safe aggregation in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_sum
Use try_to_binary for safe binary conversion	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_to_binary
Use try_to_date for tolerant date parsing	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_to_date
Use try_to_geography in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_to_geography
Use try_to_geometry in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_to_geometry
Use try_to_number for formatted numeric parsing	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_to_number
Convert strings to time with try_to_time in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_to_time
Parse timestamps with try_to_timestamp in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_to_timestamp
Use try_url_decode for tolerant URL decoding	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_url_decode
Validate UTF-8 safely with try_validate_utf8 in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/try_validate_utf8
Extract sub-variants with try_variant_get in PySpark	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.explode in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/tvf-explode
Use TableValuedFunction.explode_outer in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/tvf-explode_outer
Use TableValuedFunction.inline in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/tvf-inline
Use TableValuedFunction.inline_outer in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/tvf-inline_outer
Use TableValuedFunction.json_tuple in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/tvf-json_tuple
Use TableValuedFunction.stack in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/tvf-stack
Explode Databricks variant types with variant_explode	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/tvf-variant_explode
Use variant_explode_outer on Databricks VARIANT data	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/tvf-variant_explode_outer
Get column data types with typeof in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/typeof
Convert strings to uppercase with ucase in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/ucase
Create and use PySpark UDFs in Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/udf
Create user-defined table functions (UDTF) in PySpark	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 PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/unhex
Use the uniform random function in Azure Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/uniform
Get days since epoch with unix_date in PySpark	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 in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/unix_seconds
Convert formatted timestamps to Unix time in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/unix_timestamp
Unwrap user-defined types with unwrap_udt in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/unwrap_udt
Convert strings to uppercase with upper in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/upper
Decode URL-encoded strings with url_decode in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/url_decode
Encode strings as URLs with url_encode in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/url_encode
Get current user or database with user function	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/user
Generate UUIDs with uuid function in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/uuid
Validate UTF-8 strings with validate_utf8 in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/validate_utf8
Compute population variance with var_pop in PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/var_pop
Use var_samp aggregation in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/var_samp
Use variance alias for var_samp in PySpark	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
Retrieve Spark version with Databricks version function	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/version
Get weekday index from dates in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/weekday
Compute ISO weekofyear in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/weekofyear
Use when conditional expressions 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
Define time windows with window in Databricks PySpark	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 numeric XML values with xpath_double in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xpath_double
Get float XML values with xpath_float in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xpath_float
Get integer XML values with xpath_int in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xpath_int
Get long XML values with xpath_long in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xpath_long
Evaluate XML XPath to number with xpath_number	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xpath_number
Get short XML values with xpath_short in Databricks	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/xpath_short
Extract XML text 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 in Databricks PySpark	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/year
Partition data by 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	https://learn.microsoft.com/en-us/azure/databricks/pyspark/reference/functions/zstd_compress
Decompress Zstandard data with zstd_decompress	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 Databricks queries across workspaces	https://learn.microsoft.com/en-us/azure/databricks/query-federation/databricks
Create Unity Catalog HTTP connections for external APIs	https://learn.microsoft.com/en-us/azure/databricks/query-federation/http
Set up Lakehouse Federation for MySQL	https://learn.microsoft.com/en-us/azure/databricks/query-federation/mysql
Configure Databricks Lakehouse Federation for Oracle	https://learn.microsoft.com/en-us/azure/databricks/query-federation/oracle
Set up Lakehouse Federation for PostgreSQL	https://learn.microsoft.com/en-us/azure/databricks/query-federation/postgresql
Configure Databricks federated queries to Amazon Redshift	https://learn.microsoft.com/en-us/azure/databricks/query-federation/redshift
Use Databricks remote_query to run SQL on external databases	https://learn.microsoft.com/en-us/azure/databricks/query-federation/remote-queries
Configure Databricks federated queries to Salesforce Data 360	https://learn.microsoft.com/en-us/azure/databricks/query-federation/salesforce-data-cloud
Use Salesforce Data 360 file sharing with Databricks	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
Federate Databricks queries to Snowflake with Entra ID	https://learn.microsoft.com/en-us/azure/databricks/query-federation/snowflake-entra
Federate Databricks queries to Snowflake with OAuth tokens	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
Configure Databricks federated queries to Snowflake with PEM	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
Configure Databricks federated queries to Azure Synapse	https://learn.microsoft.com/en-us/azure/databricks/query-federation/sqldw
Read and write Avro files on Databricks	https://learn.microsoft.com/en-us/azure/databricks/query/formats/avro
Read binary files into Spark DataFrames on Databricks	https://learn.microsoft.com/en-us/azure/databricks/query/formats/binary
Read CSV files using Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/query/formats/csv
Read Delta Sharing tables with Spark DataFrames	https://learn.microsoft.com/en-us/azure/databricks/query/formats/deltasharing
Load MLflow experiment run data in Databricks	https://learn.microsoft.com/en-us/azure/databricks/query/formats/mlflow-experiment
Read Parquet files using Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/query/formats/parquet
Process text files with Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/query/formats/text
Read and write XML files 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 Databricks secrets for JDBC credentials	https://learn.microsoft.com/en-us/azure/databricks/security/secrets/example-secret-workflow
Query JSON string columns with Databricks SQL operators	https://learn.microsoft.com/en-us/azure/databricks/semi-structured/json
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
Close cursors with CLOSE in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/control-flow/close-stmt
Use BEGIN END compound statements in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/control-flow/compound-stmt
Clone Delta, Iceberg, and Parquet tables with CREATE TABLE CLONE	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/delta-clone
Use COPY INTO for Delta Lake data loading	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/delta-copy-into
Create deprecated Bloom filter indexes in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/delta-create-bloomfilter-index
Execute DELETE FROM on Delta Lake tables	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/delta-delete-from
Merge data into Delta Lake tables with MERGE	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/delta-merge-into
Update rows in Delta Lake tables with UPDATE	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/delta-update
Use ai_analyze_sentiment in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_analyze_sentiment
Classify text with ai_classify in Databricks SQL	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 with ai_fix_grammar in SQL	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 with ai_prep_search	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/ai_prep_search
Call model serving endpoints with ai_query in Databricks	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
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
Query Auto Loader state with cloud_files_state	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 data in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/from_avro
Parse CSV strings with Databricks SQL from_csv	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/from_csv
Parse JSON strings with Databricks SQL from_json	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/from_json
Parse XML to structs with Databricks SQL from_xml	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/from_xml
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
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
Construct timestamps using make_timestamp	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/make_timestamp
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 binary minus operator in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/minussign
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
Use plus + operator in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/plussign
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
Read files with read_files table function in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/read_files
Query Kafka with read_kafka 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
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
Use remote_query to access external databases in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/remote_query
Use sql_keywords function in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/sql_keywords
Manipulate linestrings with st_addpoint in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_addpoint
Compute geometry area with st_area in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_area
Export geometries as WKB with st_asbinary	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_asbinary
Export geometries as EWKB with st_asewkb	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_asewkb
Export geospatial data as EWKT with st_asewkt	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_asewkt
Convert geometries to GeoJSON with 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
Export geometries as WKB with st_aswkb	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_aswkb
Export geometries as WKT with st_aswkt	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_aswkt
Create geometry buffers with st_buffer in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_buffer
Compute geometry centroid with st_centroid	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_centroid
Compute concave hulls with st_concavehull in Databricks	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
Compute convex hulls with st_convexhull in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_convexhull
Test geometry coverage with st_covers	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_covers
Compute geometry difference with st_difference	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_difference
Get geometry dimension with st_dimension	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_dimension
Check geometry disjointness with st_disjoint	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_disjoint
Measure Cartesian distance with st_distance in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_distance
Measure spherical distance with st_distancesphere	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_distancesphere
Measure geodesic distance with st_distancespheroid	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_distancespheroid
Explode geometries into parts with st_dump	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 endpoint with st_endpoint	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_endpoint
Compute geometry envelope with st_envelope	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
Test geometry equality with st_equals in Databricks	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
Get polygon exterior ring with st_exteriorring	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_exteriorring
Swap geometry coordinates with st_flipcoordinates	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_flipcoordinates
Project geospatial data to 2D with st_force2d	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
Use st_geohash to compute geohash in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geohash
Use st_geometryn to access geometry collection elements	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geometryn
Use st_geometrytype to get geometry or geography type	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geometrytype
Use st_geomfromewkb to parse EWKB geometry	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geomfromewkb
Use st_geomfromewkt in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geomfromewkt
Use st_geomfromgeohash to get geohash grid polygons	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geomfromgeohash
Use st_geomfromgeojson to parse GeoJSON geometry	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geomfromgeojson
Use st_geomfromtext to parse WKT geometry with SRID	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geomfromtext
Use st_geomfromwkb to parse WKB geometry with SRID	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geomfromwkb
Use st_geomfromwkt to parse WKT geometry with SRID	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_geomfromwkt
Use st_intersection to compute geometry intersections	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_intersection
Use st_intersects to test geometry intersections	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_intersects
Use st_isempty to test empty geography or geometry	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_isempty
Use st_isvalid to validate geometries in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_isvalid
Use st_length to compute geography or geometry length	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_length
Use st_m to read M coordinate from point geometry	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_m
Use st_makeline to build linestrings from geometries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_makeline
Use st_makepolygon to construct polygon geometries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_makepolygon
Use st_multi to convert to multi-geospatial types	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_multi
Use st_ndims to get coordinate dimensions	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_ndims
Use st_npoints to count points in geospatial values	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_npoints
Use st_nrings to count rings in polygons and multipolygons	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_nrings
Use st_numgeometries to count geometries in collections	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_numgeometries
Use st_numinteriorrings to count polygon interior rings	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_numinteriorrings
Use st_numpoints to count points in geospatial values	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_numpoints
Use st_perimeter to compute geography or geometry perimeter	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_perimeter
Use st_point to construct point geometries with SRID	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_point
Use st_pointfromgeohash to get geohash cell centers	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_pointfromgeohash
Use st_pointn to access points in linestrings	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_pointn
Use st_removepoint to modify linestring points	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_removepoint
Use st_reverse to reverse geospatial geometries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_reverse
Use st_rotate to rotate geometries around Z axis	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_rotate
Use st_scale to scale geometries in X, Y, and Z	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_scale
Use st_setsrid to change SRID of geospatial values	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_setsrid
Use st_simplify to simplify geometries with Douglas-Peucker	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_simplify
Use st_srid to read SRID from geography or geometry	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_srid
Use st_startpoint to get first point of linestrings	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/st_startpoint
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 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
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
Cast expressions to DATE with to_date	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/to_date
Convert formatted strings to DECIMAL with to_number	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/to_number
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
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
Get current user with Databricks user function	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/user
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
Compute vector cosine similarity in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/vector_cosine_similarity
Compute vector inner product in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/vector_inner_product
Compute vector L2 distance in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/vector_l2_distance
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
Query Mosaic AI Vector Search indexes via SQL	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
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
Write SQL scripts with Databricks SQL/PSM syntax	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-scripting
Use ST geospatial functions in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-st-geospatial-functions
Alphabetical reference of ST functions in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-st-geospatial-functions-alpha
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 TABLE in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-describe-table
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
Use SHOW ALL IN SHARE to list Delta Sharing content	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-all-in-share
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 CREATE TABLE in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-create-table
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
List Delta Sharing shares with SHOW SHARES	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-aux-show-shares
List provider shares with SHOW SHARES IN PROVIDER	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
Create catalogs with Databricks SQL CREATE CATALOG	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-catalog
Define foreign connections with CREATE CONNECTION	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-connection
Create external functions with Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-function
Define materialized views in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-materialized-view
Create and manage procedures in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-procedure
Create schemas with Databricks SQL CREATE SCHEMA	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-schema
Create SQL and Python functions in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-sql-function
Create streaming tables in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-streaming-table
Use FLOW AUTO CDC with CREATE STREAMING TABLE	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-streaming-table-auto-cdc
Define constraints in CREATE TABLE and MATERIALIZED VIEW	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-table-constraint
Create managed, temporary, and external tables in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-table-using
Create views and metric views in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-view
Create Unity Catalog volumes with CREATE VOLUME	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-create-volume
Use DECLARE VARIABLE for session variables in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-declare-variable
Drop user-defined functions with DROP FUNCTION in Databricks	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-ddl-drop-function
Use INSERT syntax in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-dml-insert-into
Author SQL pipelines in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-pipeline
Compose queries in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-query
Write SELECT subqueries in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select
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
Use CTEs in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-cte
GROUP BY and advanced aggregates in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-groupby
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
Define reusable WINDOW specifications in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-named-window
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
Apply piped operations in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-pipeop
Transform rows with PIVOT in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-pivot
Use set operators in Databricks SQL queries	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-setops
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
Create inline tables with VALUES in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-values
Apply WATERMARK for streaming in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-select-watermark
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 star (*) expansion in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/sql-ref-syntax-qry-star
Use new Databricks SQL 2023 language and functions	https://learn.microsoft.com/en-us/azure/databricks/sql/release-notes/2023
Use named parameter markers in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/user/queries/query-parameters
Create and use query snippets in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/sql/user/queries/query-snippets
Implement custom stateful streaming with transformWithState	https://learn.microsoft.com/en-us/azure/databricks/stateful-applications/
Implement example custom stateful streaming apps	https://learn.microsoft.com/en-us/azure/databricks/stateful-applications/examples
Use legacy arbitrary stateful operators on Databricks	https://learn.microsoft.com/en-us/azure/databricks/stateful-applications/legacy
Handle schema evolution in transformWithState state store	https://learn.microsoft.com/en-us/azure/databricks/stateful-applications/schema-evolution
Use Avro and Schema Registry with Kafka streaming on 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
Write custom streaming sinks with foreachBatch	https://learn.microsoft.com/en-us/azure/databricks/structured-streaming/foreach
Serialize and deserialize protocol buffers in Databricks 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
Create Scala user-defined aggregate functions on Databricks	https://learn.microsoft.com/en-us/azure/databricks/udf/aggregate-scala
Create and use pandas UDFs on Azure Databricks	https://learn.microsoft.com/en-us/azure/databricks/udf/pandas
Implement Python scalar UDFs in Databricks SQL	https://learn.microsoft.com/en-us/azure/databricks/udf/python
Implement Scala scalar UDFs in Databricks 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
Integrate custom embedding models with Vector Search	https://learn.microsoft.com/en-us/azure/databricks/vector-search/custom-embedding-model
Query Mosaic AI Vector Search indexes with filters and reranking	https://learn.microsoft.com/en-us/azure/databricks/vector-search/query-vector-search
Manage files in Unity Catalog volumes across tools	https://learn.microsoft.com/en-us/azure/databricks/volumes/volume-files